Selection of Load Resistance for Boost Converters with Maximum Power Point Tracking Algorithm in Thermoelectric Generators

Abstract

Thermoelectric generators (TEGs) face challenges in efficiently converting waste heat into electrical energy. To enhance their performance, converters are employed, with the crucial feature being the implementation of the maximum power point tracking (MPPT) algorithm. However, the efficiency of the MPPT software in tracking the maximum power point (MPP) is influenced by the load connected to the converter’s output, necessitating the determination of an appropriate load range. The primary objective of this study is to identify an acceptable load range for an isolated DC-DC boost converter used in MPPT within an installed TEG system. The methodology includes building a Simulink/MATLAB model based on TEG manufacturer data, designing a DC-DC boost converter with embedded MPPT algorithms, and conducting simulations and experiments at various load range values. Simulations and experimental studies reveal that the effectiveness of algorithms in tracking the MPP is optimized when the load resistance is between the TEG’s internal resistance and three times this value. Below the internal resistance, the MPP cannot be tracked, while at high load values, the MPP significantly decreases. This underscores the critical role of load resistance selection in optimizing TEG system performance during MPPT applications.