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Enhancing the Performance of Human Motion Energy Harvesting through Optimal Smoothing Capacity in the Rectifier

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  • Ilgvars Gorņevs

    (Institute of Technical Physics, Faculty of Materials Science and Applied Chemistry, Riga Technical University, LV-1048 Riga, Latvia)

  • Juris Blūms

    (Institute of Technical Physics, Faculty of Materials Science and Applied Chemistry, Riga Technical University, LV-1048 Riga, Latvia)

Abstract

Energy harvesting offers a promising solution for powering a growing variety of low-power electronics; however, harnessing energy from human motion, with its irregular and low-frequency bursts of power, presents conversion challenges. As rectification is a common part of it, this study investigates the influence of smoothing capacitor values on rectifier output for short, intermittent signals. We propose an analytical model that identifies an optimal smoothing capacity for the full-bridge rectifier, considering harvester internal resistance, frequency, and load resistance and leading to the highest average output voltage after rectification. The model was validated with detailed computer simulations; furthermore, a similar effect was revealed on a voltage multiplier circuit as well. Experimental measurements demonstrate that deviating from the optimal smoothing capacity results in up to 10% decrease in rectified RMS voltage, leading to significant drops in output power in specific energy harvesting systems. A real-world experiment with a human motion energy harvester further confirmed the findings in a naturally varying generation environment.

Suggested Citation

  • Ilgvars Gorņevs & Juris Blūms, 2023. "Enhancing the Performance of Human Motion Energy Harvesting through Optimal Smoothing Capacity in the Rectifier," Sustainability, MDPI, vol. 15(18), pages 1-16, September.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13564-:d:1237378
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    References listed on IDEAS

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    1. Wang, Chen & Lai, Siu-Kai & Wang, Jia-Mei & Feng, Jing-Jing & Ni, Yi-Qing, 2021. "An ultra-low-frequency, broadband and multi-stable tri-hybrid energy harvester for enabling the next-generation sustainable power," Applied Energy, Elsevier, vol. 291(C).
    2. Bai, Shanming & Cui, Juan & Zheng, Yongqiu & Li, Gang & Liu, Tingshan & Liu, Yabing & Hao, Congcong & Xue, Chenyang, 2023. "Electromagnetic-triboelectric energy harvester based on vibration-to-rotation conversion for human motion energy exploitation," Applied Energy, Elsevier, vol. 329(C).
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