This work is about the transient modeling of the thermal characteristics of outer rotor SPM machines by considering a lumped parameter thermal network based approach. The machine considered here poses particular challenges for the modeling, e.g., due to the semi-closed stator surrounded by a rotor bell that provides a speed-dependent cooling of the stator coils. Starting from a simpler basic network configuration, model extensions and refinements are presented and discussed. The subsequent parameter identification is done by means of an initial design of experiments based sampling, and a subsequent single-objective and also a multi-objective optimization of error functions for the components' temperatures. Analyzing the therefrom derived Pareto fronts and the consequent tradeoff regarding achievable minimum modeling errors for different system's components gives insights into where and how the modeling can be further improved. All the investigations are based on experimental results obtained through operating a particularly developed test setup.

Approaches for Improving Lumped Parameter Thermal Networks for Outer Rotor SPM Machines / Wockinger, D.; Bramerdorfer, G.; Vaschetto, S.; Cavagnino, A.; Tenconi, A.; Amrhein, W.; Jeskey, F.. - (2021), pp. 3821-3828. (Intervento presentato al convegno 13th IEEE Energy Conversion Congress and Exposition, ECCE 2021 tenutosi a Canada nel 2021) [10.1109/ECCE47101.2021.9594930].

Approaches for Improving Lumped Parameter Thermal Networks for Outer Rotor SPM Machines

Vaschetto S.;Cavagnino A.;Tenconi A.;
2021

Abstract

This work is about the transient modeling of the thermal characteristics of outer rotor SPM machines by considering a lumped parameter thermal network based approach. The machine considered here poses particular challenges for the modeling, e.g., due to the semi-closed stator surrounded by a rotor bell that provides a speed-dependent cooling of the stator coils. Starting from a simpler basic network configuration, model extensions and refinements are presented and discussed. The subsequent parameter identification is done by means of an initial design of experiments based sampling, and a subsequent single-objective and also a multi-objective optimization of error functions for the components' temperatures. Analyzing the therefrom derived Pareto fronts and the consequent tradeoff regarding achievable minimum modeling errors for different system's components gives insights into where and how the modeling can be further improved. All the investigations are based on experimental results obtained through operating a particularly developed test setup.
2021
978-1-7281-5135-9
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2957369