Research On Torque Distribution Of In-wheel Motor Driven Automobile Based On Driving Intention

At present,as people’s voices for environmental protection are getting higher and higher,pure electric vehicles have attracted attention from all walks of life because of their low carbon energy saving and no pollution during driving.Among them,electric vehicles with four-wheel hub independent driving are highly researched in the field of pure electric vehicle control technology in recentyears due to the advantages of highly integrated transmission system and independent controllable torque of each wheel.This paper studies the torque distribution strategy based on driver’s intention for four-wheel independent driving electric vehicles.The main contents are as follows:(1)A six-degree-of-freedom driving simulator was established to realize driver-in-the-loop research,and the fidelity of the six-degree-of-freedom driving simulator was improved by washing out algorithms and steering force feedback control,laying the foundation for subsequent driver-in-the-loop tests.(2)A state estimation study of four-wheel independent drive electric vehicles was carried out.The necessity of state estimation is analyzed.For known states,the simulated annealing particle swarm optimization particle filter algorithm is used to develop a vehicle driving state estimation model.The model is verified by CarSim simulation.The research on driver intention recognition was carried out,the necessity of driver intention recognition was analyzed,and the driver’s manipulation was adaptively enhanced to establish a driver intention recognition model,and the accuracy of model recognition was determined by driving data Verified.The necessity of torque distribution and its influence on vehicle driving were analyzed,and a torque distribution strategy was formulated.According to the result of driving intention recognition,the target state is calculated,and different torque distribution strategies are formulated for different target states according to the model predictive control algorithm to improve the maneuverability and stability of the vehicle.(3)Driver-in-the-loop verification of the proposed control strategy was performed.A six-degree-of-freedom driving simulator is used as a test device,and a state estimation,driver intention recognition,and torque distribution model is introduced into the simulator system.The simulation analysis is performed under multiple operating conditions,and the simulation results are analyzed.The simulation results show that compared with the traditional estimation model,the designed state estimation model improves the comprehensive accuracy by 10%,the driving intention identification model can accurately identify the driver’s intention,the comprehensive identification accuracy of the identification model reaches more than 98%,the torque distribution model based on the driving intention can significantly improve the maneuverability of the vehicle at low speed,the turning radius at low speed is reduced by 0.7 meters,the stability at high speed is improved,and the yaw rate of the vehicle at high speed is reduced by 30%.