vol. 9, issue 2, april - june 2016 automotive mechatronics … · vol. 9, issue 2, april - june...

VOL. 9, ISSUE 2, APRIL - JUNE 2016

Introduction to Automotive MechatronicsModel Based Mechatronics RequirementsSensors and ActuatorsSliding Mode Control for Automotive ApplicationsAutomotive Smart ActuatorsActive Automobile Aerodynamic SurfacesElectric Power Steering – Technology TrendsPredictive Efficiency ManagementUsing Driver Assistance SystemsFuture Trends inAutomotive Mechatronics

Automotive Mechatronics

Colophon

[email protected]

Rahul UplapAVP

Nitin SwamyMilind PotdarKedar SaprePranjali ModakPriti RanadiveSomnath SenguptaVishal PillaiReenaKumari BeheraAditya PiratlaSrinivasa Bugga

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Mind’sye Communication, Pune, IndiaContact : 9673005089

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Editorial

Scientist Profile

Book Review

Articles

Guest

Editorial 3

Rahul Uplap

Dr. Takeo Kanade 11

Pranjali Modak

31

Priti Ranadive

4

Reecha Yadav & Ann Mary Sebastian

Model Based Mechatronics Requirements 12

Manu M Jayaramegowda

Sensors and Actuators 16

Jayashri Kamagond

Sliding Mode Control for Automotive Applications 20

Sandeep V Ambesange & Manish Bansal

Automotive Smart Actuators 26

Prashanta Vora

Active Automobile Aerodynamic Surfaces 32

Jamsheed Kolothum Thodi & Manjunath Rangaswamy

Electric Power Steering – Technology Trends 38

Jestin Karlose Thekkeveetil

Predictive Efficiency Management Using Driver Assistance Systems 44

Vimalkanth K.

Future Trends in Automotive Mechatronics 50

Smita Nair, Narendra Kumar SS & Naresh Adepu

Editorial 2

Innovate Like Edison

Introduction to Automotive Mechatronics

Contents

TechTalk@KPIT, Volume 9, Issue 2, 2016

1

C. S. Kumar

Guest Editorial

The last few decades saw the emergence of some revolutionary technologies which

transformed various spheres of life. Buttressed by the ever evolving computing

technologies which have now defied the Moore's Law, many new developments took

place in form mobile communications, GPS systems, MEMS sensors etc. to name a

few. Amongst these, the mechatronics field has been accounting for a little above 50%

of innovations through new patents being published every year since 2010 in the

automotive sector itself [1]. It has been further accelerated by some innovative

applications of computational intelligence, energy management and alternative fuels

along with safety systems in the automotive sector.

Today not only are the energy issues, environmental concerns and faster

transportation needs, life in urban situations is getting demanding, the safety concerns

that are gaining more attention by a whole new suite of developments in the

automotive sector. Drive assist systems have been continuously getting more

sophisticated starting with mechanical drive handling support and are moving towards

accurate energy estimate based driving and navigation systems as well as

autonomous systems. These spinoff technologies emerging from exciting research

and development in Robotics and Intelligent Systems applications as in unmanned

aerial vehicles in defense; extraterrestrial rovers in space; autonomous underwater

vehicles in marine environments etc. are now finding applications in the civilian

transportation with one major new consideration of safety. While costs are being driven

lower with higher adoption rates for a larger customer base, the added convenience

and safety gains while improving the quality of transportation is evident. If one looks at

the modern new automotive technologies in the Tesla sedan one can see a confluence

of several domains of energy management, embedded electronics control systems,

software and high end mobility thereby giving a new meaning to the term of

mechatronics. This area is emerging faster with inclusion of autonomous system in all

driving assist forms to a driverless system which is generating several new innovations

every year. These are also being supported by creative of new job profiles which are

getting in demand the automotive mechatronic engineers carrying out research and

development of such systems. The research and development ecosystem in this field

could never be greener as the adoption is linked to stricter safety norms emerging

along with the energy environment, management systems. This special issue would

touch upon many such domains and is expected to throw light and make aware of the

role of a typical research engineer who works in these areas in today's time for a better

future in autonomous systems.

[1] The State of Innovation in the Automotive Industry 2015, Thomson Reuters

C. S. KumarRobotics and IntelligentSystems Laboratory,Department ofMechanical Engineering,IIT Kharagpur


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Editorial

Please send yourfeedback to :[email protected]

Rahul UplapAVPKPIT Technologies Limited,Pune, India

Increasing trend towards advanced safety and driver comfort in automobiles

across the globe has seen an explosion of intelligent subsystems/components

combining mechanical, electrical, electronic (Hardware and Software)

technologies capable of seamlessly communicating with external world through

high speed wired or wireless networks. These intelligent systems are called as

mechatronic systems.

Brake-by-wire, Steer-by-wire, cam-less engines, electronic vehicle suspensions

are some of the popular mechatronic systems being commonly used in today's

automobiles providing high degree of safety as well as benefits of reduced weight

due to reduction in electrical harnesses as well as mechanical components. This

eventually results in better fuel economy.

Seamless connectivity to cloud over internet is the next generation of these

intelligent systems which are also being popularly referred to as Internet of

Things (IoT). This has opened up numerous opportunities especially for

improving the diagnostics for these highly complex systems. Internet enabled

mechatronic systems would be able to predict failures or degradation in

functionality much before the actual mal-function and trigger corrective

measures or summon service help even without the user concerned to take

corrective action.

Reliability, reduced weight, manufacturing flexibility, advanced safety features

and lower cost are some of the noteworthy benefits that these intelligent systems

have to offer.

Other popular applications for mechatronic systems could be seen in the field of

medical electronics where more and more surgeries are being carried out by

using such highly sophisticated devices equipped with cameras. Outer space

exploration and surveillance is being made possible by such technology.

Mangalyaan, India's Mars Orbiter mission is a classic example of such high end

mechatronic system being deployed in inhabitable environments beyond human

reach for gathering vital scientific information. This technology has quickly

transpired into commercial use in the form of drones which are another example

of highly sophisticated and complex mechatronic systems. These are being

widely used for surveillance and security by law enforcing agencies across the

globe.

The articles to follow have illustrated various applications of mechatronics in the

modern day automobiles which I'm sure you would enjoy reading.


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4

About the AuthorsReecha Yadav

Ann Mary Sebastian

Areas of Interest

Automotive Electronics

Engine Management Systems

Control Systems

Areas of Interest

Computer Vision

Image Processing


Introduction toAutomotive Mechatronics


5

I. Introduction

Remember the cars and trucks turning into giant robots in the sci-fi movie Transformers? Or the small waste-collecting robot whose heroics help change the fate of mankind in Wall E? Or the might of the boxing robot mirroring his master's moves in Real Steel? In that case you are already aware of the potential that 'mechatronics' holds. The term 'Mechatronics', combining 'mechanical' & 'electronics', was coined by Japanese engineer Tetsuro Mori in 1969, with an aim of describing electronic control systems meant for mechanical factory equipment. Once dismissed as a fad, today one can hardly imagine building a mechanical system that doesn't have electronics in it.

According to experts, Mechatronics represents more than just 'mechanical' and 'electronics'. Figure 1 depicts the broader definition of Mechatronics as proposed in [1]. According to the figure, mechatronics is a convergence of mechanical systems, typically involving moving parts; electrical principles governing control systems, which in turn is implemented using electronic processor chips and sensors; along with software (computers) which endows character to the mechatronic devices. Thus, mechatronics can be considered as an overlap of: mechanical systems, electronic systems, control systems, and computers.

Figure 1. Definition of Mechatronics where mechanical,electronic, control, and software engineering all meet

and the varied application fields of mechatronics.

Talking specifically about the automotive domain, recently there has been a staggering increase in the use of mechatronics in automobiles. Few factors driving this surge are: the higher performance to price ratio offered by electronics, popular market demand for innovative products incorporating smart features and redesigning existing products to incorporate mechatronics

elements with an aim of reducing manufacturing costs. The following facts point to the expanding trend of mechatronic systems in automotive: around 23% of total manufacturing cost in luxury vehicles can be attributed to the electronic systems; more than 80% of all automotive innovation now stems from electronics; High-end vehicles today may have more than 4 kilometers of wiring compared to only 45 meters in vehicles manufactured in 1955.

Applications of mechatronic systems in the automotive domain range from features for safety enhancements (e.g. ADAS), emission reduction, intelligent cruise control, brake-by-wire systems (eliminating the hydraulics), and so on, to the holy grail of the automotive world i.e. the 'autonomous vehicle'. The following content attempts to shed more light on the various use cases of mechatronics in automotive.

II. Use Cases

A. Traction

In simple words, traction is the grip of a tire on a road. Several factors contribute to loss of traction. Some of them include conditions of the road, conditions of the vehicle, driver reaction. Technologies like Antilock Braking Systems (ABS) and Electronic Stability Control (ESC) help stabilize a vehicle during situations caused by loss of traction.

Antilock braking system (ABS)

The braking system in automobiles uses the

principle of hydraulic force multiplication and

friction to slow down a vehicle. The Anti-lock

braking system is considered to be the first

ever mechatronic product used in vehicles. An

ABS prevents the tire from getting locked in

the event of loss of traction or due to excessive

skidding of the wheel. This helps the driver

slow down faster and also enables him/her to

steer while stopping.

Speed sensors enable the ABS system to

determine when a wheel is locked or about to

get locked. This information is sent to the ABS

controller, which in turn, controls the valves of

the hydraulic brake system. The speed

sensors monitor the wheel speed and are on

the lookout for either a rapid acceleration or

deceleration which is a precursor to the

wheels getting locked. The ABS controller

then brings into action a pulsing effect at the

brakes which increases and decreases the

braking pressure by opening and closing the

valves rapidly. This helps keep the wheel

speed close to the speed required for optimal

braking performance. Thus preventing the

ControlSystems

Digital ControlSystems Control

Electronics

Computers

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MechanicalSystems

MECHATRONICS

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wheels from locking up, and improving the ability to steer during maximal braking [3].

Traction Control

Traction control helps a vehicle maintain its

grip on the road in low-friction conditions. It

controls the wheel slip and it works similar to

the ABS. In fact it uses the same components

as the ABS, i. e. wheel speed sensors,

contro l lers and hydraul ic pressure

modulators. A major functional difference

between ABS and Traction Control is the

reduction in engine throttle apart from braking

in the latter. Here the ECU constantly

monitors the wheel speed sensors to detect if

any wheel is spinning faster than the others. If

so, the controller initiates a pumping action at

the brakes by controlling the hydraulic

modulators [4]. Figure illustrates traction

control.

Figure 2. An illustration of traction control

(Image courtesy of Toyota Canada)

Brake-by-wire

Brake-by-wire systems were developed to

enhance the existing mechatronic systems

like the ABS and the Traction control with an

aim to reduce the weight and complexity of the

system. Such systems can be classified into

two types, electrohydraulic brake (EHB) and

electromechanical brake (EMB) [5].

EHB - Sensors on the brake pedal measure

the position of the pedal and the hydraulic

pressure. Manipulation of hydraulic fluid to

control the brake pressure is achieved using

magnetic valves which are controlled by signal

from the ECU which work upon the data

received from the sensors.

EMB - The electromechanical brake removes

the hydraulic system from the picture. The

position and pressure sensors on the brake

pedal, sends its information to the brake

processors, which in turn use electromotors to

apply the brakes. However, doing away with

hydraulics makes the EMB less fault-tolerant,

as there is no fail-safe alternative to the

electric system.

Electronic Stability control (ESC)

Bosch developed the first Electronic Stability

Control system. An ESC is fundamentally just

a set of problem correction methods which

ultimately prevent accidents. It makes use of

ABS and traction control to stabilize an

oversteer or an understeer. An oversteer is a

situation where the car veers off its course and

turns more than intended by the driver,

ultimately causing the car to spin. Whereas,

an understeer is when the front wheels do not

turn enough to maneuver a turn, and the car

moves forward instead of turning [6].

The heart of the ESC is the yaw control sensor. Along with steering wheel position sensors and vehicle speed sensors, it senses the difference between the driver's intention and the vehicle's response. When necessary the system applies brake pressure at the appropriate wheel in order to keep the vehicle on track. Braking is applied to the outer front wheel to counter oversteer or the inner rear wheel to counter understeer [7]. Figure 4 illustrates correction of oversteer/understeer using the StabiliTrak ESC system employed by GM.

Figure 3. Illustration of the StabiliTrak correcting an oversteer

Figure 4. Illustration of the StabiliTrak correcting

an understeer.B. Steering

Conventional steering systems were purely

mechanical and used either a rack and pinion

steering system or a ball and nut steering

system. It was in the 1950s, that Chrysler

introduced the hydraulic power steering

system in cars [8]. Such systems have a

power assist wherein hydraulic pressure helps

the driver turn the steering wheel with ease.

Modern s tee r ing sys tems can be

broadly divided into Electrohydraulic/

Electromechanical power steering systems or

Steer-by-wire systems.

Without Traction Control

With Traction ControlDi t onrec iof t elrav

1

2 3Desired path

1

2

3

Car fishtails on slippery road

StabiliTrak applies outside front brakeCar returns to desired path

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Car fails to turn on slippery road

StabiliTrak applies inside rear brakeCar returns to desired path

Desi drehpat

1

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Di en

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Electrohydraulic power steering systems - Such a system is similar to the hydraulic power steering system, however it is electric power that drives the hydraulic pump instead of the vehicle engine.

Electromechanical power steering

systems – Here the steering system is a

combination of the mechanical system and an

electric motor. The electric motor provides the

necessary power boost, thus eliminating the

need of a hydraulic system.

The only problem that could occur due to a

failure of the hydraulic system is that the driver

would need to put in extra effort to steer.

Steer-by-wire

This is a technology where the steering talks to

a computer which in turn talks to the wheels

using the steering rack. This can be divided

into two categories, one where the two wheels

are connected to a rack which is connected to

an electric motor. The other where, each

wheel is connected to independent motors.

Steer-by-wire system allows for more design

freedom, better ergonomics and comfort in

driver seating arrangement by omission of the

steering column. However, a major concern

associated with steer-by-wire technology is

the removal of the steering reversibility

phenomenon. Steering reversibility allows

road shock and wheel deflections to be felt in

the steering control. Removing steering

reversibility completely in steer-by-wire

system will cause a loss of this feedback from

the steering wheel to the driver. In order to

overcome this drawback, other feedback

devices were developed for steer-by-wire

systems.

In the year 1999, LORD Corporation

introduced a Tactile Feedback Device that use

the responsive nature of certain fluids to

magnetic fields. Such materials are called

magneto-rheological (MR) fluids [9].

Application of magnetic field causes an MR

fluid to change state from liquid to semi-solid

depending on the strength of the field applied.

This principle is used to produce a controlled

torque as feedback to the steering wheel. The

steering wheel angle sensor sends its position

to an ECU, which computes the torque

required for feedback based on velocity of the

vehicle, wheel position etc. The ECU output

controls the MR fluid thus creating feedback

torque according to the computed value.

