Impact of Material and Process Variations on the Distribution of Multicrystalline Silicon PERC Cell Efficiencies

• Published in: IEEE journal of photovoltaics Vol. 7; no. 1; pp. 118 - 128
• Main Authors: Wasmer, Sven, Greulich, Johannes, Hoffler, Hannes, Wohrle, Nico, Demant, Matthias, Fertig, Fabian, Rein, Stefan
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Assembly lines; Characterization; Electrical resistance measurement; Emitters; metamodeling; Metamodels; multicrystalline silicon (mc-Si); Optical refraction; Optical variables control; Parameter sensitivity; passivated emitter and rear cell (PERC); Photovoltaic cells; Production lines; Resistance; Sensitivity analysis; Silicon; simulation; Solar cells; Variance analysis; Wavelength measurement
• ISSN: 2156-3381; 2156-3403
• DOI: 10.1109/JPHOTOV.2016.2626145

We present an approach for examining and understanding the impact of material and process variations on solar cell efficiencies using the example of an industrial feasible multicrystalline silicon (mc-Si) passivated emitter and rear cell (PERC) process. We fabricate and characterize more than 800 mc-Si PERC cells with a broad material variation and model the experimentally achieved solar cell efficiencies based on numerical 3-D device simulations, metamodeling, and Monte Carlo runs. We subject the simulated distribution of cell efficiencies to a variance-based sensitivity analysis, extracting and ranking the process- and material-related input parameters according to their share of the total variance of cell efficiencies and highlighting the parameters that need to be tuned and controlled most accurately. We are able to explain 90% of the measured total variance which divides into 68%abs. material- and 22%abs. process-related influences. Experimental indication of fill factor (FF) losses due to laterally inhomogeneous bulk lifetimes is found. The presented methodology and its findings provide a fundamental tool for a better understanding of the dependencies in a mc-Si PERC process and lays the groundwork for optimizing the quality and the yield of production lines. Furthermore, the approach is transferrable to other solar cell concepts and production lines.