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多目标遗传算法的混合动力传动系参数优化 被引量:22

Parametric Optimization of Hybrid Powertrain Based on Multi-objective Genetic Algorithm
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摘要 对基于超级电容的混合动力客车(hybrid electric bus,HEB)进行了混合动力传动系多目标参数优化设计。通过CRUISE建立HEB整车仿真模型和传动系多目标参数优化模型,以等效燃油消耗量和加速时间为优化目标,同时运用带精英策略的非支配排序遗传算法(NSGA-Ⅱ)和iSIGHT优化软件对HEB传动系参数进行多目标优化,并进行了HEB性能仿真分析。结果表明,与优化前相比,优化后的等效燃油消耗量降低了7.8%,连续换挡加速时间减少了6.5%。 Based on the characteristics analyses of a H EB of super capacitor,a multi-objective parameter optimization for HEB powertrain was designed. The multi-objective optimization model for HEB powertrain was established via CRUISE. Taking fuel consumption and acceleration time of HEB as targets of the optimization,the elitist non-dominated sorting genetic algorithm (NSGA-Ⅱ ) was applied to optimize the powertrain parameters of HEB by a optimization software iSIGHT. The per formance simulations were carried on an instance HEB,the results show that the fuel consumption is reduced by 7.8%and acceleration time is reduced by 6.5 %,compared with the road testing of the instance HEB.
出处 《中国机械工程》 EI CAS CSCD 北大核心 2013年第4期552-556,共5页 China Mechanical Engineering
基金 国家高技术研究发展计划(863计划)资助项目(2011AA11A202) 安徽省自然科学基金资助项目(1208085ME78) 合肥工业大学博士专项科研基金资助项目(2011HGBZ0931)
关键词 混合动力客车 动力传动系 多目标遗传算法 参数优化 hybrid electric bus (HEB) powertrain multi-objective genetic algorithm parameteroptimization
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