Power converters often features inductive devices in their architectures. Accurate simulation of the converters requires a well-defined response of the magnetic cores. A computationally efficient approach for the numerical modelling of hysteretic magnetic materials is presented in this work. The approach exploits the simplicity of the identification procedure for the Preisach model of hysteresis and the reduced computational costs of Neural Networks. The model for hysteresis is implemented both in direct and inverse form. Validation is performed against independent dataset, with evident computational speedup, which can be a valuable asset for magnetic cores simulations in the design of complex power systems featuring multiple converters such as the ones used in avionic applications.

Neural Modelling of Magnetic Materials for Aircraft Power Converters Simulations / Cardelli E.; Laudani A.; Lozito G.M.; Lucaferri V.; Salvini A.; Antonio S.Q.; Riganti Fulginei F.. - ELETTRONICO. - (2020), pp. 125-129. ((Intervento presentato al convegno 20th IEEE Mediterranean Electrotechnical Conference, MELECON 2020 tenutosi a ita nel 2020 [10.1109/MELECON48756.2020.9140623].

Neural Modelling of Magnetic Materials for Aircraft Power Converters Simulations

Lozito G. M.;
2020

Abstract

Power converters often features inductive devices in their architectures. Accurate simulation of the converters requires a well-defined response of the magnetic cores. A computationally efficient approach for the numerical modelling of hysteretic magnetic materials is presented in this work. The approach exploits the simplicity of the identification procedure for the Preisach model of hysteresis and the reduced computational costs of Neural Networks. The model for hysteresis is implemented both in direct and inverse form. Validation is performed against independent dataset, with evident computational speedup, which can be a valuable asset for magnetic cores simulations in the design of complex power systems featuring multiple converters such as the ones used in avionic applications.
20th IEEE Mediterranean Electrotechnical Conference, MELECON 2020 - Proceedings
20th IEEE Mediterranean Electrotechnical Conference, MELECON 2020
ita
2020
Cardelli E.; Laudani A.; Lozito G.M.; Lucaferri V.; Salvini A.; Antonio S.Q.; Riganti Fulginei F.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2158/1247544
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