Experimental Analysis of Motor Power Losses in Energy Storage Flywheel

Energy storage flywheel plays a crucial role in power compensation within modern power systems. The motor losses affect the performance of the energy storage flywheel. A testing method for measuring motor losses based on resistance power consumption was proposed in this paper. The resistive power consumption at a certain speed during the free deceleration process was measured first, and then compared with the steady-state power consumption of the motor at that speed to obtain the motor losses. The resistive power consumption and steady-state power consumption of the energy storage flywheel were measured at multiple speeds under different vacuum levels. And the motor losses of the energy storage flywheel at a speed of 20,000 rpm were calculated to be 2.24 kW and 4.15 kW at vacuum levels of 101.325 kPa and 0.1 kPa, respectively.

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Publication Details

Published
2024-10-25
DOI
https://doi.org/10.1109/acfpe63443.2024.10800812
Primary Topic
Electric Motor Design and Analysis
Type
article
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Experimental Analysis of Motor Power Losses in Energy Storage Flywheel

Jianyong Zheng, Tongtong Qie, Chuanwu Liu, Li Gui, Xudong Jiang
article en

Abstract

Energy storage flywheel plays a crucial role in power compensation within modern power systems. The motor losses affect the performance of the energy storage flywheel. A testing method for measuring motor losses based on resistance power consumption was proposed in this paper. The resistive power consumption at a certain speed during the free deceleration process was measured first, and then compared with the steady-state power consumption of the motor at that speed to obtain the motor losses. The resistive power consumption and steady-state power consumption of the energy storage flywheel were measured at multiple speeds under different vacuum levels. And the motor losses of the energy storage flywheel at a speed of 20,000 rpm were calculated to be 2.24 kW and 4.15 kW at vacuum levels of 101.325 kPa and 0.1 kPa, respectively.

Shanghai University (CN), Beijing Academy of Artificial Intelligence (CN)
Affordable and clean energy
Openalex Percentile: Top 77%
Electric Motor Design and Analysis
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