Design Document - Remote Solar Monitoring and Bateery Optimzation System

Department of Electrical Engineering,
Syed Babar Ali School of Science and Engineering,
Lahore University of Management Sciences, Lahore, Pakistan
Remote Solar Monitoring System
By
Mamoon Ismail Khalid 2014-10-0187
Mohammad Ahsan Azim 2014-10-0021
Mohammad Hamza Khawaja 2014-10-0046
A report submitted in partial fulfillment of the requirements
for the degree of
BS Electrical Engineering
Syed Babar Ali School of Science and Engineering,
Lahore University of Management Sciences
Under the supervision of
Dr./Mr. Jahangir Ikram Dr./Mr. Naveed Arshad
Designation: Associate Professor EE LUMS Designation: Associate Professor CS LUMS
Email: jikram@lums.edu.pk Email: naveedarshad@lums.edu.pk
Date: May/2014

2
Table of Contents
Acknowledgement……………………………………………………………………………………………………………………………… 4
List of Figures ................................................................................................................................................3
......................................................................................................................................................................4
Acknowledgments.........................................................................................................................................5
Problem Statement.......................................................................................................................................6
1. Simulation Results of Proposed Design ................................................................................................7
2.1 Initial System Diagram ..................................................................................................................7
2.2 Design Options within Each Project Area .....................................................................................9
2.3 Simulation Methodology for each Project Area .........................................................................14
2.4 Integrated Design Simulation .....................................................................................................14
3. Finalized Design ..................................................................................................................................17
3.1 Final System Diagram..................................................................................................................17
4. Progress of the entire year .................................................................................................................22
Hardware Implementation: ....................................................................................................................24
Switching Implementation:.....................................................................................................................26
5. Problems faced ...................................................................................................................................31
Results:....................................................................................................................................................32
Future Work:...........................................................................................................................................33
References ..................................................................................................................................................35

3
List of Figures
Figure 1 Picture of the final working project ................................................................................................4
Figure 2-A General Building and battery monitoring system .......................................................................8
Figure 3 Egauge. It identifies the solar panels output, the power consumed from the grid and the
consumption of the user...............................................................................................................................9
Figure 4 Magnetic field measurements of a lithium iron phosphate during charge and discharge...........12
Figure 5 Simulink Model of the simulation.................................................................................................15
Figure 6 Stored Charge on the battery. (State of charge vs Time) .............................................................16
Figure 7 No. of charge/discharge cycles .....................................................................................................16
Figure 8 Battery's instantaneous capacity after considering the effect of temperature, no. of cycles and
the c-rate.....................................................................................................................................................17
Figure 9 a) effect on capacity with temperature at different c-rates b) our linear approximation.........19
Figure 10 a) Effect on the capacity with umber of cycles at different DOD. b) Linear piecewise
approximation with a DOD of 30% .............................................................................................................19
Figure 11 Flowchart showing the entire process associated with the project...........................................24
Figure 12 Schematic for switching scheme based on transistor logic ........................................................27
Figure 13 Switching scheme using Relays...................................................................................................30

4
Figure 1 Picture of the final working project

5
Acknowledgments
The authors wish to express sincere appreciation to Dr. Jahangir Ikram and Dr. Naveed
Arshad for their supervision during the course of this senior project and in the
preparation of this manuscript. Thanks also to Mr. Nauman Zaffar for his valuable input
about hardware implementation of the project.

6
Problem Statement
Basically the goal of our project is to devise methods to solve the problems faced by
numerous renewable energy systems which include the accurate and cost effective
measurement of the state of charge of the installed batteries as well as the
production history of the solar panels and the consumption of the user.
There remains a need for a system for measuring the state-of-health of batteries
which ameliorates disadvantages of the prior art. There is a particular need for such
systems which can be adapted quickly to accommodate new types of battery.
Often the predicament that is faced when a Renewable Energy system (Solar, wind,
biogas etc.) is installed is that the batteries that store the generated energy are
being discharged, the users are unaware of the amount of charge left and the rate of
discharge of the battery, which can often lead to shutting down of power
instantaneously (in times of increased load or prolonged usage) without any prior
warning to the user. This is a problem of particular interest not just in stationary
renewable systems but is also an area of interest for mobile storage batteries
(Electric Vehicles). Most of the state of the charge measurement systems installed in
electronics like UPS, etc. are not accurate enough and do not give a real time
measurement of the charge left /discharge rate, Load and Energy generation levels.

