黄明.基于多目标遗传算法的发动机进排气系统优化[J].湖南大学学报:自然科学版,,():
基于多目标遗传算法的发动机进排气系统优化
Multi-objective optimization of intake and exhaust system of a gasoline engine using nondominate sorting genetic algorithm-II
投稿时间:2010-08-31  修订日期:2010-09-02
DOI:
中文关键词:  多目标优化  NSGA-II优化算法  进排气系统  发动机性能
英文关键词:multi-objective optimization  NSGA-II  intake an exhaust system  engine performance
基金项目:国家自然科学基金
作者单位E-mail
黄明 湖南大学 机械与运载工程学院 h287119285@hnu.edu.cn 
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中文摘要:
      采用改进的非支配排序遗传算法(NSGA-II)对一单缸汽油发动机的进排气系统进行了优化,以解决该发动机加装触媒催化剂后中速段扭矩明显下降的问题。首先选取发动机进气和排气系统作为优化对象,分析了进、排气管长度、直径等单个变量对发动机扭矩的影响;然后以4500和5500 r/min扭矩为优化目标,运用改进的NSGA-II方法进行了多目标优化。优化后的发动机在保证高低速扭矩的同时恢复了中速段扭矩。结果表明进、排气管长度、直径等对发动机扭矩的影响区域和影响程度都不相同,简单地调整单个变量很难同时满足多个优化目标,而通过加入精英保持策略和去除重复个体算法的NSGA-II方法能够在多维区域内快速有效地搜索Pareto解集,实现多目标优化。
英文摘要:
      An improved nondominate sorting genetic algorithm-II (NSGA-II) is used to optimize the intake and exhaust system of a single cylinder gasoline engine, whose torque at middle range speed was decreased a lot after a catalyst added. First a full GT-power model was set up and verified based on experiment data. Then the intake and exhaust system was selected as the optimization variables, the effects of the diameters and lengths of intake/exhause pipe on the engine performance were investigated individually. Finally an improved nondominate sorting genetic algorithm-II (NSGA-II) is used to solve the multi-objective optimization problem. The results show that the diameters and lengths of intake/exhause pipe have different range and degree of influence on the engine torque. It is different to satisfy the multi-objectives optimization simultaneity by adjusting those variables separately. The improved NSGA-II, with an elitist preserve strategy and duplicates removing algorithm added, can get the Pareto solution set effectively and satisfy the multi-objective optimization.
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