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Low temperature gradient thermoelectric generator: Modelling and experimental verification

Author

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  • Vostrikov, Sergei
  • Somov, Andrey
  • Gotovtsev, Pavel

Abstract

Internet of Things (IoT) and wearable sensing paradigm assume the sensing devices are available 24/7 and can be accessed from anywhere. This vision implies strict requirements to the power supply and energy harvesting which are expected to guarantee ‘perpetual’ operation of IoT devices. This paper reports on modelling and experimental verification of low temperature gradient thermoelectric generator. Obtained under the conditions of low gradient temperature approximation, the model accounts for the key physical phenomena and enables the accurate output power calculations using a closed-form expression. We perform a comparative study on the state-of-the-art models against the obtained solution and show the simplicity and performance of the proposed approach. For demonstrating practical feasibility of the model, we develop an experimental testbed consisting of the power generator, temperature control and data acquisition units. Experimental results demonstrate the average error 5.5% which improves the state-of-the-art results.

Suggested Citation

  • Vostrikov, Sergei & Somov, Andrey & Gotovtsev, Pavel, 2019. "Low temperature gradient thermoelectric generator: Modelling and experimental verification," Applied Energy, Elsevier, vol. 255(C).
    • Handle: RePEc:eee:appene:v:255:y:2019:i:c:s0306261919314734
    DOI: 10.1016/j.apenergy.2019.113786
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    Cited by:

    1. Massaguer, Albert & Massaguer, Eduard, 2021. "Faster and more accurate simulations of thermoelectric generators through the prediction of the optimum load resistance for maximum power and efficiency points," Energy, Elsevier, vol. 226(C).
    2. Wang, Xi & Henshaw, Paul & Ting, David S.-K., 2021. "Exergoeconomic analysis for a thermoelectric generator using mutation particle swarm optimization (M-PSO)," Applied Energy, Elsevier, vol. 294(C).
    3. Zhu, WenChao & Weng, Zebin & Li, Yang & Zhang, Leiqi & Zhao, Bo & Xie, Changjun & Shi, Ying & Huang, Liang & Yan, Yonggao, 2022. "Theoretical analysis of shape factor on performance of annular thermoelectric generators under different thermal boundary conditions," Energy, Elsevier, vol. 239(PD).

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