基于遗传算法的混合动力汽车动力总成悬置系统的优化设计研究

庄伟超1,王良模1,殷召平2,叶进2,吴海啸2

振动与冲击 ›› 2015, Vol. 34 ›› Issue (8) : 209-213.

PDF(1441 KB)
PDF(1441 KB)
振动与冲击 ›› 2015, Vol. 34 ›› Issue (8) : 209-213.
论文

基于遗传算法的混合动力汽车动力总成悬置系统的优化设计研究

  • 庄伟超1,王良模1,殷召平2,叶进2,吴海啸2
作者信息 +

Optimization Design on Powertrain Mounting System of Hybrid Electric Vehicle  Via Genetic Algorithm

  • Weichao Zhuang1, Liangmo Wang1, Zhaoping Yin2, Jin Ye2, Haixiao Wu2
Author information +
文章历史 +

摘要

为了提高并联式混合动力汽车动力总成五点悬置系统的隔振性能,建立了动力总成五点悬置的动力学模型,以动力总成六自由度能量解耦与固有频率的合理分配为优化目标,五个悬置点的各向刚度为设计变量,采用遗传算法对悬置系统进行优化。应用上述方法对某并联式柴电混合动力汽车悬置系统进行了优化,动力学仿真与实车试验结果表明,悬置优化后消除了整车怠速工况时方向盘抖动,验证了所提方法的合理性。同时,遗传算法克服了序列二次型规划算法(SQP)易收敛于局部最优解的缺点,得到的悬置系统解耦性能优良,优化结果稳定可靠。

Abstract

 A method to optimize the powertrain mounting system is developed to improve the vibration isolation performance of the mounting system for a parallel hybrid electric vehicle. The optimization is based on the genetic algorithm with taking the six-degree-freedom decoupling of the powertrain mounting system and the reasonable allocation of natural frequency as the objective function, and the stiffness of each mounting as the design variable. This method is applied to deal with the shaking of steering wheel for a parallel hybrid electric vehi-cle in idling process. And results of dynamics simulation verify the effectiveness of the method. Furthermore, compared to Sequential Quad-ratic Programming (SQP), genetic algorithm overcomes the fault, converging on local optimum. And the decoupling of mounting system obtained from the optimization is better and reliable.
 

关键词

动力总成悬置 / 能量解耦 / 优化 / 遗传算法

Key words

Powertrain mounting system / Energy decoupling / Optimization / Genetic Algorithm.

引用本文

导出引用
庄伟超1,王良模1,殷召平2,叶进2,吴海啸2. 基于遗传算法的混合动力汽车动力总成悬置系统的优化设计研究[J]. 振动与冲击, 2015, 34(8): 209-213
Weichao Zhuang1, Liangmo Wang1, Zhaoping Yin2, Jin Ye2, Haixiao Wu2. Optimization Design on Powertrain Mounting System of Hybrid Electric Vehicle  Via Genetic Algorithm[J]. Journal of Vibration and Shock, 2015, 34(8): 209-213

参考文献

[1] Bernard J E, Starkey J M. Engine mount optimization[R]. 1983.
[2] 孙蓓蓓,张启军,孙庆鸿,等. 汽车发动机悬置系统解耦方法研究[J]. 振动工程学报, 1994, 7(3): 240-245.
Sun Beibei, Zhang Qijun, Sun Qinhong, et al. Study on De-coupled Engine Mounting System [J]. Journal of vibration engineering, 1994, 7(3): 240-245.
[3] 周冠南, 蒋伟康, 吴海军. 基于总传递力最小的发动机悬置系统优化设计[J]. 振动与冲击, 2008, 27(8): 56-58.
Zhou Guannan, Jiang Weikang, Wu Haijun. Optimal design of enginemount system by minimizing the total force trans-mission[J]. Journal of vibration and shock, 2008, 27(8): 56-58.
[4] 童炜, 陈剑斌, 宋晓琳. 基于 ADAMS 的发动机悬置系统多目标优化[J]. 汽车工程, 2011, 33(11): 971- 975.
Tong Wei, Chen Jianbin, Song Xiaolin. Multi-objective Op-timization of Engine Mounting System Based on ADAMS[J]. Automotive Engineering, 2011, 33(11): 971-975.
[5] 吴杰, 上官文斌, 唐静, 等. 动力总成悬置系统解耦布置的鲁棒性分析[J]. 振动与冲击, 2009, 28(9): 15-20.
Wu Jie, Shangguan Wen-bin, Tang Jing, et al. Robust analysis for decoupling layout of a powertrain mounting system [J]. Journal of vibration and shock, 2009, 28(9): 15-20.
[6] Holland J H. Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence[M]. U Michigan Press, 1975.
[7] 段绪伟,李以农,郑玲,等.基于NSGA-II遗传算法的磁流变悬置多目标优化[J].振动与冲击,2014,33(3):191-196.
Duan Xu-wei, LI Yi-nong, Zheng Ling, et al. Multi-objective optimization for a MR engine mount based on NSGA-11 algo-rithm[J].Journal of Vibration and Shock,2014,33(3):191-196.
[8] Goldberg D E, Holland J H. Genetic algorithms and machine learning[J]. Machine learning, 1988, 3(2): 95-99.
[9] Androulakis I P, Venkatasubramanian V. A genetic algo-rithmic framework for process design and optimization[J]. Computers & chemical engineering, 1991, 15(4): 217-228.

PDF(1441 KB)

Accesses

Citation

Detail

段落导航
相关文章

/