Steering Assist And Electronic Differential For In-wheel-motor Electric Vehicle

The power-assisted steering system is used to solves the problem that a driver needs to overcome the large turning resistance when a vehicle is low speed or a tyre burst,so as to improve the driving comfort and safety.The traditional car gradually developed from electric power to electric power assisted,while the hub electric vehicle adopts four wheel independent drive,and the differential drive which turns to the front wheel can partly or completely replace electric power assistance.The traditional cars are gradually developed from electric power assisted by hydraulic power,while in-wheel-motor electric vehicles(IWMEV)can drive independently,which can make the steering wheel's differential drive can partly or completely replace the traditional electric power system.At the same time,vehicle differential control is always an important research topic in order to achieve smooth steering of vehicles and reduce the loss of tires.Firstly,the structure of the electric power steering system is analyzed in this paper,and its electrical parameters are measured.Based on this,vector control is used to realize the torque closed-loop control of PMSM(Permanent magnet synchronous motor).The position signal collection strategy of power assisted motor is formulated,and the electric power steering test platform is built.The typical torque curve is used to verify the torque tracking performance of the electric power steering test platform.Secondly,a differential drive assisted steering control method of IWMEV is presented by taking the assistant curve as the expected value.A dynamic model of differential drive assisted steering is set up for low speed vehicle running.The model is simplified by analyzing the influence of wheel angular velocity and acceleration on wheel longitudinal force estimation at low speed.And the influence of the lateral force and the vertical load on the positive torque is analyzed.The brush tire model is used to approximate the positive torque produced by the lateral force,so as to simplify the model further.Considering the disturbances in the model,a H infinite controller is designed.The simulation results based on the high precision dynamics software ve DYNA show that the proposed method is effective.Finally,the electronic differential control is implemented based on the Ackermann-Jeantand model.According to the slip rate and horizontal pendulum based on stability control method to realize the electronic differential has drawbacks,the desired wheel angular speed as control target,analysis of the unreasonable calculation of expected wheel angular speed with speed,speed control reference slip ratio difference based on the comprehensive consideration,and the change process of the total vehicle driving torque of steering by the time,low sliding rate of the wheel in the process as the wheel angular velocity calculated on the basis of planning expectations for steering wheel angular speed.The hub of electric vehicle steering dynamics analysis for the nonlinear and strong coupling system,this paper presents a new type of neural network PID controller,the simulation results show that PID neural network controller is better than the traditional PID controller,can track the low speed steering wheel angular speed in the process of speeding up expectations,and improves the wheel slip rate and the steering radius of the vehicle,solves the problem of electronic differential.According to the slip and yawrate stability control based on stability control method to realize the electronic differential has drawbacks,the desired wheel angular speed as control target.And considering the change process of the total vehicle driving torque of steering wheel,The wheel with lower slip ratio is used as the benchmark of wheel angular velocity,and the desired wheel angular velocity is planned.Then carried on the analysis to the wheel electric vehicle steering dynamics,aiming at the nonlinear and strong coupling system,this paper presents a new type of neural network PID controller,the simulation results show that proposed neural network PID controller is better than the traditional PID controller,which can track the desired value of wheel angular velocity in the condition of rapid acceleration steering,and improve the slip ratio of wheel and the turning radius of vehicle.