Research On Slip Rate Control Strategy Of Four In-wheel Motors Electric Vehicle Under Emergency Braking Condition

Environmental protection and safety are the two major problems that need to be solved in the modern automobile industry,and they are also the core technical difficulties that many automobile companies have been trying to overcome.With the advantages of independent wheel control and direct measurement of motor torque and speed,the four in-wheel motors electric vehicle offers the possibility to solve these two problems and has become a key research object in the development of electric vehicles.However,its structural characteristics also make the vehicle stability control more complicated.In order to improve the longitudinal stability of four in-wheel motors electric vehicle during emergency braking,further research on the theory and method of slip rate control is needed.The innovation of this paper is that considering the internal characteristics of the braking system and the coupling between various components,the speed estimation based on extended Kalman filtering and the least squares method based on limited memory are given in the slip rate control strategy under emergency braking conditions.The key technologies such as accurate identification of the optimal slip rate based on the model predictive control algorithm,stable tracking of the optimal slip rate based on the model predictive control algorithm,and rule-based braking torque distribution have improved the reliability of the longitudinal stability control of the four in-wheel motors electric vehicle.It has certain theoretical support and practical engineering significance in slip rate control.The main research contents include:Firstly,the dynamic model of the four in-wheel motors electric vehicle under emergency braking conditions is established,including the vehicle longitudinal dynamics model,the wheel dynamics model and the Lu Gre tire model.According to the working characteristics of the braking system of the controlled object,the electronically controlled hydraulic braking system model,the regenerative braking system model and the battery model of the four-wheel electric vehicle are built respectively,which lays the foundation for the design and analysis of the slip rate control strategy.Secondly,in order to make the system achieve good control effect under different road conditions,the slip rate control strategy needs to accurately estimate the longitudinal speed and identify the optimal slip rate.In terms of speed estimation,based on the Lu Gre tire model and vehicle dynamics model,the extended Kalman filter principle is used to design a vehicle longitudinal speed estimator;in terms of optimal slip rate identification,the relationship between the slip rate and the road adhesion coefficient on the classical road surface is firstly analyzed.Secondly,the road adhesion coefficient is estimated according to the vehicle dynamics,and finally the linearized Burckhardt tire model is fitted by the recursive least squares method with limited memory,and the optimal slip rate of the vehicle under different road conditions is identified.Thirdly,a layered slip rate control strategy based on the model predictive control algorithm is designed.The upper layer tracks the optimal slip rate of the four wheels based on the model predictive control,and optimizes the solution to obtain the braking torque of each wheel as the target of the lower controller.The lower layer is designed with a regenerative braking and hydraulic braking torque distribution controller.Under the constraints of the maximum torque of the motor and the SOC value of the battery,the braking torque optimized by the upper controller is reasonably distributed to complete the tracking control of the optimal slip rate.At the same time,the recovery of braking energy is maximized.Finally,the slip rate control strategy under emergency braking conditions is verified and analyzed by building a joint simulation platform of Carsim and Matlab/Simulink.The results show that the longitudinal speed estimation algorithm based on extended Kalman filter can reduce the influence of uncertainty of road friction conditions and vehicle parameters as well as noise and other factors,and estimate the longitudinal speed accurately in real time;the optimal slip rate identification algorithm based on recursive fixed memory least square can identify the optimal slip rate quickly and accurately;under different road conditions,the hierarchical slip rate control strategy can effectively shorten the braking time and distance,ensure the safety and reliability during emergency braking,and maximize the braking energy recovery at the same time.