Fuzzy-Logic Based Computation for Parameters Identification of Solar Cell Models

The identification of the electrical parameters of the organic solar cells, such as the series resistance, the shunt resistance, the diode saturation current and the diode ideality factor, is an important task to improve their models behavior and the time simulation for photovoltaic applications. The conventional extraction methods using the optimization and measurement techniques, which are based on calculating derivatives, are quite computationally expensive and difficult to code. Therefore these parameters are required new optimization and modeling methods that capture the effect of each model parameter accurately and efficiently. In the present work, a new, fast and accurate organic solar cell extraction technique using Fuzzy-Logic-based computation is presented. This approach is based on fuzzy control techniques. These techniques allow using knowledge about the model behavior into the parameter extraction method, thus simplifying the task. The procedure is applied to extract the different parameters of a single-diode solar cell model for which results show good performances. The encouraging results have indicated the applicability of the developed approach to be incorporated in solar cell simulator tools for photovoltaic applications.