Advanced Management and Protection of
Energy storage Devices (AMPED)
NAATBatt 2013 Annual Meeting
Amul D. Tevar, Ph.D., MPH
ARPA-E Fellow
Ilan Gur, Program Director
Russel Ross, Tech SETA
Jan. 18th 2013
ARPA-E Overview
1
Reduce Energy-
Related Emissions Improve Energy
Efficiency
Reduce Energy Imports
To enhance the economic and energy security of the U.S.
To ensure U.S. technological lead in developing and
deploying advanced energy technologies
ARPA-E Overview
2
time
co
st / p
erf
orm
an
ce
existing learning curve
new learning curve
transformational
Transformational & disruptive technologies
that lead to new learning curves
Steam-powered Cugnot (1769)
Benz Motorwagen (1885)
Ford Model T
(1914)
ARPA-E: 14 Focused Programs to Date
3
Stationary Power / Use
Transportation
Electrofuels BEEST
PETRO MOVE AMPED
REACT
SBIR/STTR
HEATS BEETIT GRIDS
ADEPT GENI Solar
ADEPT
Transportation and
Stationary Power / Use
IMPACCT
Stationary Power / Use
Transportation
ARPA-E: 3 Battery Programs to Date
4
Electrofuels BEEST
PETRO MOVE AMPED
REACT
SBIR/STTR
HEATS BEETIT GRIDS
ADEPT GENI Solar
ADEPT
Transportation and
Stationary Power / Use
IMPACCT
State of the Art
5
Battery trends are impressive
1. Anderson, D. Duke University Thesis, 2009.
Why BMS program over new chemistries?
‣ Purpose: Improve safety, performance and return on
investment by optimizing system design & control
– Improve the existing and future breakthroughs of DOE (e.g. VT or
HUBs)
‣ Protection/Safety
‣ Health/Second Life
‣ Performance
‣ Driver/Location change
6
Propulsion
Capacity
Overhead
Capacity
Balance of
System
Capacity needed to propel
vehicle for XX mile range
Additional capacity buffer:
safety/lifetime assurance
Physical protection
Thermal management
Charge balancing
State monitoring
Etc.
State-of-the-Art XEV
Can’t we do better with the chemistries we have today?
Why is BMS so hard?
8 1. Dreyer Nat. Matls et al, 2010
2. Kim et al, IEEE Trans. on Power Elec., vol. 27(1), Jan 2012
3. http://www.thetimes.co.uk/tto/business/industries/engineering/article3655441.ece
Could we improve this for performance and battery valuation?
‣ Change of state is not uniform between particles, cells, packs
What are we protecting against?
9
Cobalt Oxide
Graphite
Ele
ctr
oly
te S
tab
ility
Electrolyte
Oxidation
Po
ten
tia
l (E
) vs
. L
i
Capacity Lost Power Loss
Electrolyte Reduction
(Kinetically limited)
Short Circuit Safety Risk
Lithium Plating
(Dendrites)
Electrode “Breathing”
(Stress/Cracking)
Utilization Constraints
10
Cobalt Oxide
Graphite
Ele
ctr
oly
te S
tab
ility
Electrolyte
Oxidation
Po
ten
tia
l (E
) vs
. L
i
Capacity Lost Power Loss
Electrolyte Reduction
(Kinetically limited)
Short Circuit Safety Risk
Lithium Plating
(Dendrites)
Electrode “Breathing”
(Stress/Cracking)
Utilization Constraints
11
Cobalt Oxide
Graphite
Ele
ctr
oly
te S
tab
ility
Electrolyte
Oxidation
Po
ten
tia
l (E
) vs
. L
i
Capacity Lost Power Loss
Electrolyte Reduction
(Kinetically limited)
Short Circuit Safety Risk
Lithium Plating
(Dendrites)
Electrode “Breathing”
(Stress/Cracking)
Utilization Constraints
12
Cobalt Oxide
Graphite
Ele
ctr
oly
te S
tab
ility
Electrolyte
Oxidation
Po
ten
tia
l (E
) vs
. L
i
Capacity Lost Power Loss
Electrolyte Reduction
(Kinetically limited)
Short Circuit Safety Risk
Lithium Plating
(Dendrites)
Electrode “Breathing”
(Stress/Cracking)
Utilization Constraints
13
Cobalt Oxide
Graphite
Ele
ctr
oly
te S
tab
ility
Electrolyte
Oxidation
Po
ten
tia
l (E
) vs
. L
i
Capacity Lost Power Loss
Electrolyte Reduction
(Kinetically limited)
Short Circuit Safety Risk
Lithium Plating
(Dendrites)
Electrode “Breathing”
(Stress/Cracking)
Situational Awareness – Removing the Blinders
14
Electrolyte Oxidation
Lithium Plating
(Dendrites)
Internal Cell Defects
What we are protecting against What we currently monitor
Temperature
Voltage
Current
Every
Cell
G
rou
ps o
f cells
State
Sensing
Advanced Models &
Adaptive Controls
System Design
Many areas for BMS innovation
15
Active
System
Design
How did AMPED evolve?
