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Last updated in High School!
10th Grade - School Year
I started off researching Artificial Intelligence. I soon realized it
required a much stronger math background that I had at the time. Instead,
I moved on to pollution/electric vehicles. This was topic was discovered
after reading an interesting article hybrid cars. I read extensively about
the new hybrid cars for several months (this is before their commercial
release). One day I found a small ad showing a local company called Curtis
Instruments working on an electric auto-rickshaw project. I had gone to
India the previous summer and understood the problem with auto-rickshaws
(the pollution) and the electric vehicle technologies that would be needed
for such a project. I gave Curtis Instruments a call and was put in touch
with Wilfredo Chaluisant. Mr. Chaluisant, an incredibly patient, friendly,
and generous man, would become my mentor. My topic slowly shifted to "The
Effects of Electric Scooters in Developing Nations", specifically
urban air pollution. I worked with him on my 10th grade paper and on my
end of year presentation at the symposium (also available for download).
11th Grade - Summer
I interned at Curtis Instruments and learned a great deal about electric
vehicles and pollution caused by ICE (Internal Combustion Engine) vehicles.
I read extensively about pollution in developing countries and also sent
out many emails to scientists researching similar effects. However, I
soon discovered that the viability of this topic was fading. I needed
lots of data to continue and key emails I sent to researchers were never
received responses. Continuing research on this topic was looking very
precarious. Wilfredo and I met many times to look for new projects, but
no viable projects surfaced.
11th
Grade - School Year
Because no topic was present, things were pretty shaky for the first month
of school. Wilfredo got me a meeting with Jon Marshall and Gene Finger,
two engineers who worked at Curtis Instruments. I met with them and talked
about the requirements of the course and discussed my different areas
of interest up to this point. They started posing some research ideas
that sounded very viable and interesting (like working on the Curtis Electric
Bicycle project) and I was soon working on my new research project, Pulse
Charging Algorithms for Nickel Metal Hydride Batteries (Essay available
to download). It revolved around manipulating the different variables
in a pulse (e.g. amplitude, frequency) and observing the effects.
The only battery pack for testing was a group of 20 batteries that were
at many different chemical states. Some had self-discharged very low,
and were damaged, some had reasonably high float voltages. We had to condition
and normalize them before we could start any testing. As the school year
progressed, it became obvious there was no way to complete the research
in time. I decided that my attempts at conditioning and normalizing the
batteries was interesting enough for the upcoming Manhattanville competition
and the end of year school symposium (presentation available to download).
This chart shows all charge/discharge runs on the battery pack for conditioning and normalization. Before and after float voltages are shown with a connected line. You can see that the "before" line (connected red dots) varies a lot while the "after" line (connected black dots) is relatively normalized, hence normalization. You can also see that the average voltage has increased as well, hence conditioning.
12th Grade - Summer and School year
Based on ideas I had developed during last year's work, I knew exactly
what I wanted to do. I was to produce a formula that would read in the
current temperature of the battery and calculate the ideal charging current.
It’s full title was “Temperature Regulated Charge Algorithms
for Nickel Metal Hydride Battery Chemistries”. Ground work was already
complete, and much of the hardware was available. I predicted most of
the time will go into making a base formula that remotely works, this
was accurate. Many formulas were produced with different characteristics.
However, this was after a long list of preparation steps.
Abstract
Current charging technology assumes that all batteries are alike. In reality,
batteries are chemically unique and they are used in a variety of applications
that further affect batteries’ chemical states. By Identifying a
quantitative factor in batteries and exploiting this expression to control
a charging algorithm would result in a highly efficient charge. This research
produced a self-modifying charging platform that can adjust the charge
intensity based on internal resistance expression from the battery.
Method
After
identifying temperature as a good metric for determining charge intensity,
the following steps were taken to reach the final formula and charger
design.
1)
Condition and normalize all 20 available Ni-MH cells using 1C charges
and 1C discharges for one hour each. C is a capacity rating. Panasonic
rates their Ni-MH D cells at 6500 mA capacity. Therefore, 1C equals 6.5A.
This conditioning step is required to see if any batteries are unusually
different and to bring the batteries up to more uniform voltage.
2) Heat dissipation tests – Select a battery and record the temperature
at several different points on the skin of the cell. This procedure was
used to find the spot on the battery with the least lag and cleanest data.
This includes charge and discharge runs.
3) Use data found in step 2 to create a basic formula for temperature
regulated charging. This is most easily achieved by determining areas
of high and low internal resistance.
