Electric Vehicle Drive Unit Power Losses and Efficiency Estimation: A Coupled 1D Analytical and 3D CFD Approach for High Fidelity Prediction

This study presents a sophisticated approach to accurately estimating the power losses in the electric vehicle drive unit (e-DU) through a combination of 1D analytical models and 3D computational fluid dynamics (CFD). Understanding and accurately estimating these power losses is crucial for enhancing efficiency and range of electric vehicle (EV). The primary focus is on the types of power losses attributable to mechanical contact friction and oil drag within components such as gear meshes, bearings, and seals. The research specifically examines different analytical models for quantifying power losses due to gear mesh contact and bearing friction. These models were validated against experimental test data, allowing for a comprehensive understanding of their accuracy across a range of operational parameters. Additionally, the impact of oil properties and oil jet flow rates on power losses related to gear and bearing drag was analyzed using analytical methods and correlated with CFD predictions. Notably, the study found that gear contact losses, when adjusted for lubrication factors, demonstrated strong correlation with the test data across various torque and speed scenarios. The combined 1D analytical and 3D CFD framework proved to be an effective tool for estimating power loss in the e-DU, aligning closely with efficiency tests conducted on the drive unit. This not only validates the approach but also provides a reliable means to enhance the design and performance optimization of electric vehicle drive units.