摘要
为解决传统卡尔曼滤波算法在非高斯噪声环境中估计不精确以及电动半挂汽车列车的实时高速稳定性控制问题,设计了一种最大相关熵平方根容积卡尔曼滤波(MCCSCKF)算法,估计汽车列车质心侧偏角、横摆角速度和铰接角参数。在汽车列车三自由度动力学模型基础上,基于模型预测控制(MPC)算法建立了直接横摆力矩控制上层控制器,计算牵引车和挂车附加横摆力矩;并设计了基于二次规划的转矩分配控制下层控制器,优化分配各驱动轮力矩。通过搭建TruckSim和MATLAB/Simulink联合仿真平台,在状态估计有效性验证基础上,选取高速双移线工况对MPC横向稳定性控制策略的有效性进行验证。结果表明,文中状态估计器能精准估计各状态量,控制策略有效提升了电动半挂汽车列车的稳定性。
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.
作者
周一鸣
邓召文
高伟
杨涛
Zhou Yiming;Deng Zhaowen;Gao Wei;Yang Tao(Hubei Key Laboratory of Automotive Power Transmission and Electronic Control,Shiyan 442002,China;School of Intelligent Connected Vehicle,Hubei University of Automotive Technology,Shiyan 442002,China;College of Energy and Power Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China)
出处
《湖北汽车工业学院学报》
2025年第3期27-33,共7页
Journal of Hubei University Of Automotive Technology
基金
湖北省自然科学基金(2023AFB985)
湖北汽车工业学院揭榜挂帅项目(2024JBB02)。
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
maximum correlation entropy criterion
state estimation
model predictive control
stability control
torque distribution
