cranfield automotive mechatronics newsletter spring 2012

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AUTOMOTIVE MECHATRONICS NEWSLETTER Spring 2012 Page 1 AUTOMOTIVE MECHATRONICS CENTRE, DEPARTMENT OF AUTOMOTIVE ENGINEERING, CRANFIELD UNIVERSITY Whittle Building, Bedfordshire MK43 0AL | T +44 (0) 12 3475 4708 Contents Title Page Automotive Mechatronics Centre and Research Projects 1 UK Government Funded Projects FUTURE Vehicles project 3 Application of Advanced Control for HEV Torque Management 4 Directly Funded PhD Projects Alternative Powertrain: Comparative Analysis of Hybrid Powertrains 5 Methods for Real World Estimation of Energy Consumption of EV and PHEVs 6 Application of Multi Objective Design Optimization Methods for EV Powertrain 8 Vehicle Dynamics and Active Chassis Control: Low Cost Integration of Electric Power Assist Steering (EPAS) with Electronic Stability Control (ESC) 9 The Influence of Torque and Speed Sensitive Differential Characteristics During On-Limit Maneuvers 9 MSc Student Projects 10 2012 R&D opportunities By Prof. Francis Assadian, Head of the Department of Automotive Engineering and Director of Automotive Mechatronics at Cranfield University Automotive Mechatronics Centre During the last two decades, there have been substantial advances in the theory and application of robust multivariable feedback control system design. The reason for a need of such robust algorithms arises from several inherent uncertainty sources, such as various operational conditions, process changes, sensor noises and unmeasured exogenous disturbances. While robust control systems have been successfully employed to tackle a wide range of engineering applications including aerospace systems, the automotive industry has not benefited from the advantages of these modern control techniques. However, it is interesting to note that, most of the control software designs and requirements captured in the automotive engineering domain have been adopted from the aerospace industry. One of the main reasons for this is the fact that the process of developing automotive systems, unlike in the aerospace industry, is in a state of flux and has not been "standardised" as of yet. It turns out that there has been an increase in the gap between the control theory and the practical control strategies utilised in the existing production vehicles. This gap has resulted in several missed opportunities through fundamental functionalities, such as fuel economy, emissions and integration of the Automotive Mechatronics units on-board the vehicle, not being addressed. A wide range of modern automotive products is currently designed with the integration of mechanical components and electronic hardware into one packaging unit. This leads to the development of true mechatronic solutions such as HEV energy management systems, active chassis systems and next-generation HEVs etc (figure 1). On the other hand, there are various challenges for automotive systems including calibration, time and cost of production, reliability and diagnostics, control system robustness, performance issues and hardware constraints. Existing methodologies are no longer able to meet such requirements for increasingly complex new vehicles and therefore a variety of innovative

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Page 1: Cranfield Automotive Mechatronics Newsletter Spring 2012

AUTOMOTIVE MECHATRONICS NEWSLETTER

Spring  2012      

Page 1

AUTOMOTIVE MECHATRONICS CENTRE, DEPARTMENT OF AUTOMOTIVE ENGINEERING, CRANFIELD UNIVERSITY

Whittle Building, Bedfordshire MK43 0AL | T +44 (0) 12 3475 4708

Contents

Title Page Automotive Mechatronics Centre and Research Projects

1

UK Government Funded Projects FUTURE Vehicles project

3

Application of Advanced Control for HEV Torque Management

4

Directly Funded PhD Projects

Alternative Powertrain:

Comparative Analysis of Hybrid Powertrains

5

Methods for Real World Estimation of Energy Consumption of EV and PHEVs

6

Application of Multi Objective Design Optimization Methods for EV Powertrain

8

Vehicle Dynamics and Active Chassis Control:

Low Cost Integration of Electric Power Assist Steering (EPAS) with Electronic Stability Control (ESC)

9

The Influence of Torque and Speed Sensitive Differential Characteristics During On-Limit Maneuvers

