东北大学学报:自然科学版 ›› 2018, Vol. 39 ›› Issue (9): 1299-1303.DOI: 10.12068/j.issn.1005-3026.2018.09.017

• 机械工程 • 上一篇    下一篇

基于路面识别的非线性悬架系统自适应控制

孙晋伟, 秦也辰, 王振峰, 顾亮   

  1. (北京理工大学 机械与车辆学院, 北京100081)
  • 收稿日期:2017-04-03 修回日期:2017-04-03 出版日期:2018-09-15 发布日期:2018-09-12
  • 通讯作者: 孙晋伟
  • 作者简介:孙晋伟(1987-),男,山西忻州人,北京理工大学博士研究生; 顾亮(1958-),男,山东淄博人,北京理工大学教授,博士生导师.冯明杰(1971-), 男, 河南禹州人, 东北大学副教授; 王恩刚(1962-), 男, 辽宁沈阳人, 东北大学教授,博士生导师.
  • 基金资助:
    国家自然科学基金资助项目(U1564210); 中国博士后科学基金资助项目(2016M600934,BX201600017).国家自然科学基金资助项目(51171041).

Adaptive Control of the Nonlinear Suspension System Based on Road Estimation

SUN Jin-wei, QIN Ye-chen, WANG Zhen-feng, GU Liang   

  1. School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China.
  • Received:2017-04-03 Revised:2017-04-03 Online:2018-09-15 Published:2018-09-12
  • Contact: GU Liang
  • About author:-
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摘要: 针对非线性悬架系统,基于多目标布谷优化和路面识别算法,研究不同路面等级下悬架非线性系统特性,实现根据路面等级调整控制参数的目的.首先建立四分之一车辆模型,选取电流为优化变量,簧载质量加速度和轮胎动行程为优化目标;然后利用布谷优化算法求取不同路面下悬架最优参数,并利用路面识别方法得到当前路面等级,结合悬架性能需求实现悬架在不同路面下自适应调节.仿真结果表明:1)控制算法可根据不同路面情况自适应调整悬架参数,提高系统性能;2)相比于传统粒子群优化方法(PSO),基于布谷优化算法得到的控制电流能提供更为理想的悬架系统性能.

关键词: 非线性悬架, 路面识别, 布谷优化, 平顺性, 操纵稳定性

Abstract: To adjust the control parameters according to road levels and study the characteristics of suspension nonlinear parameters under different road levels, an algorithm was proposed based on cuckoo search optimization and road estimation. Firstly, a quarter nonlinear suspension model with nonlinear dampers and springs was created, which sprung mass acceleration and tire deflection were taken as the optimization objective and the current of nonlinear dampers was taken as the optimization variable. Then, a cuckoo search-based multi-objective optimization method was used to calculate the optimal control parameter, and a road estimation method was used to identify the road level to adaptively adjust the system performance according to road input. The simulation results showed that: 1) the road estimation and cuckoo search-based algorithm can adjust the control parameter adaptively according to road levels, and the proposed method can improve riding comfort when the tire keeps contacting the road surface; 2) compared with the particle swarm optimization(PSO), the current calculated by cuckoo search can provide better suspension performances.

Key words: nonlinear suspension, road estimation, cuckoo search optimization, riding comfort, handling stability

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