PEM Fuel Cell and Battery Hybrid Power Supply System Design Based On Fuel Flow Rate Control

Zhenyuan Zhang Energy Systems Research Center,

Department of Electrical Engineering The University of Texas at Arlington

Arlington. 76019 TX, USA

Wei-Jen Lee, IEEE Fellow Energy Systems Research Center

Department of Electrical Engineering The University of Texas at Arlington

Arlington, 76013 TX, USA

Meng Liu Energy Systems Research Center

Department of Electrical Engineering The University of Texas at Arlington

Arlington, 76013 TX, USA

Abstract— This paper presents a control method for charging a battery as well as for controlling a fuel cell in a battery-fuel cell hybrid system. Due to the slow start up time of a PEM fuel cell it must be augmented by an alternative source to meet the fluctuation of power demands. This paper presents a hybrid fuel cell and battery system to serve a load. Additionally, based on the State of Charge (SOC) of the battery, the fuel cell will be used to recharge the battery as well as supply the load once startup has been achieved. Once the SOC reaches the required level, the fuel cell will stop charging the battery and it will supply the load alone. Computer simulation results are provided to validate the system

Keywords- PEM fuel cell, battery, fuel flow rate control, battery charging control, hybrid, Simulink.

I. INTRODUCTION IN recent years, renewable energy development and usage

has increased considerably due to the concern on limited energy resources and the potential impact of the traditional electrical generation methods on the environment. Since it can be applied in different applications, fuel cell becomes one of the most popular sources of alternate energy today [1].

Although the development of advanced fuel cell technologies requires a complex multidisciplinary effort, the basic concept is simple. A fuel cell is an electrochemical device that converts chemical energy directly into electrical energy [2]. Like a battery, a fuel cell consists of a pair of electrodes and an electrolyte. Unlike a battery, the species consumed during the electrochemical reaction are continuously replenished so that there is never a need to recharge the cell. The basic components of a fuel cell are illustrated in Figure 1.

Figure 1 Basic Fuel Cell Components

A Fuel cell is a very energy dense device that generates clean energy without introducing any harmful emissions to the environment. A Proton Exchange Membrane (PEM) fuel cell is one typical type of fuel cell, which is commonly utilized in applications that require quick start-up, high efficiency, and low temperature environment.

Despite their advantages, PEM fuel cells have some drawbacks as well. Because they are driven by chemical reactions, they have inherent delays that cause them to be lower in power density. Additionally, they produce an inconstant voltage output when current changes suddenly [3]. Therefore, batteries or other types of bridge power are needed to work together with fuel cell in order to ensure a consistent voltage to the load.

This paper will focus primarily on the operation of a hybrid system that uses a battery in conjunction with a fuel cell. The voltage and current measured across the battery, fuel cell, and the load are used to analyze the system.

II. MODEL DESCRIPTION The hybrid system is displayed graphically in Figure 2.

Figure 2 System diagram

The system operating principle is as follows:

A lithium-ion battery and fuel cell are connected in parallel across a load. The fuel cell will be turned on when the State-of-Charge (SOC) of the battery goes below 0.4 (40%) to recharge the battery as well as power the load. When the SOC of the battery goes over 0.8 (80%), the fuel cell is powered

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down so that the battery alone is used to supply power to the load.

The rating of the fuel cell is 6 kW at 45 volts DC with a maximum current output of 105 A. The rating of the battery is 4.5Ah with the rated voltage of 100V. When fuel cell is charging the battery and driving the load, 25 A goes to charging the battery and support load at same time.

2.1 THE FUEL CELL MODEL Two models of a fuel cell stack are proposed. The first is a

simplified model while the second is more detailed [4]. These models will be described below. A. The simplified model

In the simplified model shown in Figure 3, a controlled voltage source in series with a resistor is used to represent a fuel cell stack. .

Figure 3 Simplified fuel cell stack model

The controlled voltage source (E) is described by equation 1:

0

1ln( )/ 3 1

fcoc

d

iE E NA

i sT= − ⋅

+ (1)

fc ohm fcV E R i= − ⋅ (2)

Where

ocE = open circuit voltage (V)

N = number of cells A = Tafel slope (V)

0i = exchange current (A)

dT = the response time (at 95% of the final value) (sec)

ohmR = internal resistance (Ohm)

fci = fuel cell current (A)

fcV = fuel cell voltage (V)

Equation (1) is derived from [1] and represents the stack voltage considering only the activation losses (losses due to the slowness of chemical reactions at electrode’s surfaces). In [1], these losses are modeled electrically by a parallel RC branch. Therefore, in the event of a sudden change in the stack current, the fuel cell voltage will exhibit a delay, which is approximately 3 times the time constant (t=RC), before

equilibrium can be achieved. This phenomenon is represented in equation (1) by delaying the activation losses with a first

order transfer function 1/ 3 1dsT +

with dT being the stack

settling time. Equation (2) gives the total stack voltage considering the

losses due to electrodes and electrolyte resistance (ohmic losses).