7
1. Simulation Results of Proposed Design
2.1 Initial System Diagram
Batteries are an integral part of any solar panel installation. Numerous battery banks
may be connected to the system in order to cater the needs in case of a shutdown or
simply for means of storage of charge.
These batteries are connected to our battery monitoring system. The basic purpose of
the battery monitoring system is to effectively measure the state of charge of the
batteries. Also it ensures that the batteries are well protected from deep discharging as
well as form being over charged. This is the reason why numerous backup battery banks
are be connected so that they can be switched in order to ensure uninterrupted power
supply as well efficient usage of the batteries.
Numerous battery banks
Battery Monitoring System
Building Management System
User Interface

8
Figure 2-A General Building and battery monitoring system
The Building Management system is responsible for measurement of the load
connected with the solar panels. This is an inherent problem with PV systems that
consumers are unaware of how much load can be connected to the panels without over
discharging the batteries. Hence by providing the consumers with adequate knowledge
regarding their consumption the performance and lifetime of our system can be
increased appreciatively. Furthermore the production of the panels is also measured so
that the user can identify any faults or discrepancies associated with his system and can
rectify the faults.
The web based transfer of data as the name suggests is the transmission of the
measured date from the batteries, the panels and the load to the users by means of
GSM module as well as a web based server. The end product of the user interface would
be similar to that of Egauge software based on the management of Photo Voltaic
systems. A screenshot of the Egauge is provided below[8]:

9
Figure 3 Egauge. It identifies the solar panels output, the power consumed from the grid and the consumption of the user
2.2 Design Options within Each Project Area
The major aspect of the project is the measurement of the state of charge of the
batteries. Measuring the state of charge is an extremely non trivial task given the
unreliable performance of batteries in different operating conditions. Apart from this
another severe problem faced when working with batteries is that their capacity isn’t
constant but also varies with time. Hence steps had to be carried out for the
approximation of the capacity of the battery. There are several methods for measuring
the state of charge of the batteries which are explained below:

10
1) Integrated Current:
The algorithm used for measuring the state of the charge (SOC) using integrated current
is a fairly simple and straight forward approach to the problem. You measure the
current flowing out of the batteries using an AMP-HOUR meter and quite simply
integrate the current to find the charge that is flowing out of the battery. [1]
Q( ) ∫ ( )
Now after the present charge in the battery is known the computation of the state of
charge is simple process. The initial charge in the battery (Qc) is given in the battery
parameters and the instantaneous charge flowing out the battery (Qi) is subtracted
from it. This will give us the amount of charge left in the battery. Hereon afterwards the
SOC can be calculated using the following:
SOC (t) = 100 (Qc - Qi (t)Qc).
However there are several problems associated with this approach. Firstly the rated
capacity of the battery needs to known. This is usually provided by the manufacturer
but as stated earlier the capacity of a battery is not constant but a variable dependant
on various parameters which need to be put into consideration.
Secondly due to the integral in the formula if the initial state of the charge has an error,
this error is translated in all the subsequent calculations of the SOC.
2) Electrolyte Specific Gravity:
Electrolyte Specific gravity is a function of the amount of acid in the battery and is
linearly proportional to the charge in the battery left. It is used for flooded batteries
(Lead Acid , Nickel-Cadmium etc) .

