Date of Award

12-2025

Degree Name

Doctor of Philosophy

Department

Mechanical and Aerospace Engineering

First Advisor

Claudia Fajardo-Hansford, Ph.D.

Second Advisor

Richard T. Meyer, Ph.D.

Third Advisor

Shrabanti Roy, Ph.D.

Fourth Advisor

Massood Atashbar, Ph.D.

Keywords

Electric vehicle gearbox, experimental validation, gearbox losses, heat transfer analysis, lumped-parameter thermal network (LPTN), thermal modeling

Abstract

This research investigates the thermal behavior of a high-speed electric vehicle (EV) helical gearbox with the goal of improving the prediction accuracy of component temperatures and total power losses under a range of operating conditions. The study focuses on developing a physics-based lumped-parameter thermal network model capable of capturing the main heat generation and dissipation mechanisms within the transmission. The model integrates experimentally validated loss correlations for gears, bearings, seals, and churning, as well as convective and radiative heat transfer paths.

The thermal network model was coded in MATLAB and validated through a series of controlled experiments performed on an instrumented test rig operating at multiple torque and speed combinations. Predicted and measured temperatures agreed within the industry-set 20% envelope across all test conditions, with the agreement improving to 1% at loads above 75% of the operating maximum.

The agreement confirms that the model accurately captures the heat-generation and dissipation mechanisms governing gearbox thermal behavior. Results showed that load-dependent mesh losses dominate the total power loss, while bearing losses contribute to a lesser but still significant extent. The analysis also demonstrated that accurate estimation of the coefficient of friction at the gear mesh is critical for reliable prediction of the total power loss.

The findings provide a practical framework for evaluating gearbox thermal performance during the design stage. This work advances predictive modeling for EV transmissions and contributes to improving the efficiency, durability, and reliability of electric and hybrid vehicle drivetrains.

Access Setting

Dissertation-Open Access

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