Non-Invasive Parameter Identification of DC Arc Models for MV Circuit Breaker Diagnostics
Accurate electrical arc modeling with physically meaningful parameters is essential for the assessment of medium-voltage DC circuit breakers in industrial and railway applications. Laboratory testing and characterization, as outlined in the IEC 61992 standard series for railway applications, typical...
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MDPI AG
2025-05-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/25/10/3161 |
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| author | Gabriele D’Antona Camilo Trujillo-Arboleda Massimiliano Amato Marco Riva |
| author_facet | Gabriele D’Antona Camilo Trujillo-Arboleda Massimiliano Amato Marco Riva |
| author_sort | Gabriele D’Antona |
| collection | DOAJ |
| description | Accurate electrical arc modeling with physically meaningful parameters is essential for the assessment of medium-voltage DC circuit breakers in industrial and railway applications. Laboratory testing and characterization, as outlined in the IEC 61992 standard series for railway applications, typically provide data to asses the operational behavior of the componentsin the power distribution system, including recorded waveforms of terminal voltage and current but not the insights and inputs needed for inner behavior analysis and design optimization. This paper introduces lumped-parameter multi-physics models to describe different phases of arc behavior and outlines a methodology for model–data assimilation. Using experimental test data, the approach enables performance evaluation and supports non-invasive diagnostics and potential condition monitoring of circuit breakers. |
| format | Article |
| id | doaj-art-13a721cad2e04783a2d28effb4d22cb4 |
| institution | OA Journals |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-13a721cad2e04783a2d28effb4d22cb42025-08-20T02:33:58ZengMDPI AGSensors1424-82202025-05-012510316110.3390/s25103161Non-Invasive Parameter Identification of DC Arc Models for MV Circuit Breaker DiagnosticsGabriele D’Antona0Camilo Trujillo-Arboleda1Massimiliano Amato2Marco Riva3Department of Energy, Politecnico di Milano, 20156 Milan, ItalyDepartment of Energy, Politecnico di Milano, 20156 Milan, ItalyELDS Technology Center, ABB S.p.A., 24044 Bergamo, ItalyELDS Technology Center, ABB S.p.A., 24044 Bergamo, ItalyAccurate electrical arc modeling with physically meaningful parameters is essential for the assessment of medium-voltage DC circuit breakers in industrial and railway applications. Laboratory testing and characterization, as outlined in the IEC 61992 standard series for railway applications, typically provide data to asses the operational behavior of the componentsin the power distribution system, including recorded waveforms of terminal voltage and current but not the insights and inputs needed for inner behavior analysis and design optimization. This paper introduces lumped-parameter multi-physics models to describe different phases of arc behavior and outlines a methodology for model–data assimilation. Using experimental test data, the approach enables performance evaluation and supports non-invasive diagnostics and potential condition monitoring of circuit breakers.https://www.mdpi.com/1424-8220/25/10/3161DC arc modelDC circuit breakerarc voltageparameter estimationKalman filterdata assimilation |
| spellingShingle | Gabriele D’Antona Camilo Trujillo-Arboleda Massimiliano Amato Marco Riva Non-Invasive Parameter Identification of DC Arc Models for MV Circuit Breaker Diagnostics Sensors DC arc model DC circuit breaker arc voltage parameter estimation Kalman filter data assimilation |
| title | Non-Invasive Parameter Identification of DC Arc Models for MV Circuit Breaker Diagnostics |
| title_full | Non-Invasive Parameter Identification of DC Arc Models for MV Circuit Breaker Diagnostics |
| title_fullStr | Non-Invasive Parameter Identification of DC Arc Models for MV Circuit Breaker Diagnostics |
| title_full_unstemmed | Non-Invasive Parameter Identification of DC Arc Models for MV Circuit Breaker Diagnostics |
| title_short | Non-Invasive Parameter Identification of DC Arc Models for MV Circuit Breaker Diagnostics |
| title_sort | non invasive parameter identification of dc arc models for mv circuit breaker diagnostics |
| topic | DC arc model DC circuit breaker arc voltage parameter estimation Kalman filter data assimilation |
| url | https://www.mdpi.com/1424-8220/25/10/3161 |
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