Employing Advanced CFD to Predict Oil Distribution, Churning Losses and Gearbox cooling

This presentation was held at the 2020 NAFEMS UK Conference "Inspiring Innovation through Engineering Simulation". The conference covered topics ranging from traditional FEA and CFD, to new and emerging areas including artificial intelligence, machine learning and EDA.

Resource Abstract

New Integrated Lightweight Electric Vehicles (ILEV) require a precision transmission that is both silent and durable in even the most demanding electric vehicle applications. To achieve such a high specification advanced simulation and analysis is required.

The design process for P1227F, Xtrac’s new ILEV transmission, faced a fundamental design problem – ‘how can the design of the casing and other components be modified to ensure suitable distribution of lubricant throughout the gearbox?’ Traditionally, prototypes are created and tested to verify the overall gearbox oil system.

The typical approach would be to replace the physical test with a computer simulation.  However classic CFD methods, have had prohibitively high computational costs when solving free surface problems such as splashing lubricant within a transmission – a task for which traditional method is not well suited. These classical methods require long setup and solve times, something which is unreasonable in the context of both automotive and motorsport design processes.

This paper highlights how Xtrac collaborated with EnginSoft in order to use the MPS (Moving Particle Simulation) method to predict the lubrication distribution and churning losses of the P1227F gearbox. Simulation results were compared to video footage and data from physical testing conducted at Xtrac’s in-house research and development laboratory. The MPS method allows users to go from CAD to lubrication, churning loses and cooling results in a matter of days meaning simulation can be implemented during the design phase saving both time and money during prototyping.