Browse Publications Technical Papers 2021-26-0329

Improving the Clutch Design Robustness by Virtual Validation to Predict Clutch Energy Dissipation and Temperature in Clutch Housing 2021-26-0329

During the vehicle launch (i.e. moving the vehicle from “0” speed), the clutch would be slowly engaged by the Driver or Transmission Control Unit (in Automatic Transmission/Automatic Manual Transmission vehicle) for smooth torque transfer between engine and transmission. The clutch is designed to transfer max engine torque with min heat generation. During the clutch engagement, the difference in flywheel and gearbox input shaft speed is called the clutch slipping phase which then leads to a huge amount of energy being dissipated in terms heat due to friction. As a result, clutch surface temperature increases consistently, when the surface temperature crosses the threshold limit, the clutch wears out quickly or burns spontaneously. Hence it is crucial to predict the energy dissipation and temperature variation in various components of clutch assembly through virtual simulation. During the development process of the vehicle, the clutch is tested over many duty cycles to ensure the temperature, wear rate does not exceed the material thresholds. However, performing these tests for every prototype and for every variant can be expensive and time consuming. In this paper we have proposed a simulation methodology to replicate the vehicle test cycle (Hill- Fade test,) i.e. launching the vehicle on 15% grade followed by a cooling cycle and repeated over 150 cycles in the developed virtual simulation methodology using GT-SUITE application to accurately calculate the dissipated energy and the heat transfer through the components in the clutch housing. The developed simulation model can predict the surface temperature of clutch over the defined cycle, can predict the clutch life and can perform a Design Of Experiments analysis to optimize the vehicle or clutch parameter to meet the required customer targets. With the developed simulation model results and real-world vehicle testing results has been validated. The predicated simulation results have 90% correlation with the vehicle test data.


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