A solar simulator on a budget

Light source

To get the high light intensities that I needed for this project, I hunted around for a high-performance high colour temperature white LED and came up with this one. It’s a Cree XLamp CXA2520 high lumen output and efficacy LED array. I chose the 5000K version as I wanted something that would be closer to sunlight. The device delivers 2500Lm white light at 36V and draws 0.5A. I liked the fact that it was a chip-on-board assembly that was ready to mount. I tried a smaller device but cracked it when I tried to mount it on a heatsink.

Heat considerations

We really need a heatsink here because, even though LEDs are efficient, there is still quite a lot of heat to get rid of – 20W if we assume that all electrical power is converted to heat (obviously this is the worst case scenario given that a significant amount of power should be converted into light and radiated away*). Keeping the temperature down increases the efficiency of the system and the lifetime of the LED. More importantly, we don’t want to alter the environment around our solar cell too much as this would bring in an uncontrolled variable.

I found a CPU fan/heatsink laying around and looked into bonding it using adhesive thermal tape. Assuming the thermal resistance of the fan/heatsink is 0.4K/W, and that the ambient temperature is 20C, then the heatsink will run at 28C – hopefully, the LED will be in equilibrium with this so will also be at the same temperature. I checked the specs of the heat transfer adhesive and it seems its performance is predicted to be really good. To be able to transfer 20W heat power, it would need a temperature difference of only 0.001mK across it – so the LED would be at pretty much the same temperature as the heatsink surface we can assume.

Cree XLamp CXA2520 mounted on a CPU heatsink/fan under operation at very low current. Note that the masking tape shown here was removed for final testing.

Power output

This is the most important part: the power output calculation. We need to know how much light the LED actually is going to deliver to our solar cell – in the lifetime tester application, I envisage that each solar cell under test will be assigned its own LED and this way the system would be truly modular.

On to the calculations then…What we want to know is the light intensity (irradiance) on the solar cell front surface which is simply the light power per unit area. For instance, 1 Sun illumination has an intensity equal to 1kW/m2 which is itself a unit of irradiance. Here’s how we work this out:

  • The thing is we want to know how much “real” power the LED emits in Watts. Basically, our eyes are setup to be sensitive to some wavelengths over others (the peak of the eye response happens to be tuned to the sun’s peak emission per nm which is green light at around 500nm – let’s not get drawn into a discussion about evolution here). Measuring the light output in Lumens tells us how bright the LED will be to our eyes but doesn’t tell us how much power there actually is. We need to convert units and to do this, we need to know what colour the light is. If you remember, I said that our eyes have a peak sensitivity to green light. So green light has the most number of Lumens per Watt, 683 Lm/W. Other wavelengths have less. This Lm/W number is referred to as luminous efficacy of radiation – it relates luminous to radiative flux and tells us...for a given amount of light energy, how much does this stimulate our eyes. Weird huh. Don’t get this confused with luminous efficacy of the source which is a measure of the overall efficiency of the LED in converting Watts of electrical input into Lumens of emitted light (126 Lm/W in this case). In fact, increasing luminous efficacy is one way to increase the LEDs apparent efficiency; if we made it green, it would be about twice as efficient.
  • But we don’t have a green monochromatic light source, we have a white light source? So we need to average the contribution from all the different wavelengths that make up the emitted spectrum from the LED. This gets a bit complicated. Fortunately, we can make some assumptions. Let’s assume that the spectrum of the LED approximates a blackbody that has been truncated to the visible region (normally a blackbody emitter would radiate light in the NIR and UV that we can’t see so the luminous efficacy would be much lower overall). So the luminous efficacy of radiation will be 350 Lm/W. From this, we know the total radiant power output from the LED will be 2500 / 350 = 7.1 W. We’re getting there.
  • The total radiant power is helpful but we need to know about intensity, or the number of Watts emitted over a given area. One way to go would be to assume that it’s distributed evenly over space but a better way is to assume that light emission follows Lambert’s cosine law; lambertian sources have the same brightness no matter at what angle you look at them even though their emission is not uniform. Let’s not get too drawn into the specifics here other than to say that the light intensity follows a cosine law with angle and LEDs are often approximated to lambertian emitters. So why break tradition? OK then we can now say that the peak intensity in the forward direction will be 7.1 W / π = 2.3 W / sr where sr stands for steradian (a unit of angle in 3D space. Imagine the surface of a sphere rather than the arc of a circle).
  • To get the power on the front surface of our solar cell then, we just need to know how many steradians it covers and multiply.  For a 2mm x 2mm (0.04 cm2) solar cell positioned 2 cm away from the LED (face on), I expect it to cover approximately 0.031 sr (using the formula for a cone with spherical cap) which would give us 71.3 mW incident flux and an intensity of 1781 mW / cm2 or 18 Suns! At a more reasonable distance of 5 cm, we would still have 3 Suns which would be plenty.

