You’ve done everything right. Your new high-efficiency solar module, built with the latest TOPCon cells, produces a beautiful I-V curve in the flasher. The power rating is exactly what your models predicted. But a few months later, field data tells a slightly different story. The real-world performance isn’t quite matching the datasheet, and you’re left wondering: what did we miss?
The answer might not be in the module itself, but in the light used to test it.
For decades, the solar industry has relied on solar simulators (or „flashers“) to measure a module’s power output under standard test conditions (STC). But as cell technologies evolve from PERC to TOPCon and HJT, a critical assumption is being challenged: that the light from the simulator perfectly matches „standard“ sunlight.
The truth is, it rarely does. For these advanced cell types, that small difference can have a big impact on your bottom line. This is where a deeper level of quality control—validating your simulator’s spectral match—moves from a technical formality to a commercial necessity.
The Myth of „Standard“ Sunlight in the Lab
A solar simulator’s job is to replicate the sun’s light on a clear day, as defined by the AM1.5G reference spectrum. This standard is our industry’s universal benchmark, allowing us to compare apples to apples, whether a module was made in Freiburg or Shanghai.
The IEC 60904-9 standard classifies simulators from Class A (the best) to Class C based on three criteria: spectral match, spatial non-uniformity, and temporal instability. While most modern flashers boast a Class A rating, „Class A“ doesn’t mean „perfect“—it simply means the simulator’s light intensity in specific wavelength bands is within ±25% of the AM1.5G standard.
The spectrum from a typical xenon lamp-based simulator is often spiky and irregular compared to the smooth, continuous spectrum of the sun. For years, this level of deviation was good enough. But the game has changed.
Why Your New TOPCon and HJT Modules See Light Differently
This challenge stems from a property called Spectral Response (SR), also known as Quantum Efficiency (QE), which describes how efficiently a solar cell converts photons of a specific wavelength (or color) into electricity.
Think of it like this: traditional PERC cells and next-generation TOPCon or HJT cells are like two different types of cameras. One might be excellent at capturing visible light, while the other is specially designed to capture more light in the near-infrared range.
And this is exactly the case with modern cell technologies. TOPCon and HJT cells are specifically engineered to have a better response to longer wavelengths (>1000 nm) than their PERC predecessors. This extended infrared response is a major reason for their higher efficiency.
Here’s the „aha moment“: If your solar simulator produces less infrared light than the AM1.5G standard, and you’re testing a module with infrared-sensitive HJT cells, your power measurement will be artificially low.
Conversely, if the simulator’s spectrum is skewed toward the infrared, you could be overstating your module’s performance, creating a risk for warranty claims and damaging your brand’s reputation. This discrepancy between the simulator’s light and the cell’s sensitivity is known as spectral mismatch.
Unmasking the Culprit: Spectral Mismatch
Spectral mismatch isn’t just a theoretical problem; it’s a measurable variable that can—and should—be corrected. The primary tool for this job is a spectroradiometer.
A spectroradiometer is a high-precision instrument that measures the exact spectral composition and intensity of a light source. By placing it inside the solar simulator, we can capture a detailed fingerprint of the flash and compare it directly to the ideal AM1.5G spectrum. This process is fundamental to ensuring the accuracy of any PV module prototyping and development effort.
This data provides the raw material needed to calculate a correction factor and bring measurements back to reality.
From Raw Data to Accurate Power: The Mismatch Correction Factor
Once we have the measured spectrum of our simulator, we can calculate the Spectral Mismatch Factor (MMF). While the formula can look intimidating, the concept is straightforward. It’s a correction factor that mathematically reconciles the differences between four elements:
- The ideal AM1.5G spectrum (E_ref).
- The real spectrum measured from your simulator (E_meas).
- The known spectral response of a certified reference cell (SR_ref).
- The spectral response of your module being tested (Device Under Test, or SR_DUT).
The MMF calculation produces a single number that tells you how to adjust your simulator’s measurement to get the true power rating.
- An MMF of 1.0 is a perfect match (and is practically impossible).
- An MMF of 0.98 means your simulator is causing a 2% under-measurement of power. The measured power should be divided by 0.98 (i.e., increased) to find the true value.
- An MMF of 1.02 means your simulator is causing a 2% over-measurement. The measured power should be divided by 1.02 (i.e., reduced) to find the true value.
This simple correction is one of the most important yet overlooked steps in modern module quality control.
The Real-World Impact of Getting It Wrong (and Right)
A 1-2% measurement error might sound small, but in the solar industry, it has massive financial consequences. For a 100 MW solar farm, a 2% power over-rating could represent a multi-million-dollar discrepancy between the projected and actual energy yield. It erodes investor confidence and can lead to serious contractual disputes.
On the flip side, under-rating your modules means leaving money on the table with every shipment.
By rigorously measuring and correcting for spectral mismatch, you de-risk your technology. It ensures your datasheets are accurate, your products are bankable, and your innovations are validated with objective, reliable data—a level of precision crucial for conducting advanced lamination trials or scaling a new product on a full-scale R&D production line.
FAQ: Your Spectral Match Questions Answered
What is a spectroradiometer?
A spectroradiometer is a scientific instrument used to measure the power of light at different wavelengths. In PV testing, it captures the exact „spectral fingerprint“ of a solar simulator’s flash, allowing it to be compared to the AM1.5G standard.
How often should a solar simulator’s spectrum be checked?
Best practice is to check the spectrum regularly, especially after a lamp change, as the spectrum can shift as lamps age. For critical R&D and quality assurance, it should be verified before any major test series involving new cell technologies.
Is spectral mismatch a problem for PERC modules too?
Yes, but to a lesser degree. Because the spectral response of PERC is closer to that of traditional reference cells, the mismatch effects are often smaller. The problem becomes much more pronounced with TOPCon and HJT cells due to their enhanced infrared response.
Can I use the same correction factor for all my modules?
No. The MMF depends on the specific spectral response of the module you are testing. A correction factor calculated for a TOPCon module will not be accurate for an HJT or PERC module. You need the SR data for each type of cell technology you test.
What does a „Class A“ spectral match really mean?
According to the IEC 60904-9 standard, Class A spectral match means the light intensity in six distinct wavelength bands is within 25% (0.75x to 1.25x) of the AM1.5G standard. This allows for significant spectral deviation, which is why calculating a precise MMF is still necessary for high-accuracy measurements.
Your Next Step to Measurement Certainty
The I-V curve provides the numbers, but the spectrum provides the context. As solar technology continues to advance, we can no longer afford to ignore the quality of the light source used for testing.
Understanding and correcting for spectral mismatch is no longer an academic exercise—it’s a fundamental part of modern quality assurance. It’s the hidden variable that ensures the performance you engineer in the lab is the same performance your customers get in the field.
Before you finalize your next module design or sign off on a production batch, ask a simple question: „Have we accounted for spectral mismatch?“ The answer could be the difference between market leadership and costly mistakes.