Jellyfish search algorithm based optimal thermoelectric generation array reconfiguration under non-uniform temperature distribution condition

Thermoelectric generators (TEGs) can convert heat to electricity based on the temperature difference between their hot and cold sides. However, during practical operations, low thermoelectric conversion efficiency is usually caused by non-uniform temperature difference (NTD) conditions; thus, reliable and effective maximum power point tracking (MPPT) under NTD conditions is imperative for TEG arrays. Therefore, in this study, a jellyfish search (JS) algorithm-based TEG array reconfiguration strategy is proposed to realise MPPT under NTD conditions, upon which the overall power loss is effectively decreased, the energy conversion efficiency is efficiently enhanced, and the MPPT speed is improved. In particular, the simulation results demonstrate that the JS algorithm-based TEG array reconfiguration using a random pattern can enhance the maximum output power by 23.32% for 9 x 9 symmetric TEG arrays and 15.78% for 10 x 15 asymmetric TEG arrays. Finally, a hardware-inthe-loop (HIL) test was conducted on the RTLAB platform to verify its feasibility for hardware implementation.