Sensitivity Analysis of Silicon PERC Solar Cells

To understand solar cell efficiency distributions, this work introduces a modeling-free efficiency gain analysis and an approach using metamodeling and variance-based sensitivity analysis. Metamodeling is also applied to determine both the potential of PERCs and the impact of fundamental model uncertainties on simulations. Alongside, metrology to contactless image cell performance and inline detection and evaluation of hot spots is discussed.

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With the photovoltaics entering the era of over 100 GWp annual peak power production capacity and decreasing technology life cycle times, the demand for quickly and easily applicable but yet accurate solar cell characterization and sensitivity analysis methods is growing. Also, to enhance the quality and the yield of solar cell production lines, understanding the variations of cell efficiencies is essential.
For this end, this work introduces a novel approach based on metamodeling and variance-based sensitivity analysis that allows to assign each solar cell feature and process its share in total efficiency variance. For examining and improving the absolute level of efficiencies, a modeling-free efficiency gain analysis is deduced, revealing the dominant loss mechanisms to be tackled. Using the ability of the metamodeling to simulate vast parameter spaces, the potential of PERC solar cells as well as the impact of fundamental model uncertainties on numerical efficiency simulations are determined. Alongside, metrology to measure the cell performance characteristics spatially-resolved in a contactless manner as well as inline detection and evaluation of hot spots are discussed.