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Journal of Zhejiang University SCIENCE A

ISSN 1673-565X(Print), 1862-1775(Online), Monthly

Thermal optimization of a totally enclosed forced ventilated permanent magnet traction motor using lumped parameter and partial computational fluid dynamics modeling

Abstract: In this study, we present a thermal optimization method using the overall lumped parameter (LP) and partial computational fluid dynamics (CFD) modeling for a 600-kW permanent magnet traction motor developed for high-speed trains. The motor is totally enclosed forced ventilated to achieve high power density, high efficiency, and low maintenance requirements. Considering the electro-magnetic performance, bogie space, and thermal capacity, we propose a ventilation structure with zigzag plates in sector cross-section. We focus particularly on the ventilation channels and propose an overall LP model for thermal optimization, in which the full consideration of the influence of turbulent flow is given by using a partial CFD model. Given the specific critical parameters from the optimization results, we present a complete 3D CFD model of the whole motor to obtain an accurate temperature distribution and the maximum temperature rises in local points. The benefit of zigzag plates is studied extensively using both the LP and the complete CFD models and the results are verified by equivalent thermal experiments under rated operations. Experimental results indicate that the ventilation structure fulfills the normal operational demands of high-speed trains by improving thermal performance by more than 15%. Additionally, we propose an engineering method to estimate iron loss constraint with the complete CFD model to guide the control system design.

Key words: Computational fluid dynamics (CFD); Lumped parameter (LP) model; Permanent magnet (PM) synchronous motors; Totally enclosed forced ventilated motor

Chinese Summary  <23> 基于全局热网络和局部流体动力学建模的全封闭永磁牵引电机热性能优化

关键词组:热网络模型;流体动力学;永磁电机;全封闭强制风冷


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DOI:

10.1631/jzus.A1700649

CLC number:

TM301.4

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On-line Access:

2018-11-02

Received:

2017-12-01

Revision Accepted:

2018-06-05

Crosschecked:

2018-10-29

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