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混合动力重型货车参数局部与集成优化仿真研究

Simulation Research on Local and Integrated Optimization of Parameters for Hybrid Heavy-Duty Truck
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摘要 动力耦合系统的动力源参数匹配和能量管理策略两者相互关联,为提高混合动力重型货车的综合性能,两者应集成设计。针对混合动力重型货车参数匹配需反复计算、验证的特点,在Matlab/Simulink中建立了可缩放、自动寻优的参数匹配模型。以经济性为目标函数,基于粒子群算法进行动力源参数匹配,得到局部最优动力源参数结果。针对混合动力重型货车中广泛采用的基于规则的能量管理策略,其规则控制中一些阈值参数不确定的问题,应用粒子群算法对其关键控制参数进行优化,得到局部最优控制参数。为了实现全局最优的匹配结果,将动力源部件参数和控制策略参数进行集成优化,以动力性为约束条件,经济性最优为优化目标,得到全局最优的参数匹配结果。对比显示,全局优化匹配效果相较于动力源参数局部优化提升11.4%、相较于控制策略参数局部优化提升12.4%。 The power-source parameter matching of the power coupling system and the energy management strategy are related to each other and should be integrally designed to improve the comprehensive performance of the hybrid heavy-duty truck. Due to the repeated calculation and verification in the parameter matching method for hybrid heavy trucks, a scalable and automatic optimization model for parameter matching was established by using Matlab/Simulink. Taking economy as the objective function, the power source parameters were matched based on the particle swarm optimization algorithm, and then the locally optimal parameters were obtained. Additionally, for the uncertain threshold parameters in the rule-based energy management control strategy, the particle swarm optimization algorithm was conducted to optimize the key control parameters and obtain the local optimum. In order to achieve the globally optimal matching results, the parameters of power source components and control strategy were integrally optimized by taking the power performance as the constraint condition and economy as the objective function. The parameter matching effect of the global optimization is 11.4% higher than that of the local optimization using the power source parameters, and 12.4% higher than using the control strategy parameters.
作者 杜常清 何隽逸 张佩 杨贤诚 DU Changqing;HE Junyi;ZHANG Pei;YANG Xiancheng(Hubei Key Laboratory of Advanced Technology for Automotive Components,Wuhan University of Technology,Wuhan 430070,China;Hubei Collaborative Innovation Center for Automotive Components Technology,Wuhan University of Technology,Wuhan 430070,China;Hubei Research Center for New Energy&Intelligent Connected Vehicle,Wuhan 430070,China)
出处 《汽车工程学报》 2022年第5期614-623,共10页 Chinese Journal of Automotive Engineering
基金 国家自然科学基金(51775393) 湖北省技术创新重大项目(2018AAA053) 现代汽车零部件技术湖北省重点实验室开发基地资助项目(XDQCKF2021010)。
关键词 混合动力重型货车 粒子群算法 集成优化 参数匹配 能量管理 hybrid heavy-duty truck particle swarm optimization integrated optimization parameter matching energy management
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