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Three Dimensional Electromagnetic and NVH Analyses of Electric Motor Eccentricity to Enhance NVH Robustness for Hybrid and Electric Vehicles
Technical Paper
2020-01-0412
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Electric motor whine is one of the main noise sources of hybrid and electric vehicles. Motor air gap eccentricity due to propulsion system deflection, part tolerances and manufacturing variation is typically ignored in motor NVH design and analysis. Such eccentricity can be a dominant noise source by amplifying critical motor whine orders up to 10 dB, leading to poor NVH robustness. However, this problem cannot be explained by conventional method based on symmetric 2D approach. New 3D electromagnetic (EM) and NVH analyses are developed and validated to accurately predict air gap induced motor noise to enhance NVH robustness: First, a true 3D full 360-degree electric motor model is developed to model asymmetric air gap distribution along motor stack length. Predicted 3D EM forces are mapped to mechanical finite-element mesh over the cylindrical stator surface. Furthermore, an enhanced 2.5D method is also developed that captures EM force variation along motor axial stack length, which offers reasonable accuracy and reduced computational costs. Statistical analysis is performed to predict probability of motor air gap distribution considering tolerance stack and manufacturing variation. Motor shaft bending and housing deformation induced air gap eccentricities are also analyzed to select optimal structure design that offers enhanced NVH robustness. The integrated 3D EM and NVH analyses successfully root caused and resolved eccentricity induced noise issues in a production hybrid electric vehicle (2-mode hybrid) and are used to enhance NVH robustness of General Motors’ hybrid and electric vehicles.
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He, S., Zhang, P., Gandham, M., Omell, B. et al., "Three Dimensional Electromagnetic and NVH Analyses of Electric Motor Eccentricity to Enhance NVH Robustness for Hybrid and Electric Vehicles," SAE Technical Paper 2020-01-0412, 2020, https://doi.org/10.4271/2020-01-0412.Also In
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