Post on 15-Jan-2022
ECE 4901, Fall 2020
Light intensity modulator design
Team members:Aaditya Sekar (Electrical Engineering)Adrian Gibson (Electrical Engineering)Lauren Boulay (Electrical Engineering)
Sponsoring Organization: UCONN ECE Dept
Faculty Advisor:Sung Yeul Park
sung_yeul.park@uconn.edu860-428-5647
May 6, 2021
Table of Contents
I. Abstract……………………………………………………………………………….......2II. Introduction……………………………………………………………………………….2
III. Problem Statement……………………………………………………………………......3IV. Proposed Approach and Design………………………………………………………......4
A. Signal Sensing Interface Board…………………………………………………...8B. Data Collection & Processing…………………………..………………………..10C. Optical Engineering……………………………………………………………...12
V. Project Management……………………………………………………………………..20VI. Summary and Next Steps………………………………………………………………...21
VII. References………………………………………………………………………………..22VIII. Glossary………………………………………………………………………………….23
List of Figures and Tables
I. Figure 1 - Buck converter simulated response…………………………………………....5II. Figure 2 - Voltage and current sensing circuit schematics………………………………..6
III. Figure 3 - PSpice voltage and current sensing circuit schematics………………………..7IV. Figure 4 - PSpice time domain simulation for voltage sensing circuit……………….......7V. Figure 5 - PCB schematic…………………………………………………………….......9
VI. Figure 6 - PV Panel equivalent circuit…………………………………………………...11VII. Figure 7 - Impedance plot of the equivalent circuit model……………………………...12
VIII. Figure 8 - Experimental setup…………………………………………………………...13IX. Figure 9 - Optical system using a collimating lens……………………………………...14X. Figure 10 - Photographs of collimating lenses…………………………………………..15
XI. Figure 11 - Photographs of aluminum reflectors………………………………………...16XII. Figure 12 - PV Panel Output Voltage, No Reflectors..………………………………….17
XIII. Figure 13 - PV Panel Output Voltage, Using Reflectors………………………………..18XIV. Figure 14 - PV Panel Output Voltage, All Trials………………………………………..19XV. Figure 15 - RACI chart.………………………………………………………………...20
XVI. Figure 16 - Gantt chart……………….………………………………………………....20
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Abstract
We are creating an LED driver circuit that controls an LED array to modulate the light incident
on a photovoltaic (PV) panel. This will allow us to perform impedance spectroscopy on the PV
panel so that we can determine the health of the module. To accomplish this, we have designed a
current-controlled buck converter to modulate the LED output, voltage and current sensing
circuits, a PCB for the sensing circuits, and LabVIEW programs for data processing. An
NI-DAW device was used for data collection and reference signal generation. We have tested our
designs using simulated data from PSpice and LabVIEW. In addition, we designed and tested a
collimating lens and reflector system to increase the output voltage of the PV panel.
Introduction
The purpose of this project is to design and test a LED driver circuit that controls the
current of an LED array in order to modulate the light incident on a photovoltaic (PV) panel.
This is done in order to perform impedance spectroscopy on the panel and determine equivalent
circuit parameters. Impedance spectroscopy is a testing technique where a small AC excitation
signal is applied to a material to determine equivalent circuit model resistances and capacitances.
This can be done using specialized equipment such as a frequency response analyzer; however,
the purpose of our project is to design a system that does not need this specialized equipment.
Our LED driver circuit will be able to modulate incident light and thus the voltage output of the
PV panel in order to attain impedance data over a range of frequencies that we use to derive
equivalent circuit parameters. This project is a continuation of research done at the University of
Connecticut Center for Clean Energy Engineering.
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Problem Statement
Photovoltaic (PV) panels are a growing technology in the sustainable energy industry,
especially grid-connected panels. To ensure the long term health and performance of PV panels,
it is crucial to estimate panel aging. AC characteristics of PV panels are essential for determining
health, and therefore efficiency, but the technology that is currently used in PV panel testbeds
cannot be used to assess these characteristics. We will need to create our own devices to allow
for the detection of panel deterioration.