I’ve included the details of all these calculations in this sheet.


When I mounted the LED, I was concerned about applying enough pressure to ensure a strong bond and good thermal contact. Here, they recommend pressures in excess of 100psi! I managed only 8psi. Basically, I was concerned about breaking the LED board. I had to rest a power supply on top of a toothpick box – it seemed to be just the right size to clear the LED optical surface which shouldn’t be touched. Everything was a bit unstable as you can see…

Mounting the LED onto a CPU heatsink/fan with thermal adhesive film. Pressure applied using a small open box with a power supply on top giving 8psi.
Testing out the high power LED at 34V. Note that my power supply could only deliver 31V so I had to wire a couple of C (1.5V) batteries in series with it to get up to a more suitable voltage. You can see the meter is reading a current of 0.223A rather than the recommended 0.5A.

Driving circuit

I wired up a constant current LED driver to drive the LED with a potentiometer to control brightness (see schematics below). You can see from the chart that the output scales linearly with the voltage input to the dimmer pin – at 0V, you get the maximum output and at 4.2-4.3V the output has dropped right down to 0%.

The layout of the LED driver circuit based on the RECOM constant current LED driver unit. Output power can be controlled using the potentiometer which varies voltage supplied to the dimmer input. The output current as a function of the dimmer control voltage is also shown.

This appeared to work well when I tested it out. It got fairly bright as I adjusted the dimmer voltage which you can see from the image above however, I don’t have a way of actually measuring this at present. What I need is a calibrated meter. Unfortunately, this is outside the price range of the shed right now but I intend to do this when I visit the labs in Sheffield again.

Mismatch factor

An important figure of merit when it comes to benchmarking solar simulators is the concept of mismatch factor. It’s basically a score that your light source gets on how well it represents the solar spectrum. To work it out, we need to sum up the power in wavelength intervals over the visible and near infra-red portions of the electromagnetic spectrum for the sun (reference) and simulator (LED). Have a look at this figure below…

Calculating spectral mismatch factor: LED vs solar spectrum. Upper panel: relative spectral irradiance (area normalised) for the sun (red line) and our LED (black line). Lower panel: a table of integrated intensity over specified wavelength interval with mismatch factor (rightmost column).

Hopefully, you can see straight away that there’s a big difference in the shape of the two spectra. They have been area normalised – remember that the area under the spectra is the total power from the two sources. If we divide by area under the entire spectrum, then we’re effectively setting them to the same power for comparison which is what you would do when testing a solar cell. To get the mismatch, we then sum up the areas under the spectra between the intervals shown and compare (see table). You can see that the LED has a lot of its output in the visible range (400-700 nm) and none in the NIR compared to the sun.

To qualify as a class A solar simulator, the ratio (last column in the table) of all ranges needs to stay within 0.75 – 1.25 – we’re way off! Unfortunately, for this LED, the ratio even goes outside the allowed limits for class C (0.4 – 2.0). We need some NIR component to the spectrum to fix this which is possible. For the purposes of lifetime testing on a  budget however, then I think we need to accept these limitations. It’s good to know what they are though.

How long do solar cells live? (Part 2)

Circuit design

In this post, I want to talk about the circuit that I developed to drive solar cells at their maximum power point – the main building block of a modular lifetime tester. At this point, I should credit Sarah Sofia at MIT for her article “Build Your Own Sourcemeter“. This is what really gave me the inspiration and got me thinking that this would actually be possible with an Arduino and simple electronics.

Circuit layout of the prototype lifetime tester composed of DAC, op-amp and ADC interfaced by SPI with an Arduino UNO. The Arduino is interfaced with a PC through the serial port. Note that only one channel is shown here (one DUT).

A schematic of the lifetime tester circuit is shown above. In essence, the system is composed of:

  • a two-channel DAC (MCP4822) to give me the drive voltage across the solar cell. Because there are two channels I can run two solar cells at the same time. Typically, several subcells (6-8) are made on the same substrate so here, we can test two subcells of the same device at the same.
  • solar cell output is dumped into separate small (10-100 Ohm) series resistors which allow us to measure the current from the voltage dropped across them (applying Ohm’s law). Since resistance values and currents are small, the voltage drop will be small (we don’t want to drop much voltage in our ammeter).
  • an opamp is then needed to (on each channel) to bring the voltage to something that an ADC (ADS1286) can actually read. In fact, I’ve used an inverting op-amp with variable gain up to 1000x. To account for the fact that different solar cells under test might have different efficiencies and could therefore supply a different current, the gain is variable.