9

MSc Student Projects 10

2012 R&D opportunities By Prof. Francis Assadian, Head of the Department of Automotive Engineering and Director of Automotive Mechatronics at Cranfield University Automotive Mechatronics Centre During the last two decades, there have been substantial advances in the theory and application

of robust multivariable feedback control system design. The reason for a need of such robust algorithms arises from several inherent uncertainty sources, such as various operational conditions, process changes, sensor noises and unmeasured exogenous disturbances. While robust control systems have been successfully employed to tackle a wide range of engineering applications including aerospace systems, the automotive industry has not benefited from the advantages of these modern control techniques. However, it is interesting to note that, most of the control software designs and requirements captured in the automotive engineering domain have been adopted from the aerospace industry. One of the main reasons for this is the fact that the process of developing automotive systems, unlike in the aerospace industry, is in a state of flux and has not been "standardised" as of yet. It turns out that there has been an increase in the gap between the control theory and the practical control strategies utilised in the existing production vehicles. This gap has resulted in several missed opportunities through fundamental functionalities, such as fuel economy, emissions and integration of the Automotive Mechatronics units on-board the vehicle, not being addressed. A wide range of modern automotive products is currently designed with the integration of mechanical components and electronic hardware into one packaging unit. This leads to the development of true mechatronic solutions such as HEV energy management systems, active chassis systems and next-generation HEVs etc (figure 1). On the other hand, there are various challenges for automotive systems including calibration, time and cost of production, reliability and diagnostics, control system robustness, performance issues and hardware constraints. Existing methodologies are no longer able to meet such requirements for increasingly complex new vehicles and therefore a variety of innovative

Page 2: Cranfield Automotive Mechatronics Newsletter Spring 2012

AUTOMOTIVE MECHATRONICS NEWSLETTER

Spring  2012      

Page 2

AUTOMOTIVE MECHATRONICS CENTRE, DEPARTMENT OF AUTOMOTIVE ENGINEERING, CRANFIELD UNIVERSITY

Whittle Building, Bedfordshire MK43 0AL | T +44 (0) 12 3475 4708

mechatronics-based design methodologies are desperately required. Mechatronics applications offer one of the best solutions to the challenging requirements of the automotive industry as they offer flexible opportunities with regards to functionality, cost, space requirements and quality. The key objective of automotive mechatronics is to pursue both research and development, and a harmonised approach to the design of mechatronic systems for automotive applications.

Figure 1. Automotive mechatronics applications Cranfield University is one of the leading institutes of higher education in the UK in the fields of design and engineering of automotive technology. To meet the challenges of pioneering automotive research, The Automotive Mechatronics Centre at Cranfield University was established in 2009 to help address some of the applied advanced control issues discussed above. Our research activities are mainly focused on green mobility and vehicle electrification (novel electrical and control architectures, advanced automotive control and energy management strategies), active safety, vehicle Dynamics and integrated chassis Control. The overarching goals of this centre are listed as follows: 1) To address the immediate needs and gaps in mechatronics and advanced control system design and knowledge in a coordinated pragmatic

approach through short term projects with industry. 2) To carry out long term fundamental research in the automotive green technology area, from process and methodology, to mechatronics modelling, design and development, through governmental support and long term industrial projects. 3) To address the knowledge gap in automotive mechatronics through short courses as well as establishment of an MSc program in Automotive Mechatronics in 2013. The Centre is actively looking for academic and industrial partners to create new opportunities in the green mobility area and develop an environment where knowledge transfer is enhanced. There are ample opportunities in the area of green mobility, which could be accessed and addressed through the right partnerships. Please find below a brief summary of our automotive mechatronics research projects proposals, which are currently being pursued with our partners, and some of the future research calls, which we will be looking for partners. Current Proposals: EPSRC proposal for Optimisation of Fully Electric Vehicles, Partners: University of Surrey, University of Newcastle, and University of Sheffield Proposal Submittal date: 15 June 2012 TSB proposal for Combustion Enhancement of diesel engines over 4 Litres Capacity by the use of Pulse Air Technology, Partners: Clear Air Technology, University of Warwick Proposal Submittal date: 15 July 2012 Directly Funded proposal for Low Cost Integration of Electric Power Assist Steering (EPAS) and Electronic Stability Control (ESC), Partners: Jaguar Land Rover Proposal Submittal date: 01 June 2012