Replacing the conventional mechanical or

hydraulic steering systems with electric power

steering systems or steer-by-wire systems

reduces the overall fuel consumption of the

vehicle. Steer-by-wire systems also enable to

design lighter vehicles and improve noise,

vibration and harshness performance of the

vehicle. However a failure in such systems

can lead to serious safety issues. Therefore in

order to maintain a high level of safety in such

systems, they must be designed to be fault

tolerant. Fault tolerance can be improved by

adding redundancy. One way of adding

redundancy is by adding similar components

and systems. Another way, is to add different

kinds of systems to make the entire system

failsafe e.g. adding a mechanical system as a

backup to the electronic system.

C. Powertrain

Continuously Variable Transmission (CVT)The transmission employs a range of gears, so as to effectively use the engine's torque, depending upon changes in the driving conditions. Traditional automatic transmission employ the conventional toothed, interlocking wheels to transmit and modify rotary motion and torque. However, this kind of transmission results in the driver experiencing jolts as each gear is engaged. Enters continuously variable transmission (CVT), which is a simple upgrade from a mechanical transmission sys tem to a mecha t ron i cs based transmission. In a typical rear-wheel drive, CVT mitigates the disadvantages of traditional automatic transmission by completely doing away with the gearbox. Commonly, CVT is based on a pulley system which enables varying between the highest and lowest gears without any discrete steps, thus eliminating "shift shocks". It is for this reason that auto-manufactures like GM, Audi, Nissan etc. are opting for drivetrain designs around CVTs. Moreover, CVT also helps keep the car in its optimum power range regardless of the car-speed, thus improving the fuel-efficiency [10].

Adaptive Cruise control (ACC)

ACC technology employs mechatronics,

wherein sensors and algorithms predict

accidents and actively avoid them within the

physical and dynamic limitations of the

vehicle.

D. Suspension

Imagine a vehicle without a suspension

system, you would be able to feel every bump

on the road. Suspension systems were

developed to ensure a smooth and

comfortable ride for the passengers. It plays a

major role in improving the ride quality and


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handling capability of a vehicle [11]. A few of

the recent innovations using mechatronics in a

suspension system include magnetic

dampers, active curve tilting and the

reinvention of the entire suspension system

itself by Bose [12].

Magnetic Dampers

These work on the principle of MR fluids,

which by varying the magnetic field through

them enable to adjust the stiffness of a damper

in response to road conditions. Also known as

magnetic ride control, such a system was first

introduced by General Motors. Each damper

consists of electromagnetic coils and fluid

passages through the pistons. Altering the

current through the electromagnets controls

force applied to the dampers. Body roll

sensors communicate to the ECU, which

further helps compensate for a roll by

controlling the current in appropriate dampers

[13].

Active Curve Tilting

Have you ever noticed how a motorcycle racer

negotiates a curve on the road? The rider

moves in the direction of the turn. Well, this is

in order to maintain his/her balance by

lowering the center of gravity and also

distributing the weight. Active curve tilting

enables a car to do just that. The technology is

designed to counter the effects of the

centrifugal force acting upon the car and its

occupants. The suspension is controlled in

such a way as to angle the car towards the

inside of the turn in order to lessen the lateral

acceleration experienced by the occupants.

Lateral acceleration sensors and stereo

cameras mounted on the windshield help

monitor curves and communicate to the ECU

to control the suspension system. Thus

enhancing the comfort of the ride.

Bose Suspension System

The Bose uses a linear electromagnetic motor

(LEM) at each wheel instead of the

conventional spring and damper system. The

conventional fluid based dampers have the

limitation of being affected by inertia, using

motors eliminates this, thus making it faster

and eliminating vibrations of the vehicle.

Conventional suspension systems, even the

most sophisticated computer controlled ones

can be considered as playing defense, while

the Bose suspension system, also called an

active suspension is playing offense. It does

not just react to the road conditions, but

proactively makes decisions using sensors,

the ECU and the motors attached to the

wheels, with an aim of not compromising the

ride and handling of the vehicle. Cost and

weight of the system are a major concern, and

are few of the reasons why the system is not

ready for mass production [11].

Figure 5. Toyota Pre-Collision Safety system [14]

E. Safety

Another factor responsible for the recent

surge of mechatronics in automotive is

'safety'. The success and demand of the

various 'intelligent' safety features (e.g. ADAS,

ABS) are testimonial of the power and

popularity of mechatronics in the auto

industry. These safety features involve

sensors (electronics), processing unit

(computer), control systems (electrical) etc. to

eventually direct the behaviour of the physical

(mechanical) system i.e. an automobile. Few

mechatronics based safety features are

discussed below:

Collision Preparation

Supplemental restraint

Dynamic Headlamps

Collision Preparation

Most of the cars today come with single or

multi-sensor based solutions, which increase

the real-time awareness (e.g. Lane Departure

Warning, Blind Spot Monitoring etc.) of the

driver to help avoid crashes. Figure 5 is an

illustration of the Toyota Pre-Collision Safety

system, wherein three different driver

assistance measures are chosen, impacting

the vehicle dynamics, depending upon the

probability of collision. Danger warning with

alarm and/or visual display helps alert the

driver to the possibility of an impending

collision. However, if sensors (electronics)

reflects a high probability of collision then the

controls part of the mechatronic system of

collision preparation comes into the picture in

the form of brake-assist. Intelligent brake

assist system automatically applies added

brake force in addition to that applied by the

driver to help slow the vehicle more quickly. In

case where the collision is totally unavoidable,

the collision preparation system prepares the

vehicle in terms of assisting in both,

preventing the collision as well as reducing the

damage sustained from collisions; by applying

the vehicle's brake system to help reduce the

severity of the impact [15].

l

l

l

l

Step 1 Step 2 Step 3 Step 4

Collision Collision isunavoidable

High possibilityof collision

Possibility of collisionDetection ofvehicle ahead

Diagramof systemactivation

Elapsed time

Danger warning with alarm and visual display

Brake Assist

Automatic Braking


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Supplemental Restraint System

Supplemental Restraint System (SRS) refers

to a passive safety feature which enables

airbag deployment based on inputs from

various sensors like accelerometers, impact

sensors, side door pressure sensors, seat

occupancy sensors etc. For predefined

thresholds on the sensor readings, providing

information regarding vehicle speed, the

angle and severity of the impact etc., a central

airbag control unit (electronic system) triggers

inflation of relevant airbags (physical system).

The utility of SRS is evident by its features like

seatbelt pre-tensioners (which tighten the

harness of the occupant holding them into the

seat in case of a crash situation), frontal

airbags, side bags, curtain airbags covering

the side glass, etc [16].

Dynamic Headlamps

Conventional headlights illuminate the area in

front of the car, however they seem little useful

wh i le go ing around curves. Enter

mechatronics based dynamic headlamps.

Such a system factors in parameters such as

speed, elevation and steering position to

illuminate the road ahead even as the driver

negotiates a turn. Individual sensors stream in

information regarding wheel speed (speed

sensor), vehicle's side-to-side movement

(yaw sensor), e.g., when turning a corner; how

far the steering wheel has been turned

(steering input sensor). The resultant data is

processed using an ECU to guide small

electric motors to turn the headlights so as to

move the beam by the required angle. An

additional self-levelling system helps guide

the headlight beam efficiently while driving

uphill or downhill [17].

F. X-By-Wire

Apart from the steer-by-wire and brake-by-wire systems discussed here, other X-by-wire systems are being developed. For instance, shift-by-wire, where the ECU controls the gearbox actuation in response to input sensed using Hall Effect sensors, using such a system, significantly reduces the weight of the gearbox and increases comfort of operation. Clutch-by-wire, eliminates the problems of stalling and also repeated use of the clutch pedal in stop-and-go traffic, making driving in manual mode easier. Drive-by-wire, such a system is not completely new, it has been used on fighter aircrafts. Here a computer operates all of the functions of a cars, from steering, to braking, to throttle controls and transmission shifting systems, in other words, controlling the car system totally by wire.

III. Conclusion

An automobile with multiple microcontrollers and electric motors, meters of wiring, an array of sensors and thousands of lines of code hardly qualifies for a strictly mechanical system. Clearly, it is one comprehensive mechatronic system which accounts for much of the value of the average automobile, managing everything from stability control and antilock brakes to active suspension and electro-mechanical power-assisted steering. However, the road ahead is not very smooth considering the startling increase in the complexity of automotive mechatronics system design of the future as the stakes rise on the number of components, their level of interaction, software code size etc. Going ahead, carrying out an optimal, efficient and seamless integration of mechatronics based components into the 'mechanical' dominated

automotive market ─ transforming dumb mechanical systems into smart mechatronic

systems ─ will help create a product differentiator for the automotive OEMs.

REFERENCES[1] K. Craig, "Automotive Mechatronics", 2008.[2] A. Brown, "Who owns mechatronics?", ASME Magazine, 2008.[3] Karim Nice "How Anti-Lock Brakes Work" 23 August 2000. HowStuffWorks.com.

<http://auto.howstuffworks.com/auto-parts/brakes/brake-types/anti-lock-brake.htm> 8 February 2016

[4] Brainonboard.ca, "Traction Control - Active safety features". [Online]. Available: http://brainonboard.ca/safety_features/active_safety_features_traction_control.php. [Accessed: 10- Feb- 2016].

[5] R. Isermann, Mechatronic Systems – Innovative Products With Embedded Control, 1st ed. 2005.

[6] Kristen Hall-Geisler "How Electronic Stability Control Works" 5 October 2009. HowStuffWorks.com. <http://auto.howstuffworks.com/car-driving-safety/safety-regulatory-devices/electronic-stability-control.htm> 10 February 2016

[7] http://gmfleet.com.prod-www.gm.plusline.net, "StabiliTrak Electronic Stability AssistG M T e c h n o l o g y | G M F l e e t " . [ O n l i n e ] . A v a i l a b l e :http://www.gmfleet.com/technology/stabilitrak.html. [Accessed: 10- Feb- 2016].

[8] J. Scoltock, "Francis W Davis invented a hydraulic power-steering system", Automotive Engineer, 2011. [Online]. Available: http://ae-plus.com/milestones/francis-w-davis-invented-a-hydraulic-power-steering-system. [Accessed: 09- Feb- 2016].

[9] D. Carlson, B. Marjoram, J. Toscano, D. Leroy, K. Burson, K. St Clair, A. Kintz and A. Achen, "Magneto-Rheological Technology and Applications", 2007.

[10] http://auto.howstuffworks.com/cvt.htm William Harris "How CVTs Work" 27 April 2005. HowStuffWorks.com. <http://auto.howstuffworks.com/cvt.htm> 10 February 2016

[11] William Harris "How Car Suspensions Work" 11 May 2005. HowStuffWorks.com. <http://auto.howstuffworks.com/car-suspension.htm> 9 February 2016

[12] E. Dyer and E. Limer, "3 Technologies Making Car Suspensions Better Than Ever", P o p u l a r M e c h a n i c s , 2 0 1 5 . [ O n l i n e ] . A v a i l a b l e : h t tp : / /www.popularmechanics .com/cars /a14665/why-car -suspens ions-are-better-than-ever/. [Accessed: 10- Feb- 2016].

[13] W i k i p e d i a , " M a g n e R i d e " , 2 0 1 6 . [ O n l i n e ] . A v a i l a b l e : https://en.wikipedia.org/wiki/MagneRide#History. [Accessed: 10- Feb- 2016].

[14] Toyota Motor Corporation Global Website, "Pre-Collision Safety | Toyota Motor Corporation Global Website", 2016. [Online]. Available: http://www.toyota-global.com/innovation/safety_technology/safety_technology/pre-collision_safety/. [Accessed: 09- Feb- 2016].

[15] media.gm.com, "Technology on XTS, ATS Can Help Avoid Crashes", 2012. [Online]. Available:http://media.gm.com/media/us/en/cadillac/vehicles/xts/2013.detail.html/content/Pages/news/us/en/2012/Mar/0328_atsxts_safety.html. [Accessed: 10- Feb- 2016].

[16] Allaboutautomotive.com, "Supplemental Restraint System :: All About Automotive Blog | A u t o R e p a i r S e r v i c e " , 2 0 1 4 . [ O n l i n e ] . A v a i l a b l e :http://allaboutautomotive.com/blog/category/supplemental-restraint-system/. [Accessed: 10- Feb- 2016].

[17] Brainonboard.ca, "Adaptive headlights - Driver assistance technology". [Online].Available: http://brainonboard.ca/safety_features/driver_assistance_technology_adaptive_headlights.php. [Accessed: 10- Feb- 2016].


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SC

IEN

TIS

T P

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E Scientist Profile

Dr. Takeo Kanade

About the

Areas of Interest

AuthorMs. Pranjali Modak

Intellectual Property RightsPatents

One of the world's foremost researcher in the field of computer vision, Dr. Takeo Kanade, is a Japanese computer scientist and a U.A. and Helen Whitaker Professor at Carnegie Mellon University. Born on October 24, 1945 in Hyogo, he received his Doctoral degree in Electrical Engineering from Kyoto University, Japan, in 1974. He has been associated with prestigious universities and institutes, like Kyoto University, Carnegie Mellon University and the Robotics Institute in various capacities.

Dr. Kanade works in multiple areas of robotics like computer vision, sensors, controls, multi-media, manipulators, autonomous mobile robots and medical robotics. His contributions cover a wide span from basic theories to total systems. He has more than 400 technical papers and more than 20 patents to his credit. He has also authored a couple of books on computer vision. He has been the principal investigator of more than a dozen major vision and robotics projects at Carnegie Mellon. He has served on various advisory boards, including the Aeronautics and Space Engineering Board (ASEB) of the National Research Council, NASA's Advanced Technology Advisory Committee, PITAC Panel for Transforming Healthcare Panel, and the Advisory Board of Canadian Institute for Advanced Research.

Dr. Kanade has a long list of honors, awards and achievements. Some of these are: The Bower Award and Prize for Achievement in Science from The Franklin Institute in Philadelphia, Pennsylvania; Marr Prize; Longuet-Higgins Prize for lasting contribution in computer vision; ACM/AAAI Newell Award; The C&C Award; Okawa Award; Tateishi Grand Prize; The Joseph Engelberger Award; FIT Funai Accomplishment Award; The Allen Newell Research Excellence Award; The JARA Award; IEEE Robotics and Automation Society Pioneer Award, FIT Accomplishment Award, and IEEE PAMI-TC Azriel Rosenfeld Lifetime Accomplishment Award.

He was inducted as a Fellow of the Association for Computing Machinery. He was elected as a member of National Academy of Engineering, the American Academy of Arts and Sciences and member of American Association of Artificial Intelligence, Robotics Society of Japan, and Institute of Electronics and Communication

Engineers of Japan. He is a Fellow of the IEEE, a Fellow of the ACM, a Founding Fellow of American Association of Artificial Intelligence (AAAI), and the former and founding editor of International Journal of Computer Vision. Recently, he is the Co-Director of the new Quality of Life Technology Engineering Research Center, a joint program established by NSF's funding between Carnegie Mellon and the University of Pittsburgh.

