汽车动力总成悬置系统的多目标优化方法  

Multi-objective optimization method of vehicle powertrain mounting system

作　　者：姜立标[1] 罗健 Jiang Libiao;Luo Jian(School of Mechanical and Automotive Engineering,South China University of Technology, Guangdong Guangzhou, 510641, China)

机构地区：[1]华南理工大学机械与汽车工程学院,广东广州510641

出　　处：《机械设计与制造工程》2021年第4期87-91,共5页Machine Design and Manufacturing Engineering

摘　　要：对汽车动力总成悬置系统的多目标优化问题进行了研究,明确了优化方向。基于算法融合理论,提出了结合多目标粒子群优化(MOPSO)算法和非支配排序遗传算法Ⅱ(NSGA-Ⅱ)的混合算法,并运用经典测试函数分别对MOPSO算法、NSGA-Ⅱ及混合算法进行测试,验证了混合算法的可行性和高效性。运用混合算法解决了动力总成悬置系统的解耦问题,得到了多组满足要求的解集。实例优化结果证明,该混合算法对解决复杂动力总成悬置系统多目标优化问题是有效的。The optimization direction is clarified by studying the multi-objective optimization problem of powertrain mounting system.According to algorithm fusion theory,a hybrid algorithm combining non-dominated sorting genetic algorithmⅡ(NSGA-Ⅱ)and multi-objective particle swarm optimization algorithm(MOPSO)is proposed,and classical test functions are used to compare NSGA-Ⅱ,MOPSO and hybrid algorithm.The hybrid algorithm is tested to verify the feasibility and efficiency of the hybrid algorithm.It is used in the multi-objective optimization problem of the powertrain mounting system,which solves the decoupling problem of the powertrain mounting system and obtains multiple sets of solutions that meet the requirements.The example shows that the hybrid algorithm is effective for solving complex multi-objective optimization problems of powertrain mounting systems.

关 键 词：动力总成悬置系统 多目标粒子群优化 非支配排序遗传算法Ⅱ 混合算法 多目标优化 

分 类 号：U464.13[机械工程—车辆工程]