In response to demands for higher fuel economy and stringent emission regulations, OEMs always strive hard to improve component/system efficiency and minimize losses. In the driveline system, improving the efficiency of an automotive rear-axle is critical because it is one of the major power-loss contributor. Optimum oil-fill inside an axle is one of the feasible solutions to minimize spin losses, while ensuring lubrication performance and heat-dissipation requirements. Thus, prior to conducting vehicle development tests, several dyno-level tests are conducted to study the thermal behavior of axle-oil (optimum level) under severe operating conditions. These test conditions represent the axle operation in hot weather conditions, steep grade, maximum tow capacity, etc. It is important to ensure that oil does not exceed its thermal limits (disintegration of oil leading to degradation). The aim of this work is to predict the transient thermal behavior of axle-oil and generate thermal field across all the axle-components during a typical dyno test, using commercial Computational Fluid Dynamics (CFD) tools. The predicted rise in oil temperature has been compared with those from dyno-test and good correlation (within 5%) was observed. The usage of this methodology leads to reduction of expensive dyno tests, and at the same time, shortening of axle design and development time.
Transient Thermal Modeling of an Automotive Rear-Axle
Sae Technical Papers
SAE WCX Digital Summit ; 2021
2021-04-06
Aufsatz (Konferenz)
Englisch
Transient Thermal Modeling of an Automotive Rear-Axle
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