Research On Stability And Active Fault-tolerant Control Of EVs Driven By IWMs Considering Drivers’ Characteristics

Electric vehicles（EVs）with independently driven in-wheel-motors（IWMs）have great potential in driving efficiency,driving stability,safety and vehicle development.Technology researches related to electric vehicles with independently driven in-wheel-motors and market promotion are of great significance for solving energy problems and protecting the environment.EVs with independently driven IWMs have been considered as the final solution of EVs by the domestic and foreign automobile industry,and have become the research and industrialization direction in the automobile field all over the world.In this paper,based on the control principle of human-vehicle interaction,kinematics and vehicle system dynamics,the control strategy is developed for the stability and active fault-tolerant control of EVs considering driver characteristics.Firstly,the whole vehicle dynamics model is established,including a three degree-of-freedom vehicle model,a wheel model,a tire model,a motor model and a steering system model.In addition,in order to meet the research requirements of the control strategy,a driver model is established to accomplish the simulation model of the human-vehicle-road closed-loop system.Secondly,based on steering feedback mechanism of EVs driven by IWMs,a robust coordinated control strategy for electric wheel vehicles is proposed and the influence of differential assist system on vehicle yaw stability is analyzed.H₂/H_∞mixed sensitivity controller andμsynthesis robust control are designed respectively to track the ideal steering wheel torque and ideal yaw rate,so as to improve the system robustness and vehicle steering portability,completing the coordinated control of differential assistance and stability of electric wheel vehicles.Thirdly,the parameters and states coupling adaptive nonlinear filtering algorithm based on the limited gain extended Kalman filter is studied,and the real-time estimation of the vehicle state and the failure coefficient of the hub motor actuator is completed,avoiding the filtering divergence caused by the error information.The next,based on the estimation results of the extended Kalman filter with limited gain,a hierarchical adaptive fault-tolerant control strategy is designed.Considering the nonlinearity and modeling error of the system,as well as the slip loss of the tire and the sudden change of the motor torque,a discrete adaptive sliding mode upper controller and a four-wheel motor torque nonlinear optimal distribution controller are designed respectively to track the ideal yaw rate and longitudinal speed,completing the adaptive fault-tolerant control of the whole vehicle.At last,a robust fault-tolerant control strategy is designed considering the drivers’characteristics.The drivers’response to the motor fault is studied and the influences of different parameters in the driver model are analyzed.And then the neural network algorithm is used to complete the driver’s model identification.Considering the driver’s characteristics,a double closed-loop sliding mode control fault-tolerant controller is designed for the driver vehicle system to track the desired control target and realize the personalized fault-tolerant control.Simulation and test results show that the designed control strategy can not only effectively improve the handling performance and driving stability of EVs driven by IWMs,but also can detect the IWM fault timely and accurately.The driving force loss can be compensated through the redistribution of torque,improving the active safety of the vehicle.The research content of this paper can provide theoretical support for the stability and active fault-tolerant control of EVs independently driven by IWMs.