基于双无迹卡尔曼滤波的电动汽车状态惯性监测  

Status Inertial Monitoring of Electric Vehicle Based on Double Untracked Kalman Filter

作　　者：左冬晓[1] Zuo Dongxiao(School of Automotive Engineering,Henan Vocational College of Industry and Trade,Zhengzhou Henan 450000,China)

机构地区：[1]河南工业贸易职业学院汽车工程学院,河南郑州450000

出　　处：《山西电子技术》2024年第3期27-29,共3页Shanxi Electronic Technology

基　　金：河南省基础与前沿技术研究计划项目(162300410158)。

摘　　要：为了能够对车辆动力惯性参数开展非线性评价,开发了一种分布结构驱动力电动汽车双无迹卡尔曼滤波(Dual unscented Kalman filter,DUKF)方法与状态观测系统联合系统车辆惯性监测方法。采用离散化方法建立车辆非线性动力学观测器,有效满足了车辆的非线性动力学评价要求。研究结果表明:相对DEKF方法,采用DUKF方法观测时达到了更小振荡程度,到达稳态观测阶段时,DUKF达到了更接近实际值的稳态观测效果,促进观测精度的显著提升,可以与非线性车辆动力学评价系统之间达到良好适应性。该研究有助于提高自动驾驶的稳定性,为后续的理论研究奠定一定的基础。In order to carry out nonlinear evaluation of vehicle dynamic inertia parameters,a kind of integrated vehicle inertial monitoring method of Dual unscented Kalman filter(DUKF)and state observation system with distributed driving force is developed.A vehicle nonlinear dynamics observer is established by discretization method,which satisfies the requirements of nonlinear dynamics evaluation.The results show that,compared with the DEKF method,the DUKF method can achieve a smaller degree of oscillation,and when it reaches the steady-state observation stage,the DUKF method can achieve a steady-state observation effect closer to the actual value,which promotes the significant improvement of observation accuracy,and can achieve a good adaptability with the nonlinear vehicle dynamics evaluation system.This study is helpful to improve the stability of automatic driving and lay a foundation for the subsequent theoretical research.

关 键 词：电动汽车 状态观测 惯性参数 双无迹卡尔曼滤波 

分 类 号：U461[机械工程—车辆工程] TP301.6[交通运输工程—载运工具运用工程]