The simplified model can be used to simulate a fuel cell stacks operating under nominal temperature and pressure conditions. A diode is used to prevent the flow of current into the stack. The model is implemented in SPS exactly as in Figure 3 using a controlled voltage source and a 1 μs delay to break the algebraic loop. B. The detailed model

Figure 4 Detailed fuel cell stack model

The detailed model, shown in Figure 4, represents a fuel

cell stack with variable operating parameters such as pressures, temperature, compositions, and fuel flow rate. Variations of these parameters affect the Tafel slope, the exchange current ( 0i ), and the open circuit voltage ( ocE ). The equivalent circuit of the detailed model is the same as that in the simplified model except that the parameters will have to be updated based on the input pressures and flow rates, stack temperature, and gas compositions [5].

ocE , 0i and A are modified as follows:

oc c nE K E= ⋅ (3)

2 20

( ) exp( )H OzFk P P GiRh RT

+ −Δ= ⋅ (4)

RTAz Fα

= (5)

Where R = 8.3145 J/mol

285

F = 96485 A s/mol z = number of moving electrons (z=2)

nE = Nernst voltage (V)

A = charge transfer coefficient

2HP = partial pressure of hydrogen inside the stack (ATM)

2OP = partial pressure of oxygen inside the stack (ATM)

k = Boltzmann’s constant (1.38*10-23 J/K)

h = Planck’s constant (6.626*10-34 J s) GΔ = activation energy barrier (J)

T = temperature of operation (K)

cK = voltage constant at nominal condition of operation

As shown in Figure 4, new values of ocE , 0i , and A are calculated using block A, B, and C. At first, the rates of conversion (utilizations) of hydrogen ( 2HUf ) and oxygen

( 2OUf ) are determined in block A as follows:

2

60000%fc

Hfuel fuel

RTiUf

zFP V x= (6)

2

600002 %

fcO

air air

RTiUf

zFP V y= (7)

Where

fuelP = absolute supply pressure of fuel (ATM)

airP = absolute supply pressure of air (ATM)

fuelV = fuel flow rate (l/min)

airV = air flow rate (l/min)

x = percentage of hydrogen in the fuel (%) y = percentage of oxygen in the oxidant (%)

The partial pressures and Nernst voltage are determined in block B as follows:

2 2(1 ) %H H fuelP Uf x P= − (8)

2 2(1 ) %O O airP Uf y P= − (9)

2 2( 2 % )H O O airP y Uf Pω= + (10)

2 2

0.544.431.229 ( 298) ln( )n H O ORTE T P P

zF zF−= + − + (11)

In the case that T > 373K:

2 2

2

0.544.431.229 ( 298) ln( )H On

H O

P PRTE TzF zF P

−= + − + (12)

where

2H OP = partial pressure of water vapor (ATM)

ω = percentage of water vapor in the oxidant (%) Knowing the partial pressures of the gases involved and

the Nernst voltage, the new values of the open circuit voltage and the exchange current can be calculated using equations (3) and (4) respectively. Block C calculates the new value of the Tafel slope using equation (5).

The effect of oxygen depletion (due to the air compressor delay) on the stack voltage can be modeled if the parameters for flow dynamics such as the peak utilization ( 2OUf (peak)) and the corresponding voltage undershoot (V ) are known.

The lack of oxygen inside the cell causes its utilization to increase above the nominal value and the Nernst voltage will be modified as follows:

2 2( )n n O O nomE E K Uf Uf= − − (13)

where K = voltage undershoots constant

2O nomUf = nominal oxygen utilization (%)

The proposed model is based on specific assumptions and limitations: Model assumptions:

The gases are ideal. The stack is fed with hydrogen and air. The stack is equipped with a cooling system, which mantains the temperature at the cathode and anode exits stable and equal to the stack temperature. The stack is equipped with a water management system toe maintain the humidity inside the cell at appropriate level at any load. Pressures drops across flow channels are negligible. The cell voltage drops are due to reaction kinetics and charge transport as most fuel cells do not operate in the mass transport region. The cell resistance is constant at any condition of operation.