He is well known for the “Lucas–Kanade method”, which is widely used in the field of computer vision. It is a differential method for optical flow estimation. He developed this method along with Bruce D. Lucas. Some of his other notable work in the field of computer vision includes, The Tomasi-Kanade factorization method, one of the earliest face detectors, VLSI computational sensors, shape recovery from line drawings, stereo, motion image analysis and structure-from-motion theory. Since the mid-1980's he has initiated, led and collaborated on several major autonomous mobile robots and various application systems.

Dr. Kanade has been working on an interesting visual media, since 1995. It is named as "Virtualized Reality". With this concept, a time-varying event, such as sports, dancing or surgery, is captured by a large number of surrounding cameras. It is then transformed to a complete 4-D description (time, 3D, and appearance). One application of this was a Matrix-like replay system used for broadcasting portions of Super Bowl IIIV in 2001.

Over his career lifetime, Dr. Kanade has collaborated with researchers and students from a variety of scientific disciplines. These disciplines honored him with a symposium called “TK60: Celebrating Kanade's vision” on the occasion of his 60th birthday! The program reflected Dr. Kanade's diverse interests which span the areas of computer vision, medical and assistive technologies and robotics.

With today's growing need of computer vision technology in various domains like automotive, medical image processing, security systems, etc., we are lucky to have such valuable contribution by Dr. Kanade which will prove to be useful for developing current and future solutions for these domains.


11

Born : 24 October 1945

REQUIREMENT

SIMULATION IMPLEMENTATION


12

About the Author

Areas of Interest

Vehicle System Modelling

Simulation Simulink Control Algorithm Development

Signal Processing

Manu M Jayaramegowda

Model BasedMechatronics Requirements


13

I. Introduction

II. Simulink and Carmaker Tools

As vehicles till the 90's were driven completely by mechanical systems, the cost margin was on the rise. This was a result of mechanical wear & tear caused by friction, which also affected vehicle efficiency. Due to the increase in demand for efficient and customer friendly transport systems, OEM's are coming up with mechatronic equipment involving the introduction of Electronic Control System (ECUs) which helps to control the mechanical systems effectively. Nowadays as many as 70 ECUs are embedded in a high end car, thus increasing the co-ordination and complexity in developing a system. This article details the robust system requirements development for complex vehicle systems using Simulink [1] and Car Maker [2] tools.

A Vehicle System comprises of many s u b s y s t e m s ( m e c h a n i c a l & E C U components). These directly or indirectly interact either through protocols (e.g. CAN, LIN, FlexRay, and Ethernet) or through electrical signals. The challenge faced by any system engineer is the generation of a robust, testable, measurable, error free and unambiguous set of requirements for the development team.

System requirement generation is the first step in a V software development cycle. A strong set of requirements allows optimum use of time and resources in project execution. In accordance to the need of customers for a systematic process for requirement generation, we developed a method. This method uses Simulink and Car Maker tools to simulate vehicle system (control algorithms) and environment to generate and validate the requirements.

Simulink is an environment for simulation and model-based design for dynamic and embedded systems. It provides an interactive graphical environment and a customizable set of block libraries that let you design, simulate, implement, and test a variety of time-varying systems, including communications, controls, signal processing, video processing, and image processing.

Our other prime tool, CarMaker, introduces a paradigm shift towards an integrated development of concepts, models, control systems and components. It is especially suited for the global vehicle dynamics simulation of passenger cars, race cars, lightweight trucks, articulated Lorries and buses.

In contrast to common vehicle dynamics, CarMaker a l lows for a cont inuous development process: From office simulations on PC to Hardware-in-the-Loop (HIL) testing's on single ECU and multi ECU test systems including HIL testing's on large system testing rigs.

In this article a very well-known feature under Advanced Driver Assistance System (ADAS) domain called the Adaptive Cruise Control (ACC) [3] has been considered as an example to demonstrate our method for requirement generation. ACC (also known as radar cruise control) is an optional cruise control system for road vehicles that automatically adjusts the vehicle speed to maintain a safe distance from vehicles up ahead.

The Car Maker tool provides the following simulation options to develop the ACC environment:

Car – Provides an options to select desired

OEM's vehicle

Road – To simulate curve/straight/clothoid

roads

Maneuvers – To simulate vehicle

longitudinal and lateral

dynamics behaviors

Traffic – To create moving and stationary

objects

ACC project in Car Maker provides default Simulink blocks like Environment, Driver, Vehicle body and dynamics. These Simulink models provide an option to tap interface signals generated by default models. Required signals generated by models are passed through the ACC control algorithm which is built externally and integrated with Vehicle Dynamics Module. The integration of ACC control algorithm with Vehicle Dynamics Module is depicted in 2.

The Vehicle Dynamics module generates dynamics signals like host vehicle velocity, steering angle & rate, acceleration, brake pressure etc. ACC control algorithm taps and processes these signals as per the logic implemented and feeds it back to the car maker models. The algorithm results are immediately viewed in 3D scenario videos as shown in .

III. Car Maker Scenario Integration with Acc Control Algorithm

l

l

l

l


14

Figure 1: ACC feature – Host Vehicle following Target vehicle

Figure 2: Simulink model integration with Car Maker default blocks

ACC Control Algorithm is a function of several input data like host & target velocity, distance between host & target, steering angle, steering rate, acceleration, brake pressure and etc. Numerous algorithms can be developed in Simulink using available inputs from Car Maker to achieve ACC system simulation.

ACC system simulation results can also be viewed in Car Maker 2D scope as shown in . The Graph represents the velocity achieved by the host vehicle in co-ordination with the target vehicle. Car.V represents the host vehicle velocity and Traffic.Ahead01.LongVel represents the target vehicle velocity. Table 1 below shows the variations in velocity while following a target vehicle.

From the above table it is seen that due to change in target vehicle velocity from 66 KPH to 40KPH in 6s, there was a deviation of 2s to match with target vehicle velocity. This may be due to the following reasons

Latency due to hardware

Latency due to software

Network Latency

ACC System requirement GenerationBased on simulation results (Referring to figure 3) following system requirements were developed.

ACC system shall match the target vehicle

velocity.

ACC system shall not have time deviation >

2s so as to match to the target vehicle

l

l

l

l

l

velocity, provided the rate of change of

target vehicle velocity is 2KPH/s.

ACC System shall maintain 0% deviation

when target vehicle velocity is stable for

more than 4s.

ACC system shall lock the target vehicle

velocity in <1s if target is detected in the

host vehicle path.

l

l

Figure 3 : ACC Simulation Result – Host vehicle velocity followingTarget vehicle ahead

IV. ConclusionConclusion: For the system engineers who find it difficult to justify their requirements, this article will help them to develop the requirements in a systematic way by providing appropriate justifications. The system requirement generation methodology mentioned in this art icle is direct, unambiguous, realistic, testable and measurable, thus meeting the expectations of development team.

Enhancement : The default plant model generated by Car Maker is not actual vehicle model. Therefore, it is recommended to update the values of actual vehicle properties (Engine, power train, steering profile, vehicle body etc.) into Car Maker. To generate accurate results out of Car Maker it is recommended to integrate actual plant models (like Brake, Steering and longitudinal motion models) provided by respective OEMs. This ensures that your simulation results and system requirements are more inclined towards actual vehicle model.

References

[1] http://uk.mathworks.com/videos/introduction-to-simulink-81623.html

[2] http://ipg.de/simulationsolutions/carmaker/

[3] https://en.wikipedia.org/wiki/Autonomous_cruise_control_system

Abbreviations1. ECU – Electronic Control Units2. OEM – Other Equipment Manufacturers3. ACC – Adaptive Cruise Control4. ADAS – Advanced Driver Assistance System

Environment

ModuleTap the input data from car

maker model

Driver Module Vehicle DynamicsModule

Vehicle BodyModule

Output

Send the processed data back toCar Maker

ACC ControlAlgorithm

S. L. Sim.Time

Velocity(KPH)

Deviation Remarks

1. 22 to 28 66 to 40 2s Deviation due tocontinuous change intarget velocity at therate of 2KPH/s

2. 30 to 100 40 0 Better cruising duringstable velocity


15


16

Sensors and ActuatorsAbout the Author

Areas of Interest

Vehicle Electronics

Surface Engineering

Unmanned Aerial Systems (UAS)

Jayashri Kamagond


17

I. Introduction

II. Description of Technology

Driver and passenger comfort along with “Intelligent safety” have become the buzzwords in the automotive industry in recent times. To cater to these two aspects, there has been a corresponding increase in the use of Mechatronics within the vehicle. The two primary demands of safety and comfort, viz., reducing human interaction with the vehicle and increasing the degree of personalization are easily met by the deployment of mechatronic systems in vehicles. These systems cater to a variety of features such as power seats, electronic mirrors, and automatic climate control

Automotive design involves the collaboration of many engineering domains as shown below:

Figure.1: Multidomain design of an automobile [1]

Mechatronics finds application, thus, in many vehicle features spanning varied vehicle subsystems like Engine Management, Electronic Stability Control, Cruise Control and Body Control e.g., power door locks. These applications are described in the following section.

1. Car Engine ManagementCar engine management system consists of many electronic control systems involving microcontrollers, the engine control system being one. The aim is to control the amount of fuel to be injected into each cylinder as well as control ignition, engine revolution limit, turbocharger's waste gate, and variable cam timing. The system consists of sensors supplying, after suitable signal conditioning, the input signals to the microcontroller, which in turn provides output signals via drivers to actuators.

The engine speed sensor comprises a toothed metal disk mounted on the crank shaft and stationary detector. A magnetic coil is wound on the detector. As these metal teeth move past the coil, the magnetic field is disturbed and thus, a wave of pulses of electric current is created.

The temperature sensor is usually a thermistor whose resistance varies according to the temperature.

The mass air flow sensor may be a hot wire sensor, as air passes over a heated wire it will be cooled, the amount of cooling depending on the mass rate of flow. At temperatures higher than 300 degrees Celsius, the sensor allows oxygen ions to permeate, inducing a voltage between the electrodes.

2. Electronic Stability ControlElectronic Stabi l i ty Control ut i l izes

sophisticated sensors to feed information from

the outside world to a central processing unit.

Mainly three different sensors are used.

These are:

2.1 Wheel Speed SensorWheel speed sensor is used to measure the

speed of the wheel. This sensor is located at

each wheel.

2.2 Steering Angle SensorIt measures the direction the driver aims to

drive the car. This sensor is located at the

steering column of a car.

2.3 Rotational Speed SensorThe sensor consists of a magneto resistive

sensor element. The frequency of the digital

current output signal is proportional to the

rotational speed of the gear wheel.

3. Cruise Control Acceleration and

DecelerationThe cruise control system controls the speed

of a car by adjusting the throttle position.

Instead of pressing a pedal, cruise control

actuates the throttle valve by a cable

connected to an actuator. The throttle valve

controls the power and speed of the engine by

limiting how much air the engine takes in.

4. Power Door LocksIn this system, the door lock/unlock switch

actually sends power to the actuators that

unlock the door. In more complicated systems,

the body controller decides when to do the

unlocking. The body controller is similar to a

computer which monitors all of the possible

sources of locking and unlocking signal in a

car. The system monitors the radio frequency

and unlocks the doors when the correct digital

code is received from the radio transmitter.

The actuator moves the latch up as it connects

the outside door handle to the opening

mechanism. A reverse operation serves to

disengage the door handle from the opening

mechanism.

Controls

Electrical

Magnetic

Pneumatic Electro-Chemical

Thermal

Hydraulic

Mechanical

Direct fuelinjection

Electric throttlevalue control

Activesuspension

Brake-by-wire

Steer-by-wireElectrically assistedpower steering

42-Vconverter


18

III. Components for Mechatronics Implementation in Vehicles

l

l

– Sensors

These can measure a variety of physical variables such as light using photo-resistor, level and displacement using potentiometer, direction/tilt using magnetic sensor, etc.

– Actuators

In order to actuate various controls in the vehicle, actuators such as DC servomotor, stepper motor, relay, solenoid, speaker, etc., are used.

IC-based sensors and actuators (digital-compass, -potentiometer, etc.).

Electrical elements refer to:

– Electrical components (e.g., resistor (R), capacitor (C), inductor (L), transformer, etc.), circuits, and analog signals

Electronic elements refer to:

– Analog/digital electronics, transistors, thyristors, opto-isolators, operational amplifiers, power electronics, and signal conditioning

Control interface/computing hardware elements refer to:

– Analog-to-digital (A2D) converter, digital-to-analog (D2A) converter, digital

Input/output (I/O), counters, t imers, microprocessor, microcontroller, data acquisition and control (DAC) board, and digital signal processing (DSP) board

Control interface hardware allows analog/digital interfacing

– Communication of sensor signal to the control computer and communication of control signal from the control computer to the actuator

A computer to implement algorithms by taking inputs from sensors and providing actuation signals to the actuators connected at its output.

l

l

IV. Conclusion

Implementing mechatronic solutions emerges as a logical upgrade path for active safety electronics, in which the sensors and algorithms predict accidents and actively avoid them within the physical and dynamic limitations of the vehicle.

Suppliers need to develop cost-competitive

systems by creating multifunctional and

flexible systems for mechatronics to permeate

deep into the automotive industry. Developing

common standards between systems and

across the industry is also likely to allow for

cost leveraging by facilitating the sharing of

components.

[1] https://www.slideshare.net/mobile/sayedelhussieny/automotive-electrical-and-electromechanical-system-design

[2] "9-5 Electronic Stability Program." The Saab Network. (Nov. 14, 2008) http://www.saabnet.com/tsn/models/2002/pr9.html

[3] "Active Yaw Control." Mitsubishi Motors. 2008. (Nov.13, 2008)|http://www.mitsubishi-cars.co.uk/features/ayc.asp

[4] "Anti-Lock Bakes." MSN Autos. (Nov. 14, 2008) http://editorial.autos.msn.com/article.aspx?cp-documentid=435969

[5] "Differentials and Limited Slip Differentials." Driving Fast.(Nov. 13, 2008) http://www.drivingfast.net/technology/Differentials.htm

[6] Fischetti, Mark. "Steer Clear." Scientific American. April 2007.

[7] Jewett, Dale. "Moving the metal." Automotive News.Oct. 21, 1996.

[8] Lal, Vinay. "Natraja." Manas: India and Its Neighbors. (Nov. 13, 2008)http://www.sscnet.ucla.edu/southasia/Religions/Avatars/Natar.html

[9] Nice, Karim. "How Anti-Lock Brakes Work." HowStuffWorks.com.Aug. 23, 2000. (Nov. 14, 2008) http://auto.howstuffworks.com/anti-lock-brake.htm

[10] Nice, Karim. "How Differentials Work." HowStuffWorks.com.Aug. 2, 2000. (Nov. 13, 2008) http://auto.howstuffworks.com/differential.htm

[11] Rivoli, Cascine Vica. "Oerlikon Graziano Drive Systems." April 2007.