Page 3: Cranfield Automotive Mechatronics Newsletter Spring 2012

AUTOMOTIVE MECHATRONICS NEWSLETTER

Spring  2012      

Page 3

AUTOMOTIVE MECHATRONICS CENTRE, DEPARTMENT OF AUTOMOTIVE ENGINEERING, CRANFIELD UNIVERSITY

Whittle Building, Bedfordshire MK43 0AL | T +44 (0) 12 3475 4708

Future Research Projects: European FP7 Call for Configurable and Adaptable Truck Partners: Looking for partners Proposal Submittal date: 15 July 2012 Global Mobility Network, Funding: Looking for funding stream Partners: Nottingham Trent University, AVL, Texas A&M, University of Michigan, University of California Davis, University of Zagreb, Jilin University, Chinese Academy of Science, Beijing Jiaotong University, Scorpion Power System, CADLM Proposal Submittal date: Open

Future Vehicles FUTURE is an EPSRC funded, collaborative research project between Cranfield University, Loughborough University, Oxford University, Imperial College London and Coventry University. The department of Automotive Engineering, is leading the research into system control and Multidisciplinary optimisation. Hybrid electric vehicles (HEV) are far more complex than conventional vehicles. There are numerous challenges facing the engineer to optimise the design and choice of system components as well as their control systems. At the component level there is a need to obtain a better understanding of the basic science/physics of new subsystems together with issues of their interconnectivity and overall performance at the system level. The notion of purpose driven models requires models of differing levels of fidelity, e.g. control, diagnostics and prognostics. Whatever the objective of these models, they will differ from detailed models which will provide a greater insight and understanding at the component level. Thus there is a need to develop a systematic approach resulting in a set of guidelines and tools which will be of immense value to the design engineer in terms of best practice.

The Fundamental Understanding of Technologies for Ultra Reduced Emission Vehicles (FUTURE) consortium will address the above need for developing tools and methodologies. A systematic and unified approach towards component level modelling will be developed, underpinned by a better understanding of the fundamental science of the essential components of a FUTURE hybrid electrical vehicle. The essential components will include both energy storage devices (fuel cells, batteries and ultra--capacitors) and energy conversion devices (electrical machine drives and power electronics). Detailed mathematical models will be validated against experimental data over their full range of operation, including the extreme limits of performance. Reduced order lumped parameter models are then to be derived and verified against these validated models, with the level of fidelity being defined by the purpose for which the model is to be employed.

Figure *: FUTURE Multidisciplinary Development

Optimization Process

The work will be carried out via three interlinked work packages, each having two subwork packages. WP1 will address the detailed component modelling for the energy storage devices, WP2 will address the detailed component modelling for the energy conversion devices and WP3 will address reduced order modelling and control optimisation. The tasks will be carried out

Page 4: Cranfield Automotive Mechatronics Newsletter Spring 2012

AUTOMOTIVE MECHATRONICS NEWSLETTER

Spring  2012      

Page 4

AUTOMOTIVE MECHATRONICS CENTRE, DEPARTMENT OF AUTOMOTIVE ENGINEERING, CRANFIELD UNIVERSITY

Whittle Building, Bedfordshire MK43 0AL | T +44 (0) 12 3475 4708

iteratively from initial component level models from WP1 and WP2 to WP3, subsequent reduced order models developed and verified against initial models, and banks of linear-time invariant models developed for piecewise control optimisation. Additionally, models of higher fidelity are to be obtained for the purpose of online diagnosis. The higher fidelity models will be able to capture the transient conditions which may contain information on the known failure modes. In addition to optimising the utility of healthy components in their normal operating ranges, to ensure maximum efficiency and reduced costs, further optimisation, particularly at the limits of performance where component stress applied in a controlled manner is considered to be potentially beneficial, the impact of ageing and degradation is to be assessed. Methodologies for prognostics developed in other industry sectors, e.g. aerospace, nuclear, will be reviewed for potential application and/or tailoring for purpose. Models for continuous component monitoring for the purpose of prognosis will differ from those for control and diagnosis, and it is envisaged that other non-parametric feature based models and techniques for quantification of component life linked to particular use case scenarios will be required to be derived.

