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A novel method to determine the motor efficiency under variable speed operations and partial load conditions

Author

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  • Li, Yunhua
  • Liu, Mingsheng
  • Lau, Josephine
  • Zhang, Bei

Abstract

As one of the significant parameters to characterize the motor performance, motor efficiency changes under variable speed and load conditions. Although there are many methods to measure the partial load motor efficiency under the full speed condition, few of them are available to estimate the efficiency under partial speed conditions. In this paper, a new and original concept of “load ratio” is brought forward to describe the motor performances. A simple method is proposed to estimate the motor efficiency under variable speeds operations and partial load conditions using load ratio, speed ratio, rated motor power and rated motor efficiency. To validate the accuracy of this method, the partial loads full speed operation data from the MotorMaster+ database and the published data under the variable speed conditions from other researcher’s tests are used for demonstration. The results indicate that the relative errors using the proposed method at full speed are within ±5%. Under variable speed conditions, the relative error is within 10% when the speed ratio is above 0.5.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:144:y:2015:i:c:p:234-240
    DOI: 10.1016/j.apenergy.2015.01.064
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    Citations

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    Cited by:

    1. Singh, Gurmeet & Anil Kumar, T.Ch. & Naikan, V.N.A., 2019. "Efficiency monitoring as a strategy for cost effective maintenance of induction motors for minimizing carbon emission and energy consumption," Reliability Engineering and System Safety, Elsevier, vol. 184(C), pages 193-201.
    2. Marek Turzyński & Michal Frivaldsky, 2020. "Modeling of a Quasi-Resonant DC Link Inverter Dedicated to Common-Mode Voltage and Ground Current Reduction," Energies, MDPI, vol. 13(19), pages 1-22, September.
    3. 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.
    4. Li, Weicheng & Vaziri, Vahid & Aphale, Sumeet S. & Dong, Shimin & Wiercigroch, Marian, 2021. "Energy saving by reducing motor rating of sucker-rod pump systems," Energy, Elsevier, vol. 228(C).
    5. Rassiah Raja Singh & Manickavel Baranidharan & Umashankar Subramaniam & Mahajan Sagar Bhaskar & Shriram S. Rangarajan & Hany A. Abdelsalam & Edward Randolph Collins & Tomonobu Senjyu, 2022. "An Energy-Efficient Start-Up Strategy for Large Variable Speed Hydro Pump Turbine Equipped with Doubly Fed Asynchronous Machine," Energies, MDPI, vol. 15(9), pages 1-19, April.
    6. Ding, Xiaofeng & Guo, Hong & Xiong, Rui & Chen, Feida & Zhang, Donghuai & Gerada, Chris, 2017. "A new strategy of efficiency enhancement for traction systems in electric vehicles," Applied Energy, Elsevier, vol. 205(C), pages 880-891.
    7. Burgos Payán, Manuel & Roldan Fernandez, Juan Manuel & Maza Ortega, Jose Maria & Riquelme Santos, Jesus Manuel, 2019. "Techno-economic optimal power rating of induction motors," Applied Energy, Elsevier, vol. 240(C), pages 1031-1048.
    8. Qiang Zhao & Shengming Zhou & Yongheng Yue & Bohang Liu & Qin Xie & Na Zhang, 2023. "Assessing the Dynamic Performance and Energy Efficiency of Pure Electric Car with Optimal Gear Shifting," Energies, MDPI, vol. 16(16), pages 1-21, August.
    9. Klinar, Katja & Tomc, Urban & Jelenc, Blaž & Nosan, Simon & Kitanovski, Andrej, 2019. "New frontiers in magnetic refrigeration with high oscillation energy-efficient electromagnets," Applied Energy, Elsevier, vol. 236(C), pages 1062-1077.
    10. Lei, Fei & Bai, Yingchun & Zhu, Wenhao & Liu, Jinhong, 2019. "A novel approach for electric powertrain optimization considering vehicle power performance, energy consumption and ride comfort," Energy, Elsevier, vol. 167(C), pages 1040-1050.
    11. Hosain, Md Lokman & Bel Fdhila, Rebei & Rönnberg, Kristian, 2017. "Taylor-Couette flow and transient heat transfer inside the annulus air-gap of rotating electrical machines," Applied Energy, Elsevier, vol. 207(C), pages 624-633.
    12. Lei, Fei & Du, Bin & Liu, Xin & Xie, Xiaoping & Chai, Tian, 2016. "Optimization of an implicit constrained multi-physics system for motor wheels of electric vehicle," Energy, Elsevier, vol. 113(C), pages 980-990.
    13. Qian, Suxin & Yuan, Lifen & Yu, Jianlin & Yan, Gang, 2018. "Variable load control strategy for room-temperature magnetocaloric cooling applications," Energy, Elsevier, vol. 153(C), pages 763-775.
    14. Chen, Yi & Yan, Huaxia & Yang, Hongxing, 2018. "Comparative study of on-off control and novel high-low control of regenerative indirect evaporative cooler (RIEC)," Applied Energy, Elsevier, vol. 225(C), pages 233-243.
    15. Ruan, Jiageng & Walker, Paul & Zhang, Nong, 2016. "A comparative study energy consumption and costs of battery electric vehicle transmissions," Applied Energy, Elsevier, vol. 165(C), pages 119-134.
    16. Lei, Fei & Gu, Ke & Du, Bin & Xie, Xiaoping, 2017. "Comprehensive global optimization of an implicit constrained multi-physics system for electric vehicles with in-wheel motors," Energy, Elsevier, vol. 139(C), pages 523-534.
    17. Ding, Xiaofeng & Du, Min & Zhou, Tong & Guo, Hong & Zhang, Chengming, 2017. "Comprehensive comparison between silicon carbide MOSFETs and silicon IGBTs based traction systems for electric vehicles," Applied Energy, Elsevier, vol. 194(C), pages 626-634.
    18. Victor Goman & Vladimir Prakht & Vadim Kazakbaev & Vladimir Dmitrievskii, 2021. "Comparative Study of Energy Consumption and CO 2 Emissions of Variable-Speed Electric Drives with Induction and Synchronous Reluctance Motors in Pump Units," Mathematics, MDPI, vol. 9(21), pages 1-16, October.
    19. Trianni, Andrea & Cagno, Enrico & Accordini, Davide, 2019. "Energy efficiency measures in electric motors systems: A novel classification highlighting specific implications in their adoption," Applied Energy, Elsevier, vol. 252(C), pages 1-1.

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