[12] "Saab XWD Cross Wheel Drive." Zer Customs. Nov. 20, 2007.(Nov. 13, 2008) http://www.zercustoms.com/news/Saab-XWD-Cross-Wheel-Drive.html

[13] "Turbo X World Premiere at Frankfurt Auto Show: Saab Unleashes 21st Century Black Turbo." Saab USA. Sept. 11, 2007.(Nov. 12, 2008) http://www.saabusa.com/saabjsp/about/pr_070911.jsp

[14] Y. Nemoto et al., “Development of Automotive Systems

[15] towards Environmental Protection and Safe Driving,” Hitachi

[16] Hyoron 91, pp. 755–759 (Oct. 2009) in Japanese.

[17] Y. Ohtani et al., “Development of an Electrically-Driven

[18] Intelligent Brake Unit,” SAE, 2011-01-0572 (Jan. 2011).

[19] R. Hirao et al., “Improvement in limit Region Performance of

[20] a Vehicle with Damping Force Control based on G-Vectoring

[21] Concept,” Proceedings of Technical Conference of the

[22] Society of Automotive Engineers of Japan, No.145 – 11 (Oct.

[23] 2011) in Japanese.

[24] Yano Research Institute, “Electric Power Steering Systems

[25] Market 2010,” (Sept. 2010) in Japanese.

References


19

( Position )

(Speed)

Y

X


20

Sliding Mode Controlfor Automotive Applications

About the Authors

Areas of Interest

Motor Design and Control

Power Electronics


Powertrain

On Board Diagnostics

Manish Bansal

Sandeep V. Ambesange

Areas of Interest

Model Based Powertrain Calibration

EMS Validation Engine Testing


21


22

I. Introduction

II. VSS and SMC

Motor control and design is a vital part of the multidisciplinary science 'Mechatronics', Motor control is critical in achieving low fuel consumption with minimal emissions if used in proper applications. This article focuses on the application of Sliding Mode Control (SMC) to motor control applications.

One of the prominent methods for designing the control system is VSS (Variable Structure System) approach. The variable structure systems consist of a set of continuous subsystems with proper switching logic and, as a result, control actions are discontinuous functions of system states, disturbances and reference inputs. A popular method for VSS control is the SMC (Sliding Mode Control) paradigm.

SMC is applied in the presence of the modeling inaccuracies, parameter variation and disturbances, provided that the upper bounds of their absolute values are known. It is known that standard PI control is not able to achieve speed stability in such systems.

SMC can appear in dynamic systems which are governed by differential equations with discontinous right hand sides.

Basic Concept

VSS are characterized by system structure change in accordance with current system states.

Consider a first order relay system with a state variable as (1),

Let r be the reference input, the error function can be defined as , where is the control as a relay function defined as (2)

The value of the error and the rate of change of error will have different signs if i.e. the error decays to zero in the finite duration of time at a finite rate. Thus, we can say that the system continuously switches its state at higher frequencies to give rise to the Sliding Motion.

Now consider a second order system as shown in (3),

If the above system is analyzed with the phase portraits, we see that the system consist of two linear unstable structures as shown in the figure below

Fig. 1 Portraits for the two unstable states of system in (3)

Using VSS, this system can be made stable by defining a suitable switching function with a control function (law). This switching surface is called as Sliding Surface. For this system, defining the switching function is given by (4)

Using VSS, this system can be made stable by defining a suitable switching function with a control function (law) This switching surface is called as Sliding Surface. For this system, defining the switching function is given by (4)

(4)

Where, c is a constant parameter.And the associated controller as

With , varying the system structure along , the sliding mode can be reinforced and the system can be made asymptotically stable. The corresponding sliding process can be as shown in figure 2

(5)

(6)

Fig. 2. Phase Plane of the Variable Structure system of (3)

Hence, by making the system to switch between the states the system is made stable. Also, the switching line is reached for any initial conditions. Let be the time required by the state to reach the sliding trajectory. One more interesting point can be made out from the solution [2] of the control law governing the system, which is given by (6),

is that the solution does not depend upon any of the system parameters i.e. the control is independent of the system parameters and disturbances.

X&

XX

X&

0=S

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0 0 >>candk

0&0 ==xS

(1)

e&


23

III. Application Of SMC for DC Motor

DC motors have their significant place in many of the industrial and commercial applications such as robotic arms where precision control of the speed is expected under the dynamic conditions [5].

The use of PI controllers here results in the increased settling times and the overshoots. Also, PI control presents difficulties in gain tuning for system parameter changes - for instance: winding temperature variation, converter switching effect, saturation etc. Such issues are easily taken care in SMC design.

A. DC Motor ModelThe general control structure for the DC motor can be represented as shown in the figure 3.

Fig. 3. Block Diagram of DC motor Speed Control

The speed of the motor can be varied by controlling the voltage fed to its windings. Depending upon the current, necessary gate pulses are generated by the chopper circuitry and necessary voltage is fed to the windings. The output speed of the motor is sensed and given as a feedback to compare with the desired/set/reference speed. Depending upon the control action, the current signal is generated through the speed controller. This current signal is taken as reference current and compared with the armature current with the help of a hysteresis current controller [6] and accordingly the gate pulses are generated for the voltage control. Here our main objective is to control the speed by controlling the voltage. The electric equivalent circuit of an electrical drive in its simple form can be represented as in figure 4.

Fig. 4. Electrical Equivalent Circuit of the DC Motor

Let be the measured speed and be the reference speed signal which is the desired speed of the drive. The main aim now is to design a controller such that it sets the speed to the desired value i.e. to control the speed of

the DC motor by controlling the voltage. The dynamics of the motor [2] are governed by the set of first order differential equations which are given by

(7)

(8)

Where is the armature current, L is is the armature inductance in , is the terminal voltage in volts, is the armature resistance in ohms, is the back electromotive force (EMF) constant, is the moment of inertia of motor rotor and load, is the motor torque constant and is the load torque.

The above model equations can be represented in the state space form as in (9)

(9)

B. Development of SMC Control Signal Better operation of the speed controller is guaranteed if the motor speed is maintained at the desired speed. The SMC controller is used to regulate the speed. This is done as below.

The speed error can be calculated as the difference between the reference speed and the measured speed .

Let

(10)

The change in error or the derivative of error is:

(11)

where, T is the sampling time interval and are the state variables. Now, the model equations of the motor can be represented in state space form as

(12)

Now selecting the Sliding Surface as

(13)

And is given by,

(14)

Here we are going to use the Power rate reaching law for the SMC which is given by (15).

(15)

Where

Substituting the value of equation (12) in (15) and solving, we can get the control law as

(16)

where the constant determine the convergence of the control law. The output of sliding mode control is taken as, current reference which is then given to the hysteresis current controller for generating the gate pulses.

ReferenceSpeed

SpeedController

HysteresisCurrent

ControllerChopper DC Motor

ActualSpeed

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mw

Vi

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24

IV. The Hyster is is Current ControllerHysteresis Current Controller is an instantaneous feedback system which detects the current error and produces directly the drive commands for the switches when the error exceeds an assigned band. The hysteresis controller is used to control the current and determine the switching signals for the chopper.

When then hysteresis controller gives output 0. When then it gives output equal to one [7]. In this way, Hysteresis PWM is used as pulse generator for chopper, so that current tracks the reference.

V. Simulation Results

A. SIMULINK MODELIn order to check the applicability of the developed control systems to practical drive systems, the physical model of the DC motor in the MATLAB/SIMULINK has been used with , and

Fig. 5. Hysterisis Current Controller

The SIMULINK model for the SMC is shown in figure 6 below

Fig. 6. SIMULINK Model for SMC Controller

B. Simlation ResultsThe simulations were carried out and simultaneously compared with the results of conventional controller performances [1].CASE I: The simulation for the load torque of 8 Nm and a set speed of 120 rad/s.

Fig. 7. Output of PI Controller Case I

Fig. 8. Output for SMC Controller CASE 1

From the above figures 7 and 8, we can observe that there is almost zero overshoot for the SMC controller where as there is a significant overshoot for the PI controller. Also the time required for SMC controller to reach the reference is less as compared to that of the PI controller.CASE II: The set/reference speed is kept constant and the load torque has been given a step change form 8 Nm to 16 Nm

Fig. 9. Output of PI Controller Case II

Fig. 10. Output for SMC Controller CASE II

In this case, there is significant overshoot in PI controller (figure 9) and also the time required to reach the reference speed of PI controller is more than that of the SMC controller. There is also variation in the response when there is the step change at 1sec which is not present in the SMC case (figure 10); this proves that the SMC controller gives robust performance for the load disturbances.CASE III The reference speed is subjected to change form 120 rad/s to 160 rad/s with constant load torque. From the above figures it can be observed that for the change in speed, the response of SMC (figure 12) is better than PI controllers (figure 11) with respect to both peak overshoot and settling time.

Fig. 11. Output of PI Controller Case III

Hysteresis band (HB)

Compensating current = icx Reference current = ic

Jpper hysteresis limit = i + HB/2c

Lower hysteresis limit = i + HB/2c

Switching pulse

off

on

2

2

Wref

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WZero-orderHold1

x1

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Saturation2C

Idoef

x

PI Controller

Time (sec)

Spe

ed (

rad/

s)

00

50

100

150

0.5 1 1.5 2 2.5

Reference SpeedActual Speed

SMC Controller

Time (sec)

Spe

ed (

rad/

sec)

00

50

100

150

0.5 1 1.5 2 2.5


PI Controller

Time (sec)

Spe

ed (r

ad/s

)

00

50

100

150

0.5 1 1.5 2 2.5


SMC Controller

Time (sec)

Spe

ed (

rad/

sec)

00

50

100

150

0.5 1 1.5 2 2.5


PI Controller

Time (sec)

Spee

d (ra

d/s)

00

50

100

150

0.5 1 1.5 2 2.5


200

W=05.0aR HL 01.0=205.0 kgmj =

)2/(* HBII cc +>

)2/(* HBII cc -<

CASE IV: The SMC contoller is immune to the

parameter variations which can be observed

form this case (Provided that the parameter

variations are well in limit without braeking

down the operation). Here we have changed

the armature resistance of the motor and

compared it to the results of case 1. We

observe that for SMC controller (figure 14), the

peak overshoot and the settling time is same

but for PI controller (figure 13), there is an

increase in the settling time and a slight

increase in peak overshoot.

Fig. 12. Output for SMC Controller CASE III

Fig. 13. Output of PI Controller Case IV

Fig. 14.Output for SMC Controller CASE IV

The peak overshoots and the settling time

problems can be filtered out by PI controller,

but we have to go for tuning of the gains.

However, in doing so we have to compromise

at one of the either characterstics i.e. by

decreasing overshoot, there is an increase in

the settling time and vice versa.

VI. Conclusion

This paper describes the technique of Sliding

Mode Control automotive applications such as

air-fuel ratio control, camless engines etc. As

an example, the strategy for speed control of

DC motor using the technique of Sliding Mode

Control has been elaborated and a

comparison with the traditional PI controllers

has been presented.. The SMC gives better

performance, as compared to PI control,

under load disturbances and paramter

var ia t ions i .e . i t gurantees robust

performance. Hence in many of the

applications where accurate control is very

important and critical problem, SMC can be

effictively used to design the controller.

References

[1] Ambesange, S.V.; Kamble, S.Y.; More, D.S.,

"Application of Sliding Mode Control for the speed

control of DC motor drives," in Control

Applications (CCA), 2013 IEEE International

Conference on , vol., no., pp.832-836, 28-30 Aug.

2013

[2] Vadim Utkin, Jürgen Guldner Jingxin Shi, Sliding

Mode Control in Electro-Mechanical Systems,

CRC Press Boca Raton, 2009

[3] Hung, J.Y.; Gao, W.; Hung, J.C.; , "Variable

structure control: a survey," Industrial Electronics,

IEEE Transactions on , vol.40, no.1, pp.2-22, Feb

1993

[4] B. K.Bose, Power Electronics and AC Drives,

Printice Hall, 1986

[5] M. Golam, Md. Abdur and B. C. Ghosh, “ Sliding

Mode Speed Controller of a DC Motor Drive”,

Journal of Electrical Engineering, The Institution of

Engineers, Bangladesh, vol. EE 31, No. I & II,

December 2004

[6] G. K. Dubey, Fundamental of Electrical Drives,

Tata McGraw-Hill, New Delhi, 2006

[7] S. Y. Kamble, S. V. Ambesange and M. M.

Waware, "Capacitor voltage regulation in Shunt

Active Power Filter using Sliding mode controller,"

Control Applications (CCA), 2013 IEEE

International Conference on, Hyderabad, 2013,

pp. 1135-1140.

[8] J. B. Gupta, Theory and Performance of Electrical

Machines, S. Kataria & Sons, 2009

[9] Wilfrid perquetti and Jean-Pierre Barbot, Sliding

Mode Control in Engineering, CRC Press, 200

SMC Controller

Time (sec)

Spe

ed (

rad/

sec)

00

50

100

150

0.5 1 1.5 2 2.5


200

PI Controller

Time (sec)

Spe

ed (

rad/

s)

00

50

100

150

0.5 1 1.5 2 2.5


SMC Controller

Time (sec)

Spe

ed (

rad/

sec)

00

50

100

150

0.5 1 1.5 2 2.5



25


26

Automotive Smart Actuators

About the Authors

Areas of Interest

ADAS

Guidance and Control Algorithm Design

Sensor Data Fusion

Vehicle Dynamics and Model Based Design

Prashant Vora


27

I. Introduction

II. Smart Actuator

Original equipment manufacturers (OEMs) are adding more and more advanced driver assist functions or improved manual control features and functions for improved performance and safety. As technology evolves over period, vehicles continue to become more autonomous. This makes mission and motion planning critical. Integrated and coordinated control among sub-systems will be required to have optimized performance combined with safety.For integrated control, multiple sub-systems (Steer, Transmission, Brake, and Engine) need to be integrated, and synchronized actuator control is required.

In the present vehicles, the major sub-systems (steer, brake, engine, transmission, and suspension) use actuators, which are tightly coupled with individual Electronic Control Unit) ECUs. Respective ECUs control the actuators for vehicle motion, so in the present architecture, it is difficult to achieve integrated and coordinated control without modifying the existing ECU software. The software modification for each ECU is complex. This leads to maintenance and cost issues with addition of newer features.

The solution for this problem is to have smart actuators and sensors that are not directly coupled with individual ECUs but are able to r e c e i v e c o m m a n d o n c o m m o n communication bus. Smart actuators and sensors are thus cost-effective solutions that convert control logic into smart motion.

Smart actuators are independent mechatronic sub-systems having their own electrical, electronic, and mechanical components like motor, gear, amplifier, along with ECU with software and communication medium (Figure 1). The smart actuator shall be able to control its own actuation based on command from other ECUs on communication bus.

The actuator control system has a unique address. It accept all signal from the vehicle control system and responds only to signals with its own address.

A smart actuator has its own sensor, application software and base software so that it can achieve required control action based on command inputs on the communication bus. The actuator can also return position and speed information. The actuator will also have self-diagnostic capability and in case of fault, it will communicate to other ECUs on the communication bus.