In this circuit, only the fourth quadrant (power generating region of the IV characteristic) can be accessed. Under operation, a solar cell will supply a current in the opposite direction to the applied bias. This means that the voltage across the series resistor will, in fact, be negative – one terminal is grounded, the other will be at some voltage below 0V. This signal gets fed into an inverting opamp which flips it positive again and amplifies it too. Any positive voltage at the input here will be rejected as it will be inverted to a negative output and will hit the 0V supply rail of the opamp. This means that if you try to run the solar cell in forward bias above the open-circuit voltage, giving you a forward current, you won’t get any output from the amplifier. I’ve tried to give you an illustration of this in the figure below (see lower panel).

(upper panel) LT spice model used to simulate and design the lifetime tester circuit. Note that the solar cell (DUT) has been modelled as a diode, current source and some resistors. (Lower panel) simulated input voltage from the DUT (blue line) and output (red line) voltage from the op-amp.

So did it work?…

To answer this, I connected up a solar cell and just went for a simple voltage sweep from the DAC while monitoring the current using the ADC. Here’s what the data looked like…

Using the prototype lifetime tester circuit to measure an I-V characteristic from a perovskite solar cell under illumination (black line). Power output (red line) has been calculated from DAC binary value * ADC binary value.

I was pretty happy when I saw this data. As you can see, it looks almost exactly how we expected it to from simulations and from understanding how an inverting op amp should operate. Furthermore, the fact that we can get power output curve and see a clear maximum power point (MPP) means things are looking good for doing MPP tracking. There’s some noise but I think this might have been from the fact that I was using the torch on my phone as an illumination source and it was hard to hold it exactly still. Since the measurement takes several seconds to complete, shaky hands could well be the culprit.

If you’re interested in how I coded this, then please follow the link.

How long to solar cells live?

I recently introduced DACs and ADCs. The reason that I got into this in the first place was so that I could build a cheap system for testing solar cells and ultimately measure their stability (lifetime). Perovskite solar cells are notoriously unstable and this is an area of active research right now. Clearly, a system that could monitor the efficiency of many solar cells at the same time would be really useful here.

So I got to work thinking about how we might actually do this. At the moment, this kind of measurement is done with a handful of cells kept under constant illumination with the efficiency being sampled on a timescale of minutes to hours. In between measurements, the cells will be disconnected (held at open-circuit). The illumination is fixed at an intensity of 1 Sun (100mW/cm^2). This kind of measurement really limits the amount and quality of data that we can get.

Firstly, we can’t test many solar cells at the same time (around eight) and have to wait until we’ve finished measuring all devices until we can test any others – data acquisition has to be halted and restarted by the investigator.

Secondly, we’re limited to using the same illumination intensity for all devices and that can only ever be 1 Sun (or perhaps less if you were to stick a neutral density filter over individual solar cells). Increasing illumination intensity will accelerate the test. Naively, doubling the intensity will quarter the lifetime which would remove another bottleneck in solar cell testing.

Lastly, and most importantly, leaving solar cells at open-circuit between measurements is not representative of real-world operation; solar cells need to deliver current to a load ideally at their maximum power point (MPP). At open circuit, the cell does not supply power – if we’re not going to use the power from the cell, what’s the point! One might argue that testing this way is fine for telling us about stability. However, the electric field and charge distribution inside the cell will be different here to real operating conditions, where we actually extract charge by drawing a current,  and degradation in these materials has already been linked to field assisted ion migration. Clearly, any learnings we might get using this approach would have limited practical application in developing highly stable solar cells for the real world.

Example I-V characteristics of a solar cell in the dark (black line) and under illumination (red line). Power output vs applied bias is also shown (dotted blue line) and the maximum power point (MPP) has been marked.So then the aim of the project is to build a system which can:

  1. provide high-intensity, controlled white light illumination
  2. monitor solar efficiency whilst the device is operated at MPP
  3. be modular and independent such that the number of channels can be expanded whenever the experimenter feels it’s necessary
  4. be manufactured for less than £20 per unit

System components

  • High-intensity light source – A high-intensity LED light source seemed like the natural option here. They are cheap, efficient (important if we don’t want lots of heat) and capable of delivering lots of light power which is exactly what we want. On the downside, they may not match the solar spectrum all that well. Solar simulators are classified according to how well they can reproduce the Sun’s illumination.
  • Basic source measurement unit (SMU) module – To characterise solar cells, a SMU is the instrument of choice.  It allows us to precisely control the voltage and read off current in either direction so that we can see all four quadrants of the IV characteristic. Commercially available Keithley SMUs tend to cost in the £1000’s so will obviously be out of our price range for this project. Still, we’re going to need something that can fulfil the role of monitoring power output and maintaining MPP during the lifetime test. I found a really useful article here describing how to build your own SMU from an Arduino and a DAC which I adapted to suit my needs.
  • Data acquisition and transfer to a central unit – As the solar cell is driven, the voltage, current and power output data as a function of time need to be transferred to a central unit that is interfaced with a computer (or SD card interface perhaps). This data will then be accessible to a user for further analysis offline.

In the coming series of posts, I’m going to detail what I did here including circuit design, testing and code. Watch this space…