2023
DOI: 10.1155/2023/9929496
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Inverse Heat Transfer Analysis Method to Determine the Entropic Coefficient of Reversible Heat in Lithium-Ion Battery

Abstract: An entropic coefficient of reversible entropic heat is a key parameter in determining the battery thermal responses, but its measurement is challenging due to time consuming and inaccurate traditional methods. In this regard, an analytical approach based on the inverse heat transfer problem is newly proposed to precisely determine the entropic coefficient with low experiment cost. Experiments are conducted by discharging the battery under four different current rates to inversely estimate the entropic coeffici… Show more

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Cited by 6 publications
(3 citation statements)
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“…However, current study utilized the lumped thermal capacity model, which assumed the battery as a uniform heat generation model, considering the Biot number (Bi). Generally, if the Biot number is less than 0.1, we can assume the lumped thermal capacity model International Journal of Energy Research [35]. Therefore, the Biot number for all direction was calculated as…”
Section: Numerical Modelmentioning
confidence: 99%
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“…However, current study utilized the lumped thermal capacity model, which assumed the battery as a uniform heat generation model, considering the Biot number (Bi). Generally, if the Biot number is less than 0.1, we can assume the lumped thermal capacity model International Journal of Energy Research [35]. Therefore, the Biot number for all direction was calculated as…”
Section: Numerical Modelmentioning
confidence: 99%
“…Bi x , Bi y , and Bi z are the Biot number for x-, y-, and z-direction, respectively, and h and L c are the convective heat transfer coefficient and characteristic length for each direction. The convective heat transfer coefficient is 2.3 W•m -2 •K -1 which is calculated using a generalized reduced gradient algorithm developed in our previous study [35]. k x , k x , and k x are the x-, y-, and z-directional thermal conductivity of battery, respectively.…”
Section: Numerical Modelmentioning
confidence: 99%
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