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This paper discusses approaches to properly design aluminum axles for optimized NVH characteristics. By effectively using well established and validated FEA and other CAE tools, key factors that are particularly associated with aluminum axles are analyzed and discussed. These key factors include carrier geometry optimization, bearing optimization, gear design and development, and driveline system dynamics design and integration. Examples are provided to illustrate the level of contribution from each main factor as well as their design space and limitations. Results show that an aluminum axle can be properly engineered to achieve robust NVH performances in terms of operating temperature and axle loads.

This paper presents a study of axle system NVH (noise, vibration and harshness) performance using DFSS (Design for Six Sigma) methods with the focus on the system robustness to typical product variations (tolerances / manufacturing based). Instead of using finite element as the simulation tool, a lumped parameter system dynamics model developed in Matlab/Simulink is used in the study, which provides an efficient way in conducting large size analytical DOE (Design of Experiment) and stochastic studies. The model's capability to predict both nominal and variance performance is validated with vehicle test data using statistical hypothesis test methods. Major driveline system variables that contribute to axle gear noise are identified and their variation distributions in production are obtained through sampling techniques.

This paper focuses on a P3 HEV drivetrain for a performance vehicle with a 2-speed gear shift system. The drivetrain NVH performance varies at different gear and different loading conditions, therefore creates a new level of challenges in optimizing the system. This paper presents the methodologies in optimizing the system NVH, including noise sources from both gearbox and eMotor. CAE modeling methods are discussed and illustrated for their usage in optimizing both structural and acoustic responses. Reasonable correlations to test data are achieved and presented.