Active suspension control of electric vehicle with in-wheel motors

In-wheel motor (IWM) technology has attracted increasing research interests in recent years due to the numerous advantages it offers. However, the direct attachment of IWMs to the wheels can result in an increase in the vehicle unsprung mass and a significant drop in the suspension ride comfort performance and road holding stability. Other issues such as motor bearing wear motor vibration, air-gap eccentricity and residual unbalanced radial force can adversely influence the motor vibration, passenger comfort and vehicle rollover stability. Active suspension and optimized passive suspension are possible methods deployed to improve the ride comfort and safety of electric vehicles equipped with inwheel motor. The trade-off between ride comfort and handling stability is a major challenge in active suspension design. This thesis investigates the development of novel active suspension systems for successful implementation of IWM technology in electric cars. Towards such aim, several active suspension methods based on robust H∞ control methods are developed to achieve enhanced suspension performance by overcoming the conflicting requirement between ride comfort, suspension deflection and road holding. A novel fault-tolerant H∞ controller based on friction compensation is in the presence of system parameter uncertainties, actuator faults, as well as actuator time delay and system friction is proposed. A friction observer-based Takagi-Sugeno (T-S) fuzzy H∞ controller is developed for active suspension with sprung mass variation and system friction. This method is validated experimentally on a quarter car test rig. The experimental results demonstrate the effectiveness of proposed control methods in improving vehicle ride performance and road holding capability under different road profiles. Quarter car suspension model with suspended shaft-less direct-drive motors has the potential to improve the road holding capability and ride performance. Based on the quarter car suspension with dynamic vibration absorber (DVA) model, a multi-objective parameter optimization for active suspension of IWM mounted electric vehicle based on genetic algorithm (GA) is proposed to suppress the sprung mass vibration, motor vibration, motor bearing wear as well as improving ride comfort, suspension deflection and road holding stability. Then a fault-tolerant fuzzy H∞ control design approach for active suspension of IWM driven electric vehicles in the presence of sprung mass variation, actuator faults and control input constraints is proposed. The T-S fuzzy suspension model is used to cope with the possible sprung mass variation. The output feedback control problem for active suspension system of IWM driven electric vehicles with actuator faults and time delay is further investigated. The suspended motor parameters and vehicle suspension parameters are optimized based on the particle swarm optimization. A robust output feedback H∞ controller is designed to guarantee the system’s asymptotic stability and simultaneously satisfying the performance constraints. The proposed output feedback controller reveals much better performance than previous work when different actuator thrust losses and time delay occurs. The road surface roughness is coupled with in-wheel switched reluctance motor air-gap eccentricity and the unbalanced residual vertical force. Coupling effects between road excitation and in wheel switched reluctance motor (SRM) on electric vehicle ride comfort are also analysed in this thesis. A hybrid control method including output feedback controller and SRM controller are designed to suppress SRM vibration and to prolong the SRM lifespan, while at the same time improving vehicle ride comfort. Then a state feedback H∞ controller combined with SRM controller is designed for in-wheel SRM driven electric vehicle with DVA structure to enhance vehicle and SRM performance. Simulation results demonstrate the effectiveness of DVA structure based active suspension system with proposed control method its ability to significantly improve the road holding capability and ride performance, as well as motor performance

Nondeterministic hybrid dynamical systems

This thesis is concerned with the analysis, control and identification of hybrid dynamical systems. The main focus is on a particular class of hybrid systems consisting of linear subsystems. The discrete dynamic, i.e., the change between subsystems, is unknown or nondeterministic and cannot be influenced, i.e. controlled, directly. However changes in the discrete dynamic can be detected immediately, such that the current dynamic (subsystem) is known. In order to motivate the study of hybrid systems and show the merits of hybrid control theory, an example is given. It is shown that real world systems like Anti Locking Brakes (ABS) are naturally modelled by such a class of linear hybrids systems. It is shown that purely continuous feedback is not suitable since it cannot achieve maximum braking performance. A hybrid control strategy, which overcomes this problem, is presented. For this class of linear hybrid system with unknown discrete dynamic, a framework for robust control is established. The analysis methodology developed gives a robustness radius such that the stability under parameter variations can be analysed. The controller synthesis procedure is illustrated in a practical example where the control for an active suspension of a car is designed. Optimal control for this class of hybrid system is introduced. It is shows how a control law is obtained which minimises a quadratic performance index. The synthesis procedure is stated in terms of a convex optimisation problem using linear matrix inequalities (LMI). The solution of the LMI not only returns the controller but also the performance bound. Since the proposed controller structures require knowledge of the continuous state, an observer design is proposed. It is shown that the estimation error converges quadratically while minimising the covariance of the estimation error. This is similar to the Kalman filter for discrete or continuous time systems. Further, we show that the synthesis of the observer can be cast into an LMI, which conveniently solves the synthesis problem

