四轮驱动EV自适应抗差无迹粒子滤波状态估计  

Estimation of Adaptive Robust Unscented Particle Filter State for Four-wheel Driving EV

作　　者：龙云泽 韦韬 封进[1] 张瑞宾[1] LONG Yunze;WEI Tao;FENG Jin;ZHANG Ruibin(School of Automobile Engineering,Guilin University of Aerospace Technology,Guilin 541004,China)

机构地区：[1]桂林航天工业学院汽车工程学院,广西桂林541004

出　　处：《湖南大学学报（自然科学版）》2022年第2期31-37,共7页Journal of Hunan University:Natural Sciences

基　　金：广西高校中青年教师科研基础能力提升项目(2020KY21014,2021KY0795)。

摘　　要：针对四轮毂电机驱动电动汽车转矩控制中整车质心侧偏角等关键状态参数无法直接检测及车速等测量值易受到随机误差干扰的问题,建立四轮毂电机驱动电动汽车七自由度动力学模型,进行整车行驶状态参数滤波估计.结合抗差滤波原理及无迹粒子滤波算法,提出一种整车状态滤波估计方法.运用自适应抗差无迹粒子滤波,实现电动汽车行驶过程中纵向速度、侧向速度和质心侧偏角的准确滤波估计.搭建CarSim与Matlab/Simulink联合仿真实验平台对估计算法进行验证.结果表明:所搭建四轮毂电机驱动汽车动力学模型对整车行驶状态具有较高的预测精度;基于自适应抗差无迹粒子滤波算法能实现整车行驶状态估计,能有效对测量参数进行滤波,且具有较高的估计精度.In order to solve the problem that key state parameters such as mass-center sideslip angle of the vehicle can not be directly detected in the torque control of four hub-motor driving vehicles,and the measured values such as vehicle speed are easy to be interfered by random errors,a seven degree of freedom dynamic model of four hub motor-driven electric vehicles is established,and the filtering estimation of the driving state parameters of the whole vehicle is carried out.Based on robust filtering principle and unscented particle filter algorithm,a vehicle state filtering estimation method was proposed.Using adaptive robust unscented particle filter,the accurate filtering estimation of longitudinal speed,lateral velocity and mass-center sideslip angle in the process of electric vehicle driving was realized.The joint simulation experiment platform of CarSim and MATLAB/Simulink was built to verify the estimation algorithm.The results show that the dynamic model of four hub-motor driving vehicle has high prediction accuracy for vehicle driving state,and the adaptive robust unscented particle filter algorithm can effectively filter the measured parameters and has high estimation accuracy.

关 键 词：四轮毂电机驱动 电动汽车 车辆状态估计 自适应抗差无迹粒子滤波 

分 类 号：U461.1[机械工程—车辆工程]