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Collective Losses of Low Power Cage Induction Motors—A New Approach

Author

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  • Elzbieta Szychta

    (Department of Electricity Power Plant, UTP University of Science and Technology in Bydgoszcz, 85-796 Bydgoszcz, Poland)

  • Leszek Szychta

    (Department of Power Electronics, Electric Machines and Drives, UTP University of Science and Technology in Bydgoszcz, 85-796 Bydgoszcz, Poland)

Abstract

Energy efficiency of systems of water pumping is a complex problem since efficiency of two distinct interacting systems needs to be combined: water and power supply. This paper introduces a non-intrusive method of calculating the so-called “collective losses” of a cage induction motor. The term “collective losses”, which the authors define, allows for accurate estimation of motor efficiency. Control system of a pump determines operating point of a pumping station, and thus its efficiency. General estimated performance characteristics of a motor, components of a control system, are assumed to serve selection of a range of pumping speed variations. Rotational speed has a direct effect on motor load torque, pump power and head, and thus on motor performance. Hellwig’s statistical method was used to specify characteristics of estimated collective losses on the basis of experimental studies of 21 motors rated at up to 2.2 kW. The results of simulations and experiments are used to verify validity and efficiency of the suggested method. The method is non-intrusive, simple to use, and requires minimum data.

Suggested Citation

  • Elzbieta Szychta & Leszek Szychta, 2021. "Collective Losses of Low Power Cage Induction Motors—A New Approach," Energies, MDPI, vol. 14(6), pages 1-19, March.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:6:p:1749-:d:521711
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    References listed on IDEAS

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    1. Chuanguang Chen & Haisheng Yu & Fei Gong & Herong Wu, 2020. "Induction Motor Adaptive Backstepping Control and Efficiency Optimization Based on Load Observer," Energies, MDPI, vol. 13(14), pages 1-16, July.
    2. Camila Paes Salomon & Wilson Cesar Sant’Ana & Germano Lambert-Torres & Luiz Eduardo Borges da Silva & Erik Leandro Bonaldi & Levy Ely de Lacerda De Oliveira, 2018. "Comparison among Methods for Induction Motor Low-Intrusive Efficiency Evaluation Including a New AGT Approach with a Modified Stator Resistance," Energies, MDPI, vol. 11(4), pages 1-21, March.
    3. Janusz Sowinski, 2021. "The Impact of the Selection of Exogenous Variables in the ANFIS Model on the Results of the Daily Load Forecast in the Power Company," Energies, MDPI, vol. 14(2), pages 1-18, January.
    4. Li, Yunhua & Liu, Mingsheng & Lau, Josephine & Zhang, Bei, 2015. "A novel method to determine the motor efficiency under variable speed operations and partial load conditions," Applied Energy, Elsevier, vol. 144(C), pages 234-240.
    5. Kang Wang & Ruituo Huai & Zhihao Yu & Xiaoyang Zhang & Fengjuan Li & Luwei Zhang, 2019. "Comparison Study of Induction Motor Models Considering Iron Loss for Electric Drives," Energies, MDPI, vol. 12(3), pages 1-13, February.
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    Cited by:

    1. Michal Frivaldsky, 2021. "Advanced Perspectives for Modeling Simulation and Control of Power Electronic Systems," Energies, MDPI, vol. 14(23), pages 1-2, December.

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