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Computationally Efficient Stator AC Winding Loss Analysis Model for Traction Motors Used in High-Speed Railway Electric Multiple Unit

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The aim of this proposed work is to develop a computationally efficient and accurate AC winding loss analysis model for the traction motors for use in high-speed railways (HSRs). The… Click to show full abstract

The aim of this proposed work is to develop a computationally efficient and accurate AC winding loss analysis model for the traction motors for use in high-speed railways (HSRs). The goal of the model is to be able to study AC winding loss under both sinusoidal and pulse width modulated (PWM) inverter voltage sources. The traction motor model considered for the proposed study is a form wound winding permanent magnet (PM) assisted synchronous reluctance motor (PMaSynRM). The traction motor uses an open slot with two-layer winding. First, a flux linkage table is built using finite element analysis (FEA) with sinusoidal current as the input. The machine model then includes the effect of the PWM inverter voltage source with the current controller. For the AC winding loss analysis, the fundamental component and the harmonics due to PWM are considered separately. To find the loss due to the fundamental component only, the vector potential of the slot region is mapped to the subconductors of the form wound winding and the eddy current distribution and the AC winding loss are calculated. The effect of the harmonics due to the PWM switching is then added in the post-processing stage by analytically evaluating the individual harmonic effect. The whole AC loss analysis model proposed in this work is computationally more efficient than the conventional FEA because the transient state of the system is removed. Moroover, the PWM voltage source effect is divided into the effects of the fundamental component and switching harmonics by combining the vector potentia mapping and post-processing analytical calculation.

Keywords: traction; loss; winding loss; model; loss analysis

Journal Title: IEEE Access
Year Published: 2022

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