Analytical thermal model for fast stator winding temperature prediction

Sciascera, C., Giangrande, Paolo, Papini, Luca, Gerada, C. and Galea, Michael (2017) Analytical thermal model for fast stator winding temperature prediction. IEEE Transactions on Industrial Electronics, 64 (8). pp. 6116-6126. ISSN 0278-0046

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This paper introduces an innovative thermal modelling technique which accurately predicts the winding temperature of electrical machines, both at transient and steady state conditions, for applications where the stator Joule losses are the dominant heat source. The model is an advanced variation of the classical Lumped Parameter Thermal Network approach, with the expected degree of accuracy but at a much lower computational cost. A 7-node Thermal Network is first implemented and an empirical procedure to fine-tuning the critical parameters is proposed. The derivation of the low computational cost model from the Thermal Network is thoroughly explained. A simplification of the 7-node Thermal Network with an equivalent 3-node Thermal Network is then implemented, and the same procedure is applied to the new network for deriving an even faster low computational cost model. The proposed model is then validated against experimental results carried on a Permanent Magnet Synchronous Machine which is part of an electro-mechanical actuator designed for an aerospace application. A comparison between the performance of the classical Lumped Parameter Thermal Network and the proposed model is carried out, both in terms of accuracy of the stator temperature prediction and of the computational time required.

Item Type: Article
Additional Information: (c)2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works
Keywords: Thermal analysis, electric motors, permanent magnet machines, thermal management, nonlinear dynamical systems, approximation methods, analytical models, polynomials
Schools/Departments: University of Nottingham, UK > Faculty of Engineering > Department of Electrical and Electronic Engineering
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Depositing User: Burns, Rebecca
Date Deposited: 10 Aug 2017 13:46
Last Modified: 04 May 2020 18:58

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