Multi-objective optimization of hydro-viscous flexible drive for dynamic characteristics using genetic algorithm

被引:5
|
作者
Cui, Jianzhong [1 ,2 ]
Li, Hu [3 ]
Zhang, Dong [3 ]
Xu, Yawen [3 ]
Xie, Fangwei [4 ]
机构
[1] Yancheng Inst Technol, Res Ctr Mould Intelligent Mfg Technol, Yancheng, Peoples R China
[2] Southeast Univ, Sch Mech Engn, Nanjing, Peoples R China
[3] Yancheng Inst Technol, Sch Mech Engn, Yancheng, Peoples R China
[4] China Univ Min & Technol, Sch Mech Engn, Xuzhou, Jiangsu, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Genetic algorithm; Multi-objective optimization; Dynamic characteristics; Hydro-viscous drive; Flexible transmission efficiency; ROUGH; SURFACES; CONTACT; CLUTCH; MODEL; FLOW;
D O I
10.1108/ILT-12-2020-0472
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Purpose The purpose of this study is to investigate the flexible dynamic characteristics about hydro-viscous drive providing meaningful insights into the credible speed-regulating behavior during the soft-start. Design/methodology/approach A comprehensive dynamic transmission model is proposed to investigate the effects of key parameters on the dynamic characteristics. To achieve a trade-off between the transmission efficiency and time proportion of hydrodynamic and mixed lubrication, a multi-objective optimization of friction pair system by genetic algorithm is presented to obtain the optimal combination of design parameters. Findings Decreasing the engagement pressure or the ratio of inner and outer radius, increasing the lubricating oil viscosity or the outer radius will result in the increase of time proportion of hydrodynamic and mixed lubrication, as well as the transmission efficiency and its maximum value. After optimization, main dynamic parameters including the oil film thickness, angular velocity of the driven disk, viscous torque and total torque show remarkable flexible transmission characteristics. Originality/value Both the dynamic transmission model and multi-objective optimization model are established to analyze the effects of main design parameters on the dynamic characteristics of hydro-viscous flexible drive.
引用
收藏
页码:1003 / 1010
页数:8
相关论文
共 50 条
  • [31] Structure optimization of neural network for dynamic system modeling using multi-objective genetic algorithm
    Loghmanian, Sayed Mohammad Reza
    Jamaluddin, Hishamuddin
    Ahmad, Robiah
    Yusof, Rubiyah
    Khalid, Marzuki
    NEURAL COMPUTING & APPLICATIONS, 2012, 21 (06): : 1281 - 1295
  • [32] A single front genetic algorithm for parallel multi-objective optimization in dynamic environments
    Camara, Mario
    Ortega, Julio
    de Toro, Francisco
    NEUROCOMPUTING, 2009, 72 (16-18) : 3570 - 3579
  • [33] The Parallel Single Front Genetic Algorithm (PSFGA) in dynamic multi-objective optimization
    Camara, Mario
    Ortega, Julio
    De Toro, Francisco
    COMPUTATIONAL AND AMBIENT INTELLIGENCE, 2007, 4507 : 300 - +
  • [34] Eccentricity optimization of NGB system by using multi-objective genetic algorithm
    Yazdi, H. Mosalman
    Ramli Sulong, N.H.
    Journal of Applied Sciences, 2009, 9 (19) : 3502 - 3512
  • [35] Global Shape Optimization of Airfoil Using Multi-objective Genetic Algorithm
    Lee, Juhee
    Lee, Sanghwan
    Park, Kyoungwoo
    TRANSACTIONS OF THE KOREAN SOCIETY OF MECHANICAL ENGINEERS B, 2005, 29 (10) : 1163 - 1171
  • [36] Workspace optimization of parallel robot by using multi-objective genetic algorithm
    王进洪
    LEI Jingtao
    High Technology Letters, 2022, 28 (04) : 411 - 417
  • [37] Workspace optimization of parallel robot by using multi-objective genetic algorithm
    Wang, Jinhong
    Lei, Jingtao
    High Technology Letters, 2022, 28 (04) : 411 - 417
  • [38] Multi-objective optimization design of Screw conveyor using Genetic Algorithm
    Wang Duanyi
    THERMAL, POWER AND ELECTRICAL ENGINEERING, PTS 1 AND 2, 2013, 732-733 : 402 - 406
  • [39] Multi-objective optimization of emergency evacuation using improved genetic algorithm
    Meng, Yongchang
    Yang, Saini
    Shi, Peijun
    Yang, S. (yangsaini@bnu.edu.cn), 1600, Editorial Board of Medical Journal of Wuhan University (39): : 201 - 205
  • [40] MULTI-OBJECTIVE OPTIMIZATION FOR FRANCIS TURBINE RUNNER USING GENETIC ALGORITHM
    Sato, Koma
    Tamura, Yuta
    Tani, Kiyohito
    PROCEEDINGS OF THE ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, 2014, VOL 7, 2015,