基于SRCKF的路面附着系数估计  

SRCKF-based Pavement Adhesion Coefficient Estimation

作　　者：刘艺霖 张友兵 周奎 Liu Yilin;Zhang Youbing;Zhou Kui(School of Automotive Engineers,Hubei University of Automotive Technology,Shiyan 442002,China)

机构地区：[1]湖北汽车工业学院汽车工程师学院,湖北十堰442002

出　　处：《湖北汽车工业学院学报》2024年第3期22-26,32,共6页Journal of Hubei University Of Automotive Technology

基　　金：湖北省重大科技专项(2021BED004);武汉市科技局重大专项(2022013702025184)。

摘　　要：搭建了基于Dugoff轮胎模型的七自由度四轮独立驱动电动车辆模型,基于平方根容积卡尔曼滤波(SRCKF)算法设计了路面附着系数估计器。利用Simulink与Carsim的联合仿真平台对路面附着系数进行估计,与传统容积卡尔曼滤波算法估计结果进行对比。结果表明:SRCKF算法提高了滤波的稳定性和实时估计精度。A seven-degree-of-freedom electric vehicle model driven by independent four wheels based on the Dugoff tire model was constructed,and a pavement adhesion coefficient estimator was designed based on the square root cubature Kalman filter(SRCKF)algorithm.The pavement adhesion coefficient was estimated using the joint simulation platform of Simulink and Carsim,and the results were compared with those of the traditional cubature Kalman filter algorithm.The experimental results show that the SRCKF algorithm enhances the stability of filtering and real-time estimation accuracy.

关 键 词：平方根容积卡尔曼滤波 路面附着系数 仿真 Dugoff轮胎 

分 类 号：U461.51[机械工程—车辆工程] TP391.9[交通运输工程—载运工具运用工程]