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The rate in the electrification of vehicles has risen in recent years. With intensified development more and more attention is paid to the noise and vibration in such vehicles especially from the EDU (Electric Drive Unit). In this paper the main NVH simulation process of a high-speed E-axle up to 30,000 rpm for premium class vehicle application is presented. The high speed, high-power density and lightweight design introduces new challenges. Benchmarking of different EDUs and vehicles leads to targets which can be used at the early stage of development as subsystem targets. This paper shows the CAE methodology which can be used to verify the design and guarantee the target achievement. Using CAE both source and structure can be optimized to improve the NVH behavior.

The rate in the electrification of vehicles has risen in recent years and, despite that electric vehicles are quiet, NVH remains a major requirement of vehicle development. The typical NVH issues are gear whine from the gearbox, noise from the E-machine or electromagnetic whine, as well as the noise from the inverter, and noise from inverter harmonics effect on E-machine. Simulation methodologies and CAE workflows are being enhanced to contribute to electric drive systems development. Front loading in the concept and layout design phase are necessary to avoid significant NVH issues at the end of development. The authors previously presented a workflow for combining the electric and mechanical noise for electric drives for the concept and layout design phases. This paper shows an application of the formerly presented workflow for NVH simulation and validation of a system with an Interior Permanent Magnet (IPM) E-machine.

Traditionally, Electric Machine design has primarily focused on factors like efficiency, packaging, and cost, often neglecting the critical aspects of Noise, Vibration, and Harshness (NVH) in the early decision-making stages. This disconnect between E-Machine design teams and NVH teams has consistently posed a challenge. This paper introduces an innovative workflow that unifies these previously separate domains, facilitating comprehensive optimization by seamlessly integrating NVH considerations with other E-Machine objectives, such as electromagnetic compatibility (EMC). This paper highlights AVL's approach in achieving this transformation and demonstrates how this integrated approach sets a new standard for E-Machine design. The presented approach relies on AI-driven algorithms and computational tools.