Figure 1: Smart Actuator

III. Smart Actuator Block Diagram

As shown in Figure 2, the blocks of a smart actuator consist of:

a) Central processing Unit (CPU) is processing unit which perform arithmetic, logical and IO (Input and Output) operations.

b) memory is used for store data during program execution that can be used by CPU during execution

c) a transceiver is interface between CAN controller and communication bus. It converts digital signal from CAN controller to the electrical signal required as per communication bus and vice versa

d) signal for controlling motor is generated using PWM Pulse Width Modulation (PWM);

e) an analog-digital converter that allows the analog signals of the sensors to be adapted to those of the digital processor, and

f) a voltage regulation module that adapts input at the correct levels.

The application software is part of the MCU (Micro Controller Unit) and has feedback control algorithms, which control the motor control based on reference input from the communication bus. The control strategy can be adapted based on the type of control required for specific application of actuator.

Figure 2: Smart Actuator Block Diagram

IV. Smart Actuators: Function Description

l

ll

In norml mode of operation, a smart actuator performs the following operations:

Receives desired reference signal from the communication busReceives signals from sensorCalculates control commands based on reference signal and sensor signal

Battery Voltage

Communication Bus

- Diagnostic

- Torque / Position / Speed Command

- Set up / Calibration Command

Gear BoxMotorECU

Battery

Co

mm

un

icat

ion

Bu

s

VoltageRegulator

Relay

Power

MCU

Memory

CPUTrans

receiver CAN

ECU

BridgeCircuitPWM

ADC

DIO

ReductionGear

ElectricMotor

Sensor

Electro MechanicalAssembly


28

l

l

and checks accuracy of sensor data and performs actuation operation in case of no faults in sensor or actuator

Communicates information to other ECUs regarding the action performed along with sensor inputs.

Smart actuators are also capable of compensation and self-calibration.

Continuously monitors health of actuator

V. Case Study of Integrated System Architecture with Smart Actuator

Advance Driver Assist System (ADAS) is developed to automate or adapt in certain situation so that it enhances comfort driving and improves. It alerts driver in case of potential problem. Chassis control systems are mainly overriding systems. It covers active safety task and achieve controllability in case of unstable dynamic situation. ADAS and Chassis system also control engine or transmission for specif ic features / functionality.

Today ADAS, Chassis, and Powertrain Systems are implemented in coexisting ECU's as shown in Figure 3a. Proprietary sensors and individual actuators are connected to specific ECUs.

As shown in Figure 3b, in case of Co-existent architecture, vehicle level control (outer loop) is achieved by ADAS. The inner control is achieved by the chassis controller (steer, brake, and suspension) or engine and transmission control depending on the ADAS feature . The in tegrated cont ro l is accomplished on the system level with absolute priority concerning actuator access to respective subsystem control.

Figure 3a: Co-existent System Architecture

Figure 3b: Control Architecture

As a result, vehicle level control (ADAS

control) is loosely coupled and it is not

possible to achieve the ADAS functionality

(e.g. adaptive cruise control, lane centering,

Autonomous Emergency Brake) in all

scenarios. If the integrated architecture is

developed using smart actuator, intervening at

sub-system level can be eliminated and there

will not be absolute priority at subsystem level.

The example for an integrated architecture

and control is shown in figure 4a and 4b. The

functions related to lateral and longitudinal

motion can be integrated in one ECU. The

complex networking between systems and

functions will be controlled by a coordinator, so

that the vehicle level dynamic control can be

achieved in all scenarios for ADAS features.

The vehicle level sensor, perception sensors

and sub-system sensors required for specific

sub-system (brake, suspension, steer,

transmission, and engine) can be connected

to a central data processing unit. The central

data processing unit can be connected to

ECUs through communication bus. The smart

actuators can be connected to the

communication bus and perform dedicated

control tasks based on control commands

from a dynamic controller.

Figure 4a: Integrated System Architecture

Sensors

Perception Sensors

Steer

Camera Radar

LIDAR Ultrasonic

Vehicle Sensors

IMU GPS

Subsystem Sensors

Suspension

Brake

Engine

ControlFunction

Transmission

Steer Brake Engine

Transmission

Detection

Detection Detection Detection

Observer Observer Observer

ControlFunction

ControlFunction

ControlFunction

Observer

Control Units

ADAS

Detection

ControlFunction

Fusion

Active Spring &Dampers

Transmission

Engine

FPB

Brake Booster & BrakeActuator

Power Steer

Actuators

Suspension

Detection

Observer

ControlFunction

Real Time Bus

Control Signal

Driver Setting

(if applicable)ADAS Control

Environment(Vehicle, Pedestrian,

road marking etc) PerceptionSensors

Subsystem levelsensorsVehicle

Sensors

Engine Control

Suspension Control

Brake Control

Steer Control

Transmission Control

Sub-systems control

Vehicle(Lateral andLongitudinalDynamics)

Sub-systems

Steer

Brake

Suspension

Engine

Transmission

Sensors

Subsystem Sensors

Steer

Engine

Brake

Suspension

Transmission

Perception Sensors

Camera

UltrasonicLIDAR

Radar

Vehicle Sensors

GPSIMU

Control Units

Central Sensordata processing

Observer

Fusion

Detection ADASControl

Coordinator

Dynamics Motion Control

Real Time Bus

Steering Braking Suspension

Engine Control TransmissionControl

Suspension

Active Spring &Dampers

Power Steer

Brake Booster & BrakeActuator

EPB

Engine

Transmission


29

VI. Benefits of Smart Actuator

l

l

l

With smart sensors and actuators,

distributed and layered system architecture

can be built. The architecture can be easily

scalable for any future requirement.

By using a smart actuator with a bus, only

single cable is required rather than running

a separate cable from the controller to each

actuator as in case of the traditional

approach.

As smart actuator use communication bus

for receiving command from control ECU, it

reduces substantially the cost and

complexity of integrated vehicle operation.

l

l

VII. Conclusion

With bus communications, a single control

unit can replace the need for separate

controller for different functionality

Actuators also offer the advantage of

providing status information. As smart

actuator is a plug and play unit,

replacement in case of any failure is easier.

Smart Actuators offer significant benefits for

advanced automotive technology. It is

possible to design modular and system level

integrated architecture using smart actuators,

which will enable the design and development

of complex integrated control for partial or

complete autonomous operation.

Toni Viscido, IKA, Germany, “Integration of

Chassis and Advanced Driver Assistance

Systems”, CITA conference 2005

Abbreviations

References

[1]

There is a possibility in the future, multiple

applications can combined into single

onboard computers with smart actuators to

deliver unique functionality.

Advance Driver Assist System

Analoa to Diaital Converter

Controller Area Network

Central Processing Unit

Digital Input and Output

Electronic Control Unit

Electric Power Brake

Global Positioning System

Intertial Measurement Unit

Light Detection And Ranging

Micro Controller Unit

Original Equipment

Manufacturer

Pulse Width Modulation

Radio Detection And Ranging

ADAS

ADC

CAN

CPU

DIO

ECU

EPB

GPS

IMU

LIDAR

MCU

OEM

PWM

RADAR

Definition Abbreviation


30

BOOK REVIEWB

OO

K R

EV

IEW

Author - Sarah Miller Caldicott

Michael J. Gelb and

Innovate Like Edison

“That is a good book which is opened with expectation and closed with

profit.” –Amos Bronson Alcott

This is what came to my mind when I read the book “Innovate like Edison”.

We all unanimously agree that Edison was one of the best innovators of

our times. He has 'enlightened' us in many ways and needs no

introduction. Nevertheless, it is worth to mention that he had about 2368

patents in his 62 years. In today's world, every organization strives for

innovation and thousands of people across the globe want to innovate but

there is no one way to innovation. However, Edison seemed to have the

essence of innovation. When I laid my hands on this book this is what I had

expected. I had expected to understand what made Edison so different

and how did he manage to create such successful businesses from his

ideas. The book addresses these expectations aptly.

The book is divided into 3 parts, the first one talks about the light bulb

invention and the life of Edison. The second part of the book is the most

interesting and details five competencies or skills of innovation that include

solution centered mindset, kaleidoscopic thinking, full-spectrum

engagement, master-mind collaboration and super-value creation. The

third part of the book tells us how we can expand Edison's legacy in the

21st century.

To explain the solution centered mindset the authors have given excellent

analogies. One of the analogies to explain the term mindset is that if one

wants to buy a hybrid vehicle then one would ask a question “Which hybrid

vehicles are best for me?”. Followed by which every time one drives on the

road she would notice Toyota Prius, Saturn VUE etc. In addition, the

person would automatically notice all the advertisements, hoardings,

magazines related to energy-efficient vehicles. This would happen

because the persons mind is set on hybrid. Thus, our mindset reflects our

sense of purpose and that is what helps us organize our perceptions.

Edison had a clear purpose that of bringing out the secrets of nature and

applying them for the happiness of humankind. He believed that his

success was inevitable and this energized him during his work. His

solution-centered mindset helped him to embrace complex challenges

and then overcome all the hurdles that he faced. Edison was an optimistic

person and his optimism had a magnetic effect on his co-workers,

investors and customers. He was strongly optimistic because he always

aligned his goals with his passion. The book further discusses how one can

achieve a solution-centered mindset like Edison.

The authors refer to kaleidoscopic thinking as the ability to look at multiple

problems at the same time and to look at each one from different

angles. Edison had this ability and he worked on 40 projects

simultaneously. The books tells us how to develop this ability to

generate ideas, make creative connections and identify patterns. It

teaches us how we can think visually by picturing things in our mind.

The full spectrum engagement has been related to the ability of

focusing on innovation even when you are stressed out or

overworked. The book stresses that time management is not the

answer here. The authors talk about how innovators should seek

knowledge relentlessly. Like Edison, every innovator should ask

questions and try to understand everything that is required for taking

the idea forward. Edison would read up on what others have tried in

the past. He also did one more thing unlike other innovators. Like

books, he also had many ores, minerals and all kinds of materials

stacked on his shelves. He would not just read about but experiment

and experience things. This led to multiple sensory engagement and

many hands-on experiences. His became skilled to an extent that he

could predict the results of his experiments based on different

materials being used. The authors mention about skills like speed-

reading books that can be learned from Edison.

The concept of mastermind collaboration was introduced by

Napolean Hill and this inspired Edison. Edison frequently interacted

with his co-workers because he believed that the meetings resulted in

positive and creative energy with the combined brainpower. He

believed in having people with skills in different domains and free

exchange of ideas among them. Edison also rewarded his

collaborators very generously including sharing royalty amounts for

ideas that were marketed.

The fifth competency mentioned in the book is about creating value.

Edison always worked towards only one goal that of creating

exceptional value for his future customers. During his early career, he

realized that coming up with creative ideas was good but that will not

keep him in business for long. To get ahead and be successful he has

to create and deliver. He was good at linking market trends with his

own strengths. He had spawned about 150 business but hand only six

parts in his business model i.e. manufacture, sale, distribution,

customer service and commercialization. Edison would purchase

rights of patents from his competitors so that he had something to sell

while his ideas were under development. He was also able to

understand scale-up effects i.e. he knew that prototyping an idea was

a challenge but another equally challenging part was to take it to

masses. He would do excellent branding of his ideas to his future

customers through live product demonstrations.

The last part of the book involves several assessments to understand

where one stands in terms of innovation. The book also then guides

the innovators to use a ninety days innovation literacy plan that guides

innovators to identify specific goals that are relevant and achievable

with some timelines. The plan also includes identifying ones emotions

while going through the process of innovation.

This book is a definite guide on challenges and practical approach

towards the innovation process and is necessary read for all those

who are passionate to take their ideas to market.

About the Author

Priti Ranadive

Areas of Interest

OS

RTOS

Parallel Computing

Embedded Systems


31


32

About the Authors

Areas of Interest

System Engineering

Chassis & ADAS Application

Cruise Control

Active Spoiler

Manjunath Rangaswamy

Jamsheed Kolothum Thodi

Areas of Interest

Algorithm & Software Development

Active Suspension

Cruise Control

Active Spoiler

Active AutomobileAerodynamic Surfaces


33

I. Introduction

Aerodynamics mainly deals with the forces acting on the vehicle due to air resistance. When vehicle is in stationary state, all the surfaces of the vehicle body will be at atmospheric pressure. Once the vehicle starts moving, the pressure exerted on the body of the vehicle changes proportional to the square of the velocity by which the vehicle is moving. This pressure adds resistance to the motion.

The main two forces of interest in automobile are drag and down force (opposite to lift) which is shown in the below :

Figure 1 : Aerodynamic forces acting on vehicle

Management of these two forces is crucial for

performance and fuel efficiency of the vehicle.

Minimizing drag improves the fuel efficiency of

the vehicle. Maximizing the down force

increases the loads on the tires without

increasing the weight of the car. The result is

better handling and stability at higher speeds

and cornering. The down force also provides

advantages when braking at high speeds. The

downside of increasing down force is that it

contributes to drag as well. So the automotive

engineers always try to maintain an optimum

'lift/drag' ratio to have maximum down force

within some allowable drag limit.

Automotive industry makes use of spoilers to

have an optimum 'lift/drag' ratio. Spoilers can

be fitted either front or rear. Racing industry

makes use of underbody diffuser as well.

Maximizing the down force by passive spoilers

almost always can only be achieved at the

cost of increased aerodynamic drag and the

optimum setup is almost always a

compromise between the two.

Down force exerted by the spoiler wing is

calculated by the following formula.

Where:

is down force in newton

W is spoiler wing span in meterss

H is height of the wing in meters

It is clear from (1) that down force is

proportional to square of velocity of the vehicle

and it requires a certain minimum speed in

order to produce a significant down force. So

having a passive spoiler does not offer any

significant advantage. Moreover, it can cause

a drag effect which will affect the fuel

efficiency.

The recent development in aerodynamic field

is the introduction of active aerodynamics.

Active aerodynamic consists of movable

parts, which change their position based on

vehicle speed or by driver input to improve

lift/drag ratio only when required and

necessary.

In this article, we discuss Active Rear Spoiler

(ARS). This system has been designed to

maintain a "clean" rear-end style for

showroom conditions, while still delivering the

necessary aerodynamic down force required

at high vehicle speeds to maintain vehicle

stability.

Rear spoiler in the deployed state creates a

high pressure area that pushes down the rear

of the car as shown in Figure 2.

II. Description of Technology

Figure 2 : Spoiler and down force

Active spoilers are controlled by different

methods such as pneumatic actuation,

hydraulic actuation and electro mechanical

actuation.

21)(

2

1VCHWD Ps a=


34

D

deployment of angle is a

lift oft coefficien is iC

3 ̂kg/min density air is r

m/sin velocity is V

ARS systems use an electro mechanical

setup. They consist of a geared electrical

motor attached to a single shaft as shown in

Figure 3. This mechanically rotates four bar

hinge mechanisms on each end of the shaft,

which extend/retract the spoiler. The action is

a single stage deployment or retraction. The

motor is powered by an H-bridge circuit

consisting of two relays.