Development of an Electronic Stability Control for Improved Vehicle Handling using Co-Simulation

The research project focuses on integrating the algorithms of recent automotive Electronic Stability Control (ESC) technologies into a commercial multi-body dynamics (MBD) software for full vehicle simulations. Among various control strategies for ESC, the sliding mode control (SMC) method is proposed to develop these algorithms, as it is proven to be excellent at overcoming the effect of uncertainties and disturbances. The ESC model integrates active front steering (AFS) system and direct yaw moment control (DYC) system, using differential braking system, therefore the type of the ESC model is called as integrated vehicle dynamic control (IVDC) system. The IVDC virtual model will be designed using a specialized control system software, called Simulink. The controller model will be used to perform full vehicle simulations, such as sine with dwell (SwD) and double lane change (DLC) tests on Simulink to observe its functionality in stabilizing vehicles. The virtual nonlinear full vehicle model in CarSim will be equipped with the IVDC virtual model to ensure that the proposed IVDC virtual model passes the regulations that describes the ESC homologation process for North America and European countries, each defined by National Highway Traffic Safety Administration (NHTSA) and United Nations (UN). The proposed research project will enable automotive engineers and researchers to perform full vehicle virtual simulations with ESC capabilities

Mu-synthesis PID control of full-car with parallel active link suspension under variable payload

This paper presents a combined μ -synthesis PID control scheme, employing a frequency separation paradigm, for a recently proposed novel active suspension, the Parallel Active Link Suspension (PALS). The developed μ -synthesis control scheme is superior to the conventional H∞ control, previously designed for the PALS, in terms of ride comfort and road holding (higher frequency dynamics), with important realistic uncertainties, such as in vehicle payload, taken into account. The developed PID control method is applied to guarantee good chassis attitude control capabilities and minimization of pitch and roll motions (low frequency dynamics). A multi-objective control method, which merges the aforementioned PID and μ -synthesis-based controls is further introduced to achieve simultaneously the low frequency mitigation of attitude motions and the high frequency vibration suppression of the vehicle. A seven-degree-of-freedom Sport Utility Vehicle (SUV) full car model with PALS, is employed in this work to test the synthesized controller by nonlinear simulations with different ISO-defined road events and variable vehicle payload. The results demonstrate the control scheme's significant robustness and performance, as compared to the conventional passive suspension as well as the actively controlled PALS by conventional H∞ control, achieved for a wide range of vehicle payload considered in the investigation

Development of a vehicle dynamics controller for obstacle avoidance

As roads become busier and automotive technology improves, there is considerable potential for driver assistance systems to improve the safety of road users. Longitudinal collision warning and collision avoidance systems are starting to appear on production cars to assist drivers when required to stop in an emergency. Many luxury cars are also equipped with stability augmentation systems that prevent the car from spinning out of control during aggressive lateral manoeuvres. Combining these concepts, there is a natural progression to systems that could assist in aiding or performing lateral collision avoidance manoeuvres. A successful automatic lateral collision avoidance system would require convergent development of many fields of technology, from sensors and instrumentation to aid environmental awareness through to improvements in driver vehicle interfaces so that a degree of control can be smoothly and safely transferred between the driver and vehicle computer. A fundamental requirement of any collision avoidance system is determination of a feasible path that avoids obstacles and a means of causing the vehicle to follow that trajectory. This research focuses on feasible trajectory generation and development of an automatic obstacle avoidance controller that integrates steering and braking action. A controller is developed to cause a specially modified car (a Mercedes `S' class with steer-by-wire and brake-by-wire capability) to perform an ISO 3888-2 emergency obstacle avoidance manoeuvre. A nonlinear two-track vehicle model is developed and used to derive optimal controller parameters using a series of simulations. Feedforward and feedback control is used to track a feasible reference trajectory. The feedforward control loops use inverse models of the vehicle dynamics. The feedback control loops are implemented as linear proportional controllers with a force allocation matrix used to apportion braking effort between redundant actuators. Two trajectory generation routines are developed: a geometric method, for steering a vehicle at its physical limits; and an optimal method, which integrates steering and braking action to make full use of available traction. The optimal trajectory is obtained using a multi-stage convex optimisation procedure. The overall controller performance is validated by simulation using a complex proprietary model of the vehicle that is reported to have been validated and calibrated against experimental data over several years of use in an industrial environment

