Maximize Battery Performance and Lifetime Using Big Data

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Maximize Battery Performance and
Lifetime Using Big Data
Tal Sholklapper, PhD
CEO and Co-Founder
tal@voltaiq.io
8/7/2015
Voltaiq is the platform for data-driven product
development and optimization for energy storage
and mobile power
R&D
Manufacturing
Integration
Operation
Voltaiq: Get battery products to market
faster and cheaper
• Real-time interactive access to
all battery data
Find
files
USB
transfer
Repeat per
plot type
Repeat
per test
Voltaiq UI
CSV
export
Repeat per
data type
Export
plot
Spreadsheet
import
Plot
Share
results
Cut and
paste
Find
data
vs.
Analyz
e data
• Save 5-20 hours per engineer,
per week ($25k - $100k per
engineer annually)
The battery integration challenge
•
•
•
•
•
•
•
Capacity
Power
Price
Volume
Weight
Safety
Lifetime
Longer warranties have created
new challenges
Auto / Grid
Capacity (Ah)
Consumer
Variation
1
3
2
Lifetime (Years)
4
Source: T. Baumhofer et. Al. / Journal of Power Sources 247 (2014) 332-338
How do we unlock the potential of
batteries?
• We need to better understand batteries
• We have the data, but we need to make
better use of it
Integration testing
Source: arbin.com
Field monitoring and analytics
Source: AES
Why does most battery data go underanalyzed?
Too many files, too many formats
Lousy analysis tools
Data isn’t shared across the industry value chain
R&D
Manufacturing
Integration
Field
Voltaiq: Helping you unlock the hidden insight in
your data
Observe degradation in-situ
From raw time-series
current and voltage…
Month 6
voltage
Month 3
current
one cycle
proprietary
analytics
Predict failure
Top-line stats don’t cut it
Voltaiq algorithms spot
early signs of failure
All plots generated directly in Voltaiq
using built-in analytics
Predictive analytics built in
Use Voltaiq to spot degradation sooner
No indication of cell degradation
prior to drop in capacity
Sudden drop in
capacity
Internal resistance begins to
trend upward after cycle 250
Predictive analytics enhanced
Observe degradation directly using features
extracted from time-series data
Charge
Discharge
*Peak position indicates internal resistance; peak height indicates electrode capacity
Capacity (mAh)
Voltaiq utilizes aggregate data to optimize
how you operate your batteries
Nearly 3x the specified
cycle life!
Manuf. spec
cycle life
Failure line
Cycle Number
Voltaiq is the software platform to make sure you
get the most out of your batteries
R&D
Accelerate
development
QC
Optimize system
design &
performance
Integration
Reduce total cost
of ownership
Operation
Ensure reliability
& minimize
warranty Risks
Thank you!
Tal Sholklapper
E: tal@voltaiq.io
O: 646-586-3062
Market demands require developers to maximize
battery performance while also meeting exacting
warrantied lifetimes, now often measured in multiple
years and many thousands of cycles. However,
battery lifetimes are still poorly understood, exposing
organizations to excessive liability. In this
presentation, we will highlight how to harness data
collected across the battery lifecycle, from
integration testing to real work use, using machine
learning algorithms to optimize both performance
and lifetime and minimize product liabilities.
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