Impedance Variations in Random Wound Coils of Synchronous Motors: A Statistical Approach
Differential and Common Mode impedance characterization plays a crucial role in predicting Electromagnetic Interferences prediction in electric power drives. This paper illustrates, through direct impedance measurements, that random wound coils can exhibit notable impedance differences, even among coils manufactured under similar parameters, due to inconsistencies inherent in the winding process. Predictive impedance modeling combined with wire placement simulations is utilized to analyze the variability in randomly wound coils. The findings demonstrate that winding randomness significantly contributes to impedance uncertainties, while also confirming that wire placement follows non-fully stochastic patterns, likely influenced by repeatable aspects of the manufacturing process. To analyze further the influence of design parameters, the authors propose an approach using statistical repartition of impedances. This method allows quantifying the impact of studied design variables, considering initial variations present in studied samples. This paper aims at giving a better understanding of overall interactions induced by coils design parameters on a broad frequency spectrum for random wound motors.
Authors
- Sébastien Serpaud (ORCID: https://orcid.org/0000-0002-6805-6276)
- Costa François
- Piat Arthur
- Hlioui Sami
- Lévy Pierre-Etienne
Institutions
- Centre National de la Recherche Scientifique (FR)
- Université Paris-Saclay (FR)
- Toulouse Mathematics Institute (FR)
- Laboratoire des systèmes et applications des technologies de l'information et de l'énergie (FR)
- CY Cergy Paris Université (FR)
Publication Details
- Journal
- IEEE Transactions on Energy Conversion
- Published
- 2025-08-11
- DOI
- https://doi.org/10.1109/tec.2025.3597834
- Primary Topic
- Machine Fault Diagnosis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Connecticut Department of Energy and Environmental Protection
- Agence Nationale de la Recherche
- Airbus
- Université Paris-Saclay
- Safran