11
The working of this method is based on the chemical compostion of the batteries .As the
state of the charge increase the electrolyte (sulfuric acid) gets broken down in Sulfate
ions which results in the flow of charge. The presence of acid ions in the water changes
the specific gravity of the battery water. This change in the specific gravity of the battery
water as a result of increase (or decrease) in the sulfate (acid) ions is used to monitor
the battery state of the charge.
The experimental relationship between the battery charge capacity and the specific
gravity is given below:[2]
percentage of
charge
12 volt battery
voltage
24 volt battery
voltage
specific
gravity
100 12.70 25.40 1.265
95 12.64 25.25 1.257
90 12.58 25.16 1.249
85 12.52 25.04 1.241
80 12.46 24.92 1.233
75 12.40 24.80 1.225
70 12.36 24.72 1.218
65 12.32 24.64 1.211
60 12.28 24.56 1.204
55 12.24 24.48 1.197
50 12.20 24.40 1.190
40 12.12 24.24 1.176

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30 12.04 24.08 1.162
20 11.98 23.96 1.148
Table 1: Chart from the Trojan Battery company for Trojan L-16 batteries
However Specific gravity method has its disadvantages. It requires a long rest period
before is required before charge/discharge can be measured .The reason for this lies in
electrolyte diffusion dynamics. Apart from this another salient issue is that the batteries
used in PV systems are sealed gel batteries while the specific gravity method is only well
suited for flooded batteries.
3) Quantum Magnetism:
Quantum magnetism is a new technology that is developed to efficiently and accurately
measure the battery SOC. It employs the concept that different materials have different
magnetic susceptibilities. Measuring the resulting change of the magnetic field with a
sensor responding to magnetism provides linear SOC information.
The sensor employed for this method is called the Q-MAG senor and it is installed to the
batteries. [3][4]
Figure 4 Magnetic field measurements of a lithium iron phosphate during charge and discharge

13
This method has a lot of advantages over other techniques. We see no rubber band
effect that is typical with the voltage method in which the weight of discharge lowers
the terminal voltage and the charge lifts it up. It can also be used to measure the SOC
while the battery is being charged (in addition to discharging cycle SOC measurement) .
The Q-MAG sensor does not need to be in contact with the battery terminals (which in
the case of high voltages is desirable) and is only limited in usage if the battery casing is
of a ferrous material (which is a rarity).
However this approach is still in the research phase and is not yet employed in large
scale applications.
4) Voltage Based Methods:
An important method of measuring the battery’s state of charge is by using its terminal
or open circuit voltage. A simple voltmeter suffices for this purpose. The battery voltage
decreases as the battery discharges to an extent dependent upon the discharging
current of the battery. Knowing the relationship of battery voltage and SOC allows the
voltmeter to be calibrated to report SOC. Hence the voltage would be used to measure
the state of the charge of the battery.
However there are some limitations associated with this concept as well. The battery
voltage varies with the change in the ambient temperature and the discharging current
and hence this deters the reliability of using voltage as a measure of the sate of charge
of the batteries. Another issue with this method occurs when disturbing the battery
with a charge or discharge. This agitation distorts the voltage and no longer represents
the true state-of-charge. To get accurate measurements, the battery needs to rest for at
least four hours to attain equilibrium; battery manufacturers recommend 24 hours.

14
Adding the element of time to neutralize voltage polarization does not sit well with
batteries in active duty.
2.3 Simulation Methodology for each Project Area
Our major part of the project depends on the accurate measurement of the state
of charge of the batteries. A few of the methods used for this purpose have been
explained above along with their shortcomings. The method that suited our application
was the coulomb counting method due to its fairly low dependence on temperature as
well as its higher degree of accuracy as compared to other methods. The effect of
temperature plays a vital role on the battery’s performance as especially in our
environment the temperature fluctuates and hence this effect needs to be
compensated. Another problem associated with the battery is related to their capacity
and hence in our simulation numerous factors were incorporated for the calculation of
the instantaneous capacity of the battery.
2.4 Integrated Design Simulation
Our simulation displayed the output graph for the battery’s capacity, its number
if charge/discharge cycles and the instantaneous state of charge of the battery. In our
simulation we connected two battery banks simultaneously to the load one of which
would operate at a time. The purpose of these two banks was to ensure uninterrupted
power supply as well as to prolong the life of the battery by preventing it from over
discharging or over charging. The simulation model is illustrated below along with the
output graphs:

