p-n Junction Heterostructure Device Physics Model of a Four Junction Solar Cell

نویسندگان

  • Melissa J. Griggs
  • Brendan M. Kayes
  • Harry A. Atwater
  • Thomas J. Watson
چکیده

We present results from a p-n junction device physics model for GaInP/GaAs/GaInAsP/GaInAs four junction solar cells. The model employs subcells whose thicknesses have an upper bound of 5μm and lower bound of 200nm, which is just above the fully depleted case for the assumed doping of NA = 1 x 10 cm and ND = 1 x 10 cm. The physical characteristics of the cell model include: free carrier absorption, temperature and doping effects on carrier mobility, as well as recombination via Shockley–Read–Hall recombination from a single midgap trap level and surface recombination. Upper bounds on cell efficiency set by detailed balance calculations can be approached by letting the parameters approach ideal conditions. However whereas detailed balance calculations always benefit from added subcells, the current matching requirements for series connected p-n multi-junctions indicate a minimum necessary performance from an added subcell to yield a net increase in overall device efficiency. For the four junction cell considered here, optimizing the subcell thickness is an important part of optimizing the efficiency. Series resistance limitations for concentrator applications can be systematically explored for a given set of subcells. The current matching limitation imposed by series connection reduces efficiency relative to independently-connected cells. The overall trend indicates an approximately 5% drop in efficiency for series connected cells relative to identical independently connected cells. The series-connected devices exhibit a high sensitivity to spectral changes and individual subcell performance. If any single subcell within the series-connected device is degraded relative to its optimal design, the entire device is severely hindered. This model allows complex heterostructure solar cell structures to be evaluated by providing device physics-based predictions of performance limitations.

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تاریخ انتشار 2006