Application of Advanced Control for HEV Torque Management In this EPSRC funded research project on multivariable controls, the aim was to design and develop a pragmatic advanced model-based (dynamical) controller to the torque management of HEV which is a challenging application due to the complexity of HEV dynamics. This complexity results in many challenges for both automotive OEMs and suppliers. Some of these challenges include a better definition of the roles of supplier and OEM, more efficient development processes, more expertise in the mechatronics area particularly at the OEM side, use of advanced

robust control techniques and more refined integration approaches. Our project aimed to deliver a setup with reduced fuel consumption and CO2 emissions over specific drive cycles, including the New European Driving Cycle (NEDC), by meeting the increasingly stringent emissions standards with enhanced reliability and diagnostics. This was motivated due to the fact that existing hybrid powertrain control methods are based on off-line (sub-optimal) algorithms, in which driveability is an afterthought. Model uncertainties are ignored and torque estimation errors in feedback are not considered. It also turns out that intensive calibration efforts are required.

Figure 2. The structure of the HEV for the application of torque management We have developed a Simulink package for the HEV energy management application (figure 2). This includes an empirical diesel engine model, an electric Crankshaft Integrated Motor Controller (CIMG), together with saturated actuators and torque loss models (such as ICE ancillary, pumping and friction torques). Also in the package are sufficiently realistic clutch models, adaptive torque estimation algorithms (for both ICE and CIMG output torques), an ICE speed controller and multivariable torque controllers with their associated bumpless anti-windup controls that were designed and tested in HIL (figure 3).

Page 5: Cranfield Automotive Mechatronics Newsletter Spring 2012

AUTOMOTIVE MECHATRONICS NEWSLETTER

Spring  2012      

Page 5

AUTOMOTIVE MECHATRONICS CENTRE, DEPARTMENT OF AUTOMOTIVE ENGINEERING, CRANFIELD UNIVERSITY

Whittle Building, Bedfordshire MK43 0AL | T +44 (0) 12 3475 4708

Figure 3. HIL architecture implemented based on the dSPACE platforms The results We intend to show some typical results of the multivariable robust control design, using mixed-mu synthesis, applied successfully to the case study of torque management of a Hybrid Electric Vehicle (HEV) (figure 4).

Figure 4. Robust multivariable torque control results designed and tested at Cranfield University. Yellow: Requested torque, Magenta: Estimated torque; Top: ICE torque, Middle: CIMG Torque, Bottom: Total Torque) As illustrated, the developed robust multivariable controller fully achieves our requirement from the HEV driveability viewpoint by delivering sufficiently fast total torque response. Due to different bandwidths at two ICE/CIMG control channels, the controller makes the CIMG help bring the total torque rapidly to the requested torque level. This is indeed a challenging highly-coupled multivariable control problem that single

PID loops cannot cope with. Whilst the low-frequency engine output torque responses are actually delivered by the engine, at high-frequencies modes (rapid torque requests), the electric motor effectively compensates for the engine output torque lags, referred to as ‘torque filling’. In other words, the HEV torque management application is a complex frequency-weighted problem, which can be solved by the robust MIMO, designs and as a result, drastically reduce the need for manual drivability calibration effort.