15
Figure 5 Simulink Model of the simulation
Charge Integrator
No. of charge
cycles of the
battery
Relay switching
between
batteries
Temperature
Effect and Final
Capacity
Effect of
charge cycles
on capacity

16
Output Graphs:
Figure 6 Stored Charge on the battery. (State of charge vs Time)
Figure 6 displays the constant charging and discharging of the batteries. As we have set our DOD to 30%
whenever the charge of the battery reaches 70% the relays switches the load to the second battery
bank. Furthermore it can also be observed that for the first 400 cycles the capacity of the battery
remains equal to the rated capacity due to the fact that the effect of cycle count on the negligible for
the first 400 cycles.
Figure 7 No. of charge/discharge cycles
Figure 7 illustrates the count of the discharge cycles. Whenever the battery’s state of charge reaches 70
% we count that as a complete discharge cycle. Thus due to the constant charging and discharging of the
batteries the number of cycles also progressively increases.

17
Figure 8 Battery's instantaneous capacity after considering the effect of temperature, no. of cycles and the c-rate
Figure 8 further explains the effect of all the above mentioned factors on the instantaneous capacity of
the battery. After approximately 400 cycles a decrease in the capacity can be seen. Also the successive
drops in the capacity are related to the constant discharge current or the c-rate of the battery. In
addition the two notable peaks in the capacity are due to our temperature blocks where the ambient
temperature is incremented by 5 .
3. Finalized Design
3.1 Final System Diagram
In our simulation we have connected two battery banks with the load. The state of
charge of these two batteries needs to be measured. However the instantaneous
capacity of these batteries changes and this also has to be put into consideration. The
capacity of the battery is adversely affected by the number of charge/ discharge cycles
of the battery or by the life count of the battery. The life of a battery is defined as the
number charge/discharge cycles a battery can perform before its capacity falls to 80% of
its rated capacity.
Another significant factor is the temperature. At higher temperatures the chemical
activities such as the redox reactions speed up resulting in an increase in the capacity of
the battery. Hence temperature ranging from 25 to 40 is optimum for the battery.

18
At temperatures lower than this the performance of the battery deteriorates
considerably.
Lastly the effect of c-rate is also taken into account for as it has an adverse effect on the
performance of the battery. C-rate is defined as the rate of discharge of current. Hence
for a 45Ah battery a c-rate of 0.1 means that the battery would provide us with 4.5A
current for duration of 10 hours. As the battery’s c-rate progressively increases, the
capacity of the battery is reduced as large current is being withdrawn constantly from
the battery.
Furthermore, the capacity of the battery is also linked to the depth of discharge (DOD)
at which the battery is being operated. The Depth of Discharge is defined as the amount
of charge being withdrawn from the battery. Depth of Discharge is the complementary
function as compared to the state of charge of the battery. A higher DOD means that
large currents are being withdrawn from the battery and hence due to this deep
charging the capacity is greatly affected. The significance of calculating the capacity is to
minimize the error as this instantaneous capacity is used for the state of charge
computation.
Considering these effects we have put a limit on the DOD of our batteries. Hence we
operate our batteries at a DOD of 30%. Whenever the State of Charge (SOC) equals 70%
the battery banks are switched. The purpose of this is to avoid the deep discharging of
the batteries and to prolong the number of discharge and charge cycles a battery can
perform.
The effect of temperature, number of cycles and the c-rate are illustrated in the
following graphs provided to us by the manufacturer:

19
Figure 9 a) effect on capacity with temperature at different c-rates b) our linear approximation
It can be observed from Figure 9 that as the c-rate is adversely related to the capacity of the battery.
Hence as the c-rate goes from 0.1c to 2.0c the capacity of the battery diminishes to about 10% of its
rated value. This is precisely why for our simulation we have used a c-rate of 0.1c but different c-rates
can also be accommodated in our simulation if a low capacity but a high c-rate is demanded by the user.
Figure 10 a) Effect on the capacity with umber of cycles at different DOD. b) Linear piecewise approximation with a DOD of
30%
Figure 10 shows the relationship between the number of cycles and the capacity of the battery at
numerous DOD rates.

