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Condition Monitoring of DC-Link Electrolytic Capacitors in PWM Power Converters Using OBL Method

Author

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  • Ahmed G. Abo-Khalil

    (Department of Electrical Engineering, College of Engineering, Majmaah University, Almajmaah 11952, Saudi Arabia
    Department of Electrical Engineering, College of Engineering, Assuit University, Assuit 71515, Egypt)

  • Abdel-Rahman Al-Qawasmi

    (Department of Electrical Engineering, College of Engineering, Majmaah University, Almajmaah 11952, Saudi Arabia)

  • Ali M. Eltamaly

    (Saudi Electricity Company Chair in Power System Reliability and Security, King Saud University, Riyadh 11421, Saudi Arabia
    Sustainable Energy Technologies Center, King Saud University, Riyadh 11421, Saudi Arabia
    Electrical Engineering Department, Mansoura University, Mansoura 35516, Egypt)

  • B. G. Yu

    (Division of Electrical, Electronic and Control Engineering, Kongju National University, Chungcheongnam-do 31080, Korea)

Abstract

Since the lifespan of an electrolytic capacitor is relatively short compared to other power semiconductor devices, the failure rate accounts for 60% and, thus, it is the most vulnerable component of the power conversion device. Therefore, the accurate measurement of the lifetime of an electrolytic capacitor is very important in ensuring the reliability of the entire system, including the capacitor. In this paper, an online failure detection method for a DC-link electrolytic capacitor in a back-to-back Pulse width Modulation (PWM) converter using the opposition-based learning particle swarm optimization-based Support Vector Regression (OPSO-SVR) technique is proposed. In this method, the capacitance and the DC-link capacitor power have been used in offline mode for SVR training and testing. During the offline mode, the SVR parameters have been optimized with the OPSO algorithm to use online to estimate the real value of the DC-link capacitor. The experimental results prove the superiority of the proposed technique over the SVR.

Suggested Citation

  • Ahmed G. Abo-Khalil & Abdel-Rahman Al-Qawasmi & Ali M. Eltamaly & B. G. Yu, 2020. "Condition Monitoring of DC-Link Electrolytic Capacitors in PWM Power Converters Using OBL Method," Sustainability, MDPI, vol. 12(9), pages 1-16, May.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:9:p:3719-:d:353849
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    References listed on IDEAS

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    1. Ahmed G. Abo-Khalil & Saeed Alyami & Ayman Alhejji & Ahmed B. Awan, 2019. "Real-Time Reliability Monitoring of DC-Link Capacitors in Back-to-Back Converters," Energies, MDPI, vol. 12(12), pages 1-11, June.
    2. Ahmed G. Abo-Khalil & Saeed Alyami & Khairy Sayed & Ayman Alhejji, 2019. "Dynamic Modeling of Wind Turbines Based on Estimated Wind Speed under Turbulent Conditions," Energies, MDPI, vol. 12(10), pages 1-25, May.
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    Cited by:

    1. Ahmed G. Abo-Khalil & Walied Alharbi & Abdel-Rahman Al-Qawasmi & Mohammad Alobaid & Ibrahim M. Alarifi, 2021. "Maximum Power Point Tracking of PV Systems under Partial Shading Conditions Based on Opposition-Based Learning Firefly Algorithm," Sustainability, MDPI, vol. 13(5), pages 1-18, March.
    2. Ahmed G. Abo-Khalil & Ali M. Eltamaly & Praveen R.P. & Ali S. Alghamdi & Iskander Tlili, 2020. "A Sensorless Wind Speed and Rotor Position Control of PMSG in Wind Power Generation Systems," Sustainability, MDPI, vol. 12(20), pages 1-19, October.

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