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Overvoltage Suppression Method Based on Machine Learning for Motor Drive Systems

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents an overvoltage suppression method based on machine learning for motor drive systems. Overvoltage in motor drive systems causes electrical stress that leads to insulation breakdown in motors. This paper investigates the impact of cable length and reference voltage on overvoltage to identify critical operating conditions. Machine learning is employed to adjust the reference voltage dynamically in response to varying drive conditions, thereby mitigating overvoltage. The effectiveness of the proposed method is validated through simulation results.

Original languageEnglish
Title of host publicationICEMS 2025 - 28th International Conference on Electrical Machines and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3118-3122
Number of pages5
ISBN (Electronic)9788986510232
DOIs
StatePublished - 2025
Externally publishedYes
Event28th International Conference on Electrical Machines and Systems, ICEMS 2025 - Busan, Korea, Republic of
Duration: 16 Nov 202519 Nov 2025

Publication series

NameICEMS 2025 - 28th International Conference on Electrical Machines and Systems

Conference

Conference28th International Conference on Electrical Machines and Systems, ICEMS 2025
Country/TerritoryKorea, Republic of
CityBusan
Period16/11/2519/11/25

Bibliographical note

Publisher Copyright:
© 2025 Korean Institute of Electrical Engineers Electrical Machinery and Energy Conversion Systems Society.

Keywords

  • Artificial neural network
  • Machine learning
  • Motor drive system
  • Overvoltage

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Mechanical Engineering

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