In order to analyze the health and performance of the PV panels, we must perform
impedance spectroscopy (IS) to characterize the electrochemical structures in the solar cells. We
will need to create testing apparatus that can perform IS using an intensity-modulated light
source operated using an LED driver circuit.
We will be using impedance spectroscopy to analyze electrochemical structures within
photovoltaic panels, which will aid in the estimation of PV panel aging. The IS method will be to
modulate the intensity of an LED light source at a range of frequencies. We will apply this light
source to the PV panel and sweep the frequency of modulation, and then measure the impedance
at each frequency value. This will allow us to extract impedance information from the PV panel,
giving us components such as the recombination resistance and chemical capacitance. We
therefore must construct an LED driver circuit to provide the correct DC offset and AC ripple
current to the light source.
For this project, we will not be able to use MOSFETs in the power converter because
they do not have fast enough switching characteristics. The power converter will need to supply
a small-signal perturbation with frequencies up to 65 kHz. This will require a high switching
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frequency, which can lead to switching losses and power dissipation, and will require careful
planning to mitigate.
This project will be tested on a 250W monocrystalline rooftop PV panel. The frequency
of the light modulation will range between 1Hz and 65kHz. The LED driver circuit must be able
to handle 300W, with 20V output and 15 +/-1.5A. Hardware from dSPACE, NI DAQ, and
Opal-RT will be used to create a real-time hardware-in-the-loop controller. Measurement devices
must also be used to determine the voltage and current of the PV panel as well as the current
through the LED for current control. LabVIEW will be used to program the controller and collect
data from the PV panel. Bench power supplies, a function generator, and an oscilloscope will be
necessary for design and testing of our device.
Proposed Approach and Design
To begin, our team first did background research on impedance spectroscopy by studying
previous experiment reports. These reports were able to effectively show results using
specialized equipment to provide an AC signal. We were also introduced to another research
experiment done by researchers at the University of Connecticut which was also able to show the
type of results that we were to expect. Based on our background readings, the next step is to
perform similar experimentation using our designed driver circuit to push the AC signal.
Our team had previously worked on two design approaches for the LED driver circuit to
determine which will be simpler to implement and better suited to the application. We
determined that one of these, using an operational amplifier circuit, was not suited for our power
requirements. Instead, our approach for the LED driver circuit is to use a current-controlled buck
converter. The buck converter will convert a 50Vdc source voltage to a current-controlled output
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with the desired offset and sinusoidal perturbation. NI-DAQ will be used to provide the reference
current, which will be compared to the output current. The current control loop uses a PI
compensator designed to have a high bandwidth to avoid attenuation of the AC component at
frequencies up to 65kHz.
Figure 1: Simulated response of buck converter showing reference current (blue) and load
current (red) at 10kHz
A voltage and current sensing circuit will be used to measure the output of the PV panel.
The voltage sensing circuit will consist of two INA154 difference amplifiers, two LM741 op
amps, a voltage source, seven capacitors, and six resistors of various values as described below.
This is then passed through an analog-to-digital converter. The current sensing circuit contains
one INA154 difference amplifier, two LM741 op amps, a current source, six capacitors, and five
resistors of various values. The schematics for the voltage and current sensing circuits are shown
in the figure below.
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Figure 2: A circuit schematic showing the voltage sensing (top) and current sensing (bottom)
circuits.
Our input signal contains a DC voltage with a relatively small AC ripple. Therefore, our
AC value has a low resolution and is difficult to measure with precision. We want to bring the
resolution of the AC ripple up so that we can maximize its measurement. The INA154 amplifiers
are used to shift the output voltage of the signal downwards, and the op amps are used to amplify
the AC ripple of the signal without amplifying the DC component. This gives our AC value a
higher resolution so that we can easily measure it in relation to the DC value.
