融合解析计算的轮毂电机电动汽车主动悬架最优控制

于曰伟; 李波; 赵雷雷; 张方圆; 王学成

doi:10.7652/xjtuxb202608020

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融合解析计算的轮毂电机电动汽车主动悬架最优控制

更新时间：2026-07-28

- 融合解析计算的轮毂电机电动汽车主动悬架最优控制
- Optimal Control of Active Suspension for In-Wheel-Motor-Driven Electric Vehicles Integrating Analytical Calculation
- 西安交通大学学报 2026年60卷第8期页码：229-239
- 作者机构：
  
  山东理工大学交通与车辆工程学院，255000，山东淄博
  山东省新能源车辆集成设计与智能化重点实验室，255000，山东淄博
- 作者简介：
  
  作者简介：于曰伟（1989-），男，副教授，博士生导师；
  李波（通信作者），男，教授，博士生导师。
- 基金信息：
  
  国家自然科学基金资助项目(52305266;52375105);山东省重点研发计划资助项目(2024TSGC0765)
- DOI：10.7652/xjtuxb202608020
  中图分类号： U461.1
- 收稿：2025-10-28，
  
  网络首发：2025-12-09，
  
  纸质出版：2026-08-10
- 稿件说明：
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于曰伟, 李波, 赵雷雷, 等. 融合解析计算的轮毂电机电动汽车主动悬架最优控制[J]. 西安交通大学学报, 2026,60(8):229-239.

YU Yuewei, LI Bo, ZHAO Leilei, et al. Optimal Control of Active Suspension for In-Wheel-Motor-Driven Electric Vehicles Integrating Analytical Calculation[J]. Journal of Xi'an Jiaotong University, 2026, 60(8): 229-239.
于曰伟, 李波, 赵雷雷, 等. 融合解析计算的轮毂电机电动汽车主动悬架最优控制[J]. 西安交通大学学报, 2026,60(8):229-239. DOI： 10.7652/xjtuxb202608020.

YU Yuewei, LI Bo, ZHAO Leilei, et al. Optimal Control of Active Suspension for In-Wheel-Motor-Driven Electric Vehicles Integrating Analytical Calculation[J]. Journal of Xi'an Jiaotong University, 2026, 60(8): 229-239. DOI： 10.7652/xjtuxb202608020.

摘要

针对轮毂电机驱动电动汽车（IWMD-EV）主动悬架最优控制中，存在控制性能评价指标实时求解效率低、控制加权系数自适应调整困难的问题，提出了一种基于解析计算的加权系数设计方法。首先，基于IWMD-EV三自由度主动悬架模型，利用随机振动理论和留数定理积分求解方法，推导得到基于最优控制的IWMD-EV主动悬架系统的车身垂向振动加速度、悬架动行程和轮胎动位移均方根解析计算公式；然后，从理论分析角度，将复杂的控制加权系数求解问题转化为同尺度量化系数和性能评价权重系数求解问题，建立基于解析计算的IWMD-EV主动悬架最优控制加权系数自适应调整方法，实现了控制加权系数随车辆行驶工况的快速动态调整；最后，利用台架试验对所建立方法的可靠性进行了验证。研究结果表明：解析计算与试验测试结果的最大偏差在8%以内，所建立的均方根解析计算式正确可靠；相较于传统线性二次型高斯控制和

∞

控制方法，所提方法能够显著提高不同行驶工况下IWMD-EV的乘坐舒适性。该研究可为基于最优控制的IWMD-EV主动悬架设计提供新思路。

Abstract

To address the problems of low real-time solution efficiency of control performance evaluation indicators and difficulty in adaptive adjustment of control weighting coefficients for the optimal control of active suspensions in in-wheel-motor-driven electric vehicles (IWMD-EVs)

an optimal control weighting coefficient design method based on analytical calculation was proposed. First

based on a three-degree-of-freedom active suspension model of IWMD-EVs

the analytical formulas for the root mean square (RMS) values of the vehicle body vertical acceleration

suspension dynamic stroke

and tire dynamic displacement for optimal control-based IWMD-EV active suspension systems were derived using random vibration theory and the residue theorem integral solution method. Then

from a theoretical analysis perspective

the complex

problem of solving the control weighting coefficients was transformed into a problem of solving the same-scale quantization coefficients and the performance evaluation weighting coefficients. An adaptive adjustment method for optimal control weighting coefficients of IWMD-EV active suspension systems based on analytical calculation was established

by which rapid dynamic adjustment of control weighting coefficients is realized with changes in vehicle driving conditions. Finally

the reliability of the established method was verified through bench tests. The results show that the maximum deviation between analytical calculation results and experimental test results is within 8%

indicating that the established RMS analytical formulas are correct and reliable; compared with traditional linear quadratic Gaussian control and

∞

control methods

the proposed method significantly improves the ride comfort of IWMD-EVs under different driving conditions. This study provides a new approach for the design of optimal control-based IWMD-EV active suspension systems.

关键词

Keywords

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