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<p>To address the issues of friction part burning and engagement impact during continuous transmission shifting, this study develops a dynamic model of the wet clutch engagement process. It investigates the influence of key parameters engagement oil pressure, lubricant viscosity, and speed difference on dynamic engagement characteristics. Using nonlinear regression analysis and the multi-objective grey wolf optimizer (MOGWO), a matching strategy for control parameters is proposed. The results indicate that the speed difference is the dominant factor affecting sliding work and friction torque. Under high-speed difference conditions (&gt;1000 rpm), its contribution to sliding work exceeds 95 %. The optimal parameter matching scheme obtained through multi-objective optimization (oil pressure: 0.2 MPa, viscosity: 0.69–0.71 Pas, speed difference: 330 mm/s) was experimentally validated. This scheme reduces sliding work by 3540 J and decreases engagement impact by 5.08 %. This study provides a theoretical reference for parameter matching and performance optimization in the dynamic engagement process of wet clutches.</p>

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Parameter optimization and testing for wet clutch engagement

  • 期刊论文

  • 发表日期：

    2026年4月9日

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  • Yongqiang Zhao,
  • Xiangdong Ni,
  • Jingzhong Zhou,
  • Ming Zhang,
  • Fang Niu,
  • Lan Lan,
  • Jinjie Wang

摘要

To address the issues of friction part burning and engagement impact during continuous transmission shifting, this study develops a dynamic model of the wet clutch engagement process. It investigates the influence of key parameters engagement oil pressure, lubricant viscosity, and speed difference on dynamic engagement characteristics. Using nonlinear regression analysis and the multi-objective grey wolf optimizer (MOGWO), a matching strategy for control parameters is proposed. The results indicate that the speed difference is the dominant factor affecting sliding work and friction torque. Under high-speed difference conditions (>1000 rpm), its contribution to sliding work exceeds 95 %. The optimal parameter matching scheme obtained through multi-objective optimization (oil pressure: 0.2 MPa, viscosity: 0.69–0.71 Pas, speed difference: 330 mm/s) was experimentally validated. This scheme reduces sliding work by 3540 J and decreases engagement impact by 5.08 %. This study provides a theoretical reference for parameter matching and performance optimization in the dynamic engagement process of wet clutches.