16
Timeline: 6-8 Months from Program Conception to Execution
Envision
Establish
Engage
Evaluate
Contract Negotiation
and Awards
Program Conception
(Idea / Vision)
Workshop
Further Refinement
& FOA DevelopmentFOA Announced
Concept Paper
Review
Award
Announcements
Technical
Deep Dive
Project
Selection
Full Proposal
Panel ReviewInternal Debate
Proposal
Rebuttal Stage
Program
Execution
Metrics created for AMPED Program
‣Safety
– Fault detection, prevention of thermal runaway
‣Performance
– Reduce cost (Mobile), increase revenue (Grid)
‣Prognostics
– Prediction of remaining life
‣No chemistry or additive changes
– Projects should be chemistry independent
‣System-level context for projects
17
AMPED Project Portfolio
18
1. Sensing – Monitor internal cell temperature in real time?
– Monitor intercalation strain for SOC/SOH estimation?
– Track physical/chemical states with optical sensing?
– Track gas signatures of various degradation modes?
2. Modeling & controls – Employ real-time physical state and degradation
models to optimize utilization and balancing control?
3. Systems – Implement cost effective cell-level power management?
– Utilize flexible power architectures for diff’l diagnostics?
– Wireless communications and control
– Design intra-cell thermal management systems?
ALSO: Diagnostics & prognostics – Identify degradation/failure modes quickly with non-
destructive acoustic inspection?
– Measure high-precision columbic efficiency on
production cells and practical drive cycles?
Takeaways
‣ AMPED aims for system level innovation & safety
– Exploit current and future chemistry innovation
‣ Can we improve valuation, utilization or cost?
– Lifetime meter
‣ Highly adaptable approaches
– Stochastic systems need flexible controls
19
I am intrigued, now what?
‣ Get to the ARPA-E Summit in February!
‣ Get involved!
‣ Follow-Up with Me, Ilan, or Russ
– Projects, PIs, Contact Info on Website
20
Questions?
