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Motor Stator Insulation Stress Due to Multilevel Inverter Voltage Output Levels and Power Quality

Author

Listed:
  • Arshiah Yusuf Mirza

    (Electrical and Computer Engineering, University of Connecticut, Storrs, CT 06269, USA)

  • Ali Bazzi

    (Electrical and Computer Engineering, University of Connecticut, Storrs, CT 06269, USA)

  • Hiep Hoang Nguyen

    (Electrical and Computer Engineering, University of Connecticut, Storrs, CT 06269, USA)

  • Yang Cao

    (Electrical and Computer Engineering, University of Connecticut, Storrs, CT 06269, USA)

Abstract

Multilevel Inverters (MLIs) are widely sought after in medium-voltage applications like electric ships, electric aircraft, and renewable energy integration due to excellent advantages like lower device stress, better power quality, and modularity. However, non-sinusoidal excitations from MLIs pose a serious problem to motor-insulation and lead to their premature breakdown. This paper investigates stress in medium-voltage motor insulation when the stator winding is excited by 3-, 5-, and 7-level multilevel inverter output waveforms. The effect of firing angle on insulation stress is also studied for each of the multilevel inverters. Results show that in addition to the number of output voltage levels, PWM wave shape is a critical factor which affects the insulation stress. Both these factors work together to impact the insulation health. A strong correlation is shown between the increase in the voltage root mean square (RMS) value and increase in dielectric stress when ignoring the dv / dt impact for a fixed DC input voltage and operating frequency of the inverter. Similarly, the dielectric stress in the stator insulation increased with an increase in firing angle for each of the MLIs. This paper shows a potential that both the RMSs can be optimized to reduce the insulation stress and improve the power quality of MLIs in medium voltage drives.

Suggested Citation

  • Arshiah Yusuf Mirza & Ali Bazzi & Hiep Hoang Nguyen & Yang Cao, 2022. "Motor Stator Insulation Stress Due to Multilevel Inverter Voltage Output Levels and Power Quality," Energies, MDPI, vol. 15(11), pages 1-18, June.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:11:p:4091-:d:830341
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    References listed on IDEAS

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    1. Christian Gianoglio & Edoardo Ragusa & Paolo Gastaldo & Federico Gallesi & Francesco Guastavino, 2021. "Online Predictive Maintenance Monitoring Adopting Convolutional Neural Networks," Energies, MDPI, vol. 14(15), pages 1-23, August.
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    Cited by:

    1. Adam Decner & Marcin Baranski & Tomasz Jarek & Sebastian Berhausen, 2022. "Methods of Diagnosing the Insulation of Electric Machines Windings," Energies, MDPI, vol. 15(22), pages 1-24, November.

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