Abstract

The clutch temperature field is critical for the clutch design and lifetime analysis. In this paper, a new approach for reconstructing the temperature field of the clutch assembly based on the inverse analysis of thermal boundary conditions is present. Three typical types of thermal boundary conditions during the clutch operation were analyzed and integrated into a numerical model with several coefficients assumed. The optimal coefficients are obtained by optimizing the derivation between temperature simulation and rig test based on the reverse problem analysis. The NLPQL optimization algorithm, coupled with the Kriging response surface model, is utilized to improve the computation efficiency. Finally, the optimum parameter combination is conducted and the effectiveness of the proposed method is validated by the rig test data under the continuous engagement and disengagement condition. The results indicate that the clutch temperature distribution and the dynamic mechanism of the clutch contact status using the approach proposed agrees very well with the test data of the rig test. The temperature deviations between the model corrected and the rig test data are within 10 °C, with over 80% of the temperature deviations being less than 5 °C. This study establishes a new clutch temperature field simulation method based on reverse problem analysis and gives a significant insight and foundation for improving the prediction of the temperature distribution of the clutch.

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