Model Limitations:

The flow of gases or water through the membrane is not taken into account. The effect of temperature and humidity of the membrane on the stack resistance is not considered.

For the simplified model, a typical polarization curve

always consists of three regions as Figure 5

286

Figure 5 Typical V-I Curve

The first region represents the activation voltage drop due

to the slowness of the chemical reactions taking place at electrode surfaces. The delay depends on the operating temperature and pressure, the type of electrodes, and the catalyst used. The second region represents the resistive losses due to the internal resistance of the fuel cell stack. Finally, the third region represents the mass transport losses resulting from the change in concentration of reactants as the fuel is used.

In order to accurately model the fuel cell dynamics, current step and interrupt tests must be made on a real stack [6]. Figure 6 shows the stack response with the required parameters, ( dT ,

2OUf (peak) and uV ), labeled.

Figure 6 Stack responses with different parameters

2.2 THE BATTERY MODEL The battery model used is one that can represent most

popular types of rechargeable batteries [7]. The equivalent circuit of battery is shown below in Figure. 7:

Figure 7 Battery Model

Equations 14 and 15 are used for the model to represent a

lithium-ion battery: In the discharge mode (i* > 0):

*1 0 exp( )Q Qf E K i K it A B it

Q it Q it= − ⋅ ⋅ − ⋅ ⋅ + ⋅ − ⋅

− −(14)

In the charge mode (i* < 0) *

2 0 exp( )0.1Q Qf E K i K it A B it

it Q Q it= − ⋅ ⋅ − ⋅ ⋅ + ⋅ − ⋅

+ − (15)

Where:

0E = Constant voltage (V)

exp( )B it− ⋅ = Exponential zone dynamics (V)

K = Polarization constant (Ah-1) or Polarization resistance (Ohms)

*i = Low frequency current dynamics (A) i = Battery current (A) it = Extracted capacity (Ah)

Q = Maximum battery capacity (Ah)

A = Exponential voltage (V) Based on its discharge characteristics, the parameters of

the equivalent circuit can be modified to represent a particular battery type [8]. As shown in the Figure 8, a typical discharge curve is composed of three sections:

Figure 8 Typical Discharge Characteristics

287

The first section represents the exponential voltage drop when the battery is charged. Depending on the battery type, this area is more or less wide. The second section represents the charge that can be extracted from the battery until the voltage drops below the battery nominal voltage. Finally, the third section represents the total discharge of the battery and the voltage drops rapidly. When the battery current is negative, the battery will recharge following a charge characteristic as shown below:

Figure 9 Typical Charge Characteristics

A 100% State-Of-Charge (SOC) indicates a fully charged

battery and a 0% SOC indicates a fully discharged battery. The SOC is calculated as:

0100 (1 )

tidt

SOCQ

= ⋅ − ∫ (16)

III. THE SYSTEM BUILT IN SIMULINK

3.1 FUEL CELL SYSTEM The Fuel Cell model provided in MATLAB is used for

PEM Fuel Cell. This model is designed based the state equations and output voltage equations mentioned before.

The preset model, PEMFC-6kW-45Vdc, was chosen which has 65 cells. The nominal power is roughly 6 kW with an output voltage of 45 V. In order to control the fuel flow rate, the “Detailed” model is selected.

The nominal parameters of the fuel cell are as listed below: Stack power: Nominal = 5998.5W

Maximum = 8325W Fuel cell resistance = 0.07833 ohms Nernst voltage of one cell [En] = 1.1288V Nominal Utilization: Hydrogen = 99.56%

Oxidant = 59.3% Nominal Consumption: Fuel = 60.38 slpm

Air = 143.7 slpm

Exchange current [ 0i ] = 0.29197 A

Exchange coefficient [α ] = 0.60645

Putting the parameters into the equations 3 – 12, its V-I characteristic is shown in Figure 10:

0 50 100 150 200 25030

40

50

60

70

(225,37)

(133.3,45)

Stack voltage vs current

Vol

tage

(V)

Current(A)

0 50 100 150 200 2500

5

10

(8.325kW)

(5.9985kW)

Stack power vs current

Pow

er(k

W)

Current(A)

Figure 10 V-I and P-I Curve Fuel Cell Used in System Compared with manufacture’s VI curve, it is a near perfect

match [9]. DC/DC converter

To implement the DC/DC converter, a 100V buck converter is used.

