MULTIOBJECTIVE DESIGN OPTIMISATION ALGORITHMS APPLIED TO IMPROVE INTAKE/EXHAUST SYSTEM PERFORMANCE OF A CAR ENGINE
In this paper, we discuss the nondominated sorting genetic algorithm (NSGA) . We present the NSGA algorithm to solve this class of problems and its performance is analyzed in comparing its results with those obtained with four others algorithms. Finally, the NSGA is applied to solve the design problem of an exhaust manifold to map the Pareto-optimum front This result suggests that the pipe radius is effective to maximize the temperature at the end of the exhaust manifold ,the merging configuration is very effective to improve the charging efficiency. And The present system has successfully found solutions that have less environmental impact and more engine power simultaneously than the initial design.The resulting Pareto front also reveals the tradeoff between the two objectives.
co-evolutionary algorithms Multiobjective Optimization NSGA charging eflficiency an exhaust manifold
Gaoping Wang Yongji Wang
School of Information Science and Engineering, Henan University of Technology, Zhengzhou 450052 ,Chi Department of Control Engineering, Huazhong University of Science and Tecnology ,Wuhan 430074, China
国际会议
5th International Conference on e-Engineering & Digital Enterprise Technology(第5届e工程及数字企业国际学术会议)
贵阳
英文
353-356
2006-08-16（万方平台首次上网日期，不代表论文的发表时间）