Comparative Analysis of Hybrid Powertrains With tightening legislations and ongoing crude oil price volatility, the automotive industry has been under increasing pressure to develop vehicles that are more fuel efficient and lower in emissions. This increasing pressure could also be attributed towards change in market demands due to perceived risks of climate change and depleting fossil fuel resources. As a result, hybrid powertrains are gaining considerable momentum, in tandem with more fuel-efficient internal combustion engines. Hybrid powertrain is defined as two or more power sources to propel a vehicle. For the purpose of this thesis, hybrid powertrains are divided into following main architectures:

• Series Hybrid

• Parallel Hybrid

Fuel ICE M INV

Batt INV M

Wheel

C

T ACDC

DCAC T

DC

DC BUS

Trn T

Fuel ICE

Batt

Wheel

C

AC

T

T

TDC

Torque BUSINV M

TrnClutch 2T

Clutch 1T

T

Page 6: Cranfield Automotive Mechatronics Newsletter Spring 2012

AUTOMOTIVE MECHATRONICS NEWSLETTER

Spring  2012      

Page 6

AUTOMOTIVE MECHATRONICS CENTRE, DEPARTMENT OF AUTOMOTIVE ENGINEERING, CRANFIELD UNIVERSITY

Whittle Building, Bedfordshire MK43 0AL | T +44 (0) 12 3475 4708

• Compound Hybrid

Within these architectures, the following energy storage solutions are being investigated in further detail:

• Tank storage (Fossil Fuel and Hydrogen) • Battery • Ultracapacitors • Hydraulic Accumulators • Flywheel

Along with the following energy converters: • ICE • Electric Motor/Generator • Hydraulic pump • Fuel Cell

However, with a myriad of hybrid configurations possible, it is beneficial that the right system is chosen for the desired vehicle class and usage profile. This PhD research investigates this issue, by suggesting a tool to critically evaluate different hybrid powertrain topologies. A ranking algorithm provides a systematic and objective approach to comparing different hybrid powertrain topologies, and it will enable powertrain topologies to be compared against criteria that are defined by vehicle class and usage profile. As a result, this potentially enables powertrain topologies to be ranked according to their advantages and disadvantages, for a given vehicle application. The scope of this research is summarised in the Venn diagram:

This PhD research aims to compare hybrid powertrains in terms of:

• Cost

• Fuel economy and emissions

• Reliability (Component Count)

• Packaging size and weight

• Well-to-wheels energy efficiency (with

UK-based energy data)

• Performance

Methods for Real World Estimation of Energy Consumption of EV and PHEVs Within the automotive and road transport sector, one of the main drivers for technological development and innovation is the need to reduce the vehicle’s fuel consumption and the emission of Carbon Dioxide (CO2). This research funded by Morgan Motor Company makes use of two real-world test programs of an EV and a conventional vehicle, to study the relation between usage patterns and vehicle component design. Calculation of the component sizes for EVs and PHEVs remains one of the main design challenges. In the context of a PHEV the

Fuel ICE

M IVN

Batt IVN M Wheel

C

AC DC DC AC

DC

T

T

T

T

T

Torque BUSTorque BUS

DC BUS

Page 7: Cranfield Automotive Mechatronics Newsletter Spring 2012

AUTOMOTIVE MECHATRONICS NEWSLETTER

Spring  2012      

Page 7

AUTOMOTIVE MECHATRONICS CENTRE, DEPARTMENT OF AUTOMOTIVE ENGINEERING, CRANFIELD UNIVERSITY

Whittle Building, Bedfordshire MK43 0AL | T +44 (0) 12 3475 4708

challenge is further compounded by the choice of ICE, HV battery and the energy management strategy. Within a number of applications the HV battery system constitutes the single largest contributor to vehicle mass and cost. Furthermore, it was determined that the usage pattern has a significant impact on the performance of the vehicle. However, legislative procedures do not address these issues. This research, which is depicted in Figure 1, aims to understand the relation between the usage patterns, component sizes of the PHEV and the appropriate energy management strategies.

Figure 1. Area of Research The aim of this research is broken to four objectives. Objective 1: Real-World Usage Analysis • Provide a consistent framework for the

analysis of real-world data. • This data would then be analysed for

determining usage patterns and also development of the vehicle model.

