基于粒子群算法的被动分数阶汽车悬架参数优化设计

游浩,申永军,杨绍普

振动与冲击 ›› 2017, Vol. 36 ›› Issue (16) : 224-228.

PDF(1219 KB)
PDF(1219 KB)
振动与冲击 ›› 2017, Vol. 36 ›› Issue (16) : 224-228.
论文

基于粒子群算法的被动分数阶汽车悬架参数优化设计

  • 游浩,申永军,杨绍普
作者信息 +

Parameters Design for Passive Fractional-order Vehicle Suspension Based on Particle Swarm Optimization

  • YOU Hao, SHEN Yong-jun, YANG Shao-pu
Author information +
文章历史 +

摘要

本文利用粒子群算法研究了被动分数阶汽车悬架参数的优化设计。分数阶汽车悬架系统是指运动微分方程中含有分数阶微分项的汽车悬架系统。建立了被动分数阶悬架系统的仿真模型,利用Oustaloup滤波器算法实现了该模型中分数阶微积分的近似计算。随后,利用粒子群算法寻找一组最优的悬架参数来协调汽车操纵稳定性和乘坐舒适性的关系以到达最优的悬架性能。最后,对比了原悬架系统和优化后悬架系统在A、B、C、D共四级路面输入下的响应及其频率特性。研究结果表明利用本文方法对被动分数阶悬架参数进行优化设计,在保证汽车操纵稳定性的前提下乘坐舒适性得到明显改善。

Abstract

In this paper the optimal design of passive fractional-order vehicle suspension parameters is researched based on particle swarm optimization. A vehicle suspension system whose motion differential equation contains fractional-order derivatives is called fractional-order vehicle suspension system. The simulation model of passive fractional-order vehicle suspension system is built, and the approximate solution of fractional-order derivatives in this system is obtained by using Oustaloup filter algorithm. Then, in order to achieve optimal performance of the passive fractional-order vehicle suspension, the relationship between the ride comfort and drive stability is coordinated by using particle swarm optimization to find a set of optimal suspension parameters. Finally, the responses of original and optimized passive fractional-order suspension systems are compared when the vehicle is running on different road levels from A to D respectively, and their frequency characteristics are also compared. The study results indicate that the ride comfort is improved greatly on the premise of guaranteeing drive stability, when the passive fractional-order vehicle suspension parameters are optimized by using this method.
 

关键词

汽车悬架 / 分数阶微积分 / 粒子群算法 / Oustaloup滤波器

Key words

 vehicle suspension / fractional-order derivatives / particle swarm optimization / Oustaloup filter algorithm

引用本文

导出引用
游浩,申永军,杨绍普. 基于粒子群算法的被动分数阶汽车悬架参数优化设计[J]. 振动与冲击, 2017, 36(16): 224-228
YOU Hao, SHEN Yong-jun, YANG Shao-pu. Parameters Design for Passive Fractional-order Vehicle Suspension Based on Particle Swarm Optimization[J]. Journal of Vibration and Shock, 2017, 36(16): 224-228

