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基于NSGA-Ⅱ算法的汽车电子电气架构多目标优化 被引量:7

Multi-Objective Optimization of Automotive Electronic and Electrical Architecture Based on NSGA-Ⅱ Algorithm
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摘要 在汽车研发阶段电子电气架构的评价是个核心要素,在研发的末期不仅要验证电子电气架构的功能和技术上的正确性,还要实现最优化,而电子电气架构的经济性、量化性和负载性是评价电子电气架构的重要指标。建立了以电子电气架构总线成本、质量和负载的目标函数,建立了电子电气架构优化设计的多目标数学模型,利用精英控制策略快速非支配排序遗传算法(Fast and elitist non-dominat-ed sorting genetic algorithm,NSGA-Ⅱ)对该架构模型设计求解,得到符合条件的Pareto解集并进行分析,为决策者在工程实际中选择优化方案提供了有效方法,提高了工作效率,同时也为优化电子电气架构提供了一种新方法。 The evaluation of the electrical and electronic architecture in the automotive research and development stage phase is a core element. At the end of research and development stage,it is not only necessary to verify the functional and technical correctness of the electrical and electronic architecture,but also to optimize,while the economics,quantification and load of the electrical and electronic architecture. It is an important indicator for evaluating the electrical and electronic architecture. In this paper,the objective function of the cost,weight and load of the electrical and electronic architecture bus is established, and the multi-objective mathematical model of the optimization design of the electrical and electronic architecture is established. The fast and nondominant-sorting genetic algorithm is adopted by the elite control strategy( Fast and elitist nondominat-ed sorting). (Genetic algorithm,NSGA-Ⅱ) solves the architecture model and obtains the Pareto solution set and analyzes it. It provides an effective method for decision makers to choose the optimization scheme in engineering practice and improve the work efficiency.. At the same time,it also provides a new method for optimizing electronic and electrical architecture.
作者 关志伟 赵洪林 杜峰 唐风敏 李俊凯 GUAN Zhiwei;ZHAO Honglin;DU Feng;TANG Fengmin;LI Junkai(School of Automation and Transportation,Tianjin University of Technology and Education,Tianjin 300222,China;China Automotive Technology Research Center Co.,Ltd.,Tianjin 300300,China;School of Mechanical Engineering,Hebei University of Technology,Tianjin 300401,China)
出处 《重庆理工大学学报(自然科学)》 CAS 北大核心 2020年第7期87-93,共7页 Journal of Chongqing University of Technology:Natural Science
基金 国家重点研发计划项目(2017YFB0102500) 天津市科技创新平台计划项目(16PTGCCX00150) 天津市人工智能科技重大专项(17ZXRGGX00070) 天津市科技发展战略研究计划重点招标项目(18ZLZDZF00390)。
关键词 电子电气架构 多目标优化 NSGA-Ⅱ算法 PARETO解集 electronic and electrical architecture multi-objective optimization NSGA-Ⅱalgorithm Pareto solution
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