Using PSpice, we designed the voltage and current sensing circuits and ran a time domain
simulation to measure the voltage of the input and output waveforms over the span of 50ms. For
this simulation, our input voltage had a DC offset of 4V and a 40mV AC ripple. The output gives
an AC ripple that is four times greater than the amplitude of the input signal. The figure below
shows the voltage and current sensing circuits in PSpice respectively.
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Figure 3: Our PSpice-simulated voltage sensing (top) and current sensing (bottom) circuits.
Figure 4: A PSpice time domain simulation for the voltage sensing circuit. The input wave is
shown in the bottom graph in green, and the output wave is shown in the top graph in red.
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Signal Sensing Interface Board
To implement the design to PCB form, a schematic was designed using Altium Designer,
taking into account how to drive the various supply and reference voltages throughout the board.
The board was designed to sense the voltage and currents of the PV panel and the LED driver.
Each stage had three separate parts; the first part was to sense the voltage and current signals. For
the voltage signals, this was done through direct connection from the PV panel/LED driver to the
board. Both of these signals were connected to a voltage divider in order to meet signal
requirements for the NI-DAQ. The current signals were sensed through a hall effect sensor.
The second part was to clip DC offset voltage from our obtained signal. This was done by
supplying the signal to a differential amplifier along with a DC reference voltage that would have
to be clipped. To do this, we used amplifiers to modify a 2.5VDC signal in order to reach our
desired reference voltage. Through testing the board, we found that the sensed voltages did not
require any voltage to be clipped, but the sensed currents required clipping. Each of the current
signals required us to remove 14mVDC before proceeding to the next step. To do this, we had to
make our original 2.5V smaller using a dual inverting amplifier system, then provide it to the
differential amplifier to clip.
The final step is to amplify the signals in order to meet NI-DAQ requirements. Similarly
to the reference voltages, this was also done using dual inverting op-amps. The voltage signals
were already modified through a voltage divider during sensing, so these remained unchanged.
The current signals had to be amplified since the hall effect sensors we used only output
40mV/A. The PV panel current would have to be amplified with a gain of 200; we expect a gain
of about 8V between 0 and 1A. Testing resulted in a gain of about 7.9V. The LED driver current
would have to be amplified with a gain of 82, with an expected gain of 3.3V from 0 to 1A.
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Testing resulted in a gain of about 3.25V. Final signals are then sent to the NI-DAQ system for
processing.
Figure 5: Schematic and block diagram of voltage and current sensing circuits, to be used for
PCB.
While the PCB we developed was able to perform the necessary tasks we needed to
complete this project, further improvements can be made. The major change to be implemented
is to allow for faster alteration of the clipping reference voltage to match different currents. This
could be implemented using a potentiometer rather than replacing board components. In
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addition, the original board design had implemented a method of sensing currents that used a
shunt resistor rather than a hall effect sensor. This was not tested for this project due to the
unavailability of desired parts. Finally, the board mounted power supplies could be replaced by
different models that are rated for the power that this board uses.
Data Collection & Processing
The third stage of our design is data collection and signal processing. For this, we will
use NI-DAQ modules in LabVIEW, a programming environment suited to these applications. We
will collect voltage and current data at each frequency and use algorithms to preprocess the data,
estimate the peak voltage and current, estimate the phase difference, and calculate the impedance
from these values. Our methods are adapted from those presented in [1]. At present, our focus
has been on translating the math presented in the paper into LabView code. Our program is
currently able to subtract the DC component of voltage or current data to extract the AC ripple,
and then estimate the peak voltage. This algorithm is defined in the following equations [1].
