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基于多目标遗传算法的汽车动力传动系统参数优化设计

Parametric Optimization Design of Automobile Powertrain Based on Multi-objective Genetic Algorithm

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【作者】 颜伏伍胡峰田韶鹏袁智军

【Author】 Yan Fuwu1,Hu Feng1,Tian Shaopeng1,2,Yuan Zhijun2 (1.Wuhan University of Technology;2.SAIC-GM Wuling Automobile Co.,Ltd)

【机构】 武汉理工大学上汽通用五菱汽车股份有限公司

【摘要】 建立了汽车动力性和燃油经济性仿真模型,并在此基础上建立了汽车动力传动系统参数多目标优化模型,引入了带精英策略的非支配排序遗传算法NSGA-Ⅱ作为优化算法。以某微型车为例,对其进行了性能仿真计算和传动系统参数优化设计。结果表明,仿真结果与道路试验结果基本吻合,该仿真模型具有较高的精度;优化后整车动力性和燃油经济性结果令人满意。

【Abstract】 A simulation model of automobile power performance and fuel economy is established in the paper,and on this basis a multi-objective model for automobile powertrain is set up.The elitist non-dominated sorting genetic algorithm NSGA-Ⅱ has been adopted to do the optimization.The paper takes a mini car as example to carry out performance simulation calculation and powertrain parametric optimization design.The results show that the simulation results basically agree with the road test results,the simulation model has high degree of precision;the vehicle dynamic performance and fuel economy after optimization are satisfactory.

  • 【文献出处】 汽车技术 ,Automobile Technology , 编辑部邮箱 ,2009年12期
  • 【分类号】U463.2
  • 【被引频次】28
  • 【下载频次】528
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