Integrated control of vehicle chassis systems

This thesis develops a method to integrate several automotive intelligent chassis systems, such as Anti-lock Brake System, Traction Control System, Direct Yaw Control and Active Rear Wheel Steering, using evolutionary approaches. The Integrated Vehicle Control System (IVCS) combines and supervises all controllable systems in the vehicle, optimising the over all performance and minimising the energy consumption. The IVCS is able to improve the driving safety avoiding and preventing critical or unstable situations. Furthermore, if a critical or unstable configuration is reached, the integrated system should be able to recover a stable condition. The control structure proposed in this work has as main characteristics the modularity, extensibility and flexibility, fitting the requirements of a 'plug-and-play' philosophy. The investigation is divided into four steps: Vehicle Modelling, Soft-Computing, Behaviour Based Control, and Integrated Vehicle Control System. Several mathematical vehicle models, which are applied to designing and developing the control systems, are presented. MATLAB, SIMULINK and ADAMS are used as tools to implement and simulate those models. A methodology for learning and optimisation is presented. This methodology is based on Evolutionary Algorithms, integrating the Genetic Leaming Automata, CARLA and Fuzzy Logic System. The Behaviour Based Control is introduced as the main approach to designing the controllers and coordinators. The methodology previously described is used to learn the behaviours and optimise their performance, and the same technique is applied to coordinators. Several comparisons with other controllers are also carried out. From this an Integrated Vehicle Control System is designed, developed and implemented under a virtual environment. A range of manoeuvres is carried out in order to investigate its performance under diverse conditions. The leaming and optimisation method proposed in this thesis shows effective performance being able to learn all the controller and coordinator structures. The proposed approach for IVCS also demonstrates good performance, and is well suited to a 'plug-and-play' philosophy. This research provides a foundation for the implementation of the designed controllers and coordinators in a prototype vehicle.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Research and Implement of PMSM Regenerative Braking Control for Electric Vehicle

As the society pays more and more attention to the environment pollution and energy crisis, the electric vehicle (EV) development also entered in a new era. With the development of motor speed control technology and the improvement of motor performance, although the dynamic performance and economical cost of EVs are both better than the internal-combustion engine vehicle (ICEV), the driving range limit and charging station distribution are two major problems which limit the popularization of EVs. In order to extend driving range for EVs, regenerative braking (RB) emerges which is able to recover energy during the braking process to improve the energy efficiency. This thesis aims to investigate the RB based pure electric braking system and its implementation. There are many forms of RB system such as fully electrified braking system and blended braking system (BBS) which is equipped both electric RB system and hydraulic braking (HB) system. In this thesis the main research objective is the RB based fully electrified braking system, however, RB system cannot satisfy all braking situation only by itself. Because the regenerating electromagnetic torque may be too small to meet the braking intention of the driver when the vehicle speed is very low and the regenerating electromagnetic torque may be not enough to stop the vehicle as soon as possible in the case of emergency braking. So, in order to ensure braking safety and braking performance, braking torque should be provided with different forms regarding different braking situation and different braking intention. In this thesis, braking torque is classified into three types. First one is normal reverse current braking when the vehicle speed is too low to have enough RB torque. Second one is RB torque which could recover kinetic energy by regenerating electricity and collecting electric energy into battery packs. The last braking situation is emergency where the braking torque is provided by motor plugging braking based on the optimal slip ratio braking control strategy. Considering two indicators of the RB system which are regenerative efficiency and braking safety, a trade-off point should be found and the corresponding control strategy should be designed. In this thesis, the maximum regenerative efficiency is obtained by a braking torque distribution strategy between front wheel and rear wheel based on a maximum available RB torque estimation method and ECE-R13 regulation. And the emergency braking performance is ensured by a novel fractional-order integral sliding mode control (FOISMC) and numerical simulations show that the control performance is better than the conventional sliding mode controller