Determining the phase difference requires performing a FFT, for which LabVIEW
provides an existing VI module. The VI outputs the magnitude and phase each as a cluster
containing the start frequency, the frequency interval between each point, and an array
containing the magnitude or phase data. The fundamental frequency of the waveform is found by
finding the index of the maximum value of the magnitude, then multiplying this index by the
frequency interval and adding the start frequency. The phase of the waveform is found by
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extracting the value of the phase array at that same index. The phase of the impedance is defined
in [1] as the phase of the voltage waveform minus the phase of the current waveform.
Another LabVIEW program was written to interface with the NI-DAQ device, provide
the reference signal for the current-controlled LED driver, and collect the frequency sweep data.
This program generates an array of frequencies to sweep based on user-inputed start and end
frequencies and number of steps. The program then used NI-DAQ modules to generate a sine
waveform and modify the frequency by changing the sample clock rate. This waveform is used
as the reference signal to the current controller. The program also collects current and voltage
data from the PV panel sensing circuit, and separates this data into chunks for each test
frequency. The impedance and frequency can then be calculated for each chunk, and this data is
used to calculate the equivalent circuit parameters of the PV panel.
The basic equivalent circuit model for a PV panel is a series resistance, a parallel
resistance, and a capacitance [5]. This diagram is shown below in Figure 6. The impedance
plane, which refers to the real impedance on the x-axis and the negative imaginary impedance on
the y-axis, is used to observe the frequency characteristics of an equivalent circuit model. The
model used here takes the shape of a semicircle as shown in Figure 7 [5].
Figure 6: The PV panel equivalent circuit model used in our project
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Figure 7: The impedance plot of the equivalent circuit model
As can be seen in the diagram, the points where the plot crosses the real axis represent the
series resistance Rs and the series resistance plus the parallel resistance, Rs+Rp, respectively.
The peak imaginary impedance represents the resonant frequency of the equivalent circuit and
can be used to find the capacitance. This is done according to the equation
𝐶 = 1𝑗2ω
𝑐 𝑝𝑒𝑎𝑘(𝑍
𝑖𝑚 )
The equivalent circuit calculation thus works by finding the frequency corresponding to
the peak imaginary impedance, and then calculating the capacitance from this information.
Optical Engineering
In order to optimize the output voltage being generated by the PV panel, we will want to
maximize the efficiency of our lab setup so as much light from the LED array as possible can be
collected by our panel. To do this, we want the light from the LED array to hit the PV panel at a
90 degree angle, we want to prevent light from spilling over the edges of the PV panel, and we
want to stop ambient light in the surrounding area from reaching the PV panel. Our lab setup is
shown in Figure 8 below.
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Figure 8: Our experiment setup, showing our microcontroller, driver, LED array with
collimating lens, and PV panel.
To mitigate some of these effects, we first implemented a 60 degree beam angle
collimating lens into our system. A collimating lens is able to align photons so that beams of
light are parallel to each other instead of spreading outwards from a source. This allows us to
more accurately control the direction of the beams of light, so we can position the LED array and
prevent any light from spilling over the edges of the PV panel. This also ensures light is spread
evenly over the effective area of the panel, whereas before light would be concentrated at the
center of the panel. The effects of a collimating lens on our system can be seen in Figure 9
below.
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Figure 9: A diagram showing the path of light beams in an optical system using a collimating
lens.
In later tests, we purchased a 120 degree beam angle collimating lens for our system. We did
this because we calculated that with a wider degree beam angle, we could move the LED array
closer to the PV panel while still allowing the light to spread evenly over the effective surface
area of the panel. We calculated that, using this 120 degree lens, we could position the LED array
4 inches away from the PV panel and get our optimal output voltage. The figure below shows
both our 60 degree and 120 degree collimating lenses.
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Figure 10: A photograph of our 60 degree beam angle collimating lens (left) and our 120 degree
beam angle collimating lens (right).
To stop light from spilling over the edges of the panel and to prevent ambient light from being
picked up by our PV panel, we created aluminum light reflectors to be placed around the LED
array and collimating lens. These reflectors allowed any stray beams of light to bounce off of the
reflectors and reflect back to the PV panel. These reflectors were constructed using cardboard,
aluminum foil, and duct tape.
