Advanced Series Resistance Imaging for Silicon Solar Cells via Electroluminescence

Abstract

Herein, a method for advanced series resistance imaging via electroluminescence (EL) for silicon solar cells is presented. The well‐known method by Haunschild et al. is revisited. The Fuyuki assumption of a linear relation between diffusion length and EL signal is shown to be not applicable to silicon devices nowadays due to larger minority charge carrier diffusion lengths and thinner solar cells. A new relation derived by Breitenstein is used here instead. The updated method for series resistance and saturation current imaging based on two EL images, which show a far superior separation of contrast and almost 60% shorter data acquisition times in comparison with the original method by Haunschild, is presented. The Weber contrast of the unwanted signal caused by recombination in resistance image is reduced from 0.89 to 0.44, using the advanced method for a prominent feature on the sample cell. The contrast due to resistance stays at the same level. The dark saturation current density images show 20% higher peaks at recombination active areas and also a 5% low.

Extracting individual solar cell data from photovoltaic module electroluminescence images and current-voltage curves

“…Ultimately, the cell bias voltage is given by (6) This equation again holds for a negligible voltage drop over Rint(rmax). Therefore, this methodology allows for the calculation of the operating voltages for each solar cell in the module subjected to the conditions of EL testing, that is, dark conditions.…”

“…Two EL images at different current-voltage points (one at a higher voltage point Vh and one at a lower voltage point Vl) are used to generate maps according to the iterative method by Dost et al [6], applied to an individual cell. Here, the local series resistance RSL(r) is given by [7] (7) whereas the local dark saturation current density j0(r) is approximated by (8) In this method, C(r) is the calibration factor calculated for each pixel of the EL image at the lower bias condition.…”

“…( 8) yields dimensionless maps for RSL(r) and j0L(r). In order to obtain quantified values, a scaling factor must be applied, f according to [6] (9) implying the transformations RSL(r) → f RSL(r) and j0L → j0L(r)/f where RSmean is the dimensionless mean value of the unscaled RSL(r) map.…”

“…To distinguish whether a dark contrast in an EL image is caused by recombination effects or by resistive effects, we apply the non-linear method presented in Section B [6].…”

Learning an Empirical Digital Twin from Measurement Images for a Comprehensive Quality Inspection of Solar Cells

“…[6,7] For this, inline approaches are currently being developed. [8] At present, they require a special measurement setup and evaluation algorithms for image analysis.…”