Handling Stability And Energy Efficient Control For Distributed Drive Electric Vehicles

To mitigate the adverse effects of the use of traditional fuel vehicles on the environmental and energy issues, our country has formulated the regulations of emission and fuel consumption more and more strictly, which also contributed to acceleration of electric driven technology’s research and application for major automobile companies in the world. One kind of all electric driven technology, called distributed electric driven technology, not only has advantages of low energy consumption and less pollution, but also has the wheels’ torque controlled flexibly and independently, which has created favorable conditions for vehicle dynamics and energy control. This paper showed the research on the method of wheels’ torque control to develop an effective control strategy to improve vehicle handling and stability and energy efficiency in different conditions.To meet the requirement of control strategy’s development and validation, vehicle model has been built and simulation platform has been calibrated in chapter two. Firstly, vehicle model with seven degrees of freedom has been established for design of vehicle state observer. The response characteristic of the electric driving / electric braking torque has been described through experimental modeling of electric driven system. To meet the needs of the validation of control strategy, vehicle dynamic simulation platform with high accuracy based on d SPACE-asm has been built in this paper. Vehicle model with seven degrees of freedom and simulation platform based on dSPACE-asm have been calibrated and validated using vehicle test to lay the foundation of development for control strategy.Vehicle state parameters are important for dynamics control. This paper used state observer to estimate the key vehicle parameters which can’t be directly measured by sensor. Sliding mode control algorithm is widely used in system dynamics control for its quick response and good robustness. Based on the second-order supercoiled sliding mode control algorithm, this paper designed vehicle state observer to enhance the velocity and accuracy in observing vehicle state. The third chapter also conducted a study to identify the driver’s intention and designed vehicle yaw motion controller. The output of identifying driver’s intention is objective of vehicle control, the accuracy of which has an important influence on the effects of the dynamics control. Based on the simplified vehicle model with two degrees of freedom including sideslip angle constraint, driving intention has been recognized to achieve the balance between vehicle stability control and steering control. After obtaining the vehicle’s actual and desired yaw rate through the above steps, vehicle yaw motion controller has been designed based on the sliding mode control to calculate the control amount of yaw moment which was transferred to the layer of wheel torque distribution.The fourth chapter studied the control allocation of wheel torque in extremely driving conditions. Vehicle handling and stability is the primary control objective for wheel torque control in extremely driving conditions like high speed and poor road with lower adhesion coefficient. This paper proposes a yaw stability control method of differential driving, differential braking based on direct sliding rate allocation. The priority of four wheels’ driving and braking has been set considering the characteristics of chassis dynamics to reduce the variation range of vehicle speed and improve the fault tolerance ability for control. Based on Magic tire model, the relationship between vehicle active yaw moment and the sliding rate of each wheel has been established as well as the limitation of sliding rate allocation. According to that, the active yaw moment can be assigned to sliding rate of four wheels in accordance with the preset priority.In the fifth chapter, wheel torque distribution in general condition has been studied. This chapter focused on a multi-objective optimization control allocation method to realize the control allocation of driving and braking torque in different conditions including straight driving / braking conditions and steering driving / braking conditions. Before establishing multi-objective optimization problem, this paper compared several construction methods of objective function in the present literature, based on which, the non-convex and nonlinear optimization problem has been established indicating three goals including the active yaw moment control, energy efficiency control for electric driven system and wheel slip rate control. In steering and braking conditions, the distribution of the regenerative braking and hydraulic braking torque was divided into three cases according to the intensity of the driver’s brake torque to reduce the complexity of the control strategy. In the optimization problem solving session, taking the cost of computing into account, this paper presented a complex optimization problem solving method with both offline and online to decrease the amount of computation of the controller, meanwhile the accuracy was guaranteed.Chapter six presents the experimental verification of control strategy. Firstly, based on real vehicle experiments, the algorithm of vehicle state estimation was validated. The experiments were done on snow road and dry asphalt road in driving conditions of a single lane and the step input of steering wheel angle. Hardware experimental platform with driver has been built based on d SPACE, using which the validation of maneuverability and energy efficiency in general conditions has been done as well as vehicle yaw stability control strategy in extremely driving conditions.