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.