Objective 2: Component Sizing PHEV • Develop a scalable PHEV based on the data

from Objective 1. • Make use of an optimisation routine to select

the ideal component sizes based on various constraints.

• Identify the variation in component sizes for different use case scenarios, control strategies and legislative requirements.

Objective 3: Supervisory Controller

• Development a robust sub-optimal instantaneous real-time controller for the management of the two energy sources.

• Improve the performance of the controller using GPS / pattern recognition data obtained from Objective 1.

Objective 4: • Observe and understand the links between

these various objectives. A novel frame work based on neural networks was formulated for the recognition of the various driving environments. Figure 2 shows the energy consumption for different driving environments. The range of the EV can vary by much as 30 % based on the driving environment.

Figure 2. Energy Use for different environments Currently, an instantaneous optimal controller based on equivalent fuel consumption minimisation method is being developed. Early results show the controller consistently out performs a rule based strategy by 10 – 15 %. This can be achieved by including predictive abilities to the controller such as journey distance. Figure 3 shows the operation of the PHEV over a typical real-world cycle for the various control strategies.

Page 8: Cranfield Automotive Mechatronics Newsletter Spring 2012

AUTOMOTIVE MECHATRONICS NEWSLETTER

Spring  2012      

Page 8

AUTOMOTIVE MECHATRONICS CENTRE, DEPARTMENT OF AUTOMOTIVE ENGINEERING, CRANFIELD UNIVERSITY

Whittle Building, Bedfordshire MK43 0AL | T +44 (0) 12 3475 4708

Finally genetic algorithms have been chosen since the optimisation problem is non-linear and discontinuous. Currently, research is focused on developing algorithms for the evaluation of the vehicle models over legislative test procedures. The end stage of the research would be to understand the relation between sizing routine, control strategy and usage scenarios.

Figure 3. Engine ON/OFF operation for various controllers (a) Rule Based Strategy (b) EFCM (c) Predictive EFCM

Application of Multi Objective Design Optimization Methods for EV Powertrain This research is aimed to develop a methodology to design and optimise the powertrain architecture, powertrain component and supervisory control for battery electric vehicle. This project comprises of three main areas. • Battery Electric vehicle powertrain architecture

and components sizing • Battery electric vehicle supervisory control

algorithm • Multi-disciplinary and multi-objective

optimisation for Battery electric vehicle Powertrain architecture and component sizing includes selecting the appropriate electric vehicle powertrain layout and designing the number and sizing of powertrain components.

The purpose of this design is to identify the architecture that responds to the vehicle requirements and driving cycle. Supervisory control is focused on the interaction of components. Multidisciplinary design optimisation technique is planned to select the optimum points among the designs of powertrain architecture along with the design of supervisory control (Figure 4). Finally, the comparison of current production battery electric vehicle will present with the optimisation results. This research process is divided into three phases. 1. Using the multi-objective optimisation

method to optimise the battery electric vehicle powertrain based on the currently available EV.

2. Alternative architecture of battery electric vehicle powertrain, the possibility of different powertrain component and powertrain sizing will be considered. The optimisation technique is also used to identify the better possible of efficiency EV powertrain.

3. Control algorithm will be integrated to the EV powertrain to determine the optimal management logic. Concurrent optimisation will be used to optimise the parameters of powertrain components and control system of the battery electric vehicle.

motor

Transmission

Torque,Speed

Gear typeGear ratioDiff. ratio

Battery

Power

Size of motor [kW]

MotorEff.map

Vehicle

Torque,Speed

CdA

R_wheelUrr

MassInertia

gAir dent.

Vehicle type

Optimiser

MassInertia

MassInertia

Mass

SpeedRef.

