Study On Integrated Control Of AFS And DYC For In-Wheel-Motor Electric Vehicle

In the in-wheel-motor electric vehicle,the driving torque of each wheel can be controlled independently,so the energy saving control strategy can be conducted.Meanwhile,combining with the X-by-wire system,many active chassis control systems can be realized,so the in-wheel-motor electric vehicle will be the ideal system for vehicle dynamics control,and it will be the ultimate driving form of the pure electric vehicle.For the vehicle yaw stability control,the most used systems are the active front steering system(AFS)and the direct yaw moment control system(DYC).The AFS system alters the lateral tire force to acquire the corrective yaw moment,when the lateral tire force reaches it saturation,the system function fails.The DYC system uses the longitudinal tire force to conduct yaw stability control,and the longitudinal vehicle speed is affected in the control process.To avoid the shortcoming of each single system and improve the comprehensive performance of the yaw stability control system,the AFS/DYC integrated control system has been studied based on the in-wheel-motor electric vehicle.To establish the algorithm development/debugging platform for vehicle dynamics control,the 8-DOF vehicle model and the Magic Formula tire model are built on the Matlab/Simulink platform.The vehicle dynamics analysis software CarSim is adopted to verify the 8-DOF vehicle model,simulation results show that the model built in the Simulink has high accuracy under both high and low adhesion coefficient roads.In order to provide the controller with necessary information,like real-time vehicle states and road adhesion coefficient,based on the 3-DOF vehicle model,the extended kalman filter(EKF)is adopted to design the vehicle state estimator.Simulation results show that the EKF can estimate the vehicle states effectively.As for the estimation of road adhesion coefficient,the BP neural network is built and the wheel state is taken as the input of the estimator.Simulation results show that the recognition accuracy of the network is up to 95.619%.To estimate the performance of the AFS system and DYC system,some performance items are compared based on the simulation results,which includes performance sustainability,maximum correction ability,impact on vehicle speed and the system economy.Simulation results show that driving DYC system has the best performance sustainability,while the AFS system and the driving DYC system have a minimum impact on vehicle longitudinal speed.In the AFS/DYC integrated control strategy,a modified sliding mode controller is employed to calculate the required corrective yaw moment,so as to improve the reliability of the control strategy.To make better use of the subsystems in the integrated control system,the operation region division based integrated control strategy is proposed.The lateral tire force's boundary points under different working conditions are fitted into two interfaces,which is used to divide the operation regions of AFS and DYC subsystems.Simulation results show that the operation region division based integrated control strategy can activate the appropriate subsystem to achieve the control goal according to the driving conditions,and it outperforms the average division based integrated control strategy.