Analysis and optimization of noise and vibrational performance of an e-axle

As the electric mobility landscape evolves, there is a growing emphasis on addressing the Noise, Vibration, and Harshness (NVH) challenges associated with electric drivetrains. The absence of an IC engine in EVs shifts the focus to other noise contributors such as gear meshing, electric machine operation, and structural vibrations. Despite the known influence of micro-geometry on gear dynamics, current optimization practices often rely on empirical adjustments or standard guidelines without fully utilizing advanced computational methods to predict and optimize NVH performance. There exists a pressing need for a systematic approach to analyse and optimize gear micro-geometry to reduce noise and vibration in high-speed e-axle applications. This research aims to bridge that gap by investigating the relationship between micro-geometry optimization and NVH characteristics of an e-axle. Through detailed modelling and optimization techniques, this research aims to identify optimal gear micro-geometry parameters that minimize transmission error and reduces noise from an e-axle. In this paper, transmission error (TE) is calculated for four different load cases based on motor’s torque-characteristic curve. Then, equivalent radiated power (ERP) is calculated at these load cases to determine major source of excitation and then acoustic analysis is done without micro-geometry optimization (MGO) to record the sound pressure level. After this, gears micro geometries are optimized and same process is repeated to measure the optimized sound pressure level. It is seen that after micro-geometry optimization, sound pressure level corresponding to first harmonic of 1st gear pair decreased by approximately 30%, 20%, 23% and 21% for load cases 1, 2, 3 and 4 respectively and the sound pressure level for same loads corresponding to first harmonic of second gear pair has decreased approximately by 58%, 36%, 23% and 20% respectively. It is also observed that sound pressure level of electric motor remains unaffected by gear micro-geometry optimization. Thus the research shows that noise and vibrations can be reduced by optimizing the micro-geometry parameters using computational tools and by optimizing the noise levels at the initial design stages we can avoid design changes and project delays at the later stages of project.