Comprehensive experimental study of thermoelectric generators under transient boundary conditions

As the applications of thermoelectric generators (TEGs) have become more extensive in last decades, the transient characteristics of TEGs have gradually attracted attention. The current transient studies on TEG systems, however, mostly rely on simulation learning. Moreover, the small number of designed experiments mostly considered a single heating pulse process. The transient study of output performance of TEG lacks a comprehensive experimental study in a complex and transient input heat source. Therefore, in order to fulfill this lack, an experimental platform is designed in this work to investigate electrical response of TEGs under transient boundary conditions. A classical maximum power point tracking (MPPT) algorithm is employed to apply optimal variable electrical load on TEGs for maximum power generation. Critical design parameters in system level are evaluated for two TEGs with different geometries. Constant, transient but periodic and random heat inputs are applied to the TEG. Further, the initial investment cost of the system and Levelized cost of energy (LCOE) are calculated. The results show that, the system parameters can improve the average output power and conversion efficiency. The MPPT algorithm is proved to be an effective and important tool to enhance the output power of the system especially under random boundary condition. The LCOE of the proposed TEG system is improved 13.2% compared to normal TEG system with steady-state heat input.

Automated summary

This study investigates the electrical response of thermoelectric generators (TEGs) under different transient boundary conditions and designs an experimental platform to study output performance. It is found that system parameters and the maximum power point tracking (MPPT) algorithm are crucial for improving TEG output power and efficiency. The proposed TEG system's Levelized Cost of Energy (LCOE) shows a significant improvement compared to conventional systems.