Because the chemical reactions in a fuel cell are not easy to control, the output voltage and current can only be adjusted by the flow rate regulator. To guarantee a constant and stable output voltage, a DC/DC buck convert should be employed [10]. The diagram is shown below:

4

- FC

3

+ FC

2

-

1

+

v+-

1

0.001s+1Transfer Fcn

L

Ec dc

Duty Cycles

UBus

UrefEc

100

Constant

Duty Cycle

+

-

A

Chopper

CBus

Figure 11 DC/DC Converter Model Built in Simulink

IGBT was adopted in DC/DC model to build the buck

converter. In Figure 11, an S-Function is used to create a closed loop system. Using feedback to the IGBT’s, a more accurate output can be obtained.

Fuel Flow rate control

To implement control over the fuel rate, a flow rate regulator is modeled to create a closed loop system. The control method uses the fuel cell output current to control the fuel flow rate. The output current is used as the input to the current regulator and based on the operating temperature (65oC) and the number of cells (65) the flow rate is calculated using Equations 6 and 7. A saturation limit control can be series connected to the flow rate regulator. In the system

288

described here, the upper limit is set at 85 lpm and the lower limit is set at 0 lpm. The output of the loop system connects to the FuelFr port of the PEM fuel cell model.

Figure 12 Closed Loop System for Fuel Flow Rate Control

Based on this fuel rate system, the operational status of the

fuel cell can easily be controlled. When the output current is 0A, the fuel flow rate will lowered down to 0. During this time, the fuel cell system is in the standing by mode. However, when the flow rate regulator detects a current output, the regulator will adjust the flow rate and send a turn on signal to fuel cell. At this time, the system will be turned on but the output current and voltage will be decided by the fuel flow rate.

The control diagram of the fuel cell system is shown in Figure 13.

Figure 13 Control Diagram of PEM Fuel Cell System

3.2 BATTERY SYSTEM Model of a lithium ion battery provided by MATLAB is

used to model the battery system. The nominal battery voltage is 100 V with a capacity of 4.5 Ah.

Base on this model, the parameters are listed below: Initial State of Charge = 100% Maximum Capacity = 116.39 Ah Nominal Discharge Current = 1.9565 A Internal Resistance = 0.222 ohm

In the system model, the load connected to battery is constant to maintain a current of 50A. The current discharged from the battery is kept at half that value or 25 A.

The discharge characteristic curve is shown in Figure 14.

0 1 2 3 4 5 6

80

100

120

Nominal Current Discharge Characteristic at 0.43478C (1.9565A)

Ampere-hour (Ah)

Vol

tage

Discharge curve

Nominal areaExponential area

0 1 2 3 4 5 6

80

90

100

110

Ampere-hour (Ah)

Vol

tage

E0 = 108.3377, R = 0.22222, K = 0.12544, A = 8.4958, B = 13.5693

25 A

Figure 14 Discharge Characteristic for Battery Used in System

The system was built in Simulink as shown in Figure 15.

Continuous

pow ergui

Scope2

Scope1

1/100

Gain

s -+

25

Constant+

_

m

100 volts, 4.5 Ah Lithom-Ion battery

<SOC (%)> SOCSOC

<Voltage (V)>

Figure 15 Battery System

3.3 FULLY MODELED SYSTEM Using the fuel cell and battery models described earlier,

the whole system is implemented in the Simulink environment as shown in Figure 16.

The operating principles of the whole system are described as follows: 1. System start-up process:

When the system starts, the fuel cell stars up slowly. The batteries initial SOC is 100% percent and the battery is used to supply current to the load while the fuel cell starts up. 2. Charge battery process:

After the fuel cell system starts, the battery continues to discharge. As long as the SOC is higher than 40%, the load continues to be supplied by only the battery. If the SOC falls below 40%, a signal is sent through the relay allowing the fuel cell to begin supplying current to the load. In addition to supplying current to the load, the fuel cell is used to charge

Continuous

powergui

v+-

Scope2

Scope1

FuelFr m

+

-

m

+

- FuelFr

Fuel Cell Stack

Currentflow rate

Flow rate regulator

i+ -+ FC

- FC +

-

100Vdc BuckDC/DC Converter (average value)

<Voltage>

<Current>

DC bus voltage

DC bus current

<Utilization (%) [O2(Yellow); H2(Magenta)]> <Stack Efficiency (%)>

<Stack consumption (lpm) [Air(Yellow); Fuel(Magenta)]>

Fuel flow rate (lpm)

FuelFr

m

+

-

m

+

-

FuelFr

Fuel Cell Stack

Currentf low rate

Flow rate regulator

<Volta

<Curre

289

battery. During this time, the fuel cell outputs 50A, 25A to charge the battery, and at the same time support the load. Once the SOC exceeds 80%, fuel cell is once again removed from the system and battery is used to fully support the load.

