基于改进粒子群算法的同步器多目标参数优化
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摘要
为兼顾变速器中同步器更短同步时间和更高寿命的要求,基于牛顿第二定律和粘着磨损理论、M-B分形接触模型分别建立以同步时间和同步器寿命为目标的数学模型,运用理想点法构造评价函数进而建立以二者为目标的多目标参数优化模型,利用层次分析法确定各目标在多目标优化模型中所占权重值,并借助改进粒子群算法对多目标参数优化模型进行优化求解。结果表明:优化后与优化前相比同步时间减少了8%,同步器寿命增加了9%,二者得到较好的改善。改进粒子群算法的使用使同步器性能得到较好的提升,而理想点法的运用有效的避免了多目标优化中大数量级目标支配优化结果的问题。
To meet the requirements of shorter synchronization time and higher life for the synchronizer in transmission, mathematical models aiming at synchronization time and synchronizer life were established separately based on Newton's second law and adhesive wear theory, M-B fractal contact model. The evaluation function was constructed by ideal point method to establish a multi-objective parameter optimization model with the two objectives. Using the AHP to determine weight value of the target in the multi-objective optimization model, and using the improved particle swarm algorithm to optimize the multi-objective parameter optimization model. The results show that the synchronization time is reduced by 8% and the synchronizer life is increased by 9% compared with that before optimization, the two objectives are improved better. The using of the improved particle swarm algorithm improves the performance of the synchronizer, and the application of the ideal point method effectively avoids the problem that the high order of magnitude dominates the multi-objective optimization.
To meet the requirements of shorter synchronization time and higher life for the synchronizer in transmission, mathematical models aiming at synchronization time and synchronizer life were established separately based on Newton's second law and adhesive wear theory, M-B fractal contact model. The evaluation function was constructed by ideal point method to establish a multi-objective parameter optimization model with the two objectives. Using the AHP to determine weight value of the target in the multi-objective optimization model, and using the improved particle swarm algorithm to optimize the multi-objective parameter optimization model. The results show that the synchronization time is reduced by 8% and the synchronizer life is increased by 9% compared with that before optimization, the two objectives are improved better. The using of the improved particle swarm algorithm improves the performance of the synchronizer, and the application of the ideal point method effectively avoids the problem that the high order of magnitude dominates the multi-objective optimization.
引文
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[3] 戴丰,鲁统利,张建武. 基于分形理论的同步器接触磨损模型[J]. 汽车技术, 2009, 404(05): 15-18.DAI Feng, LU TongLi, ZAHNG JianWu. A model for Synchronizer contact wear based on fractal theory[J]. Automobile Technology, 2009, 404(05): 15-18(In Chinese).
[4] 宋京伟,李克诚. 同步器的优化设计和工作过程仿真[J].现代机械, 2014, 181(3): 57-60.SONG JingWei, LI KeCheng. On optimization design and working process simulation of synchronizer[J]. Modern Machinery, 2014, 181(3): 57-60(In Chinese).
[5] Naunheimer H, Bertsche B, Ryborz J, et al. Automotive Transmission[M]. Second edition. Berlin: Springer-Verlag, 2011: 314-325.
[6] 刘惟信. 机械最优化设计[M]. 第2版. 北京: 清华大学出版社, 1994: 334-337.LIU WeiXin. Mechanical optimization design[M]. Second edition. Beijing: Tsinghua University Press, 1994: 334-337(In Chinese).
[7] 葛世荣,朱华. 摩檫学的分形[M]. 第1版. 北京: 机械工业出版社, 2005: 250-252.GE ShiRong, ZHU Hua. Fractal of rubbing[M]. First edition. Beijing: China Machine Press, 2005: 250-252(In Chinese).
[8] 温诗铸,黄平. 摩檫学原理[M]. 第2版. 北京: 清华大学出版社, 2002: 301-354.WEN ShiZhu, HUANG Ping. Rubbing principle[M]. Second edition. Beijing: Tsinghua University Press, 2002: 301-354(In Chinese).
[9] 朱淳逸. 同步器同步过程中磨损及失效的建模与研究[D]. 汉中: 陕西理工学院, 2016: 13-35.ZHU ChunYi. Modeling and study of wear and failure in the synchronizer working process[D]. Hanzhong: Shanxi Sci-Tech University, 2016: 13-35(In Chinese).
[10] Halling J. Principles of Tribology[M]. First edition. London:The Macmillan Press, 1975: 81-83.
[11] 李文平,鹿云,朱之龙等. 同步器摩擦材料摩擦学特性的研究[J]. 汽车工艺与材料, 2013, 293(05):53-57.LI WenPing, LU Yun, ZHU ZhiLong, et al. Study on tribological characteristics of synchronizer friction material[J]. Automobile Technology & Material, 2013, 293(05): 53-57(In Chinese).
[12] 周凯,宋军全,邬学军. 数学建模竞赛入门及提高[M]. 第1版. 杭州: 浙江大学出版社, 2011: 57-60.ZHOU Kai, SONG JunQuan, WU XueJun. Introduction and improvement of mathematical modeling contest[M]. First edition. Hangzhou: Zhejiang University Press, 2011: 57-60(In Chinese).
[13] 高飞. MATLAB智能算法超级学习手册[M]. 第1版. 北京: 人民邮电出社, 2014: 250-273.GAO Fei. Super learning manual of MATLAB intelligentalgorithm[M]. First edition. Beijing: Posts and Telecommunications Press, 2014: 250-273(In Chinese).