scholarly journals Extraction of Temperature-Dependent Thermoelectric Material Parameters of a Thermoelectric Cooler by the Non-Linear Least Squares Method

Energies ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 169
Author(s):  
Shanjun Nie ◽  
Mingfu Wang ◽  
Xiaodong Gao ◽  
Jingyu Liao

This paper presents a method of extracting temperature-dependent parameters of thermoelectric material from the operating conditions of thermoelectric cooler (TEC). Based on the finite element method of calculating TEC’s performance, non-linear least squares method is used for extracting temperature-dependent material parameters including the seebeck coefficient, electrical resistivity and thermal conductivity (α, ρ, κ) as operating current, thermal load and hot end temperature are taken as inputs and cooling temperature is taken as output. To further improve the voltage calculation accuracy, the electric resistance error factor which includes electrical contact resistance and the calculation model error is extracted with the voltage being output on the basis of extracted material parameters. The cooling temperature and voltage of another TEC with the same thermoelectric material are recalculated by the extracted parameters and the exact parameters provided by manufacturer respectively. Compared with the experimental results, the extracted material parameters have the advantages of high accuracy, wide application ranges and easily implementing in evaluating TECs’ performance.

1985 ◽  
Vol 11 (1) ◽  
pp. 84-92 ◽  
Author(s):  
Jun Fukai ◽  
Minoru Watanabe ◽  
Takatoshi Miura ◽  
Shigemori Ohtani

2020 ◽  
Vol 8 ◽  
Author(s):  
Aly Zein Elabdeen Kassem

This study utilizes the non-linear least squares method to estimate the impact of temperature on COVID-19 cases per million in forty-three countries, divided into three groups as follows: the first group is composed of thirteen countries that announced the first COVID-19 cases in January 2020, while the second and third groups contain thirteen and seventeen countries, respectively, that witnessed the pandemic for the first time in February and March of the same year. This relationship was measured after four time periods from the date of reporting the first case until April 1, April 15, May 15, and July 8, 2020. The results show an inverse relationship between COVID-19 cases per million and the temperature in the studies of the four-time periods for the three-country groups. These results were only significant statistically (p < 0.1) after 110.8, 164.8 days on average from the beginning of the pandemic in the case of “January” countries.


Sign in / Sign up

Export Citation Format

Share Document