20
Design of an amp hour meter is mostly based on the design of an ammeter. A shunt is
used to measure current and it must be inserted in the negative leg of the battery
input/output terminal. A shunt is actually a very low resistance which produces voltages
across its terminal proportional to the current flowing through it. The voltage that
occurs across the shunt is put through an op-Amp In order to scale it to +5/-5 volts. The
output of the op-Amp becomes input to an Analog to digital converter. The output of
the ADC is fed to the micro controller where the blocks would be implemented.
Explanation of the Simulation:
Source Block
We have simulated the batteries in our simulation with function blocks that have a
charging current of 8A while a discharging current of 9A. The disparity amongst these
figures is due to the fact that batteries discharge in a shorter period of time.
Integrator Block
The next block is the current integration block where the equation
Q( ) ∫ ( ) is computed. This tells us the amount of charge that is present in the
battery. The rest of the simulation is based on the computation of the capacity of the
battery from which the state of charge needs to be obtained.
Cycle Count Block
The second block is called the cycle count block and it calculates the number of
discharge cycles of the battery. A discharge cycle has been defined when the SOC
reaches 70% of its value or when it has to be recharged again.

21
Relay Block
As mentioned previously two battery banks are connected with each operating at a DOD
of 30%. Hence when battery A reaches a SOC of 70 % it is disconnected from the load
and is recharged while Battery B is consequently connected to the load so that load
receives uninterrupted power supply.
Cycle count vs Capacity Block
Furthermore, after the charge cycles of each battery have been calculated we move into
the block where the relationship between the capacity of the battery and the number of
cycles is devised by using piecewise linear approximation of the graphs provided by the
manufacturer. This block incorporates the effect on the capacity by the no. of discharge
cycles and the DOD of the battery.
Temperature & C-Rate vs. Capacity Block
Lastly the dependence of the capacity on the ambient temperature and the c-rate has to
be considered. As mentioned previously an increase in temperature increases the
capacity while c-rate has an inverse relationship with the capacity of the battery. These
relationships are formulated in this block by using the graphs illustrate previously. In
order to model the variation of temperature we have used a function block where the
temperature remains constant at 25 for majority of time but at significant intervals it
increases by 5 resulting in an increase in the capacity of the battery.
The final capacity that is calculated from these blocks is our instantaneous capacity
which is fed back to all blocks for calculation of instantaneous capacity as well as the
state of charge of the battery.

22
4. Progress of the entire year
6th September
Submission of the project proposal
6th October
Order the components required for
implementation and understand all the designs and
research related to the project
6th Novemeber
Deciding the best technique for implementation of
the project especially for calculating the state of
charge of the installed batteries
6th December
Have a running simulation for all the parameters
involved including State of Charge and the
production levels.

23
21st January
Initial Harware implementation and interfacing
with smaller lithium ion batteries
21st February
Used the DAQ Card and ensured proper interfacing of the
software simulation in order to ensure accurate data
processing.
21st March
Designed the overall switching scheme between the
installed batteries using transistor logic which introduced
numerous glitches.
21st April
Rectified the switching scheme using an entirely different
approach. Calculated the power input and output of the
batteries instanatenously and plotted the results on an
application similar to EGAUGE
28th April
Open house for the projects. Presented the idea as well
completely functional project to members of reputed
organizations and faculty members.

24
Hardware Implementation:
Figure 11 Flowchart showing the entire process associated with the project
First of our proposed tasks was to calculate the charging and discharging currents
of the batteries. However detecting currents and feeding it into digital circuitry is never
a trivial task. We achieved this by using shunt resistors of negligible resistance and
connected them in series with the load. The voltage across these resistors was then
detected and fed into the DAQ card which then was processed using the Simulink model
developed earlier. The temperature feature was incorporated by using