Figure 16 Whole System Including Fuel Cell System and

Battery System

IV. TEST RESULTS AND DISCUSSION Test Conditions:

In this system, the load can be varied. The battery voltage is 100V with a capacity of 4.5Ah. The PEM fuel cell stack’s power output is 6kW operating at 45V DC. The DC/DC boost converter will convert the fuel cell output voltage to 100V. The fuel cell is able to operate properly as long as load current is less than 85 A. Process Specification of each process

1 System start, one load (25 A) 2 PEMFC switched on, battery charging and one

load (25 A) 3 SOC of battery reached 80%, PEMFC switched

off, one load (25 A) 4 Two loads (25 A and 25 A), supported by battery 5 Battery charging, PEMFC switched on, two load 6 Battery return to system, PEMFC switched off,

two load

1. Start-up process: When system starts, the system is initiated using only

battery power, the PEMFC gives no output current, while the battery output 25A to power the load. The system overall output is stable.

For battery performance (without charging), the Simulink also shows clearly. After roughly 625s of using only the battery to supply current to the load, the battery voltage and

state of charge decrease to 0, and SOC goes to 0 for 10 seconds later. See Figure. 17.

Figure 17 Battery Without Recharge

2. Battery charge process:

At t = 356s, the SOC drops under 40%. A signal is transmitted through the relay to connect the fuel cell to the system. At this time, the fuel cell system acts as a DC generator with a output current of 50 A, 25A goes to the load and 25A charges the battery. The results are shown in Figure 18 and Figure 19. 3. PEMFC switched off process:

At t = 639s, the SOC reaches 80% and the relay removes the fuel cell from the system. Once the SOC goes below 40% again, the cycle restarts. Fig. 18 and 19 show the relation between SOC and PEMFC output. 4. Two loads process

When the load is suddenly increased, the battery will continue support the load until SOC under 40%. PEMFC is switched on to supply 75A current, 50A to load and 25A to recharge battery. Once SOC reached 80%, PEMFC will be switched off from system while battery will support load alone. (See Figure 18 and 19)

Figure 18 PEM Fuel Cell System Output Performance

Continuou

s powergu

i

v+-

Scope2

Scope1

Scope

Relay

1/100

Gain

FuelFr

m

+

-

m

+

-

FuelFr

Fuel Cell Stack

Current flow

rate Flow rate regulator

i+ -

s -

+

s -

+

25

Constant1

+ FC -

FC +

-

100Vdc Buck DC/DC

Converter (average value)

+

_

m

100 volts, 4.5 Ah Lithom-Ion

battery

<Voltage> <Current>

DC bus voltage

DC bus current

<Utilization (%) [O2(Yellow); H2(Magenta)]>

<Stack Efficiency (%)>

<Stack consumption (lpm) [Air(Yellow); Fuel(Magenta)]>

Fuel flow rate (lpm)

<SOC (%)>

SOC

SOC

<Voltage (V)>

Vol

tage

(V)

SOC

(%)

PEM

FC O

utpu

t Cur

rent

(A)

PEM

FC O

utpu

t Vol

tage

(V)

290

Figure 19 Battery Output Performance and SOC

V. CONCLUSION The paper presents a study of a hybrid system that employs

both a PEM fuel cell and a lithium-ion battery to drive a constant impedance load. When the SOC of the battery is high, > 40 %, the battery is used to drive the load. When the SOC is low, the fuel cell is used to drive the load and recharge the battery until the battery is recharged. The system has been simulated using MATLAB to demonstrate its successful operation. It has been shown that a fuel cell and a lithium-ion battery can be used in combination so that the shortfalls of each can be overcome using the other creating a system that is always driven using renewable energy resources.

REFERENCES [1] J. Jia, Y.T. Cham, W.K. Au “A review of PEM Fuel Cells”, World

Hydrogen Technologies Convention (WHTC 2005), Singapore, 03-05 October, 2005

[2] James Larminie, Andrew Dicks, “Fuel cell systems explained”, 2nd ed. John Wiley and Sons Ltd.

