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- W3011472838 abstract "The presence of magnetic stress harmonics inside the electrical machine is generally responsible for vibrations and acoustic noise generation. This phenomenon is called e-NVH (Noise, Vibrations and Harshness due to electromagnetic excitations) and has to be considered in the machine design to meet with NVH standard requirements, especially in automotive applications. The e-NVH assertion requires a multiphysics simulation including electromagnetic, mechanical and acoustic models, which must be fast and accurate especially for early design stages. This industrial PhD thesis takes part of the internal research program of EOMYS ENGINEERING company, which develops and commercializes MANATEE software, dedicated to the e-NVH simulation of electrical machines. In this modeling context, the present thesis investigates and extends the semi-analytical electromagnetic model, called Subdomain Method (SDM), for the computation of two-dimensional airgap magnetic stress harmonics in various topologies of electrical machines, mainly focusing on Surface Permanent Magnet Synchronous Machines (SPMSMs) and Squirrel Cage Induction Machines (SCIMs). The thesis also investigates two scientific open questions concerning the contribution of circumferential excitations to the overall vibration level and the slotting modulation effect, which appears in electrical machines with a close number of poles and teeth. For this purpose, an experimental test rig including a particular noisy machine (a SPMSM with 12 slots and 10 poles) and appropriate sensors has been designed and built. The test rig also aims at benchmarking the different multiphysics models currently used in e-NVH simulation workflow" @default.
- W3011472838 created "2020-03-23" @default.
- W3011472838 creator A5005015646 @default.
- W3011472838 date "2018-12-13" @default.
- W3011472838 modified "2023-09-23" @default.
- W3011472838 title "Electromagnetic subdomain modeling technique for the fast prediction of radial and circumferential stress harmonics in electrical machines" @default.
- W3011472838 hasPublicationYear "2018" @default.
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