Figure 3 : ARS Mechanism

A. Block Diagram

Heart of the system is an electronic computer

(ARS computer). ARS computer operates the

relays which actuates the electric motor to

deploy or retract the spoiler. Spoiler/motor

position is determined using two micro

switches operated by a cam connected to the

motor shaft. Micro switch status is feedback to

the ARS computer to close the loop. ARS

computer uses the micro switch feedback to

determine the position of the spoiler. A high

level block diagram of ARS system is as

shown in Figure 4.

Figure 4 : ARS Block Diagram

B. Types of Control

The types of control modes available for ARS

system are Fully Active Control and Driver

Activated Control.

1) Fully Active Control Mode

Fully Active Control mode is designed to

provide a fully autonomous actuation of the

spoiler. This is accomplished by ARS

computer taking vehicle speed sensor input

and different vehicle parameters like gear

position and parameters which vary across

vehicle variants etc. to calculate when to

deploy and retract the rear spoiler. Speed

thresholds at which spoiler deploys and

retracts are configurable in ARS computer

during development phase. This gives the

flexibility for tuning during development

phase, so that spoilers can be made available

only when it is required to provide down force

to keep the vehicle stable.

2) Driver Activated Control Mode

Driver Activated Control mode is designed to

give the driver to control the active rear spoiler

using a switch in the middle console. A brief

press of the switch causes the spoiler to

deploy to the fully extended position and

pressing and holding the switch cause full

retraction of the spoiler. ARS computer

receives the driver switch input from the Driver

Interface Module and take the decision to

operate the relays accordingly. This control

mode is available both in a static environment

and below a determined speed.

Driver activated mode is inhibited above the

automatic deployment speed of the spoiler to

ensure vehicle stability at higher speed for

safety reasons.

In case of failures (electrical or mechanical), if

the system is not able to operate the spoiler,

then ARS computer displays a warning

message on the Message Console for driver

information. It also takes necessary steps to

keep the vehicle in safe state at higher speeds

by limiting the maximum speed.

III. Specific Issue Encountered & Methodology Applied

A. Meeting Functional Safety Standards

As ARS ensures vehicle stability at high

speeds, failure to deploy the spoiler at high

speeds results in vehicle instability and may

leads to severe accident scenarios. ISO

26262 - Functional Safety for Road Vehicles

VehicleSpeedSensor

VehicleSpeed

SwitchInput

DriverInterface

MessageConsole Warning

Message

CAN ARSComputer

De

plo

ye

d

Re

tra

cte

d De

plo

y

Re

tra

ct

Motor

Micro SwitchAssembly

SpoilerAssmebly

Drive 2

Relay H-Bridge

R2

R1Drive 1


35

Standard shall be used for hazard identification and risk classification of the system. In order to meet the higher safety level we need to have electrical redundancy to address the failure situations. But the redundancy comes with the cost wherein we need to ensure robust communication between main & redundant module.

1) Use Case for RedundancyFor an example, one of the OEM's (Original Equipment Manufacturer) added redundancy using the external module to control the actuator power. The requirements were given to external module to switch OFF the actuator supply whenever the speed was greater than deployment threshold + delta or when the ignition is OFF. The main module had to meet the requirement to allow the driver to retract the spoiler for specific period after ignition is turned OFF. When the Software went for production there was lot of DTCs (Diagnostic Trouble Codes) reported with respect to actuator supply failure. After investigation it was found that vehicle power mode status monitored to determine ignition OFF state were different between main & redundant module.

B. Variant Specific ChallengesOEM builds many vehicle variants such as Coupe, Convertible, Racing pack etc. aiming different customer classes. Variants pose many challenges due to varying aero-dynamic behavior. For e.g.: spoiler wings in deployed state compromise vehicle top speed over vehicle handling. Computer has to take decision without compromising vehicle handling but still achieve top speed.

Compromise on top speed due to spoiler deployment is illustrated mathematically below.

Drag force experienced by the vehicle is

The top speed is defined when the propulsive

force of the engine equals that of the drag force.

ARS system addressed this challenge by re-designing aerodynamic shape of the spoiler and introducing a Racing Control mode. In Racing Control mode the driver can stow the spoiler at high speed to meet the speed demand. The redesigned aerodynamic shape of the spoiler provides just enough down force to keep the vehicle stable even at retracted state. ARS system still has to deploy the spoiler wing for sharp corners to keep the vehicle stable. In such situations ARS computer will take decision to exit Racing Mode and go to Fully Active Control mode and deploy the spoiler. Once the vehicle passes through the corner ARS computer switch the mode back to Racing Control mode and stow the spoiler.

C. Market Specific ChallengesOEM's introduce same vehicle in different markets (geographical locations). Vehicles sold in different markets have to comply with the legal regulations in that market region. Sometimes these legal regulations lead to a design modification or a modification in the control strategy of the system. Depending on the impact on the vehicle, OEM's have to take wise decisions.

Certain markets have legal requirement, driven by vehicle insurance, on low speed crash impact. These rules restrict deploying spoiler beyond the rear bumper at low speeds. If the spoiler in fully deployed state overhangs the bumper, then without having a change in the design, these vehicles cannot be sold in those markets.

Multi-stage and multi-direction adjustable spoilers are the future trends in active spoilers. Multi-state spoilers can be deployed stage by stage considering vehicle speed and other vehicle and environmental conditions. Multi-direction spoiler can be deployed at different angles or directions depending on the need.

Active diffusers are another area which is increasing in popularity in the racing industry. These devices lower once the vehicle speed crosses a certain threshold and help in reducing the drag.

Retractable vents and in-motion height adjustments are other active aerodynamic designs to keep vehicles firmly planted on the road while maintaining optimum efficiency

IV. Expected Future Growth in such Application Areas

References[1] Katz, Joseph. Race Car Aerodynamics: Designing for Speed.[2] Merkel, James P. “Development Of Multi-Element Active Aerodynamics For The Formula SAE Car” [3] https://www.quora.com/What-are-some-cars-that-have-active-aerodynamics[4] https://en.wikipedia.org/wiki/Spoiler_(automotive)[5] https://en.wikipedia.org/wiki/Downforce[6] http://www.buildyourownracecar.com

When spoiler deploys, effective area increases and the top speed get compromised.

2

2

1VACF dPd =

V

PFp =

(2)

(3)

3

1

2÷÷ø

öççè

æ=

AC

PV

dP

Equating (1) with (2) gives the top speed


36

m/sin velocity is

3 ̂kg/min density air is

drag of coefficent is

atmosphere toexpose area is

newtonin force drag is

V

C

A

F

d

d

r

Where,

Where,

speed vehicleis

at wheel producedpower is

force propulsion is

V

P

Fr


37


38

About the Author

Areas of Interests

Control Systems Design

Systems Modeling and Simulation

Model Based Development

Jestin Karlose Thekkeveetil

Electric Power Steering –Technology Trends


39

I. Introduction

II. Description of Electric Power Steering (EPS)

Steering is an important vehicle control

function contributing to the safety of the

vehicle. Technology of steering system has

evolved, starting from pure mechanical

steering to power assisted steering and

advanced steering with many control

functions for safety and driver comfort.

Mechanical steering connects the driver

steering wheel to steering column and

mechanism to orient the wheels to control the

direction of vehicle motion. Disadvantage of

the mechanical steering is the large amount of

force driver has to apply on the steering wheel

especially at low vehicle speeds and on bad

roads. Addition of a hydraulic actuator on the

steering mechanism gave additional force to

assist the driver to steer with less effort. Initial

problems with hydraulic mechanism were

leakage of hydraulic fluid, vibrations and fire

hazards etc. Electro hydraulic actuator gave

provision for better control of the hydraulic

force. Hydraulic actuator was replaced by

electric motor for more efficiency, better

control and low maintenance. With electronic

controller and software, more control and

compensation functions are added into

electric power steering (EPS) making it more

robust, smooth to transform it to a driver

comfort feature.

A. System Overview

Figure 1: Schematic of EPS system check all fig if thishas been taken from any copyright content

If yes mention references, or redraw

Electric power steering consists of a mechanism to couple an electric motor to the steering system, sensor to measure steering torque, steering angle etc., electronic controller and embedded software as shown in Figure 1. Motor can be coupled to the steering mechanism through steering column, rack or pinion. Steering torque is measured by measuring the torsional displacement in the column using non-contact sensors. Motor is

usually a Brushless Direct Current (BLDC) or Permanent Magnet Synchronous Motor (PMSM) to provide required torque assist and dynamic response. Electronic controller interfaces with the sensor and provides the necessary monitoring and controls the motor to provide required assist torque. The embedded software does the sensor signal processing, monitors vehicle states through Controller Area Network (CAN) messages, executes the motor control algorithm, checks necessary diagnostics and provides safety and fail safe states [2].

Figure 2: EPS boost curve

B. Sensors and ActuatorsTorque sensor is a critical part of the EPS that measures the torque applied by the driver on the steering wheel. The steering column consists of a torsion bar and the rotation in the torsion bar is proportional to the driver torque. Non-contact type optical or magnetic torque sensor produces pulses as per the rotational displacement in the torsion bar. Battery voltage is measured using Analog to Digital Converter (ADC) input to the controller. Resolver or encoder is used for motor position sensing. Motor should have high torque and efficiency, less torque ripple and heating. Motor phase currents are measured through voltage drop across shunt resistor. Pulse Width Modulation (PWM) signals from the controller drive the motor phases through a set of Metal Oxide Semiconductor Field Effect Transistors (MOSFET).

C. Electronic ControllerElectronic control receives input signals from the sensors , CAN messages from the vehicle bus, executes the software, produces the PWM signals that drives the power switching devices to excite the motor. The controller has ADC interface to receive voltage input measurements and digital I/O s for receiving status signals.

D. Embedded SoftwareSoftware executes the sensor and actuator signal processing, receives vehicle CAN messages, determines the vehicle state, computes the desired torque demand and executes the motor control loops to generate required assist

Steering Wheel

Gear box Motor

Motor Drive

Vehicle speed

Vehicle StatesECU

Motorcurrentposition

TorqueSensor

10

20

30

40

50

60

70

-10 -8 8-6 6-4 4-2 20 10

V = 100 kphV = 80 kphV = 60 kph

V = 40 kph

V = 20 kph

V = 0 kph

Driver torque (Nm)

Ass

ist

torq

ue

(Nm

)


40

torque. In addition, the software executes the diagnostic routines to detect faults with the sensors, actuators and CAN messages and switch the operating mode to reduced functionality level in order to provide fail safe. Also the diagnostic routine logs correct Diagnostic Trouble Codes (DTC) in case of detection of faults. Prognostic routines are executed to limit the operation within the safe level. For example: reducing the motor current to limit the motor temperature.

Basic control functions of the EPS is the torque control and the motor control as shown in Figure 3. Assist torque is determined based on the driver torque and the vehicle speed, using a lookup table representing the boost curve as shown in Figure 2. Purpose is to provide high assist torque at low speed and reduce it gradually as the vehicle speed increases. This is because of vehicle is difficult to steer at low speed and easy to steer at high speed because of varying tire-road friction. Assist torque also increases with increase in driver steering torque. Selection of boost curve is dependent on the vehicle parameters such as mass, inertia and tire characteristics etc. Proper tuning of the boost curve contributes to steering stability and driver comfort [3].

III. EPS Control Functions

Figure 3: EPS basic controls

EPS control also provides a feature of returning the steering wheel to the center just after the steering is completed and driver release the steering wheel. This is achieved by measuring the steering wheel angle and using it for feedback control to bring to zero automatically. Damping is applied through the control loop so that the steering wheel comes back to the center without oscillations or overshoot.

Desired torque from the torque control is input to the motor control to achieve the steering. Motor control is based on field oriented control.

The software has diagnostic routines to check the faults in CAN messages, sensor and actuators, hardware peripherals like ADC,

IV. Diagnostics, Safety and Fail Safe

Digital I/O etc. Once the faults are detected, DTCs are logged for diagnostic services. More importantly, based on criticality of the fault, the system goes to safe state with reduced performance. For example, if the CAN message of vehicle speed fails, the system assumes a set speed and continues at reduced level of assist. More severe faults like torque sensor fail results in steering assist completely disabled and the steering can work in a limp home mode with just manual steering as shown in Figure 4. Recovery from limp home mode is possible from service station. Motor current and temperature are monitored to take action to limit the motor current in case of motor temperature exceeding the allowable limit. Motor current also reduces if the battery voltage goes below a limit to prevent battery charge

Figure 4: EPS Diagnostics, safety and fail safe

V. Advanced EPS FeaturesAdvanced EPS features are for better driver comfort and safety [1]. They provide necessary compensating torque to provide robustness in EPS control as shown in Figure 5. Following are some of the advanced features.

A. Friction CompensationFriction between road and tire varies based on the type of road, vehicle mass, vehicle speed, steering velocity, yaw rate and the tire characteristics. Additional assist torque is introduced to compensate for friction so that performance of the steering is smooth and stable.

B. Inertia CompensationEffect of inertia of the vehicle is severe during steering reversals resulting in a steering lag. This can be compensated by additional assist torque generated based on the steering velocity, yaw rate and vehicle parameters.

C. Torque Steer CompensationImbalance in engine torque transmitted to the left and right wheels causes undesired steering disturbances. The effect is more when the vehicle is accelerating and the vehicle may be pulled to left or right. Main cause of torque steer is unequal length of left and right axles due to which torque transmitted

DriverSteeringTorqueVehicleSpeed

SteeringWheelAngle

Assist torquedemandBoost curve

Dampingtorque

Returntorque

Active ReturnControl

DampingControl

ComputerMotor

currentDesiredMotor

Current

MotorControl

PWMSignals

Motor Current

Motor Drive

Motor

CANMessages

Sensors

Motor

ECU

Diagnostics Safety and Fail Safe

FaultStatus

ReducedPerformance

[Mediumfault]

[Severefault]

NormalOperation

Limp homeMode

[Severefault]

[Nofault]


41

draining off.

to the wheels are slightly different. Torque steering is also caused by unequal tire characteristics on left and right. This includes difference in tire radius or thread due to wear, or difference in tire inflation. Because of torque steer, driver has to exert additional steering torque to balance the vehicle and causes driver discomfort.

D. Pull Drift CompensationEffect of road crowning or steady wind has a gradual effect on the orientation of the vehicle. Road crowning causes gravitational pull to one side of the vehicle causing changes to the vehicle steer over a period of time. In case of steady wind laterally, it causes vehicle orientation to drift. Compensation of the factors result in better driver convenience while driving on straight roads. Automatic compensation involves recognizing the scenarios, estimating the impact and applying necessary compensation through assist torque.

Figure 5: Function diagram of EPS software

VI. Problems and Technical ChallengesEPS has inherent problems due to stability and vibrations.

A. StabilityCharacteristics of EPS system changes due to conditions of the road, vehicle speed, yaw rate and external disturbances. At high speeds and slippery road conditions, the steering system can become unstable leading to over steer. Proper tuning of the boost curve and providing required damping through motor control can maintain stability and good performance.