Objective

VCapacity (Ah)

Constrain

min SOCmax P

max RPMmax torque

Energy consumptionΔ SOC

Speed error

Multidisciplinary Design Optimisation for Battery Electric Vehicle

Gear effDiff. eff

No. of cellarrangement

Figure 4: structure of multi-objective design optimisation method of EV powertrain

Page 9: Cranfield Automotive Mechatronics Newsletter Spring 2012

AUTOMOTIVE MECHATRONICS NEWSLETTER

Spring  2012      

Page 9

AUTOMOTIVE MECHATRONICS CENTRE, DEPARTMENT OF AUTOMOTIVE ENGINEERING, CRANFIELD UNIVERSITY

Whittle Building, Bedfordshire MK43 0AL | T +44 (0) 12 3475 4708

Low Cost Integration Electr ic Power Assist Steering (EPAS) with Electronic Stabi l i ty Control (ESC) The main goal of this research is to propose a novel control system and a control functional architecture for integration of Electric Power Steering (ESP) and Electronic Stability Control (ESC) systems to enhance driver comfort as well as vehicle safety. In addition, virtual sensing will be developed and utilised where necessary to reduce the overall cost of the final system. The deliverables can be classified into four groups, as follows:

1. Design and development of a customised functional architecture for control integration of ESP and ESC by utilising and modifying a previously developed Advanced Global Chassis Control system (Figure 4).

Figure 5: Structure of AGCC system for lateral motion control

2. Model based control design, by using the

novel neo-classical method, of a yaw stability high-level controller including the tyre self-aligning torque estimation as a virtual sensing. Model based control

design of low-level smart actuator controllers for EPAS and ESP systems.

3. Design and development of a unique control integration concept for EPAS and ESP system using the Fuzzy Logic approach.

Figure 5: The proposed integrated EPS & ESC HIL configuration

4. Design and fabricate an integrated ESP & ESC HIL system with driver in the loop capability. This HIL system will be used as a rapid control development tool as well as a test rig for functional and non-functional testing of ESP and ESC system (Figure 5).

The Influence of Torque and Speed Sensitive Differential Characteristics During On-Limit Manoeuvres

This research is carried out with the support of Xtrac Limited who design and manufacture transmission solutions for the motorsport industry. In such a competitive environment, there is benefit in being able to offer tailored designs and understanding the impact of the transmission on vehicle handling. In light of this, differential characteristics play an essential part of transmission development. Much of this is centred on how the differential changes its torque transfer

Page 10: Cranfield Automotive Mechatronics Newsletter Spring 2012

AUTOMOTIVE MECHATRONICS NEWSLETTER

Spring  2012      

Page 10

AUTOMOTIVE MECHATRONICS CENTRE, DEPARTMENT OF AUTOMOTIVE ENGINEERING, CRANFIELD UNIVERSITY

Whittle Building, Bedfordshire MK43 0AL | T +44 (0) 12 3475 4708

characteristics during cornering and how torque transfer application can be made more progressive. Passive Limited Slip Differentials (PLSD) are a well-established means of improving the traction limitation imposed by standard automotive open differentials and achieve this by transmitting a bias torque from a faster to slower rotating driven wheel. This torque bias is typically proportional to the differential input torque or the speed difference between wheels. Common examples of these include plate type (see Figure 6) and viscous coupling differentials.

Figure 6: Xtrac Plate Differential Assembly

Many types of modern PLSD device which operate in this way have been used as the basis for handling investigations in the mainstream automotive sector. These have focused on the benefits of one particular method of torque bias control. In the motorsport environment however, there exists devices which are able to bias torque through both methods simultaneously, but to date, remain unexplored with respect to their influence on handling and the differential models required to study them. This research uses both Matab/Simulink simulation tools and Xtrac’s in-house differential test rig to help characterise differential torque bias characteristics. An 8 degree of freedom vehicle model and preview steering driver model (see Figure 7) provides the basis to explore the dynamic effects of differentials on vehicle handling performance.

Figure 7: Vehicle Model Simulation Structure

MSc Student Projects 1. Modelling and Simulation of SCR

Hydraulic Components 2. Modelling Mechanical Hybrid Powertrain 3. Parametric Clutch Torque Modelling and

Analysis for Control Applications 4. Development of an Integrated EPAS/ESP

Test Rig/HIL System