Research On Integrated Control Of Four-wheel Steering And Distributed Drive

As one of the measures to solve the energy crisis and environmental pollution,electric vehicles have been vigorously promoted by countries around the world.With the implementation of relevant policies such as carbon neutrality and new energy subsidies,the market prospect and penetration rate of electric vehicles have been significantly improved.According to kind flexible drive form and newly designed chassis,vehicle chassis control on electric vehicle has been studied and applied by researchers,as distributed-drive control and four-wheel steering control.With the application of high performance motors,distributed-drive technology has the advantages of simple structure,high transmission efficiency and good controllability.Four-wheel steering technology can significantly improve vehicle flexibility at low speeds and stability at high speeds.If the two are advantageously coupled,the handling stability of vehicle can be further improved.This problem has also become a research hotspot in this field.Relying on the National Natural Science Foundation of China and the Science and Technology Development Plan of Jilin Province,this subject has carried out the following research on the integrated control of four-wheel steering and distributed drive:The ideal two degree of freedom model for front wheel steering and the integrated model for four-wheel steering distributed drive based on vehicle parameters are established.The vehicle steering system,driving system,etc.are modified in the Car Sim simulation software to complete the construction of the simulation platform.Based on the intelligent chassis,which independently developed by the team,the construction of the test platform is completed by the addition of corresponding sensors and the modification of the VCU control program.Aiming at the longitudinal demand,a PI controller is designed to obtain the longitudinal driving force to maintain the driver’s desired vehicle speed.Aiming at the lateral demand,adopting the hierarchical control thought,three types of vehicle stability controllers are designed for different usage scenarios.The details are as follows:（1）In order to realize the vehicle flexibility at low speed and the stability at high speed,and at the same time consider the running time of the control algorithm and the design complexity,this project firstly builds an upper layer controller based on LQR control.Solving the Riccati equation in real time through an iterative method to obtain the rear wheel rotation angle and additional yaw moment,so as to complete the optimization of the side slip angle and yaw rate.The lower layer performs four-wheel torque distribution on the obtained longitudinal force and additional yaw moment through two driving force distribution methods: average distribution and sequential quadratic programming.It can be seen from the simulation and test results that the controller can make the vehicle side slip angle and yaw rate better track the ideal value,and the vehicle stability is improved.At the same time,compared with the average distribution method,the sequential quadratic programming method can better reduce the tire load factor and increase the service life of the motor controller.（2）In order to solve the problem of extreme value constraints such as rear wheel angle and additional yaw moment during vehicle operation,this project builds an upper layer controller based on model predictive control.Based on the integrated model of four-wheel steering and distributed drive,the prediction equation is derived to optimize the side slip angle,yaw rate,rear wheel angle and additional yaw moment,establish extreme constraint conditions such as wheel angle and additional yaw moment,and rolling to solve the quadratic programming problem.The lower layer controller obtains the four-wheel torque through the sequential quadratic programming method.The simulation and test results show that the controller can maintain the vehicle stability well under the driving constraints.（3）In order to eliminate the influence of inaccurate measurement of vehicle yaw moment of inertia and small-scale fluctuation of tire cornering stiffness on control accuracy,this project builds an upper layer controller based on adaptive sliding mode control.The sliding surface is constructed according to the error between the actual value and the ideal value of the vehicle side slip angle and yaw rate,the Lyapunov equation is established,and the output with the estimated value of the system matrix is obtained according to the La Salle invariance principle.The lower layer controller obtains the four-wheel torque through the sequential quadratic programming method.The simulation results show that the controller still has a good control effect under parameter perturbation.