25
LM35(temperature sensor) whose output voltage was fed in the DAQ card and the
temperature was calibrated with the output voltage levels.
The voltage acquired was converted into current using simply Ohm’s law and
then the current was integrated over sampling time in order to obtain the instantaneous
charge of the batteries. The charge of the batteries was then compared and then DAQ
output was used to implement the switching scheme of the batteries which is described
below.
The implementation of proper switching between the batteries was an integral
part of our project. The basic concept of switching was that as soon as the SOC of
battery 1 drops to below 70% of its instantaneous capacity the battery should be
disconnected from the load and connected to the charging source while battery 2
should provide power to the load. The number of battery banks could be increased
which was facilitated by our code but the number was kept to 2 simply due to cost
constraints. The switching ensured uninterrupted power supply to the load as well
increased efficiencies for the batteries. The response time for the switching was also
calculated to be less than 0.1 second ensuring that the user did not notice any adverse
effects of switching.
For the prototype the load we used was a 16W Energy Saver. A 150 W inverter
was connected in our circuit in order to provide AC supply to the load. The load was
generic and any other equipment could be connected but due to limited capacity of the
batteries we decided to use energy savers due to their favorable response in steady
state conditions.

26
Switching Implementation:
Our first approach towards switching between batteries was based upon
transistor logic and their gate driving circuitry. The DAQ outputs for active switching
were fed into the gate drivers whose low and high outputs were used for the turning on
and off of the power mosfets used. The inherent anti parallel diodes of the mosfets
were taken care of by power diodes connected with all the transistors. The schematic of
this approach is provided below.

27
Figure 12 Schematic for switching scheme based on transistor logic
The transistor logic introduced a few glitches in our scheme which included the
clamping of the load voltage to around 8 volts. Although this could be acceptable for the
sake of our projects but we still tried to devise other methods to overcome this
obstacle. The underlying problem was that at low frequencies the gate drivers are not
able to persistently keep the transistors on. Hence the transistors even when in the on
Charging
Source
Battery 1
Battery 1
Gate Driving Circuit
Electrical Load
Emergency
Shutdown switch

28
state had impedance and restricted the flow of current resulting in a substantial voltage
drop across the mosfets. One of the methods that we tried to implement was charge
pumps.
A charge pump is a kind of DC to DC converter that uses capacitors as energy
storage elements to create either a higher or lower voltage power source. Charge
pumps use some form of switching devices to control the connection of voltages to the
capacitor. For instance, a two-stage cycle can be used to generate a higher pulsed
voltage from a lower-voltage supply. In the first stage of the cycle, a capacitor is
connected across the supply, charging it to that same voltage. In the second stage of the
cycle, the circuit is reconfigured so that the capacitor is in series with the supply to the
load. Ignoring leakage effects, this effectively provides double the supply voltage to the
load (the sum of the original supply and the capacitor). The charge pumps seemed to
beneficial for our purposes as they could ensure constant current to the gates of the
transistors keeping them persistently on and avoiding any appreciable voltage drop
across the transistor. However numerous problems are associated with the practical
implementation of charge pumps. These include excessive dependence on noise as well
as voltage levels of the circuit. Hence we also surveyed for another method which was
primarily based on the application of relays.

29
The relay logic mainly consisted of two relays; one for the charging side of the
batteries while the other for the discharging side of the batteries. The digital output of
our logic circuit was fed into the relay for the energizing/de-energizing of the relay coil.
This relay then provided separate paths for the charging and discharging of the
batteries. The schematic of this scheme is illustrated below:

30
Figure 13 Switching scheme using Relays
The relay logic provided us with fruitful results as proper switching between
batteries was obtained. The DC source for the charging of batteries was WAPDA
however solar panels were also tested with the batteries which worked perfectly.
However the use of panels at this moment was not feasible as 1 24V panel was not
sufficient enough to provide large charging currents required by the batteries.
Relay(Discharging)
Electrical Load
Battery 1
Battery 2
Relay
(Charging)

