Solar Cell Lab

Solar energy was the focus of our lab experiment today. Our goal was to find the relationship between light intensity and voltage and also between light’s wavelength and voltage.
We wanted to prove that greater distance results in a decrease of both light intensity and voltage.

Let me just give you some background information about solar energy and photovoltaics [read solar cells] so you have a basic knowledge of the subject before moving on to the experiment. I’ll start off with voltage and current.

CURRENT is a moving charge
VOLTAGE is the amount of energy per charge required to move charge around a circuit

The relationship between these two is seen in an electrical circuit. In a circuit, like the one pictured below, it is voltage that drives current. To better explain how this works I’ll use an analogy and hopefully this will make a bit more sense. Think of an electric circuit like a pipe system. In a pipe system, a pump pushes water through a closed pipe. This pipe is like the wire of an electric circuit and the pump is the battery. In a pipe, pressure drives water through the pipe much like an electric circuit in which voltage, generated by the battery, drives the current (electrons).

With the relationship between voltage and current explained we can move on to the big stuff. First, there’s photovoltaics which is a fancier way of saying solar cells. These cells provide a direct current of constant electricity. The amount of voltage/current of them is dependent on wavelength of light which is the length of a single cycle of the wave. Light intensity is a measure of the energy of light. Higher intensity means greater current and voltage because of the increase in the amount of generated photons.

Just these simple definitions and explanations should be enough to help develop a greater sense of what’s happening in the experiment. That’s finally out of the way so in the words of Marvin Gaye, “Let’s Get It On.”
Here’s the equipment what we used for the experiment:

• One solar cell (pictured on right)
• One voltage probe
• One NXT adaptor
• NXT with light sensor
• One light source
• Labview VI
• Ruler
• Colored film filters (red, orange, purple, blue)
• Excel sheet

Outline of what we were to do:
Part I: Steps (measurements of voltage)
1. With no light
2. With light 0 cm away
3. Distance 1 (varied by student groups): 5 cm
4. Distance 2 (varied by student groups): 10 cm
5. Distance 3 (varied by student groups): 15 cm
Part II: Re-do with 4 colored filters – red, orange, purple, and blue (used in this order)
Part III: Graph Results – voltage vs. intensity (varies by distance); voltage for 4 different filters

Here are our results with no filters

No Light                        0 cm                     5 cm                       10 cm                       15 cm
-0.01469                           0.47285                  0.46002                  0.42153                      0.30606
-0.02752                           0.54983                  0.42153                    0.39587                     0.30606
-0.04035                           0.47285                  0.4087                     0.47285                      0.25474
-0.04035                          0.51134                    0.4087                     0.48568                      0.30606
0.06229                            0.51134                   0.46002                   0.42153                       0.24191
-0.01469                           0.47285                  0.4087                      0.38304                      0.37021
-0.02752                           0.537                       0.44719                    0.39587                      0.42153
-0.02752                           0.51134                   0.42153                    0.48568                      0.34455
-0.02752                           0.46002                 0.4087                      0.44719                       0.35738
0.01097                             0.49851                  0.39587                   0.39587                       0.44719
avg:-0.01469                    avg:0.499793 avg:0.424096                avg:0.430511             avg:0.335569

 

The first column shows voltage with no light. You can see that results are mostly negative in number. This means that when no light is present, voltage is at its lowest because light is not as readily detected. The second column shoes results when light is 0 cm away, we held the flashlight directly against the solar cell. Here, voltage, and in turn light intensity, is greatest. This is evidence that the closer/more direct light is to the cell, the greater voltage/light intensity will be. With the following three sequences, voltage/light intensity decreases with increased distance away from the solar cell. This supports our theory that greater distance results in a decrease of both light intensity and voltage.

We used the colored filters in this order: red, orange, purple, blue. We weren’t sure what kind of results to expect. Here are our results using the colored filters:

Red                                   Orange                                   Purple                                        Blue
0.4087                                0.49851                                      0.34455                                         0.39587
0.39587                              0.47285                                      0.39587                                         0.37021
0.49851                              0.47285                                      0.31889                                         0.37021
0.51134                               0.48568                                     0.34455                                         0.35738
0.47285                              0.46002                                     0.2804                                           0.26757
0.48568                              0.42153                                      0.31889                                         0.25474
0.4087                                0.46002                                     0.35738                                         0.26757
0.39587                              0.47285                                      0.29323                                         0.2804
0.46002                             0.47285                                      0.30606                                         0.29323
0.39587                             0.48568                                      0.29323                                          0.29323
avg:0.443341                   avg:0.470284                            avg:0.325305                    avg:0.315041

Filters yielded voltage/light intensity from greatest to least: orange, red, purple, blue. From these results we found that the darker the color value of the filter, the darker light it let through. The solar cell detected most light from the orange and the least from the blue. This means that bright/lighter light is more easily detected when passing through lighter/brighter color values than through darker/deeper color values and that is why the voltage/light intensity was greater for orange and red than it was for purple and blue. Furthermore, filters only transmits one wavelength of color to pass through whereas no filter allows all wavelengths to pass and that is why voltage/light intensity is greater with no filter versus with a filter regardless of color.

