Online model-predictive thermal management of inverter-fed electrical machines

Aachen / ISEA (2018, 2019) [Book, Dissertation / PhD Thesis]

Page(s): 1 Online-Ressource (viii, 154 Seiten) : Illustrationen, Diagramme

Abstract

All electrical machines generate losses in the form of heat generation, which leads to a constant change of operating temperature of the machines. This temperature variation jeopardizes machine control quality, and could cause damage to the machine at high temperatures. This thesis introduces a generic thermal modeling methodology based on space-resolved lumped parameter thermal network, which allows an automated thermal modeling procedure for electrical machines with scalable model complexity. The resulting high accuracy real-time temperature observer strongly improves torque accuracy of an induction machine. Based on the accurate thermal model, a model predictive algorithm is proposed which dynamically limits the operating range of electrical machines to achieve maximum thermal utilization. Both results are experimentally validated on test bench.

Authors

Authors

Qi, Fang

Advisors

de Doncker, Rik W.
Hameyer, Kay

Identifier

  • REPORT NUMBER: RWTH-2019-08304

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