Research On Stability Control For In-wheel Motor Driven EV Under Critical Working Conditions

The dual pressure of energy and environment promotes the development of electric vehicles.Due to the characteristics of independent torque output control,free distribution,and fast response,the in-wheel motor driven electric vehicle provides convenient conditions for the research of vehicle stability control.The high speed of automobile and the flow quantification of traffic makes the vehicle easy to be in the critical condition,which increases the probability of instability.How to improve the stability and safety of in-wheel motor driven electric vehicle in the critical working conditions has become a research focus.This paper takes the in-wheel motor driven electric vehicle as the target and carries out the research of vehicle stability control under the critical working condition.Firstly,the vehicle parameters are matched based on the vehicle system dynamics system provided by CarSim software.Due to the traditional vehicle provided by CarSim,the driving form needs to be modified and the driving torque input interface is set.The driver speed model and the external motor model are built based on Simulink module.CarSim and Simulink are built jointly to constitute a simulation test platform for dynamics control of in-wheel motor driven electric vehicle.Secondly,the stability of in-wheel motor driven electric vehicle is analyzed,and yaw velocity and sideslip angle are selected as control variables.Because sideslip angle cannot be measured directly,a state observer of sideslip angle is designed to estimate the sideslip angle in real time,providing real-time data support for vehicle stability control.The yaw velocity threshold method and sideslip angle plane method are combined to judge the stability,providing accurate intervention time for vehicle stability control.Then,in order to improve the stability and adaptability of in-wheel motor driven electric vehicle under the critical working conditions,based on the sliding mode control algorithm,the coefficient of the variable sliding mode surface was selected by using the fuzzy algorithm,and the direct yaw moment controller was designed to achieve the stability of in-wheel motor driven electric vehicle.The designed direct yaw moment controller was verified in the double lane condition,serpentine condition,angle step condition and fishhook condition based on the built simulation platform.The test results show that the direct yaw moment controller designed in this paper can effectively improve the vehicle running stability and is adaptive to the complex running conditions.Finally,the yaw moment obtained by the designed direct yaw moment controller,needs to be distributed rationally,and the torque distributor is designed.In this paper,considering uncertainty of road conditions,the road adhesion is estimated in real time;Taking the minimum tire load rate as the objective function,the optimal torque distributor based on pavement recognition is designed in combination with the restrictions of pavement conditions and actuators.And compared with the average distribution method,load distribution method,the optimal torque distribution method known road is compared,the test results show that the optimal torque distributor based on road recognition improves vehicle stability margin in critical working conditions to some extent,makes the vehicle stability enhancement,and improves the adaptability of vehicles running.In summary,to improve the stability and adaptability of in-wheel motor driven electric vehicle under the critical working condition,the direct yaw moment controller based on the adaptive sliding mode algorithm and the optimal moment distributor based on the road surface recognition are designed.The simulation results show that the driving stability and adaptability of the vehicle can be effectively improved.