四轮驱动车辆路面附着系数实时估计
CSTR:
作者:
作者单位:

(1.哈尔滨工业大学(威海) 汽车工程学院, 264209 山东 威海; 2.吉林大学 机械科学与工程学院, 130025 长春)

作者简介:

赵立军(1975—), 男, 博士后, 副教授.

通讯作者:

赵立军, zhaolijun@hitwh.edu.cn.

中图分类号:

U461

基金项目:

国家自然科学基金(51275126);威海市科技发展计划项目(2012DXGJ13).


Real-time road condition estimation for four-wheel-drive vehicle
Author:
Affiliation:

(1.School of Automobile Engineering, Harbin Institute of Technology(Weihai), 264209 Weihai, Shandong, China; 2. College of Mechanical Science and Engineering, Jilin University, 130025 Changchun, China)

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    针对目前无法直接测得车辆路面附着系数的问题,通过设计扩张状态观测器及利用递推最小二乘法来实时估计该值.建立7自由度车辆模型, 给出车轮受力平衡方程,设计二阶非线性扩张状态观测器.根据轮胎驱动转矩及车轮转速估计当前利用附着系数, 并对观测器进行仿真.结果表明, 观测器能够有效观测利用附着系数.在已观测出的利用附着系数的基础上, 推导了利用附着系数与峰值附着系数间的递推公式, 利用递推最小二乘法设计峰值附着系数估计器, 并在Matlab/Simulink中进行仿真.结果表明, 估计器可以较为快速有效地实现峰值附着系数识别,较为准确地实时估计附着系数.

    Abstract:

    The road condition can be estimated by the extended state observer and the recursive least square method based on a 7DOF nonlinear vehicle model. in which the wheel force is analyzed, the force equilibrium equation is put forward and then the second order nonlinear extended state observer is designed. The results show that the extended state observer can achieve the observation of the utilization adhesion coefficient. Then a recurrence formula is derived based on the simplified tire model. The model shows the relationship between the utilization adhesion coefficient and the peak adhesion coefficient. The peak adhesion coefficient estimator is designed based on the recursive least square method, and the Matlab/Simulink simulation results show that the estimator can identify the peak adhesion coefficient quickly. The adhesion coefficient estimator can obtain the real-time estimation accurately.

    参考文献
    相似文献
    引证文献
引用本文

赵立军,邓宁宁,葛柱洪,刘昕晖.四轮驱动车辆路面附着系数实时估计[J].哈尔滨工业大学学报,2014,46(11):42. DOI:10.11918/j. issn.0367-6234.2014.11.007

复制
相关视频

分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2013-12-12
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2014-11-29
  • 出版日期:
文章二维码