基于模型预测控制的滑移率控制方法

doi:10.13229/j.cnki.jdxbgxb.20221401

Abstract

Abstract:

In automotive electronic controls， safety issues are always of paramount importance. Therefore， this paper proposes a slip rate control method based on MPC to improve the longitudinal stability of four-wheel-wheel electric vehicles during emergency braking. Firstly， the vehicle longitudinal velocity estimator based on extended Kalman filter accurately estimates the longitudinal speed of the vehicle， and then the recursive least squares method based on limited memory is used to identify the optimal slip rate of the vehicle under the emergency braking condition. Secondly， the upper model predicts that the controller tracks the optimal slip rate， optimizes the braking torque required by the front and rear wheels under different road surface attachment conditions to meet the safety constraints， and the lower torque distribution controller distributes hydraulic and regenerative braking torque under the constraints of battery state of charge to improve the energy recovery efficiency. Finally， simulation experiments are carried out under different working conditions and it is shown that the proposed control system can ensure the safety and reliability of the emergency braking process.

Key words: vehicle engineering, slip rate control, model predictive control, optimal slip rate identification, longitudinal velocity estimation

CLC Number:

TP273

Shou-tao LI,Lu YANG,Ru-yi QU,Peng-peng SUN,Ding-li YU. Slip rate control method based on model predictive control[J].Journal of Jilin University(Engineering and Technology Edition), 2024, 54(9): 2687-2696.

Figures/Tables 8

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