Browse Publications Technical Papers 2017-01-2439
2017-10-08

Estimation of Clutch Life for Manual Transmission Vehicle Through Thermal Modeling of Clutch Housing and Clutch Facing 2017-01-2439

Poor clutch life is a major issue for some light commercial vehicle models. Clutch overheating is the primary cause for clutch failure. Some of the reasons include inappropriate gear selection by the driver, poor low-end dynamic torque availability from an engine, heavy stop and go traffic, vehicle overloading resulting in excessive clutch slippage especially in gradients, riding of the clutch pedal by the customer etc. These situations lead to a high thermal energy dissipation at the clutch, increasing clutch wear and in extreme conditions leading to not only poor shift quality but also eventual clutch failure. Unfortunately, it is not practical to monitor clutch temperature in a production vehicle due to high costs or technical challenges involved.
This paper describes 1-D thermal modeling of single plate dry clutch typically used in passenger car/truck and bus applications. The objective of simulation is to estimate the temperature rise on the clutch facing and clutch housing. This can be used in conjunction with supplier provided data (facing temperature vs facing wear ratio) for different clutch materials to estimate clutch life at an early design stage. Drive cycle data collected in Chennai city (India) are used for the analysis.
The simulation results for clutch housing temperature shows a good correlation with the test results (>90%). The prediction of clutch life/wear using clutch facing temperature shows good match with test results for both accelerated and regular vehicle level testing. The clutch life is analyzed for different facing materials and RWUP test cycle. Finally, DOE evaluation (effect of first gear ratio, final drive ratio, engine torque, clutch size, tire size, vehicle weight, and road grade) is carried out from the correlated model in GT SUITE. Clutch temperature modeling can be used as a tool to optimize designs and reduce testing efforts.

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