Optimal Operation & Management of Energy Storage Systems based on Real-Time Predictive

Modeling and Adaptive Battery Management Techniques

Venkat R. Subramanian Department of Chemical Engineering, University of Washington, Seattle, WA

Shriram Santhanagopalan

Transportation and Hydrogen Systems Center, National Renewable Energy Laboratory, Golden, CO

BMS Implementation

Efficient reformulation

Improved

SafetyPrecise

SOC

Accurate

SOH

Time

RemainingBetter Cell-

Balancing

Advanced

BMS

Different capacity fade mechanisms

2D thermal-electro-chemical coupled physics

based model

Technology

Thermal Model Results

Contact Information

PI: Venkat Subramanian

Washington Research Foundation Associate Professor of

Chemical Engineering and Clean Energy,

Department of Chemical Engineering,

University of Washington Seattle, WA

Phone: +1 – 206-543-2271

Email: vsubram@uw.edu

Website: http://depts.washington.edu/maple

Wide Range of Phenomena Dictate Different

Computational Demands

Predictability

CP

U t

ime

Porous

Electrode P2D

x

r

Stack

Thermal

Model

MD, KMC, etc

Equivalent-

Circuit Models Intercalation + Faraday’s law

Electrochemical Engg. + Faraday’s

law+ intercalation

Typically solved offline

P2D +Stress-

strain

Plane shifts

Li+

stress & strain in graphite during intercalation / deintercalation

Stress effects on Graphite structure

P2D

+Population

balance

Award: DE-AR0000275

0.1 to 5C

Model validated at

different operating

temperatures

Model based control will provide

optimal charging protocols

Capacity (Ah)

0.1 to 3C

Capacity (Ah)

Ce

ll V

olt

ag

e (

V)

Ce

ll V

olt

ag

e (

V)

-17° C 30° C

Experiment

Model

+ x

10°C Bound

No Temp Bound

Mathematical Reformulation

Coordinate

Transformation Original System 3000-10000 DAEs

0x

Final System 30-50 DAEs

Orthogonal

Collocation

A

0X 1X

C A

px l p sx l l p s nx l l l

S

C

S

-1 1 0 x

-1

1

0 f(x

)

Analytical Solutions

Reduces into

x

r

x

r

Single

Particle

Model

Recent Publications and Codes • P.W.C. Northrop, M. Pathak, D. Rife, S. De, S. Santhanagopalan and V.R. Subramanian,

“Efficient Simulation and Model Reformulation of Two-Dimensional Electrochemical

Thermal Behavior of Lithium-Ion Batteries”, J. Electrochem. Soc., (Under Review)

• M. Lawder, P.W.C. Northrop and Venkat R. Subramanian, "Model-Based SEI Layer Growth

and Capacity Fade Analysis for EV and PHEV Batteries and Drive Cycles", J. Electrochem.

Soc., 161(14), A2099-A2108 (2014).

• B. Suthar, P. W. C. Northrop, R. D. Braatz and Venkat R. Subramanian, “Optimal Charging

Profiles with Minimal Intercalation-Induced Stresses for Lithium-Ion Batteries Using

Reformulated Pseudo 2-Dimensional Models, J. Electrochem. Soc., 161(11), F3144-F3155

(2014).

• P. W. C. Northrop, B. Suthar, V. Ramadesigan, S. Santhanagopalan, R. D. Braatz and Venkat

R. Subramanian, "Efficient Simulation and Reformulation of Lithium-Ion Battery Models for

enabling Electric Transportation", J. Electrochem. Soc., 161(8), E3149-E3157 (2014).

UNIVERSITY of WASHINGTON

Reformulated model validated with COMSOL for low

aspect ratios

Ce

ll V

olt

ag

e (

V)

Time (s) Position (m) Position (m)

Liq

uid

ph

as

e

co

nc

en

tra

tio

n (

mo

l/m

3)

Te

mp

era

ture

(K

)

Battery Voltage, Current

Sensors

Temperature

Sensor data

Voltage, current, energy, and charge command

CAN interface

Control Hardware Incorporating Battery Model

Power Source/Sink

CAN message for charging/discharging

Battery charging/discharging

Acknowledgements • Manan Pathak and Dayaram Sonawane, University of Washington, Seattle

• Matt Lawder and Bharat Suthar, Washington University in St. Louis

• Myungsoo Jun, Aron Saxon and Mitchell Powel, National Renewable Energy Laboratory, Golden, CO