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基于SRCKF的路面附着系数估计

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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。
SRCKF-based Pavement Adhesion Coefficient Estimation
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 coeffi-cient 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.

square root cubature Kalman filterpavement adhesion coefficientsimulationDugoff tire

刘艺霖、张友兵、周奎

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湖北汽车工业学院 汽车工程师学院,湖北 十堰 442002

平方根容积卡尔曼滤波 路面附着系数 仿真 Dugoff轮胎

2024

湖北汽车工业学院学报
湖北汽车工业学院

湖北汽车工业学院学报

影响因子:0.304
ISSN:1008-5483
年,卷(期):2024.38(3)