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Limitations and Characterization of Energy Storage Devices for Harvesting Applications

Author

Listed:
  • Roberto de Fazio

    (Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy)

  • Donato Cafagna

    (Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy)

  • Giorgio Marcuccio

    (Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy)

  • Paolo Visconti

    (Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy)

Abstract

This paper aims to study the limitations and performances of the main energy storage devices commonly used in energy harvesting applications, namely super-capacitors (SC) and lithium polymer (LiPo) batteries. The self-discharge phenomenon is the main limitation to the employment of SCs to store energy for a long time, thus reducing efficiency and autonomy of the energy harvesting system. Therefore, the analysis of self-discharge trends was carried out for three different models of commercial SCs, describing the phenomenon in terms of self-discharge rate and internal resistance. In addition, physical interpretations concerning the self-discharge mechanism based on the experimental data are provided, thus explaining the two super-imposed phenomena featured by distinct time constants. Afterwards, the dependence of self-discharge phenomenon from the charging time duration (namely, SCs charged at 5 V and then kept under charge for one or five hours) was analyzed; by comparing the voltage drop during the self-discharge process, a self-discharge reduction for longer charging durations was obtained and the physical interpretation provided (at best −6.8% after 24 h and −13.4% after 120 h). Finally, self-discharge trends of two commercial 380 mAh LiPo batteries (model LW 752035) were acquired and analyzed; the obtained results show an open circuit voltage reduction of only 0.59% in the first 24 h and just 1.43% after 124 h.

Suggested Citation

  • Roberto de Fazio & Donato Cafagna & Giorgio Marcuccio & Paolo Visconti, 2020. "Limitations and Characterization of Energy Storage Devices for Harvesting Applications," Energies, MDPI, vol. 13(4), pages 1-18, February.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:4:p:783-:d:319369
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    References listed on IDEAS

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    1. Henry Miniguano & Andrés Barrado & Cristina Fernández & Pablo Zumel & Antonio Lázaro, 2019. "A General Parameter Identification Procedure Used for the Comparative Study of Supercapacitors Models," Energies, MDPI, vol. 12(9), pages 1-20, May.
    2. Adnane Houbbadi & Rochdi Trigui & Serge Pelissier & Eduardo Redondo-Iglesias & Tanguy Bouton, 2019. "Optimal Scheduling to Manage an Electric Bus Fleet Overnight Charging," Energies, MDPI, vol. 12(14), pages 1-17, July.
    3. Lingxi Kong & Chuan Li & Jiuchun Jiang & Michael G. Pecht, 2018. "Li-Ion Battery Fire Hazards and Safety Strategies," Energies, MDPI, vol. 11(9), pages 1-11, August.
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    Cited by:

    1. Paolo Visconti & Nicola Ivan Giannoccaro & Roberto de Fazio, 2021. "Special Issue on Electronic Systems and Energy Harvesting Methods for Automation, Mechatronics and Automotive," Energies, MDPI, vol. 14(23), pages 1-5, December.
    2. Roberto De Fazio & Roberta Proto & Carolina Del-Valle-Soto & Ramiro Velázquez & Paolo Visconti, 2022. "New Wearable Technologies and Devices to Efficiently Scavenge Energy from the Human Body: State of the Art and Future Trends," Energies, MDPI, vol. 15(18), pages 1-37, September.
    3. Paolo Visconti & Francesco Iaia & Roberto De Fazio & Nicola Ivan Giannoccaro, 2021. "A Stake-Out Prototype System Based on GNSS-RTK Technology for Implementing Accurate Vehicle Reliability and Performance Tests," Energies, MDPI, vol. 14(16), pages 1-22, August.
    4. Carolina Del-Valle-Soto & Ramiro Velázquez & Leonardo J. Valdivia & Nicola Ivan Giannoccaro & Paolo Visconti, 2020. "An Energy Model Using Sleeping Algorithms for Wireless Sensor Networks under Proactive and Reactive Protocols: A Performance Evaluation," Energies, MDPI, vol. 13(11), pages 1-31, June.
    5. Roberto de Fazio & Donato Cafagna & Giorgio Marcuccio & Alessandro Minerba & Paolo Visconti, 2020. "A Multi-Source Harvesting System Applied to Sensor-Based Smart Garments for Monitoring Workers’ Bio-Physical Parameters in Harsh Environments," Energies, MDPI, vol. 13(9), pages 1-33, May.
    6. Roberto De Fazio & Mariangela De Giorgi & Donato Cafagna & Carolina Del-Valle-Soto & Paolo Visconti, 2023. "Energy Harvesting Technologies and Devices from Vehicular Transit and Natural Sources on Roads for a Sustainable Transport: State-of-the-Art Analysis and Commercial Solutions," Energies, MDPI, vol. 16(7), pages 1-46, March.
    7. Paolo Visconti & Laura Bagordo & Ramiro Velázquez & Donato Cafagna & Roberto De Fazio, 2022. "Available Technologies and Commercial Devices to Harvest Energy by Human Trampling in Smart Flooring Systems: A Review," Energies, MDPI, vol. 15(2), pages 1-38, January.

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