31
At the output of the relay a 150W inverter was connected in order to provide us
with 220V AC line voltage to the load. A 16 W energy saver was selected due to
distinctive peaks associated with these devices at the start and then smooth steady
state behavior. However we did test our system with other prototype loads which
include tungsten film bulbs, DC loads such as DC fans as well as 12 V motors.
Lastly the most important phase of our project was to display all the data in a
visually appealing manner to the user. This data included the effective state of charge of
the batteries, the power drawn by the load, the input power of the battery through the
charging circuit and the power output of the load. The next step was to record all this
real time data and display it instantaneously to the user. Also the control of the
application and the usage of the batteries were handed to the user who had the control
over the threshold limit of the Depth of Discharge of the batteries. According to the
demand posed by the load the user could set his depth of discharge threshold of each
battery in order to ensure that the load continues to receive uninterrupted power
supply.
5. Problems faced
Hardware implementation was the most important challenge we faced throughout our
project. Some of the problems associated with the hardware implementation are as
follows:
 The real time behavior of batteries is not a well specified quantity which changes
due to numerous factors and displays various anomalies. All these irregularities
needed to be incorporated.

32
 Interfacing the analog circuitry with the digital part is always a non-trivial task
especially due to the fact that we had to sense the current. Different ground
terminals of analog and digital also posed problems for us.
 Most importantly the transistor logic that we used for the switching scheme had
too many glitches which forced us to opt for another approach. The clamping of
voltage and the significant losses were the undesirable features that forced us to
use relays.
 Lastly, after the extraction of all data the setup of e-gauge like software was a
daunting task due to construction of a dedicated storage unit as the extraction of
real time data from MATLAB. Generally MATLAB provides data only after the
simulation has run its course but did devise a method of extracting instantaneous
data and display it simultaneously to the user.
Results:
Our project primarily helped us to achieve greater efficiencies associated with
batteries. By incorporating an efficient switching scheme and calculating
instantaneous capacity we were able to deal with one of the most unreliable
technologies affiliated with renewable energy systems. With our switching
algorithm we were able to increase the efficiencies of batteries by approximately
30%. Battery state of charge, input and output power was also accurately
calculated and displayed instantaneously which is only currently available in state
of the art solar monitoring technologies such as EGAUGE.

33
Future Work:
 Implementation of an android application for the display and record of physical
data.
 Set up of a web server to be accessed throughout LUMS based on similar lines as
EGAUGE
 A publication also in the works for the efficient usage of batteries in renewable
systems

34

35
References
A Reliable Approa’ch to Charge-Pumping Measurements in MOS Transistors
GUIDO GROESENEKEN, HERMAN E. MAES, NICOLAS BELTRAN, AND ROGER F. DE KEERSMAECKER
METHOD FOR DETERMINING BATTERY STATE or CHARGE BY MEASURING A.C. ELECTRICAL PHASE ANGLE
CHANGE Edward J. Dowgiallo, Jr., Oxon Hill,
[1]. “Battery State-of-Charge Estimation” , Shuo Pang, Jay Farrell, JieDu, and Matthew Barth ,Electrical
Engineering, University of California, Riverside, Proceedings of the American Control Conference
Arlington, VA June 25-27, 2001
[2].Other Power, “Battery metering”,
http://otherpower.com/otherpower_battery_metering.html
[3]. “How to Measure State-of-charge” , Battery University ,
http://batteryuniversity.com/learn/article/how_to_measure_state_of_charge
[4]. “Impedance Spectroscopy Checks Battery Capacity in 15 Seconds”,Battery University
,http://batteryuniversity.com/learn/article/impedance_spectroscopy_checks_battery_c
apacity_in_15_seconds
[5]. “Technical note on “How is IR measured” by
CellTrak”,http://www.celltraksystems.com/downloads/How%20is%20IR%20measured.pd
f
[6].Battery University ,“Rapid Testing Portable Batteries
“,http://batteryuniversity.com/learn/article/rapid_testing_portable_batteries
[7]. “Rapid-testing of large batteries”,Buchmann , http://www.buchmann.ca/article22-
page1.asp
[8]. EGAUGE, www.Egauge.net/Devices .
[9].Cadex ,SPECTRO™ TEST PLATFORM FOR LEAD ACID BATTERIES ,
http://www.cadex.com/technology/our-technologies/spectro
[10]. Cell Track Integrates ,http://www.celltraksystems.com/technology.html

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