Construction of Unified Transfer Function for Energy Harvesters Based on Grey Wolf Optimization Parameter Identification

Environmental energy harvesting technology has become increasingly important for powering wireless sensor networks, IoT devices, and wearable electronics sustainably. This paper focuses on establishing unified transfer functions for energy harvesters under varying environmental excitations. Previous studies have primarily used equivalent circuit models to derive transfer functions for energy harvesters, but the diversity in device types poses a challenge for standardization. Parameter identification studies based on equivalent circuit models have been conducted for thermoelectric generators, photovoltaic panels, and piezoelectric cantilever-beam energy harvesters. However, there is a need for more accurate and efficient identification algorithms, especially for photovoltaic cells with nonlinear characteristics. This paper proposes a grey wolf optimization parameter identification method and presents unified transfer functions for energy harvesters under different environmental excitations.