4) Construct Five Temperature sensors. (Used LM335 as the base for each
sensor. The LM335 output voltage is the temperature in Kelvin. 1mV = 1°K.
) Used potentiometers to calibrate to equal levels.
5) Build a “divide by 20” amplifier (Used a LM324 as the base).
This is used to convert the 0-10V range on the DAQ card (Note: the DAQ
card also has two 0-10V analog output channels that will be used to control
charge) to the 0-500mv range the Hewlett Packard power supply (HP6264B)
required for “External Voltage for Programming Output Current”
mode. Thus, by varying the 0-10V on the DAQ card, the HP supply will vary
from no current to maximum current; in this case the HP supply can output
0-20A.
6)
Use one output on the TP430A supply (0-32V 0-2.5A) to simulate the DAQ
card’s analog output channel (0-10V). The current from the supply
was then put through the amplifier (scaling the voltage to 0-.5V). The
amplifier was then connected to remote control terminals A4 and A6 on
the HP supply. After confirming the TP430A supply was controlling the
current on the HP supply, it was important to determine if the output
current was linear. It was not. To acquire a scaling formula, it was necessary
to test the supply from 0V to 10V in .5V increments and graph it with
the current data from a shunt. A cubic regression proved to be the best
fit with R2=.998. This scaling formula is used to convert the program’s
desired amperage to a compensated voltage value that will be sent to the
analog output channel on the DAQ card. Noise, wire resistance, etc. will
cause values to differ slightly than the predicted current.
7) Full testing on the setup using a shunt as the load and manually supplied
temperature data.
8) Check if the desired current is achieved by comparing what programming
predicts current should be and what the 25A shunt reads. If amperage is
significantly different, revise scaling formula. In this case, the formula
found in step 6 was not appropriate when using the 0-10V on DAQ card (step
6 simulated a DAQ card using another supply). This was solved by programming
a new Virtual Interface (VI) that allowed the analog output voltage on
the DAQ card to be manually controlled. Data in .5V increments was taken.
A new, superior scaling formula was created.
9)
Incorporate formula found in step 9 into VI. Complete full testing on
the setup using a shunt as the load and using manually supplied temperature
data instead of a real battery.
10) If scaling formula is still flawed, “tweak” until difference
is acceptable. Differences of up to .5A were experienced, which was not
acceptable. In order to scale correctly, two formulas were used. This
was caused by a conflict with polynomial equations with powers greater
than 3 in Labview. A single formula (3rd power) had residuals up to .8
amps and low R2 values because of this, so two formulas with 3rd power
equations were used, each with very high R2 values (.9995+). One formula
controlled current from 0A to 7.32A while the other controlled current
7.32A to 15A (a 15 amp limit was programmed in for safety). The new dual-formula
scaling system had differences no greater than .2A. This was acceptable.
11) Modify VI to read battery temperature instead of manual input for
testing purposes.
12) Test setup with battery. Record temperature/current/voltage data for
charge run. If desired, modify temperature regulation formula (original
was found in step 3), discharge battery and charge with new formula.
13)
Repeat step 13 until formula is controlling charge efficiently.
Development
By
late August setup was complete and full testing could begin on a full
range of test formulas. These formulas had already been created by studying
previous data on temperature during charging. A few formulas stood out
and were refined further. Over several months 9 different candidate formulas
were produced. The final Formula, number 9, started at a 15A charge, but
had sufficient temperature dampening so that the battery never exceeded
33°C. A paper was written for the Intel/Westinghouse Competition,
which can be downloaded.
I enjoyed much success in various science competitions, ultimately reaching the very prestigious International Science and Engineering Fair (2002), where I won 4th place in Engineering.
Progress:
Patent process started! - 9/27/02
International
Science and Engineering Fair (ISEF) 4/(11-18)/02
- 4th place "Engineering"
New York State Science and Engineering Fair (NYSSEF) 4/9/02
- Herbert Hoover Young Engineer Award
- United States Army Award
- 1st place “Engineering”
- Advance to international level
Upstate
Junior Science and Humanities Symposium 4/4-5/02
- 3rd Place “Physical Sciences and Engineering”
Westchester
Science and Engineering Fair (WESEF) 3/16/02
- Herbert Hoover Young Engineer Award
- 1st Place “Engineering”
- Advance to state level
Westchester Rockland Junior Science and Humanities
Symposium (WR-JSHS) 2/9/02
- 3rd Place “Physics, Chemistry, and Engineering”
- Advance to state level
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