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基于粒子群算法的汽车悬架弹簧的优化设计 被引量:2

Optimization Design of Automobile Suspension Spring Based on Particle Swarm Algorithm
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摘要 粒子群算法容易理解、易于实现、编程简单。利用粒子群优化算法对汽车悬架弹簧进行优化设计,其速度要比用其他的方法快得多,仅迭代很少的次数就能得出比较优的结果。有利于提高设计的速度,使设计易于实现,更大程度地提高设计的质量,为钢板弹簧系统、汽车悬架和整车的分析计算奠定坚实的基础。同时为少片弹簧和多片弹簧的优化设计提供了一种新的方法。 The particle swarm algorithm (PSO) is easy to be understood, realized and programmed. The PSO was used for optimization design of automobile suspension spring, which increased the speed of the design a lot than other methods and only had few times of repeating to obtain much better results. Design speed was well improved, and was easy to be realized, and the design quality was enhanced in greater de- gree. The solid foundation for the steel board spring system, the automobile suspension and the entire vehicle analysis computation is laid. At the same time, a new method is provided for optimization design with the few leaf springs and the multi-leaf springs.
作者 刘培 黄玲
出处 《汽车零部件》 2013年第6期73-75,共3页 Automobile Parts
关键词 粒子群算法 汽车悬架弹簧 优化设计 Particle swarm algorithm Automobile suspension spring Optimization design
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参考文献4

  • 1吴启迪,汪镭著..智能微粒群算法研究及应用[M].南京:江苏教育出版社,2005:300.
  • 2刘惟信.机械最优化设计[M].北京:清华大学出版社,1994.. 被引量:184
  • 3王庆五..渐变刚度钢板弹簧设计研究[D].昆明理工大学,2003:
  • 4李建勇..粒子群优化算法研究[D].浙江大学,2004:

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