参考文献

[1] 杨建伟, 李敏, 孙守光. 汽车半主动磁流变悬架的自适应双模糊控制方法 [J]. 振动与冲击, 2010, 29(8): 45-51.
YANG Jian-wei, LI Min, SUN Shou-guang. Adaptive dual fuzzy control method for automotive semi-active suspension with magneto-rheological damper [J]. Journal of Vibration and Shock, 2010, 29(8): 45-51.
[2] 任勇生, 周建鹏. 汽车半主动悬架技术研究综述 [J]. 振动与冲击, 2006, 25(3):162-165.
REN Youg-sheng, ZHOU Jian-peng. Vehicle semi-active suspension techniques and its applications [J]. Journal of Vibration and Shock, 2006, 25(3):162-165.
[3] 刘永强, 杨绍普, 申永军. 基于磁流变阻尼器的汽车悬架半主动相对控制 [J]. 振动与冲击, 2008, 27(2): 154-161.
LIU Yong-qiang, YANG Shao-pu, SHEN Yong-jun. Emi-active relative control schemes for vehicle suspension using a magneto-rheological damper [J]. Journal of Vibration and Shock, 2008, 27(2): 154-161.
[4] Abushaban M H, Abuhadrous I M, Sabra M B. A new fuzzy control strategy for active suspensions applied to a half car model [J].  Journal of Mechatronics, 2013, 1(2): 128-134.
[5] 申永军,刘献栋,杨绍普. 基于最优控制的汽车被动悬架参数优化设计 [J]. 振动、测试与诊断,2004, 24(2): 96-99.
SHEN Yong-jun, LIU Xian-dong, YANG Shao-pu. Optimization of parameters of passive vehicle suspension based on optimal control theory [J]. Journal of Vibration, Measurement and Diagnosis, 2004, 24(2): 96-99.
[6] 谢能刚, 岑豫皖, 方浩, 等. 被动悬架参数的多目标博弈设计 [J]. 机械强度, 2010, 32(1): 079-085.
XIE Neng-Gang, CEN Yu-Wan, FANG Hao, et al. Multi-objective design parameters of passive suspension based on game theory [J]. Journal of Mechanical Strength, 2010, 32(1): 079-085.
[7] Gemant A. A method of analyzing experimental results obtained from elasto-viscous bodies [J]. Physics, 1936, 7(8): 311-317.
[8] Makris N and Constantinou M C. Fractional-derivative Maxwell model for viscous dampers [J]. J Struct Eng: ASCE1991; 177: 2708–2724.
[9] Oustaloup A, Moreau X, Nouillant M. The CRONE suspension [J]. Control Engineering Practice, 1996, 4(8): 1101-1108.
[10] 刘晓梅, 李洪友, 黄宜坚. 磁流变阻尼器的分数阶 Bingham 模型研究 [J]. 机电工程, 2015, 32(3): 338-342.
    LIU Xiao-mei, LI Hong-you, HUANG Yi-jian. Fractional derivative Bingham model of MR damper [J]. Journal of Mechanical and Electrical Engineering, 2015, 32(3): 338-342.
[11] 陈杰平, 陈无畏, 祝辉, 等. 基于Matlab/Simulink的随机路面建模与不平度仿真 [J]. 农业机械学报, 2010, 3(3): 11-15.
CHEN Jie-ping, CHEN Wu-wei, ZHU Hui, et al. Modeling and simulation on stochastic road surface irregularity based on Matlab/Simulink [J]. Journal of agricultural machinery, 2010, 3(3): 11-15.
[12] You H, Shen Y J, Yang S P. Optimal design for fractional-order active isolation system. Advances in Mechanical Engineering, 2015, 7(12).
[13] Shen Y J, Yang S P, Xing H J. Dynamical analysis of linear single degree-of-freedom oscillator with fractional-order derivative [J].  Acta Physica Sinica, 2012, 61: 110505-11.
[14] Oustaloup A,Levron F,Mathieu B,et al. Frequency-band complex non-integer differentiator: characterization and synthesis [J]. IEEE Transactions on Circuit and Systems-I: Fundamental Theory and Applications,2000,TCS-47(1) : 25-39.
[15] Shakoor P, Ricardo A, Delfim F M T. Numerical approximations of fractional derivatives with applications [J]. Asian J Control 2013, 15: 698–712.
[16] Kennedy J, Eberhart R C. Particle swarm optimization [M]. Proceeding of IEEE International Conference on Neural Networks, Piscataway, New Jersey, 1995: 1942-1948.
[17] Reynolds C W. Flocks, herds, and schools: A distributed behavioral model [J]. Computer Graphics, 1987, 21(4): 25-34

PDF(1219 KB)

489

Accesses

0

Citation

Detail

段落导航
相关文章

/