Solar Simulator Spatial Non-Uniformity Compensation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Solar simulators often suffer from spatial non-uniformities in illumination, leading to errors in measuring the efficiency of solar cells, as they do not provide a smooth illumination area, especially when testing large solar cells, and existing methods fail to accurately compensate for these non-uniformities.
Innovation Solution
A method involving a spatial map of the intensity distribution using a reference cell to identify and calculate the expected illumination levels for arbitrary solar cells, allowing for better prediction of light intensity across the illumination plane, even for multi-junction solar cells with different sizes and shapes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If reference cells are used to measure illumination in one area of the illuminating beam, then temporal instabilities can be compensated, but spatial non-uniformities of 5% and larger across the illuminated area are not detected
Solution Approach 1:
The illuminated area is divided into multiple discrete measurement points arranged in a grid pattern. Instead of using a single reference cell, multiple reference cells are positioned at different locations to independently measure illumination at each point, enabling detection of spatial non-uniformities across the entire illuminated area.
Solution Approach 2:
The measurement approach transitions from a single-point temporal measurement to a multi-dimensional spatial mapping. By arranging reference cells in a grid pattern across the illuminated area, the system creates a two-dimensional map of illumination intensity, adding spatial dimensionality to the measurement process.
2Adaptability or versatility
If spectral filtering or focusing is done to adjust sunlight conditions, then spectral balance can be controlled, but spatial distribution across the illumination plane changes and becomes non-uniform
Solution Approach 1:
The system uses the measurement data from the grid of reference cells to create a spatial map of illumination non-uniformities. This feedback information is then used to calculate correction factors that compensate for the spatial variations introduced by spectral filtering or focusing operations.
Solution Approach 2:
The system changes the measurement parameters by using multiple reference cells at different positions rather than a single reference cell. This allows the system to detect and quantify spatial non-uniformities that arise from spectral filtering or focusing operations.
3Device complexity
If a single reference cell is used to represent the entire illuminating beam, then device complexity is reduced, but measurement accuracy decreases due to assumed uniformity
Solution Approach 1:
The single reference cell is segmented into multiple reference cells positioned at different locations across the illuminated area. This segmentation allows each cell to independently measure local illumination conditions, providing accurate spatial information without requiring an overly complex system architecture.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables accurate compensation for spatial non-uniformities, improving the reliability of solar cell testing by ensuring precise measurement of illumination levels, thereby enhancing the testing efficiency and accuracy of solar cells in solar simulators.
Implementation Method 1
Solar cells convert the sun's energy into useful electrical energy by way of the photovoltaic effect
Data Source
AI summary
An apparatus and methods for compensating for spatial non-uniformities in solar simulators. This is accomplished in part by acquiring a spatial map of the intensity distribution that the solar simulator produces across the illumination plane using a reference cell, identifying an area of an arbitrary solar cell within the illuminated area, and then calculating the expected illumination levels for that solar cell in that specific location based on the spatial mapping. The results of that process can then be used to determine the efficiency of the arbitrary solar cell during a test in which the reference cell (of known efficiency), located in a different part of the illuminating beam, simultaneously measures the illumination in one area of the illumination beam.