Evaluation on High-Efficiency Thermoelectric Generation Systems Based on Differential Power Processing

Abstract

Thermoelectric generators (TEGs) convert thermal energy directly into electrical energy using thermoelectric materials, with attractive advantages such as a lack of noise and pollution, considerable reliability, and a long lifetime. Because of the low output power and low output voltage of each TEG module, conventional thermoelectric generation systems are constituted by a centralized converter with series-connected multiple TEG modules. Power mismatch usually occurs in this system configuration due to the unbalanced temperature difference distribution, which results in lower conversion efficiency. In this paper, two solutions based on differential power processing (DPP) have been proposed to enhance the output power and conversion efficiency of the TEG system: the centralized-distributed hybrid structure and the cascaded power transfer structure, both of which realize the maximum power point tracking of each TEG module. The circuit designs and control strategies of the two proposed systems are here presented. Experimental results have demonstrated the feasibility and effectiveness of these two solutions; they have higher output power and better efficiency than the conventional TEG system. Each of these two solutions exhibits its own features and has suitable application situations. If the temperature difference distribution of all TEG modules has significant variations, the centralized-distributed hybrid structure outperforms the cascaded power transfer structure on the output power. While the temperature difference distribution is comparatively stable, the cascaded power transfer structure is superior to the centralized-distributed hybrid structure. With detailed evaluation and comparison between the two structures, the overall design for DPP-based TEG systems with different connection types has been proposed in this paper, which is the reference for the future implementation of practical TEG applications.