• CN:11-2187/TH
  • ISSN:0577-6686

›› 2014, Vol. 50 ›› Issue (24): 130-136.doi: 10.3901/JME.2014.24.130

• 论文 • 上一篇    下一篇

多种群遗传优化的客车防侧翻鲁棒控制方法

金智林;张甲乐;马翠贞   

  1. 南京航空航天大学车辆工程系
  • 出版日期:2014-12-20 发布日期:2014-12-20

Robust Control Strategy of Passenger Car Rollover Prevention with Multi-population Genetic Optimization

JIN Zhilin;ZHANG Jiale;MA Cuizhen   

  • Online:2014-12-20 Published:2014-12-20

摘要: 为改善客车主动防侧翻能力,提出多种群遗传优化的防侧翻鲁棒控制方法。考虑车轮侧倾外倾、侧倾转向、悬架变形外倾和变形转向对轮胎侧偏特性影响,以及客车垂向与侧倾运动的耦合特性,建立6自由度客车侧翻动力学模型;针对客车的实际干扰及参数不确定性,以最大横向载荷转移率为控制目标,融合差动制动原理设计客车主动防侧翻的鲁棒控制方法;应用多种群遗传理论对控制器的权函数进行动态优化,增强控制系统的抗干扰能力;选取J-Turn及Worst-Case典型侧翻工况进行数值仿真,分析防侧翻控制方法对不同行驶工况的适用性、前轮转向干扰及路面干扰下的抗干扰稳定性以及簧载质量和车速变化时参数摄动鲁棒性。结果表明该方法能将客车侧翻危险速度提高75%以上,有效改善客车主动防侧翻能力;且对不同行驶工况、不同类型干扰及参数变化均有强鲁棒性。

关键词: 多种群遗传优化, 客车防侧翻, 鲁棒控制, 汽车主动安全

Abstract: In order to improve performance of passenger car rollover prevention, the robust control strategy with multi-population genetic optimization is presented. Taking the roll casting, roll steering, and the coupling relationship between vertical motion and roll motion into consideration, a six degrees of freedom model is established on the rollover dynamic theory of passenger car. As a control target, the maximum lateral-load transfer ratio(LTR) is applied to the robust control strategy for passenger car rollover prevention with differential braking. To enhance the anti-disturbance capability, the multi-population genetic methodology is used to optimize the weight function of controller. Some characteristics of the control strategy are discussed by numerical cases, such as the adaptive ability of the strategy in two typical driving conditions including J-Turn and Worst-Case, and the robustness of the strategy under the front wheel steering interference and pavement interference, as well as the sprung mass and speed variation. The results show that the critical velocity can be increased by over 75%, and the strategy is successful with good robustness at various driving conditions, external disturbances and parameter perturbations.

Key words: multi-population genetic optimization, passenger car rollover prevention, robust control, vehicle active safety

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