[3] J.Jia, Q. Li, Y.Wang, Y.T.Cham, M.Han, “Modeling and Dynamic Characteristic Simulation of Proton Exchange Membrane Fuel Cell” IEEE Trans. Control System Technology , vol. 24, no. 16, pp. 283-291, Mar. 2009

[4] J.M. Lee, B.H. Cho., “A Dynamic Model of a PEM Fuel Cell System”, Applied Power Electronic Conference and Exposition, 2009. APEC 2009. Twenty=Fourth Annual IEEE, Pages (s): 720-724.

[5] Woonki Na, Bei Gou and Bill Diong “Nonlinear control of PEM fuel cells by exact linearization”, Industry Application Conference, 2005. Fourtieth IAS Annual Meeting. Conference Record of the 2005 Volume 4, Issue, 2-6 Oct. 2005 Page(s): 2937-2943 Vol.4

[6] Faryar Jabbari, Jack Brouwer, Rory Roberts, Scott Samuelsen, “Dynamic Modeling and Control of Fuel Cell Hybrid System”, 3rd Annual DOE/U.N. Hybrid Conference and Workshop

[7] C.M. Shepherd, “Design of Primary and Secondary Cell – Part 2. An equation describing battery discharge”, Journal of Electrochemical Society, Volume 112, Jul, 1965, pp. 657-664.

[8] Tremblay, O.; Dessaint, L.-A; Dekkiche, A.-I., “A Generic Battery Model for the Dynamic Simulatuin of Hybrid Electric Vehicles”, Vehicle Power and Propulsion Conference, 2007. VPPC 2007. IEEE 9-12 Sept. 2007, pp. 287-289

[9] ‘Data sheet of a 1.2kW Ballard NEXA Power Module’, Ballard Power System Inc., 2004 Ballard Power System Corp. AN2001-04.

[10] Kong Xin, Ashwin M. Khambadkone, “Dynamic modeling of fuel cell with power electronic current and performance analysis”, IEEE Trans. On Power Electronic and Drive System, 2003. PEDS 2003. The Fifth International Conference, Volume 1, 17-20 Nov. 2003 Page(s): 607-612

BIOGRAPHY

Zhenyuan Zhang was born in Xi’an, China in 1986. He received the B.S degree from Chang’an University, Xi’an, China in 2007. He is now pursuing his Ph.D. degree in Energy System Research Center, Department of Electrical Engineering, the University of Texas at Arlington, Arlington, Texas, USA. Focus in areas of Arc Flash analysis, hybrid energy storage in smart grid, and renewable energy. He is the only Student Assistant of the IEEE/NFPA Collaboration on Arc Flash Phenomena Research Project.

Wei-Jen Lee (S’85-M’85-SM’97-F’07) received the B.S. and M.S. degrees from National Taiwan University, Taipei, Taiwan, and the Ph.D. degree from the University of Texas at Arlington, in 1978, 1980 and 1985, respectively, all in electrical engineering.

In 1985, he joined the University of Texas at Arlington, where he is currently a Professor in the Electrical Engineering Department and the Director

of the Energy Systems Research Center. He has been involved in the revision of IEEE Std. 141,339,551, and 739. He is the Secretary of the IEEE/IAS Industrial and Commercial Power Systems Department (ICPSD) and an Associate Editor of the IEEE Industry Application Society and the International Journal of Power and Energy Systems. He is the Project Manager of the IEEE/NFPA Collaboration on Arc Flash Phenomena Research Project. He has been involved in research on utility deregulation, renewable energy, smart grid, micro-grid, arc flash, load forecasting, power quality, distribution automation and demand-side management, power system analysis, online real-time equipment diagnostic and prognostic systems, and microcomputer-based instruments for power systems monitoring, measurement, control, and protection. He has served as the Primary Investigator (PI) or Co-PI of over 90 funded research projects. He has published more than 200 journal and conference proceeding papers. He has provided on-site training courses for power engineers in Panama, China, Taiwan, Korea, Saudi Arabia, Thailand, and Singapore. He has refereed numerous technical papers for IEEE, IET, and other professional organizations.

Prof. Lee is a Registered Professional Engineer in the State of Texas.

Meng Liu received her B.S. degree from Shandong University (SDU), Jinan, China in June 2010. She is currently pursuing the Ph.D. degree in the area of Energy Systems at the University of Texas at Arlington (UTA). She is a member of the research group at the Energy Systems Research Center at UTA. Her areas of interest are fuel cells energy, wind energy and energy storage, system steady state power flow analysis, and short circuit current analysis.

Bat

tery

Out

put C

urre

nt (A

) B

atte

ry O

utpu

t Vol

tage

(V)

SOC

(%)

291