Knowing the beam angle associated with each collimating lens, the effective area of the PV
panel, and the size of the LED array, we were able to perform basic trigonometry to determine
the optimal distance that the LED array must be from the PV panel so that the light can reach the
edges of the PV panel and spread across the effective area equally. If the array is too close to the
panel, light would be concentrated in the center of the panel and this would decrease the output
voltage, but if the array is too far away from the panel, light will spill over the edges of the panel
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and have a high amount of loss from reflecting off of the edges of the reflector and hitting the PV
panel at a non- 90 degree angle.
For our 60 degree collimating lens, we created one reflector that was fitted to encase the area
between the LED array and the PV panel at a distance of 11 inches between the two. For the 120
degree collimating lens, we created two reflectors. One of the reflectors, which we named the
‘short-range reflector’, we created to fit with a distance of 4 inches between the LED array and
the PV panel. The second reflector, which we named the ‘long-range reflector’, was created to fit
with a distance of 9 inches between the LED array and the PV panel. The three reflectors can be
seen in the Figure below.
Figure 11: A photograph showing the aluminum reflector for our 60 degree collimating lens and
the two reflectors for the 120 degree collimating lens.
To see if the addition of the collimating lens and reflector improved the output voltage of the
PV panel, we wanted to input a constant voltage into the LED array, but change the distance
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between the PV panel and the array, the beam angle of the collimating lens, and the type of
reflector used. We used distances in increments of 4 inches, starting with the LED array 4 inches
from the PV panel and increasing it until it was 24 inches from the PV panel. We tested both the
60 degree and 120 degree collimating lens at each distance, and used each lens with and without
its associated reflector(s). Then, we recorded the PV panel’s output voltage for each trial.
Without the use of any collimating lenses or reflectors, the PV panel gave a maximum
output of 15V at a distance of 16 inches from the LED array.
Testing the collimating lenses with no aluminum reflectors gave us the results shown in
the Figure below.
Figure 12: The PV panel output voltage for both collimating lenses without using any aluminum
reflectors.
As seen in the graph, the 120 degree lens works better at shorter distances, and the 60
degree lens works better over longer distances. This is because the 120 degree lens has a wider
beam angle, so at a shorter distance, the light is more evenly distributed, and at greater distances
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the light spills over the edges of the panel. At shorter distances, the 60 degree lens doesn’t reach
the entire surface area of the panel, and it is able to at greater distances.
Next, we tested each collimating lens with their reflectors. The results are seen in the
Figure below.
Figure 13: The PV panel output voltage for each collimating lens while using its associated
aluminum reflector(s).
As seen in Figure 13, the 120 degree lens with the long-range reflector consistently
produces the highest output voltage over long distances. The three trials all produced the same
maximum voltage of 20V at a distance of 8 inches. Despite the 60 degree lens working better at a
large distance without a reflector, using the long-range reflector gives the 120 degree lens a
higher output voltage.
We put the data from all trials into the Figure below, for comparison.
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Figure 14: A graph comparing the output voltage for each collimating lens, with and without
using its associated reflectors.
As seen in Figure 14, we can reach a maximum output voltage at a distance of 8 inches
using a reflector for any collimating lens, or using the 120 degree lens with no reflector. In
addition, the 120 degree lens with a long-range reflector gives the highest output voltage over
long distances.
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Project Management
Figure 15: The RACI chart displaying the responsibilities of each member for our project.
Figure 16: A Gantt chart showing the timeline for each task associated with our project.
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Summary/Recommendation for future work
This design project involves the creation of an LED driver circuit that will perturb the
light intensity incident on a PV panel. This signal perturbation will allow us to perform
impedance spectroscopy in order to determine the health of the panel. We have done background
research on this topic through various sources and have created an outline of the necessary tasks
performed by our design: signal generation, signal measurement, and signal processing. We have
developed approaches to realize all three of these objectives. Future work includes the testing of
the completed system and collection of real PV panel data to compare with the simulated models.
