Model Parameter Extraction for InGaN/GaN Multiple Quantum Well-Based Solar Cells Using Dynamic Programming

A dynamic programming algorithm is proposed for parameter extraction of the single-diode model (SDM). Five parameters of SDM are extracted from current-voltage curves of InGaN/GaN multi-quantum wells solar cells under AM1.5 standard sunlight conditions, with indium compositions of 7% and 18%. The range of series resistance of the device is adaptively selected and its value is randomly determined. After the series resistance and the range of ideal factors are planned, the parameters of SDM are iteratively solved using the root mean square error (RMSE) of the current-voltage curve and the photoelectric conversion efficiency. Based on this parameter extraction approach, the proposed algorithm is faster and more accurate compared to other conventional algorithms. Additionally, the obtained RMSE value is controlled within 1.2E−5, and the calculated fill factor and photoelectric conversion efficiency are consistent with the measured values. This study provides a reference for power optimization of advanced semiconductor photovoltaic cell systems.