Multi-Fidelity Surrogate Modeling of Electric Machines

Bibhu Prasad Nayak; Stefan Sallinger; Jan Hansen

doi:10.1007/s00502-025-01399-x

Multi-Fidelity Surrogate Modeling of Electric Machines

Titel in Übersetzung: Multi-Fidelity-Ersatzmodellierung elektrischer Maschinen

Bibhu Prasad Nayak^*
, Stefan Sallinger
, Jan Hansen

^*Korrespondierende/r Autor/-in für diese Arbeit

Institut für Elektronik (4390)

Publikation: Beitrag in einer Fachzeitschrift › Review eines Fachbereichs (Review article) › Begutachtung

Abstract

Elektrische Maschinen innerhalb von E‑Fahrzeugen sind relevante Pfade für die Auskopplung elektromagnetischer Emissionen. Für die Einhaltung der elektromagnetischen Verträglichkeit (EMV) ist deren Modellierung von entscheidender Bedeutung, aufgrund komplexer Geometrien jedoch mit hohem Rechenaufwand verbunden. In diesem Beitrag wird ein Multi-Fidelity-Surrogate-Modellierungsansatz vorgeschlagen, der Low-Fidelity-Schaltungssimulationen mit High-Fidelity-3D-Elektromagnetiksimulationen kombiniert. Es wird eine Kriging-Methode vorgestellt, bei der frequenzbezogene Korrelationen verwendet werden, um LF- und HF-Daten zu kombinieren. Die Methode wird anhand eines vereinfachten Modells einer elektrischen Maschine demonstriert. Im Vergleich zu herkömmlichen MF-Ansätzen verbessert die vorgeschlagene Methode die Genauigkeit bei Resonanzstellen und reduziert gleichzeitig die Anzahl notwendiger 3D-Elektromagnetiksimulationen.

Titel in Übersetzung	Multi-Fidelity-Ersatzmodellierung elektrischer Maschinen
Originalsprache	englisch
Fachzeitschrift	Elektrotechnik und Informationstechnik
DOIs	https://doi.org/10.1007/s00502-025-01399-x
Publikationsstatus	Elektronische Veröffentlichung vor Drucklegung. - 3 Feb. 2026

ASJC Scopus subject areas

Elektrotechnik und Elektronik

Fields of Expertise

Information, Communication & Computing

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title = "Multi-Fidelity Surrogate Modeling of Electric Machines",

abstract = "The electric machines in vehicles are major coupling paths for electromagnetic emission. Accurate modeling is critical for ensuring electromagnetic compatibility (EMC), but is computationally expensive due to complex geometries. This paper proposes a multi-fidelity (MF) surrogate modeling approach that combines low-fidelity (LF) equivalent-circuit models with high-fidelity (HF) 3D electromagnetic simulations. A novel frequency-adaptive Kriging method is introduced, using frequency-wise correlation to selectively merge LF and HF data. This method is demonstrated on a simplified electric machine model to illustrate and validate the effectiveness of the proposed MF strategy. Compared to conventional MF approaches, the proposed method improves accuracy near resonances while reducing reliance on costly HF simulations, enabling scalable and efficient EMC analysis and optimization of electric machines and surrounding systems.",

keywords = "Electric machine, Electromagnetic compatibility, High fidelity, Low fidelity, Multi-fidelity",

author = "Nayak, \{Bibhu Prasad\} and Stefan Sallinger and Jan Hansen",

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AU - Nayak, Bibhu Prasad

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N2 - The electric machines in vehicles are major coupling paths for electromagnetic emission. Accurate modeling is critical for ensuring electromagnetic compatibility (EMC), but is computationally expensive due to complex geometries. This paper proposes a multi-fidelity (MF) surrogate modeling approach that combines low-fidelity (LF) equivalent-circuit models with high-fidelity (HF) 3D electromagnetic simulations. A novel frequency-adaptive Kriging method is introduced, using frequency-wise correlation to selectively merge LF and HF data. This method is demonstrated on a simplified electric machine model to illustrate and validate the effectiveness of the proposed MF strategy. Compared to conventional MF approaches, the proposed method improves accuracy near resonances while reducing reliance on costly HF simulations, enabling scalable and efficient EMC analysis and optimization of electric machines and surrounding systems.

AB - The electric machines in vehicles are major coupling paths for electromagnetic emission. Accurate modeling is critical for ensuring electromagnetic compatibility (EMC), but is computationally expensive due to complex geometries. This paper proposes a multi-fidelity (MF) surrogate modeling approach that combines low-fidelity (LF) equivalent-circuit models with high-fidelity (HF) 3D electromagnetic simulations. A novel frequency-adaptive Kriging method is introduced, using frequency-wise correlation to selectively merge LF and HF data. This method is demonstrated on a simplified electric machine model to illustrate and validate the effectiveness of the proposed MF strategy. Compared to conventional MF approaches, the proposed method improves accuracy near resonances while reducing reliance on costly HF simulations, enabling scalable and efficient EMC analysis and optimization of electric machines and surrounding systems.

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KW - Electromagnetic compatibility

KW - High fidelity

KW - Low fidelity

KW - Multi-fidelity

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DO - 10.1007/s00502-025-01399-x

M3 - Review article

SN - 0932-383X

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JF - Elektrotechnik und Informationstechnik

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Multi-Fidelity Surrogate Modeling of Electric Machines

Abstract

ASJC Scopus subject areas

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