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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
rahul.uplap@kpit.com
Rahul UplapAVP
Nitin SwamyMilind PotdarKedar SaprePranjali ModakPriti RanadiveSomnath SenguptaVishal PillaiReenaKumari BeheraAditya PiratlaSrinivasa Bugga
Designed and Published by
Suggestions and Feedback
Mind’sye Communication, Pune, IndiaContact : 9673005089
crest@kpit.com
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
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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
TechTalk@KPIT, Volume 9, Issue 2, 2016
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Editorial
Please send yourfeedback to :rahul.uplap@kpit.com
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.
TechTalk@KPIT, Volume 9, Issue 2, 2016
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TechTalk@KPIT, Volume 9, Issue 2, 2016
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About the AuthorsReecha Yadav
Ann Mary Sebastian
Areas of Interest
Automotive Electronics
Engine Management Systems
Control Systems
Areas of Interest
Computer Vision
Image Processing
Automotive Electronics
Introduction toAutomotive Mechatronics
TechTalk@KPIT, Volume 9, Issue 2, 2016
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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
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TechTalk@KPIT, Volume 9, Issue 2, 2016
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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
1
2
3
Car fails to turn on slippery road
StabiliTrak applies inside rear brakeCar returns to desired path
Desi drehpat
1
2 3
Di en
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TechTalk@KPIT, Volume 9, Issue 2, 2016
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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
TechTalk@KPIT, Volume 9, Issue 2, 2016
8
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
TechTalk@KPIT, Volume 9, Issue 2, 2016
9
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.
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[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].
TechTalk@KPIT, Volume 9, Issue 2, 2016
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SC
IEN
TIS
T P
RO
FIL
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.
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Born : 24 October 1945
REQUIREMENT
SIMULATION IMPLEMENTATION
TechTalk@KPIT, Volume 9, Issue 2, 2016
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About the Author
Areas of Interest
Vehicle System Modelling
Simulation Simulink Control Algorithm Development
Signal Processing
Manu M Jayaramegowda
Model BasedMechatronics Requirements
TechTalk@KPIT, Volume 9, Issue 2, 2016
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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
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l
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l
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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
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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.
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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
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TechTalk@KPIT, Volume 9, Issue 2, 2016
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Sensors and ActuatorsAbout the Author
Areas of Interest
Vehicle Electronics
Surface Engineering
Unmanned Aerial Systems (UAS)
Jayashri Kamagond
TechTalk@KPIT, Volume 9, Issue 2, 2016
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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
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III. Components for Mechatronics Implementation in Vehicles
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– 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.
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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
TechTalk@KPIT, Volume 9, Issue 2, 2016
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( Position )
(Speed)
Y
X
TechTalk@KPIT, Volume 9, Issue 2, 2016
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Sliding Mode Controlfor Automotive Applications
About the Authors
Areas of Interest
Motor Design and Control
Power Electronics
Automotive Electronics
Powertrain
On Board Diagnostics
Manish Bansal
Sandeep V. Ambesange
Areas of Interest
Model Based Powertrain Calibration
EMS Validation Engine Testing
TechTalk@KPIT, Volume 9, Issue 2, 2016
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TechTalk@KPIT, Volume 9, Issue 2, 2016
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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.
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TechTalk@KPIT, Volume 9, Issue 2, 2016
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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.
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TechTalk@KPIT, Volume 9, Issue 2, 2016
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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
-+
WZero-orderHold1
x1
-+
++
c1
K-0.6
Constant
x212
Unit Delay
|u|v
u 1
LMathFunction
Abs1
Sign1zx1
++ 15 2
Wref
0.8
C2
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
Reference SpeedActual Speed
PI Controller
Time (sec)
Spe
ed (r
ad/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
Reference SpeedActual Speed
PI Controller
Time (sec)
Spee
d (ra
d/s)
00
50
100
150
0.5 1 1.5 2 2.5
Reference SpeedActual Speed
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
Reference SpeedActual Speed
200
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
Reference SpeedActual Speed
TechTalk@KPIT, Volume 9, Issue 2, 2016
25
TechTalk@KPIT, Volume 9, Issue 2, 2016
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
TechTalk@KPIT, Volume 9, Issue 2, 2016
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
TechTalk@KPIT, Volume 9, Issue 2, 2016
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
TechTalk@KPIT, Volume 9, Issue 2, 2016
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
TechTalk@KPIT, Volume 9, Issue 2, 2016
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
TechTalk@KPIT, Volume 9, Issue 2, 2016
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TechTalk@KPIT, Volume 9, Issue 2, 2016
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
TechTalk@KPIT, Volume 9, Issue 2, 2016
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=
TechTalk@KPIT, Volume 9, Issue 2, 2016
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
TechTalk@KPIT, Volume 9, Issue 2, 2016
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.
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TechTalk@KPIT, Volume 9, Issue 2, 2016
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m/sin velocity is
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About the Author
Areas of Interests
Control Systems Design
Systems Modeling and Simulation
Model Based Development
Jestin Karlose Thekkeveetil
Electric Power Steering –Technology Trends
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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
)
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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]
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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
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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
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Predictive Efficiency ManagementUsing Driver Assistance Systems
About the Author
Areas of Interest
Advanced driver assistance systems
Connected cars
Vimalkanth K
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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.
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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
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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
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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
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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
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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
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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.
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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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