The increased trend of automatic and automated transmissions across a breadth of applications is one of the market drivers for the development of wet clutch systems. Key product differentiators that drive the use of wet clutches in specific applications are (a) Compactness, (b) Low inertia, (c) Higher energy density, (d) Better NVH characteristics, and (e) Longer wear life.
The above-stated product differentiators are dependent on performance of both the clutch cooling system and the friction system for two different operating events, namely engagement and disengagement. During engagement, slip under load between the clutch plates generates heat, which must be carried away by the oil, necessitating a high oil flow demand to all friction surfaces. Failing to achieve this leads to excessive plate temperatures and wear, ultimately resulting in poor performance and reduced clutch life. On the other hand, disengagement events demand minimal oil flow, failing which may lead to poor fuel economy and shift performance due to high viscous drag. These two conflicting requirements make it critical to have an optimized design that considers multiple performance measures.
Eaton has been successful in developing Computational Fluid Dynamics (CFD)-based models for prediction of performance measures like flow uniformity, plate temperature, drag torque and drag decay time using commercial software tools like STAR-CCM+® and in-house custom codes. The presented paper gives an overview of the different types of methods developed at Eaton for wet clutch performance prediction, challenges faced during development, validation with experimental data, and performance improvements and benefits achieved through application of the methods.