B. VibrationsVibration in the steering is due to spring compliance of the torsion bar of the steering column, gear box and motor coupling and the torque ripples in the steering as well as external disturbances like rough roads. Selection of the design parameters to keep the resonance frequency of the system away from the operating frequency is the basic necessity. Gearbox and coupling design has to be analyzed to improve the design. Vibration introduced by the motor torque ripple can be reduced by current control loop compensation techniques.

VII. Technology Advancements

Recent advancement in steering is the Active Front Steering (AFS) and Four Wheel Steering (4WS).

AFS uses variable gear ratio to convert steering wheel rotation to the steering column rotation. At low speeds and parking it increases the gear ratio so that driver need to turn less to make full turn of the vehicle. At high speeds where steering requirement is less, the gear ratio is reduced so that it will not cause over steer. It uses a mechanism with planetary gear system coupled with electric motor to achieve the objective. Main advantages of the AFS is stability and driver comfort.

In 4WS, both front and rear wheel are turned to steer the vehicle [6]. 4WS works in two modes of operation. At low speed such as making a sharp turn at traffic junction, U-turn, parking maneuver etc., the rear wheels are turned in opposite direction of the front wheels. This results in smaller turning radius there by resulting smooth and faster turning of the vehicle. At high speeds, steering is used for lane correction or lane change. In that case, the rear wheels are turned in the same direction as the front wheel and avoid over steer of the vehicle. Benefit of 4WS at high speed is the stability of the vehicle.

VIII. Vehicle System Integration

A. Automatic ParkingAFS is an important technology advancement to achieve automatic parking. Using AFS, the steering angle can be precisely controlled based on estimated orientation of the vehicle and the path planning. Interface between the automatic parking and AFS is the steering angle updated dynamically based on the desired path and actual path of the vehicle.

B. Automatic Lane Keeping AssistAutomatic lane departure control involves camera based lane detection system, estimation of lane departure and steering correction and actual steering adjustment to maintain the vehicle within the lane. Estimated steering correction is transmitted to the EPS to achieve desired steering correction.

C. Vehicle Stability ControlSteering is an important aspect in the vehicle stability especially at high speeds and slippery roads. Global chassis control integrates Antilock braking (ABS), Suspension, steering, Yaw and Roll stability controls to have an intelligent vehicle control.

DriverSteeringTorque

VehicleSpeed

SteeringWheelAngle

Assist torquedemand

Boost curve

Dampingtorque

Returntorque

Active ReturnControl

DampingControl

Currentdemand Limit

Motor current

ComputerMotor

current DesiredMotor

Current

VehicleStates

TorqueCompensation

Fiction Inertia TorqueSteer

PullDrift

Advanced features for torque compensation

CAN, I/O, Signals,ECU status

Limits/Constraints

DiagnosticsSafety

and Fail Safe


42

IX. Steer By Wire

Steer by wire does not have a direct

mechanical link between driver steering wheel

and the steering mechanism connecting to the

wheels of the vehicle. Measurement of the

steering wheel angle is used by the control

system and translated to the mechanical

movement using actuation of the electric

motor.

Elimination of many mechanical components

make the steering system assembly compact

and easy and less maintenance. Vibrations

due to road disturbances, gear box and motor

are not transmitted to the driver steering

wheel. Also, elimination of the steering column

avoids the resonance vibration problem in the

conventional EPS.

Steer by wire is one of the steps towards

autonomous vehicles [5]. Steering commands

from the autonomous driving system is directly

transmitted to the motor control system to

achieve desired steering without involving the

steering wheel and the steering column [4].

[1] Aly Badawy, Jeff Zuraski, Farhad Bolourchi and

Ashok Chandy, “Modeling and Analysis of an

Electric Power Steering System” in Society of

Automotive Engineers, 1999

[2] Hiroyuki MIYAZAKI, “TECHNICAL TRENDS IN

STEERING SYSTEMS” Symposium on Fluid Power,

TOYAMA 2008

[3] Valentina Ciarla, Violaine Cahouet, Carlos Canudas

de Wit, Franck Quaine, "Genesis of booster curves

in Electric Power Assistance Steering Systems",

HAL Id: hal-00744384, https://hal.archives-ouvertes.

fr/hal-00744384, Submitted on 23 Oct 2012

[4] J.-H. Kim and J.-B. Song, “Control logic for an

electric power steering system using assist motor,”

Mechatronics, vol. 12, no. 3, pp. 447–459, 2002.

[5] Z. Jianjun, Z. Man, C. Min'gang, L. Su, and L. Bin,

“Automatic navigation system for electric power

vehicles with EPS,” in Proceedings of the IEEE

Vehicle Powered Propulsion Conference (VPPC '08),

September 2008

[6] Saket Bhishikar, Vatsal Gudhka, Neel Dalal,

Paarth Mehta, Sunil Bhil, A.C. Mehta, “Design and

Simulation of 4 Wheel Steering System” in

International Journal of Engineering and Innovative

Technology (IJEIT) Volume 3, Issue 12, June 2014

References

Environmentally FriendlyElectric cars enjoyed popularity between the mid-19th century and early 20th century, when electricity was among the preferred methods for automobile propulsion, providing a level of comfort and ease of operation. Advances in technology which reduced prices of gasoline cars to less than half that of equivalent electric cars, led to a decline, effectively removing it from important markets.

However, in recent years, increased concerns of the environment has brought about renewed interest in electric cars,which are perceived to be

more environmentally friendly. In December 1982, Naval Tata received a letter from P. G. Thakar enclosing photographs of an electric car owned by Sir Dorabji Tata.

The car worked on electric power derived from accumulator batteries and worked on 110 volts. The peculiarity of this car was that it had no steering wheel. It had two horizontal rods, one near the driver's seat and the other near the back. The car could either be operated from the front or from the back using these horizontal rods.

It had no gears or clutch but one regulator with variable speeds. It had 30-40 mph speed and could run 40 miles on one charge. After that the batteries had to be recharged. The Tata Hydro Companies had a fleet of such vehicles for heavy transport.

In his reply Naval Tata said: “I remember Sir Dorabji Tata driving the car by Miller. I also Lady Meherbai Tata driving the car sitting from the back seat by using the two horizontal rods.”

Reference - http://www.tatacentralarchives.com/tata_trivia/tata_trivia.htm


43


44

Predictive Efficiency ManagementUsing Driver Assistance Systems

About the Author

Areas of Interest

Advanced driver assistance systems

Connected cars

Vimalkanth K


45

I. Introduction

At the Paris climate conference in December 2015, a legally binding global climate deal. The agreement charters a global action plan to put the world on track to avoid irreversible climate change by limiting global warming to much below 2°C. One of the action plans is to reduce the emissions and this is clearly a job at hand for the Automotive OEMS to introduce new techniques to close in the gap between the real driving fuel consumption and the emission.

OEM's specifications of fuel consumptions and Co emissions are based on the New 2

European Driving cycle and the EPA Federal Test procedures. Though, it has never been the claim to generate representative Figures for all driving circumstances in real customer use cases, OEMs are striving to reduce the gap between the advertised fuel efficiency (from the driving cycle) and the real world fuel efficiency.

Driver assistance aims at reducing the fuel consumption by using the intelligent connection of on-board sensors, as these sensors provide information about the upcoming driving situation and preparing the vehicle for optimal operational efficiency.

II. Predictive Horizons

l

l

l

Looking ahead and anticipating upcoming driving situation has always been the key for safe, comfortable and efficient driving, because in an unfamiliar road, the driver is not aware of upcoming curves or speed limits or how long the traffic light remains red. Until recently the cars did not have the ability to look ahead and it was the task of the driver to:

select correct gear before entering a narrow curve,

release the throttle in advance to avoid unnecessary braking,

initiate a motor stop when stopping for more than several seconds,

which are a few situations where anticipation is helpful. Complexity rises when vehicles become more electrified. For example, it would be quite challenging for the driver of a hybrid electric car to control the battery's state of charge manually to enable the battery management systems to regenerate the maximum amount of brake energy on the next hill-descent.

It becomes important to introduce predictive features in the vehicle by combining the route ahead with the vehicle system state to optimize the operating strategy of the vehicle.

The horizon ahead of the vehicle became predictable with the help of eHorizon systems, which hold the topological information about the roads including curvature, slopes, junctions, roundabouts, traffic signs etc.

The required prediction range and data resolution varies with the scope of a particular predictive feature. Therefore, different sources of information are used, creating discrete virtual horizons stretching from only a few meters to several hundred kilometers. The three prediction horizons are illustrated in Figure 1.

Figure 1: Predictive horizons

The longest prediction range is available when the driver uses the vehicle's navigation

sys tem . Based on t he map da ta complemented with real time traffic

information (RTTI), the road characteristics can be determined all the way until the final destination. This particular horizon is relevant for all features that affect long term planning like the vehicle's operating strategy. Therefore, the most relevant characteristics of this horizon are estimated speed, slope, road type and remaining distance and driving time as they affect the vehicle's energy demand. Sensor data from camera or radar play a subordinate role since decisions are made based on information far beyond visual range.

For the second group of predictive efficiency functions, the focus lies on predictive longitudinal guiding in a medium to short range horizon. Typical situations that can be detected are: changing speed limits and slopes, curves and turns but also vehicles in front. Therefore, this horizon consists of fusion of sensor and map based data.

Stop on the move, for example is a situation adaption feature, in which only short prediction distances need to be covered. The camera system plays an important role in this feature.

I I I . P r e d i c t i v e E f f i c i e n c y Management (PEM)

Look ahead information such as speed, slopes, road types, road curvature, information about the road types and other topographical information are stored in a special kind of maps called the ADAS maps.


46

Once the driver sets a destination through the navigation systems in the vehicle, the information about the most optimised selected route reaches the eHorizon system. The algorithm inside the eHorizon extracts the data out of the ADAS maps based on the route information provided to it. The topographical information about the entire journey can be extracted at once and conveyed to the predictive efficiency management system at the very outset of the journey.

ADAS applications continuously receives the information about objects, other vehicles on the road and traffic signal information using the RADAR and cameras. This information is transmitted to the PEM along with the ACC status and its set speed values.

The PEM is a part of the power train control module in the vehicle and communicates through the Ethernet /CAN/flexray to the eHorizon and the ADAS.

Figure 2: Predictive efficiency management

As illustrated in Figure 2; based on the information received from the eHorizon and ADAS,

PEM creates a situational intelligence continuously throughout the journey.

A command generator in the PEM gets both the line of sight and beyond line of sight information from the situation intelligence.

Supervisory control in the power train control module continuously feed engine running status and drive mode (battery or ICE operation) and the information about battery to PEM.

Based on the information, PEM calculates the operational limits of the battery by calculating the remaining SoC.

The supervisory control takes this information to switch the transmissions between the battery and ICE on the go.

Coasting and stop on the move commands are given to the supervisory control based on the traffic information and the gradient

l

l

l

l

l

l

information.

The supervisory control calculates the required torques and clutch commands for the optimised driving which results in the real world fuel efficiency.

As illustrated in Figure 1, predictive feature in the power train and transmission control unit are classified into three different types based on range of data required for the operation. One feature, each using long range, mid-range and line of sight data are described below :

l

A. SoC Management in Hybrid and Electric Vehicle

Default strategy of a Plug in hybrid vehicle is to maximize use of battery at the very outset of the journey. As depicted in the Figure 3, knowing the gradients and speed in advance for a long journey helps to fully utilize the essence of the electric driving. Full electric driving in low speed zones and near the final destination is ensured. Depending on the predicted speed near the final destination, this function prepares the vehicle for an electric driving zone of variable length, even if the battery state of charge is low.

Figure 3: SoC depletion rate

In short, the PEM budgets the energy needs of the vehicle by collecting the topographical data in advance. Upcoming downhill sections with the possibility to regenerate energy are detected at the start of the journey and processed in PEM. So the charge depletion is carefully monitored so that it does not go beyond the threshold from where the charging is not possible through a regenerative braking.

This way the use of battery is optimized which results in the real world fuel efficiency and an emission free electric driving for even longer stretches on the road.

B. Intelligent ACC and Adaptive Gear Shift

Fuel efficiency reduces greatly due to unnecessary braking, idling and acceleration. The PEM along with the cruise control systems can intelligently adapt the speed and shifts gears based on the characteristics of the road and traffic rules coming up. The intelligent ACC adapts to the speeds based on the inputs coming from the ADAS maps, which avoids the braking by the driver on a road zone having a speed limit less than the set speed.

TractionBattery

Engine

ElectricMachine

TransmissionClutch

Command

Limits

AbsoluteSoC

EM

torque

torque

Supervisory

Control

HybridMode andpropulsion

torqueManagement

State ofCharge

Management

Coasting andStart stop

Management

EnginerunningstatrusSpeed

Driver mode

Battery

Information

SoCOpearational

limits

SOTM inhibit

Coasting inhibit

PEM

Situation Intelligence

SoC limits, costing andSOTM command generator

eHorizon

ADAS(RADAR

andCamera)

Speed,topologyand road

typeinformation

ACCstatus

and Setspeedvalue

with out PEM

SOC

with out PEM

30

30

30

60 5050

70 70


47

Figure 4: Automated gear shift using predicted road topology

Figure 5: Inefficient stop Vs efficient stop

The cost of restart is the basis of the feature SOTM, which calculates the time required for the engine restart at a particular situation on the road .The RADAR and the camera systems along with the topology maps predicts the flow of the traffic and assists the PEM to calculate stop time. At 4-ways stops in residential areas where the traffic is rare, the stop time will be less than the cut-off time te, PEM will increase fuel efficiency by providing a situation based strategy.

Predictive energy management features are being deployed in various vehicle segments from 2012. Commercial vehicle OEMs started to use it first in Europe, followed by the premium passenger car manufacturers. The real world fuel efficiency improvement of around 7 to 9% were reported ever since its inception. With the advancement in sensors and road mapping technologies and driven also by the new emission norms, it is fast transitioning from 'good to have' to a 'must have' feature for OEMs.

IV. Conclusion

Abbreviation

References

[1] http://www.audi-technology-

portal.de/de/mobilitaet-der-zukunft/audifuture-

lab-mobility/audifuture-engines/praediktiver-

effizienzassistent, 2012.

[2] http://www.scania.se/images/Scania%20Active%

20Prediction%20-%20Presentation_tcm85-

287549.pdf

[3] https://www.press.bmwgroup.com/usa/download.

html?textId=161119&textAttachmentId=198820

[4] https://www.daimler.com/innovation/efficiency/int

elligent-driving.html

VEHICLE STAYS IN IDEAL GEARPREVENTION OF UNNECESSARYGEAR SHIFTS

AUTOMATIC TRANSMISSION SWITCHES TOLOWER GEAR AHEAD OF THE CORNERINCREASED DRAG TORQUESUPPORTS DECELERATING

SOVEREIGNACCELERATING

INCREASEDCOMFORT

Gear selectionw/o foresight

Gear selectionw/ foresight

8

7

6

5

87

6

5

67

86 5 67

8

inefficientengine stop

efficientengine stop

Auto Start Stopfuel savings

cost of restart

time / ste

fue

l s

av

ing

s /1

ACC

PEM

SOTM

ADAS

RTTI

SoC

ICE

A daptive cruise control

Predictive efficiency management

Stop On the move

Advanced driver assistance systems

Real time traffic information

State of charge

Internal combustion engine


48

In addition to using speed limits for predictive driving, topology will also be used in the ADAS for Cruise Control to generate a benefit in fuel consumption. Using downhill situations in order to save energy, coasting generates kinetic energy that can be used for battery charging.

