A robust type-2 fuzzy logic-based maximum power point tracking approach for thermoelectric generation systems

A robust type-2 fuzzy logic (FL)-based approach for maximum power point tracking (MPPT) is proposed in this work. The method is used to increase the energy efficiency of thermoelectric generators (TEGs). Type-2 FL was applied to adapt the variable step size of incremental resistance (INR) MPPT to track the maximum available power of a TEG. The output power from a TEG relies mostly on the difference in temperature of its two sides added to the load value. Consequently, MPPT must be robust to extract the optimum operation point continually under varying operational conditions. The aim of the suggested approach is to enhance the dynamic response and eradicate fluctuations around the maximum power point (MPP). The results employing the type-2 FL are compared with conventional methods including INR, perturb and observe (P&O), and type-1 FL. With a variable load (15, 20, and 25 omega), the proposed approach takes around 7 ms to reach a steady state with 2.6, 3.9, and 5.2 W overshoot, respectively, and almost zero oscillation. With a fixed load and a fixed temperature difference, our proposed tracker decreases the response time by 35.84%, 45.27%, and 96.50% compared to INR, P&O, and conventional FL, respectively. With a fixed load and a varying temperature difference, the proposed tracker decreases the response time by 53.33%, 94.07%, and 96.53% compared to INR, P&O, and conventional FL, respectively. The results confirmed the ability of the proposed method to keep the conversion efficiency of TEGs high and stable, reducing energy loss.

Automated summary

A robust type-2 fuzzy logic-based MPPT approach is proposed in this work to enhance the energy efficiency of thermoelectric generators. By adaptively adjusting the step size of incremental resistance MPPT, the method achieves stable extraction of the maximum power point of TEG under varying operational conditions.