[1]寇发荣,常航涛,王倩磊,等.基于状态估计的车辆横摆稳定性分析方法研究[J].郑州大学学报(工学版),2025,46(03):105-110.[doi:10.13705/j.issn.1671-6833.2024.06.015]
　KOU Farong,CHANG Hangtao,WANG Qianlei,et al.Research on Vehicle Yaw Stability Analysis Method Based on State Estimation[J].Journal of Zhengzhou University (Engineering Science),2025,46(03):105-110.[doi:10.13705/j.issn.1671-6833.2024.06.015]
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基于状态估计的车辆横摆稳定性分析方法研究()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
46
期数:
2025年03期
页码:
105-110
栏目:
出版日期:
2025-05-13

文章信息/Info

Title:
Research on Vehicle Yaw Stability Analysis Method Based on State Estimation
文章编号:
1671-6833(2025)03-0105-06
作者:
寇发荣;  常航涛;  王倩磊;  方　博
西安科技大学 机械工程学院,陕西 西安 710054
Author(s):
KOU Farong;  CHANG Hangtao;  WANG Qianlei;  FANG Bo
School of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
关键词:
横摆稳定性;  车辆状态估计;  相平面法;  扩展卡尔曼滤波;  多层感知机
Keywords:
yaw stability;  vehicle state estimation;  phase plane method;  extended Kalman filtering;  multilayer perceptron
分类号:
TP13 U461.4
DOI:
10.13705/j.issn.1671-6833.2024.06.015
文献标志码:
A
摘要:
针对车辆横摆稳定性分析过程中状态参数难以获取、分析结果单一等问题,建立了二自由度车辆模型作为横摆稳定性分析和状态估计的参考模型;采用质心侧偏角及其角速度构建相平面,以分析车辆横摆稳定性,设计了基于多层感知机的工况自适应相平面稳定域,根据车辆实时状态及相平面稳定域构建横摆稳定性评价指标———横摆稳定度;设计了一种基于扩展卡尔曼滤波的车辆状态估计算法,提出了一种基于状态估计的车辆横摆稳定性分析方法;在双移线工况下进行100 km/h仿真试验与30 km/h实车试验,验证所提出的横摆稳定性分析方法的有效性与实用性。结果表明:基于状态估计的横摆稳定性分析方法的质心侧偏角估计平均误差小于0.1°,纵向速度估计平均误差小于0.03 m/s,该方法能够根据估计的车辆状态参数输入将横摆稳定性量化到0~1上,体现车辆横摆稳定性的动态变化。
Abstract:
Aimed at the problem that the state parameters were difficult to obtain and the analysis results were single in the process of vehicle yaw stability analysis, a two-degree-of-freedom vehicle model was established as a reference model for yaw stability analysis and state estimation. The phase plane was constructed by using the sideslip angle and its angular velocity to analyze the yaw stability of the vehicle, and the adaptive phase plane stability domain based on multi-layer perceptron (MLP) was designed. According to the real-time state of the vehicle and the phase plane stability region, the yaw stability evaluation index was constructed. A vehicle state estimation algorithm based on extended Kalman filter (EKF) was designed, and a vehicle yaw stability analysis method based on state estimation was proposed. In order to verify the effectiveness and practicability of the proposed yaw stability analysis method, simulation tests at 100 km/h and real vehicle tests at 30 km/h were conducted in double lane change conditions. The simulation and real vehicle test results showed that the average error of sideslip angle estimation based on state estimation was less than 0.1°, and the average error of longitudinal velocity estimation was less than 0.03 m/s. This method could quantify the yaw stability from 0 to 1 based on the estimated vehicle state parameter input, reflecting the dynamic changes in vehicle yaw stability.

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更新日期/Last Update: 2025-05-22