This lab gave me a lot of insight into some things I see in my everyday life such as the differences in light that I’ve noticed in head lights versus tail lights. Now I’ll know the background behind those differences in light. Pretty cool.


Our First Lego Mindstorm Activity

 

After watching each installment of Michael Bay’s box office hit, I found the true origins of America’s favorite robots. No the Transformers aren’t from Cybertron but from the bottom of a box of Legos and constructed by students like me and my classmates. Well not really, but the drama of that is so much more exciting.
Anyhow, this is the first of our activities and in it we set out to study the motion of our newly constructed robots as well as the measurements of distance and power. We calculated our results using a few key formulas. The set of formulas we used formed a Jenga tower. Each piece supported another and if you miscalculated one thing the whole came crashing down and you had to start all over.
First we started with measuring diameter of the robot’s tires in order to calculate circumference. We measured using a standard and converted from inches to centimeters to meters.
Here’s the conversion equations:
cm = in • 2.54
m = cm/100
The diameter of the tires equaled 0.0508 m. From this we calculated circumference using this equation: circumference = π • diameter or   C = πd. From this we calculated that C=0.1596. This is the number we input into the computer program for Lego Mindstorm.
We powered on our robots to begin and the math still wasn’t over. With the circumference we needed to figure out number the of wheel turns. For this we had another equation:
Number of Wheel Turns = (rotation°) / (360°/1 Turn)
Then both wheel turns and circumference were used to calculate the distance our robot travelled:
Distance (meters) = Number of Wheel Turns • Circumference
Distance was entered into yet another equation to find velocity:
Velocity = Distance (meters) / Time (seconds)
It all seems very mathematical, and it is, but most of the information could be inputted into the program and was automatically calculated; we recorded the given information.
To begin the actual experiment, we cleared a pathway for the robot to travel without any obstructions (like its power cord which kept getting in the way) and adjusted the power so that the distance would not exceed the measurement of our ruler, 12 inches or 30.48 centimeters or 0.3048 meters.
We conducted a trial of one power level (75) and three sets of testing for increased accuracy. We found that our measurements of distance we never the same and always greater than those measured by the computer. This could be due to eyeballing exact distances when they fell between the marked lines of the ruler. I’ll list our measurements or distance (D) and velocity*(V) compared to those of the computer in addition to number of wheel turns (WT).
*Because in our tests we set time (seconds) = 1, velocity and distance are equivalent in number
Test 1
Students                                  Computer
D = 0.27305                            D = 0.227873
V = 0.27305                            V = 0.227873
WT = 1.42778
Test 2
Students                                  Computer
D = 0.2795                              D = 0.24605
V = 0.2795                              V = 0.24605
WT = 1.54167
Test 3
Students                                  Computer
D = 0.27432                            D = 0.246493
V = 0.27432                            V = 0.246493
WT = 1.54444
At the end of our trial set we were to calculate our margin of error in order to measure how applicable our results would be on the grand scale. A high margin of error means results are less accurate/applicable and a low margin of error means results are more accurate/applicable. To measure this we used this equation:
% Error = ( (Distance measured – Distance calculated by computer) / ((Distance measured + Distance calculated by computer) / (2) ) •100%
The margin of error for each test is detailed below.
Test 1
% Error =  ( (0.27305 – 0.227873) / ( (0.27305 + 0.227873) / 2) ) •100%
% Error =  ( (0.045177) / ( (0.0500923 / 2) )  • 100%
% Error = ( (0.045177) / (0.2504615) ) • 100%
% Error = 0.18037503 • 100% = 18.04%
Test 2
% Error = ( (0.2795 – 0.24605) / ( (0.2795 + 0.24605) / 2) )  • 100%
% Error = ( (0.03345) / ( (0.52555 / 2) ) • 100%
% Error = ( (0.03345) / (0.262775) )  •100%
% Error = 0.12729521 •100% = 12.73%
Test 3
% Error = ( (0.27432  – 0.246493) / ( (0.27432 + 0.246493) / 2) )  •100%
% Error = ( (0.027827) / ( (0.520813) / 2) ) • 100%
% Error = ( (0.027827) / (0.2604065) ) • 100%
% Error = 0.10685985 •100% = 10.69%
The average for the % error for all three tests is as follows:
Average % Error = (% Error Test 1 + % Error Test 2 + % Error Test 3) / (Total Number of Tests)
Average % Error = (18.04% + 12.73% + 10.69%) / 3
Average % Error = (41.46%) / 3 = 13.82%
Given the small sample size of our testing, I think our margin of error is reasonable though next time we can do more to improve our measuring accuracy.
That’s all for this Lego Mindstorm experiment. Until next time!