Knowing the road ahead will assist the automated gear system in the vehicle to switch to an appropriate gear and optimize the consecutive gear changes .As illustrated in Figure 4 ,not only the gear shifts are avoided, PEM also ensures that the vehicle stays in ideal gear by knowing the road beyond the next bend and avoid wastage of fuel.

C. Situation Adaptation – Stop on the move

Current auto Start stop systems cuts off theengine during a stop, especially at a trafficsignal. The driver can activate the function instandstill by simply putting the gear intoneutral and releasing the clutch. Wheneverthe driver depresses the clutch, the engine willautomatically start again. The electric starterand fuel injection will speed up the engine

in Figure 5. The cost for the restart is mainly

determined by the inertia and losses of theengine.

to idling speed. While the current design of the

function significantly decreases the fuelconsumption especially in urban drivingenvironments, there is still room for furtherimprovement. Turning off the engine, forexample at a stop light, will reduce theengine's idling consumption to zero.Depending on the duration of the stop, there isa break-even between the cost for the restartand the Auto Start Stop fuel savings, as shown


49


50

Future Trends inAutomotive Mechatronics

About the Authors

Areas of Interest

Image Processing

Machine Learning

Future Technologies

Smita Nair

Narendra Kumar S S

Areas of Interest

Programming and debugging

Computer Networks

Cyber Security

Internet of Things

Areas of Interest

Machine Vision

Artificial Intelligence

Data Mining

Naresh Adepu


51

I. Introduction

II. Evolution from Mechanical to Mechatronics

The automotive industry is in the grip of a new revolution. This is being driven by advancement in the field of mechatronics. Mechatronics functionality is highly explored in the area of robotics, especially the industrial robots and the days are not far when such robots would be plying our roads as autonomous vehicles or driverless cars.

The increasing demands for high level of reliability, better performance, enhanced safety and comfort is driving the market for smart innovative products. Safety and comfort remains the key areas of development for the automobile industry. Safety features provided by the advanced driver assistance systems (ADAS) is revolutionizing the automotive industry. Features such as automatic braking systems (ABS) and the cruise control functionality, that was seen only with the upper vehicle segment is finding way into the regular models. With driver comfort given equal importance to safety, various comfort features such as advanced human-machine-interface (HMI), real time Internet and self-learning cars seems to be the next reality. Analysis has shown that with increased sophistication in the vehicles, the future drivers would be in a more confused and stressed out state, especially the older generation. Tremendous research to understand the driver's state under various real time scenario is being carried out. In the coming years, our cars would be more human like, handling the role of a virtual companion that would provide the driver a stress free drive.

In this article, we discuss the latest developments and the future trends in the area of mechatronics as related to automotive domain.

The term 'Mechatronics' first defined by Yakasawa [1], is the merger of electronics and mechanical streams that would create a seamless border between the two fields in the future products. As per K.Criag [2], key requirement for modern day engineering design should meet performance, reliability, low cost, robustness and sustainability. The multidisciplinary field of mechatronics addresses this key requirement and the best example is the automotive industry. In the beginning, automobiles were pure mechanical systems for e.g., the first gasoline powered vehicle by Carl Benz in the late 19th century and which is now moving towards the autonomous trend by 2020.

The early automobiles were purely

mechanical or electrical systems with radio as the only electronic device until mid of 20th century. The introduction of microprocessors in the early 1980s revolutionized the traditional ways of engineering designs. New developments in the areas of Internet, wireless technology, smart sensor designs and embedded architectures form the core of development of mechatronics products. Internet and wireless technology together are also revolutionizing mechatronic products. Today's electronic control units (ECU's) are making use of these communication technologies to exchange data and take quick decisions. Mechatronics systems of today are running 8-bit, 16-bit and 32-bit central processing units

(CPU). For example: seat, mirror control, and

window lift systems are using 8-bit

processors. Antilock brake system (ABS),

traction control system (TCS), vehicle

dynamics control (VDC), instrument cluster,

and air conditioning systems are using 16-bit

p r o c e s s o r s ; e n g i n e m a n a g e m e n t ,

transmission control and airbags are using 32-

bit processors [1].

Safety is the most important aspect in the

design of automobile, with various disruptive

technologies that have emerged for

passenger safety. The safety glass windows

were introduced by Cadillac in the year 1924,

followed by the seat belts that was offered by

Ford, Chrysler and GM around 1950s [1].

Today the advance driver assistance systems

(ADAS) forms the core of the vehicle safety.

Wireless technologies and cloud computing

would help vehicle to infrastructure and

vehicle to vehicle communication providing

live traffic and road conditions to other vehicle

thus providing an additional dimension to the

safety aspect of the vehicle.

We are entering the next phase of evolution

wherein cars of the future would be

connected, with fully autonomous capability

and advance designs. Cyber security which is

a prime concern for the future automobiles, is

seen as a potential research area.

New features are getting introduced in each and every part of the vehicle. Drive towards developing modular systems for plug-n-play has increased the importance of mechatronics subsystems. Key areas that are driving the development are safety, comfort, powertrain and communication. Safety:

III. Present and Future Applications/features


52

The advanced driver assistance systems

(ADAS) which includes lane change assist,

adaptive cruise control, and blind spot assist,

forward collision warning etc., form the core of

vehicle safety today. The requirement of these

advanced features have led to the introduction

of new sensors such as radio detection and

ranging (RADAR), light detection and ranging(

LiDAR), cameras, ultrasound sensors etc.

(Figure 1). With advancement in the area of

micro electro mechanical systems (MEMS)

and nanotechnology, future sensors would be

of miniature size practically sensing the entire

vehicle environment.

AdaptiveCruiseControl

Eme genc Brakinr y

gPe st a n Det ct onde r i e i

io vce

Collis n A oidan

Surround View

LaneDepartureWarning

ParkAssitance/Surround

ViewRearCollisionWarning

ParkAssit

ParkAssit

CrossTraficAlert

B il ndpotS

et iD ect on

Surround View

Figure 1 : Different Vehicular sensors to assist driver [3]

Advanced sensing and warning from ADAS

will help in improving the safety of passengers

by controlling the mechatronic systems. For

example, ADAS will help in sensing the crash

well ahead of time. This information will be

passed on to airbag control system, which will

release the airbags before the actual crash.

Powertrain/ Drivetrain:

Globally all governments are trying to reduce

the emission by the vehicles and industries

and are passing stringent legislations. The

automobile OEM's are trying to reduce the

emission, by developing new systems like

ultra-low emission or virtual zero emission

systems [4]. Companies are looking at

producing hybrid cars, electric cars and solar

cars. Areas such as traffic decongestion and

traffic management is getting more attention

to smooth the traffic flows and improve fuel

economy. To reduce the greenhouse gasses,

advanced automobile microcontrollers are

used to improve the efficiency of the engine

[5].

Health/Comfort:

In-vehicle cameras with advancement in

computer vision technology is used to detect

and recognize the owner of the vehicles, thus

helping to reduce theft and misuse of the

vehicles by unauthorized persons.

Future application can be built using gesture

and voice recognition to control vehicular

systems such as music systems, wiper

function, climate control, power windows etc.

The new Cadillac XTS and ATS vehicles have

inbuilt advance gesture recognition systems

[6].

Advancement in bio-electro-mechanical

systems/sensors (Figure 2) would predict the

driver's health conditions such as body

temperature, heartbeat, pulse rate, blood

pressure, etc., in the future. Self-learning

vehicles will be able to analyze this data and

assist the driver in case of emergency.

Temperature sensingInfraed sensors in the steering wheel

spokes monitor the driver's facialtemperature while sensors in the steering

wheel rim track changes in the plams

Biometric Seat Research

Ambient temperatureAn infrared sensor under the steeringcolumn provides a cabin temperature

to compare against the driver

Heart rate monitoringConductive sensors like those found onexercise machines are used to measure

changes in the driver's heart rate

RespirationA piezoelectric sensor in the seatbelt

counts the driver's breathing rate

Figure 2 : Ford's driver health monitoring system [7]

Communication:

In the near future vehicle-to-vehicle (V2V)

communication will assist other vehicles in

case of traffic congestion, accidents, bad

roads etc. vehicle-to-infrastructure (V2I)

communication can assist fleet operators in

case of vehicle theft or accidents. The Internet

of things (IoT) would integrate the home and

cars networks that would enable the vehicle to

control home electronics. For example, car will

sense that the driver is heading home and will

send a signal to home IoT to switch on the air

conditioner. Many such applications are being

worked out and will soon see light of the day.

Electronics:

Recent versions of the ABS concept not only

prevent wheel lock under braking, but also

electronically control the front-to-rear brake

bias. This function, depending on its specific

capabilities and implementation, is known as

electronic brake force distribution or electronic

stability control. Mechatronics systems such

as active steering, electro-hydraulic brakes

are coming into commercial productions.

These systems will assists in adaptive cruise

control (ACC) and collision mitigation

functionalities. Sensors in the fuel tanks will

check oil quality, tire sensor will remotely

monitor the air pressure in the tire – These can

warn the drivers and assist them in

maintaining the health of the automobile.


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Electronic Controlling Unit (ECU) Network:

The networking of various vehicular ECU's is

illustrated using adaptive cruise control

system as an example. The radar sensor

measures the distance of the vehicle ahead. If

the distance is less than the pre-specified

minimum distance, then the ECU will send this

info to the engine management unit, which in

turn reduces the torque, thus reducing the

driving speed. If this is not sufficient, the

electronic stability program (ESP) also

generates brake pressure to decelerate the

vehicle. Pretentions are set for emergency

standby. All this communication between the

ECUs cannot take more than fractions of a

second

Many such applications are already coming

into the commercial vehicle and would

revolutionize the automotive industry.

IV. Future Trends

The future of mechatronics looks bright, with advancements in the field of bio-electro-mechanical systems, quantum computers (Figure 3), pico systems and advanced computer networks. Future cars will be smarter, powerful and much more complex. This cannot be achieved only by increasing the number of mechatronics units, which will increase the cost and the weight of the vehicle. Hence, the future trend is inclined towards redesign of existing systems to incorporate intelligence into the mechatronic elements.

Figure 3 : Quantum computing chip set [8]

Modern automobiles can be looked at as an interconnected and distributed network of smart mechatronic systems. Advanced smart sensors will act as eyes and ears of future cars, providing information about various internal and external conditions. Futuristic technologies such as vehicle-to-vehicle communication (V2V), vehicle-to-infra communication (V2I), cloud computing, Internet of Things (IoT), etc., also provide information about external circumstances, through Bluetooth or wireless communication channels. The intelligence built into these

smart mechatronic systems will have to combine all these data for taking quick and intel l igent decisions under dynamic conditions. Various technologies such as smart sensors, wireless communication and cloud computing will influence the usage of mechatronic systems such as heating, ventilation, and air-conditioning (HVAC) systems, human machine interfaces (HMI), steering, braking and acceleration controls, etc., to improve the passenger safety and comfort.

Future cars will have large number of advanced smart sensors, which will generate huge amount of data, in the order of Giga bits per second [9]. In addition to this, the exchange of data between the vehicles and to the infrastructure via V2V, V2I and cloud would be humungous. All this data will be travelling through the in-vehicle network, which will help the mechatronic systems in taking quick and intelligent decisions. The existing in-vehicle network such as control area network (CAN), local interconnect network (LIN), FlexRay, etc., are inadequate to handle huge amount of network traffic produced by these sensors. Researchers are looking at replacing the existing in-vehicle network with Ethernet network that would increase efficiency and improve time to market. Frost & Sullivan and Strategy Analysis estimates that, close to 300 million automotive Ethernet ports will be in use by 2020 [10].

Any new technology/ innovation would be like two sides of a coin having positive and negative aspect to it. With vehicles being a part of the World Wide Web, hacking would be seen as a common threat to the future vehicles. Studies have shown that, hackers can gain entry into cars through network communication channels and take control of different mechatronics systems such as braking, acceleration, steering etc. [11]. Automotive cyber security and personal privacy will play a crucial role in the success of connected cars.

The future cars will have to execute complex algorithms and take quick decisions. One example is, finding an optimum path to reach a destination in a city of high population density during peak hour traffic. The computing power of current mechatronic systems will not be able to solve these problems. So, future mechatronic systems will have to incorporate advanced computing systems such as quantum computer.

As the computing power of mechatronic systems increase, their sizes will also increase. This will increase the size of vehicles which will result in consumption of more power and fuel. Advanced research in the field of nano and pico electromechanical systems will help in addressing this issue in the future.


54

V. Conclusion

Reduction in the cost of microprocessors, advancement in the areas of nano technology, wireless technology, smartphones and smart sensors have ushered the revolution in automotive mechatronics. Today, automotive mechatronics is the one of the fastest growing areas with an increasing demand on safety and security, communication, emission control and energy-saving. Mechatronics has become a major differentiator for OEM's to sell their cars. New applications are built around mechatronic systems, which are making cars smarter. Days are not far off, when cars will be communicating with each other and will be driving on their own. These developments are also throwing up new challenges such as hacking, incompatibility of parts manufactured by di fferent suppl iers, nonstandard communication protocols, etc. Industry is gearing up to address these challenges and these are going to define the future of automotive industry.

References

[1] Robert H.Bishop, “The Mechatronics- An Introduction”.

[2] [3Dr. Kevin Craig, “Automotive Mechatronics”.[3] Chris Edwards, “Car safety and the digital

dashboard”, October 2014.[4] B. T. Fijalkowski , “Automotive Mechatronics:

Operational and Practical Issues, Volume 1”[5] European Editors, “Using Microcontrollers to

Reduce Fuel Consumption in Powertrain Applications”, DigiKey Electronics, March 2014.

[6] http://www.cadillac.com[7] Bill Howard, “Ford smart car locks your phone

when you're stressed or distracted”, July 2012.[8] Kelly Dickerson, “Here's why we should be really

excited about quantum computers”, April 2015.[9] Guilherme Miguel Taveira Pinto, Global Markets

Business Consultant, Hitachi Data System, “The Amount of Data Generated by a Connected Vehicle Exceeds 25GB per Hour” https://www.hds.com/assets/pdf/hitachi-point-of-view-internet-on-wheels-and-hitachi-ltd.pdf.

[10] http://www.frost.com/prod/servlet/press-release.pag?docid=281841015

[11] Dr. Charlie Miller, Chris Valasek, "Remote Exploitation of an Unaltered Passenger Vehicle".


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