摘要
在建立2自由度1/4车辆悬架振动模型基础上,提出了利用卡尔曼滤波算法估计车辆行驶振动状态的方法。通过设计卡尔曼滤波算法,对在不平路面上行驶车辆的车身垂向位移、垂向速度和车轮垂向位移、垂向速度状态进行估计,并通过Matlab/Simulink对估计效果进行验证。验证结果表明,该方法能够在不同路面、不同车速下准确估计车辆的相关参数,为汽车主动悬架的最优控制提供了基础。
Based on the establishment of the two-degree-of-freedom 1/4 vehicle active suspension vibration model, the method to estimate vehicle vibration state by using Kalman filter algorithm was proposed. The vertical displacement and vertical velocity of the body and wheel of vehicles on uneven road surface were estimated by the design of the Kalman filter algorithm, and the estimation effect was verified by Matlab/Simulink. The resuhs show that the proposed Kalman filter algorithm can accurately estimate the relevant vehicle parameters at different speeds and on different road surfaces, providing foundation for the optimal control of active suspension.
作者
钟孝伟
陈双
张不扬
Zhong Xiaowei Chen Shuang Zhang Buyang(Liaoning University of Technology, Jinzhou 121000 State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022)
出处
《汽车技术》
CSCD
北大核心
2017年第5期14-18,共5页
Automobile Technology
基金
国家自然科学基金项目(51605213)
辽宁省科技厅项目(201602367)
辽宁省教育厅科学研究项目(L2015227)
关键词
汽车悬架
状态估计
卡尔曼滤波
Automobile suspension, State estimation, Kalman filter
