热电制冷器用于自适应个人热管理的数值建模与性能优化

Abstract Thermoelectric coolers (TECs) offer a compact and reliable solution for thermal management by utilizing the Peltier effect for efficient cooling. This study investigated the influence of critical TEC design and operating parameters on device performance using numerical modeling in COMSOL Multiphysics. Key input parameters analysed include thermoelectric leg height, inter-leg spacing, current input, and heat transfer coefficient (h). The performance metrics evaluated are cooling capacity (Qc), power consumption, coefficient of performance (COP), and temperature difference (ΔT), with an emphasis on achieving maximum efficiency. Advanced statistical techniques, including Design of Experiments (DOE) and Analysis of Variance (ANOVA), were employed to quantify the significance of these parameters and optimize TEC performance. Results revealed that current input (I) and heat transfer coefficient (h) are the most critical parameters influencing TEC performance. ANOVA results showed high F-values for Qc (269.44), power consumption (977.99), and COP (307.87), with corresponding p-values < 0.0001, confirming the statistical significance of these parameters. Increasing the current input significantly enhanced the ΔT from 8.4 °C to 87 °C but diminished COP and Qc beyond 0.2 A due to excessive Joule heating . The heat transfer coefficient positively affected energy efficiency, improving COP from 0.69 to 2.27 and Qc from 2.13 mW to 3.7 mW while reducing ΔT and power output. Regression analysis validated the predictive accuracy and robustness of the numerical model, with R 2 values of 0.9972, 0.9991, and 0.9959 for Qc, power consumption, and COP, respectively. These findings highlight the reliability of the model in optimizing TEC performance and demonstrate the importance of current input and the heat transfer coefficient in achieving high-efficiency operation.