Vertical Tire Forces Estimation of Multi-Axle Trucks Based on an Adaptive Treble Extend Kalman Filter

作     者：Buyang Zhang Ting Xu Hong Wang Yanjun Huang Guoying Chen Buyang Zhang;Ting Xu;Hong Wang;Yanjun Huang;Guoying Chen

作者机构：Jihua LaboratoryFoshan 528200GuangdongChina State Key Laboratory of Automotive Simulation and ControlJilin UniversityChangchun 130022China Tsinghua Intelligent Vehicle Design and Safety Research InstituteTsinghua UniversityBeijing 100084China Department of Mechanical and Mechatronics EngineeringUniversity of WaterlooWaterlooCanada. 

出 版 物：《Chinese Journal of Mechanical Engineering》 (中国机械工程学报（英文版）)

年 卷 期：2021年第34卷第3期

页      面：317-335页

核心收录：

学科分类：080902[工学-电路与系统] 0809[工学-电子科学与技术（可授工学、理学学位）] 082304[工学-载运工具运用工程] 08[工学] 080204[工学-车辆工程] 0802[工学-机械工程] 0823[工学-交通运输工程] 

基　　金：Supported by Basic and Applied Basic Research Foundation of Guangdong Province of China(Grant No.2019A1515110763) 

主　　题：Estimation theory Adaptive treble extend Kalman filter Vehicle dynamics Multi-axle truck Vertical tire force estimation 

摘      要：Vertical tire forces are essential for vehicle modelling and dynamic ***,an evaluation of the vertical tire forces on a multi-axle truck is difficult to *** current methods require a large amount of experimental data and many sensors owing to the wide variation of the parameters and the *** simplify the design process and reduce the demand of the sensors,this paper presents a practical approach to estimating the vertical tire forces of a multi-axle truck for dynamic *** estimation system is based on a novel vertical force model and a proposed adaptive treble extend Kalman filter(ATEKF).To adapt to the widely varying parameters,a sliding mode update is designed to make the ATEKF adaptive,and together with the use of an initial setting update and a vertical tire force adjustment,the overall system becomes more *** particular,the model aims to eliminate the effects of the over-constraint and the uneven weight *** results show that the ATEKF method achieves an excellent performance in a vertical force evaluation,and its performance is better than that of the treble extend Kalman filter.