Abstract

With the increasing development of self-powered wearable electronic devices, there is a growing interest in thermoelectric generators (TEGs). To achieve more comprehensive and reliable functionality of wearable devices, improving the power generation performance of thermoelectric devices will be the key. It has been shown that integrating a heat sink at the cold end of the TEG increases the effective temperature difference and, thus, maximizes the power output of the thermoelectric device. However, the space left for the power supply is often limited. How to optimize the integrated system of micro-thermoelectric generators and heat sinks in a height-confined space has become the key. In this study, we have established a corresponding model using a numerical calculation method, systematically studied the influence of TEG geometric size on the number of fins and fin height, and determined the optimal number of fins for the highest equivalent convective heat transfer coefficient corresponding to different fin heights. We also conducted the co-design of TEG and fin topological structure to study the effects of the ratio of leg height to fin height (l/H), the width of legs (w), and the number of thermoelectric leg pairs (N) on the maximum output power density per unit area (Pm1) and the maximum output power density per unit mass (Pm2) of the device. When N = 16, w = 0.3 mm, l/H = 2.5 (that is, l = 3.57 mm, H = 1.43 mm), and Pm1 reaches the maximum value of 30.5 μW/cm2; When N = 2, l/H = 0.25 and w = 0.3 mm, and Pm2 reaches a maximum value of 5.12 mW/g. The measured values of the open-circuit voltages of fabricated micro-TEGs with different thermoelectric leg heights (l = 0.49 mm, l = 1.38 mm, and l = 1.88 mm) are basically consistent with the simulated values. When N = 2, l = 0.49 mm, H = 3.74 mm, and w = 0.85 mm, and Pm2 reaches 0.44 mW/g. The results provide insights into the optimal design of wearable micro thermoelectric generator working in a height-confined space and highlight the importance of co-designing TEGs and fin topological structures for optimizing their performance.

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