This also includes testing of the closed-loop controller. Future improvements could be made to
the equivalent circuit parameter calculation program by using more sophisticated curve fitting to
better characterize the impedance plot. It may be the case that other resistances, capacitances, or
inductances may be at play in the real PV panel, and the model may need to be refined after
future testing. Finally, the overall purpose of this project is to characterize PV panel aging,
meaning that the completed system will be used to find the equivalent circuit parameters of a
panel at different conditions of age.
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References
[1] S. M. R. Islam and S. Park, "Precise Online Electrochemical Impedance Spectroscopy
Strategies for Li-Ion Batteries," in IEEE Transactions on Industry Applications, vol. 56, no. 2,
pp. 1661-1669, March-April 2020, doi: 10.1109/TIA.2019.2958555.
[2] M.S. Suresh, Measurement of solar cell parameters using impedance spectroscopy, Solar
Energy Materials and Solar Cells, Volume 43, Issue 1, 1996, Pages 21-28, ISSN 0927-0248,
https://doi.org/10.1016/0927-0248(95)00153-0.
[3] D. Chenvidhya, K. Kirtikara, C. Jivacate, PV module dynamic impedance and its voltage
and frequency dependencies, Solar Energy Materials and Solar Cells, Volume 86, Issue 2, 2005,
Pages 243-251, ISSN 0927-0248, https://doi.org/10.1016/j.solmat.2004.07.005.
[4] Pankaj Yadav, Kavita Pandey, Vishwa Bhatt, Manoj Kumar, Joondong Kim, Critical
aspects of impedance spectroscopy in silicon solar cell characterization: A review, Renewable
and Sustainable Energy Reviews, Volume 76, 2017, Pages 1562-1578, ISSN 1364-0321,
https://doi.org/10.1016/j.rser.2016.11.205.
[5] O.I. Olayiwola, P.S. Barendse, “Photovoltaic Cell/Module Equivalent Electric Circuit
Modeling Using Impedance Spectroscopy,” IEEE Transactions on Industry Applications, vol. 56,
no. 2, pp. 1690-1701, 2020.
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Glossary
Altium - PCB and circuit design software developed by Altium Ltd.
Buck Converter - DC/DC converter that steps down voltage from input to output; switched-mode
power supply
Impedance spectroscopy - measures resistance and capacitance of material via injection of AC
signal
INA154 - difference amplifier IC
LabView - system programming & automation software developed by National Instruments
LED - Light-emitting diode
NI-DAQ - data acquisition system developed by National Instruments
PCB - printed circuit board
PV Panel - Photo-voltaic panel (also known as solar panel)
Schematic - symbolic representation of circuit and connections
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Senior Design Project Checklist
Project name:
2103 Light intensity modulator design
Sponsor:
UCONN ECE Department
Team members (majors/programs):
Aaditya Sekar, Lauren Boulay, Adrian Gibson (Electrical Engineering)
Faculty advisor(s):
Dr. Sung-Yeul Park
Skills, Constraints, and Standards: (Please check (√) all those that apply to your project.)
Skills: (√)Analog circuit design and troubleshooting √Digital circuit design and troubleshooting √Software development/programming √Embedded Systems/MicrocontrollersWeb designRF/wireless hardwareControl systems √Communication systemsPower systems √Signal processing √Machine shop/mechanical designOther (please specify):Constraints:Economic (budget)Health/safety √ManufacturabilityEnvironmental (e.g., toxic materials, fossil fuels)Social/legal (e.g., privacy)Standards:List standards/electric codes that you used (e.g.,IEEE 802.11, Bluetooth, RS-232, VHDL, etc.)
If applicable, list the name or # here:
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