The electronic properties of solar cells, particularly multicrystalline silicon-based ones, are distributed spatially inhomogeneous, where regions of poor quality may degrade the performance of the whole cell. These inhomogeneities mostly affect the dark current-voltage (I-V) characteristic, which decisively affects the efficiency. Since the grid distributes the local voltage homogeneously across the cell and leads to lateral balancing currents, local light beam-induced current methods alone cannot be used to image local cell efficiency parameters. Lock-in thermography (LIT) is the method of choice for imaging inhomogeneities of the dark I-V characteristic. This contribution introduces a novel method for evaluating a number of LIT images taken at different applied biases. By pixel-wise fitting the data to a two diode model and taking into account local series resistance and short circuit current density data, realistically simulated images of the other cell efficiency parameters (open circuit voltage, fill factor, and efficiency) are obtained. Moreover, simulated local and global dark and illuminated I-V characteristics are obtained, also for various illumination intensities. These local efficiency data are expectation values, which would hold if a homogeneous solar cell had the properties of the selected region of the inhomogeneous cell. Alternatively, also local efficiency data holding for the cell working at its own maximum power point may be generated. The amount of degradation of different cell efficiency parameters in some local defect positions is an indication how dangerous these defects are for degrading this parameter of the whole cell. The method allows to virtually 'cut out' certain defects for checking their influence on the global characteristics. Thus, by applying this method, a detailed local efficiency analysis of locally inhomogeneous solar cells is possible. It can be reliably predicted how a cell would improve if certain defects could be avoided. This method is implemented in a software code, which is available.

In this contribution the use of electroluminescence imaging, bias-dependent lock-in thermography, special dark and illuminated lock-in thermography techniques, and electron microscopy techniques is demonstrated for investigating the physical mechanism of breakdown in multicrystalline silicon solar cells. Two dominant breakdown mechanisms are identified, which are breakdown at recombination-active crystal defects, showing a relatively soft breakdown, and avalanche breakdown at dislocation-induced etch pits, which occurs very steep (hard breakdown) and dominates in our cells at high reverse bias.