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基于遗传-蚁群算法的PHEB模糊控制策略优化 被引量:5

Optimization of Fuzzy Control Strategy for Parallel Hybrid Electric Bus Based on Genetic-ant Colony Algorithm
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摘要 以并联式混合动力客车(PHEB)为研究对象,设计了以整车需求转矩与发动机最佳转矩之差以及超级电容荷电状态为输入,以发动机转矩为输出的模糊控制器,并应用遗传-蚁群算法对其进行隶属度函数和控制规则优化。基于MATLAB/Advisor建立了PHEB模糊控制策略模型和整车模型,并对优化前后的实例PHEB性能进行了仿真分析。研究结果表明,优化后的模糊控制策略能够满足设计要求,且等效燃料消耗量比优化前降低了10.2%。 For a kind of PHEB,a fuzzy controller was constructed by using the difference between the requested torque and optimal engine torque and taking the super capacitor state of charge as inputs,and the engine torque as the output.The membership functions and rules of fuzzy controller were optimized simultaneously by using genetic-ant colony algorithm.A simulation model of the fuzzy control strategy was established by MATLAB/Advisor.The performance of the optimized PHEB were simulated.The results show that the optimized fuzzy control strategy can meet the requirements of overall vehicle performance and the fuel consumption is reduced by 10.2% compared with the non-optimized PHEB.
机构地区 合肥工业大学
出处 《中国机械工程》 EI CAS CSCD 北大核心 2011年第14期1754-1759,共6页 China Mechanical Engineering
基金 国家高技术研究发展计划(863计划)资助重大项目(2008AA11A139)
关键词 并联式混合动力客车(PHEB) 遗传-蚁群算法 模糊控制策略 优化 parallel hybrid electric bus(PHEB) genetic-ant colony algorithm fuzzy control strategy optimization
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