Contact Info:
Amul D. Tevar, ARPA-E Fellow
Ilan Gur, Program Director
Russel Ross, Tech SETA
AMPED Information:
http://arpa-e.energy.gov/
21
Technology
• Ford, Arbin & Sandia National Lab will develop a
commercially viable battery testers with measurement
precision ten times more precise than SOA
High Precision Tester for Automotive
and Stationary Batteries
Ford Motor Company
Mr. Alvaro Masias, Research Engineer
313.418.9606 | [email protected]
Variable Tester Precision
Present Target
Columbic
Efficiency ppm 349 50
Voltage ppm 200 25
Current ppm 200 50
Impact of Improved Precision on Prediction
Technology
• Washington University will create 2D thermal-
electrochemical coupled models with capacity fade
mechanisms integrated into BMS
Optimal Operation and Management of
Energy Storage Systems Based on Real
time Predictive Modeling and Adaptive
Battery Management Techniques
Dr. Venkat Subramanian
314-935-4622
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
Metrics State of the Art Proposed Metric
1D EC model ~1 min ~30 ms
Pseudo 2D EC model 1-2 min ~100 ms
2D Thermal EC coupled ~15 min < 5 s
Models for BMSCircuit based/
Empirical
Detailed 2D,
thermal-EC model
with capacity fade
Technology
• GE will develop an ultrathin sensor array capable of
measuring strain and temperature
• U-M will use multiphysics models for selecting the
critical sensor locations
• Ford will be implementing and testing the sensors
• The program objective is to
demonstrate that the sensor and
controls implemented lead to
increased cell utilization by 20%
Control Enabling Solutions with
Ultrathin Strain and Temperature Sensor
System for Reduced Battery Life Cycle
Cost
General Electric, U. of Michigan, Ford
Aaron J. Knobloch, Senior Scientist
518-387-7355 [email protected]
Performance Targets
Fault Sensing in Operating Batteries
• Battelle and its team member, the University of Akron,
will modify the internal structure of a battery cell to
function as an optical waveguide.
• The operating cell will be monitored continuously for
impending faults, providing sufficient early warning to the
control system.
Technology
Battelle
James Saunders, Research Leader
614 424-3271; [email protected]
Performance Targets
Metric Battelle Target
•Measurement of fault
signatures in a special
fixture.
•Measurement in a
visual cell
•Measurement in a Li-
ion battery
Determine early warning
time of incipient, local
faults before they
become a global event.
Demonstrate calibrated
signal above background
in a test fixture, a visual
cell, and a battery.
cathode
anode
Fiber #2
separator
dendrite
Fiber #1
Optical output altered by dendrite
Technology • LLNL and Yardney are partnering to demonstrate BMS that
utilizes distributed addressable wireless sensors
• Can serve as early indicators of the onset of thermal runaway
and be used to control their operation.
Metrics State-of-Art LLNL-YTP System
Failure detection speed 1x ≥9x
Sensors per cell 0.3 ≥3
Wire-caused failures 1x 0
Sensor comm. protocol wired wireless
Battery Management System with
Distributed Wireless Sensors
Lawrence Livermore National Lab
Dr. Todd M. Bandhauer
Performance Targets
Please contact regarding: R&D Collaboration, Funding
Technology
Heat Conduction in a Li-ion Cell
• The ORNL and Farasis Energy team is developing a
new cell design and temperature control technology for
large format Li-ion cells.
• In-plane cooling and temperature control will be 20-30
times more efficient.
Temperature Self-regulation for Large
Format Li-ion Cells
Oak Ridge National Laboratory
Dr. Hsin Wang, Senior R&D Staff
Tel: (865)576-5074, E-mail:wangh2@@ornl.gov
Performance Targets
Please contact Shaun Gleason ([email protected]) regarding: r&d collaboration, funding, press
Cu
Al
Al
Cu
Measured Thermal Conductivity:
Through thickness ~ 1.5 W/mK
In-plane ~ 30W/mK
A factor of 20 improvement!
Accessing high thermal
conductivity Cu and Al
is the key! Metrics State-of-Art ORNL/Farasis
Maximum Cell Temperature ~45ºC <30ºC (25Ahr 5C Discharge)
Cell cycle life (10% drop) ~1000 cycles ~1250 cycles
Pass safety pinch test ~85-90% SOC 100% SOC
(ORNL/UL)
BACKUP SLIDES
28
29
Metrics
30
Metrics Task #1 Task #2 Task #3
Safety Fault Detection Prevent Runaway
Performance 25% Cost (EV) 2x Revenue 2x Charge Rate
Prognostics Remaining Life
Example – Residual Value
31
Battery Experts Controls Experts
System Design
Diverse Community Needed
32
Po
wer E
xp
erts
D
iag
no
sti
c E
xp
ert
s
