| With the worsening environment and people’s attention to environmental issues,the management of automobile exhaust is becoming more and more strict.Therefore,while major automobile manufacturers are studying exhaust treatment,they are also actively looking for alternatives that can be used for internal combustion engines.The development of new energy vehicles is on the agenda.With the rise of new energy vehicles,distributed drive electric vehicles have received widespread attention as the best alternative.However,the electronic differential problem of distributed drive electric vehicles is still a problem we need to solve urgently.This paper takes the distributed drive electric vehicle directly driven by the hub motor as the research object,and takes the wheel slip ratio as the control target to improve the steering stability of the vehicle.The main research contents of the paper include:(1)First determine the drive system of the distributed drive electric vehicle,compare the performance advantages of various motors,select a permanent magnet brushless DC motor(BLDCM)as the drive motor,and build a BLDCM model.Secondly,a tire model is established based on the "magic formula",and the model is verified by several common road experience values.Finally,a two-degree-of-freedom car model is built.(2)Based on the RBF neural network control algorithm,a slip rate control strategy is proposed for the electronic differential control system.This paper uses two methods for speed control: one is direct speed distribution,and a speed distribution model is established under the constraints of motor failure,road adhesion,and vehicle dynamic performance to control the speed of each wheel when the car turns;Second,the direct slip rate allocation,based on the magic tire formula,determines the relationship between the wheel slip rate and the yaw moment acting on the car’s center of mass,controls the speed of the motor,and finally uses the slip rate tracking strategy to control the speed of each wheel.Based on the above work,the built model’s adaptability under differentworking conditions is simulated and tested for feasibility verification.Simulation results show that this control strategy can smoothly realize the starting,acceleration,deceleration,steering,and braking operations of the car. |
