湖北汽车工业学院学报2025，Vol.39Issue(3)：27-33,7.DOI:10.3969/j.issn.1008-5483.2025.03.005
基于MCCSCKF算法的电动半挂汽车列车状态估计与MPC稳定性控制
State Estimation and MPC Stability Control of Electric Semitrailer Based on MCCSCKF Algorithm
摘要
Abstract
In order to solve the problems of inaccurate estimation of traditional Kalman filter algorithm in non-Gaussian noise environments and real-time high-speed stability control of electric semitrailer train,a maximum correlation entropy square root cubature Kalman filter(MCCSCKF)algorithm was de-signed to estimate the sideslip angle,yaw rate,and articulation angle parameters of the semitrailer train.Based on the three degrees of freedom dynamic model of the semitrailer train,the upper controller of di-rect yaw moment control was established based on the model predictive control(MPC)algorithm to cal-culate the additional yaw moment of the tractor and trailer.The lower controller of torque distribution control based on quadratic programming was designed to optimize the torque distribution of each driv-ing wheel.Based on the verification of the effectiveness of the state estimation,the effectiveness of the MPC lateral stability control strategy was verified by selecting the high-speed double line change condi-tion through the construction of the TruckSim and MATLAB/Simulink co-simulation platform.The re-sults show that the proposed state estimator can accurately estimate the state variables,and the control strategy effectively improves the stability of the electric semitrailer train.关键词
最大相关熵准则/状态估计/模型预测控制/稳定性控制/转矩分配Key words
maximum correlation entropy criterion/state estimation/model predictive control/stability control/torque distribution分类
交通工程引用本文复制引用
周一鸣,邓召文,高伟,杨涛..基于MCCSCKF算法的电动半挂汽车列车状态估计与MPC稳定性控制[J].湖北汽车工业学院学报,2025,39(3):27-33,7.基金项目
湖北省自然科学基金(2023AFB985) （2023AFB985）
湖北汽车工业学院揭榜挂帅项目(2024JBB02) （2024JBB02）
