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Variance-based global sensitivity analysis of a hybrid thermoelectric generator fuzzy system

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  • Zhang, Feng
  • Wang, Xinhe
  • Hou, Xinting
  • Han, Cheng
  • Wu, Mingying
  • Liu, Zhongbing

Abstract

In this paper, Hybrid thermoelectric generators (HTEG) model was established based on nonequilibrium thermodynamics and Newton's heat transfer law. Fuzzy theory was used to describe the decision-making and cognitive uncertainty of HTEG design variables in working environment and material. The influence of the fluctuation of design parameters on the output performance is studied using a variance-based global sensitivity analysis. Taking a sampling sample N = 10,000, the main and total Global sensitivity indices of design parameters are calculated, and the sensitivity ranking are obtained. In addition, the analysis was applied to contact effects and the number of serial and parallel components on the sensitivity of the output to the uncertainty of the design variables. The results show: the heat and cold source temperature, load resistance and Seebeck coefficient had a greater impact on the output power and the impact on the conversion efficiency mainly came from the heat and cold source temperature, load resistance and thermal resistance of the thermoelectric module. The contact effects and the number of thermoelectric components connected in series and parallel exerted a certain influence on the uncertainty of output response. The results can be used to guide the performance analysis and parameter optimization of HTEG in application.

Suggested Citation

  • Zhang, Feng & Wang, Xinhe & Hou, Xinting & Han, Cheng & Wu, Mingying & Liu, Zhongbing, 2022. "Variance-based global sensitivity analysis of a hybrid thermoelectric generator fuzzy system," Applied Energy, Elsevier, vol. 307(C).
    • Handle: RePEc:eee:appene:v:307:y:2022:i:c:s0306261921014756
    DOI: 10.1016/j.apenergy.2021.118208
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    3. Zhang, Feng & Wang, Xinhe & Wang, Weiyue & Zhang, Jiajia & Du, Ruijie & Li, Bingqiang & Liu, Wei, 2023. "Uncertainty analysis of photovoltaic cells to determine probability of functional failure," Applied Energy, Elsevier, vol. 332(C).

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