2243671
Cooperative Agreement
Overview
Grant Description
Sbir Phase II: Forecasting Battery Health and Maintenance Using Data-Driven Predictive Analytics -The Broader Impact of This Small Business Innovation Research (SBIR) Phase II Project Includes Enhancing US Economic Competitiveness, Improving the Health and Welfare of the American Public, and Developing the US Technical Workforce.
The Success of This Project Will Have a Direct Impact on the Manufacturers, Integrators, and Operators of Battery-Powered Assets. Empowering Battery Engineering Teams With Predictive Analytics Across Their Product Life Cycle Will Be a Crucial Competitive Advantage to Accelerating the Scale-Up of Domestic Battery Technology Development and Deployment.
Bringing Better Battery Technology to Market Faster and Ensuring a Long, Safe Operating Life Will, in Turn, Catalyze the Transition Away From Fossil Fuels and Towards Electric Vehicles, Grid-Scale Energy Storage, and Other Clean Technologies.
The Social and Economic Implications Include Clean Energy Jobs, Improved Environmental Quality, and Ubiquitous Low-Cost Energy. The Potential Commercial Impact of This Project Will Help Accelerate the Development and Deployment of New Battery-Powered Vehicles, Energy Storage Systems, and Other Assets.
It Will Allow the Company to Serve the Wider Battery Industry by De-Risking Operation and Extending Service Life of Battery Assets, Thereby Increasing Customer Revenue and Avoiding Costly Warranty Events.
This Small Business Innovation Research (SBIR) Phase II Project's Goal Is to De-Risk the Deployment, Operation, and Maintenance of Battery Energy Storage Systems. It Will Combine Results From the Phase I With Data From Partners to Forecast System Maintenance and Inform Warranty Design, Thereby Lowering the Total Cost of Ownership and Minimizing Liability.
Access to Cell Testing, Outgoing Quality Control, and Field Data Will Allow for a Deep Dive Across the Product Life Cycle to Identify How Known Degradation Mechanisms Manifest in the Real-World Battery Data. Physics-Informed Feature Engineering Will Be Used to Extend Models to Incorporate These Insights and Then Implement These Models at Scale in the Cloud.
Criteria for Success Include: 1) Correlating Real-World Operating Conditions With Known Lithium-Ion Battery Degradation Pathways, 2) Engineering New Features That Are Correlated With Physics- and Electrochemical-Based Insights, 3) Accurately Estimating Remaining Useful Life to Within 5% of Total Cycle Life, and 4) Implementing Data-Driven Model in a Scalable Cloud Environment.
This Award Reflects NSF's Statutory Mission and Has Been Deemed Worthy of Support Through Evaluation Using the Foundation's Intellectual Merit and Broader Impacts Review Criteria.- Subawards Are Not Planned for This Award.
The Success of This Project Will Have a Direct Impact on the Manufacturers, Integrators, and Operators of Battery-Powered Assets. Empowering Battery Engineering Teams With Predictive Analytics Across Their Product Life Cycle Will Be a Crucial Competitive Advantage to Accelerating the Scale-Up of Domestic Battery Technology Development and Deployment.
Bringing Better Battery Technology to Market Faster and Ensuring a Long, Safe Operating Life Will, in Turn, Catalyze the Transition Away From Fossil Fuels and Towards Electric Vehicles, Grid-Scale Energy Storage, and Other Clean Technologies.
The Social and Economic Implications Include Clean Energy Jobs, Improved Environmental Quality, and Ubiquitous Low-Cost Energy. The Potential Commercial Impact of This Project Will Help Accelerate the Development and Deployment of New Battery-Powered Vehicles, Energy Storage Systems, and Other Assets.
It Will Allow the Company to Serve the Wider Battery Industry by De-Risking Operation and Extending Service Life of Battery Assets, Thereby Increasing Customer Revenue and Avoiding Costly Warranty Events.
This Small Business Innovation Research (SBIR) Phase II Project's Goal Is to De-Risk the Deployment, Operation, and Maintenance of Battery Energy Storage Systems. It Will Combine Results From the Phase I With Data From Partners to Forecast System Maintenance and Inform Warranty Design, Thereby Lowering the Total Cost of Ownership and Minimizing Liability.
Access to Cell Testing, Outgoing Quality Control, and Field Data Will Allow for a Deep Dive Across the Product Life Cycle to Identify How Known Degradation Mechanisms Manifest in the Real-World Battery Data. Physics-Informed Feature Engineering Will Be Used to Extend Models to Incorporate These Insights and Then Implement These Models at Scale in the Cloud.
Criteria for Success Include: 1) Correlating Real-World Operating Conditions With Known Lithium-Ion Battery Degradation Pathways, 2) Engineering New Features That Are Correlated With Physics- and Electrochemical-Based Insights, 3) Accurately Estimating Remaining Useful Life to Within 5% of Total Cycle Life, and 4) Implementing Data-Driven Model in a Scalable Cloud Environment.
This Award Reflects NSF's Statutory Mission and Has Been Deemed Worthy of Support Through Evaluation Using the Foundation's Intellectual Merit and Broader Impacts Review Criteria.- Subawards Are Not Planned for This Award.
Awardee
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NSF SMALL BUSINESS INNOVATION RESEARCH PHASE II (SBIR)/ SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAMS PHASE II", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF22552
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Seattle,
Washington
98105-4026
United States
Geographic Scope
Single Zip Code
Related Opportunity
22-552
Analysis Notes
Amendment Since initial award the End Date has been extended from 09/30/25 to 03/31/26 and the total obligations have increased 20% from $1,000,000 to $1,197,313.
Astrolabe Analytics was awarded
Cooperative Agreement 2243671
worth $1,197,313
from National Science Foundation in October 2023 with work to be completed primarily in Seattle Washington United States.
The grant
has a duration of 2 years 5 months and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
SBIR Details
Research Type
SBIR Phase II
Title
SBIR Phase II:Forecasting Battery Health and Maintenance using Data-Driven Predictive Analytics
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project includes enhancing US economic competitiveness, improving the health and welfare of the American public, and developing the US technical workforce. The success of this project will have a direct impact on the manufacturers, integrators, and operators of battery-powered assets. Empowering battery engineering teams with predictive analytics across their product life cycle will be a crucial competitive advantage to accelerating the scale-up of domestic battery technology development and deployment. Bringing better battery technology to market faster and ensuring a long, safe operating life will, in turn, catalyze the transition away from fossil fuels and towards electric vehicles, grid-scale energy storage, and other clean technologies. The social and economic implications include clean energy jobs, improved environmental quality, and ubiquitous low-cost energy. The potential commercial impact of this project will help accelerate the development and deployment of new battery-powered vehicles, energy storage systems, and other assets. It will allow the company to serve the wider battery industry by de-risking operation and extending service life of battery assets, thereby increasing customer revenue and avoiding costly warranty events._x000D_ _x000D_ This Small Business Innovation Research (SBIR) Phase II project's goal is to de-risk the deployment, operation, and maintenance of battery energy storage systems. It will combine results from the Phase I with data from partners to forecast system maintenance and inform warranty design, thereby lowering the total cost of ownership and minimizing liability. Access to cell testing, outgoing quality control, and field data will allow for a deep dive across the product life cycle to identify how known degradation mechanisms manifest in the real-world battery data. Physics-informed feature engineering will be used to extend models to incorporate these insights and then implement these models at scale in the cloud. Criteria for success include: 1) correlating real-world operating conditions with known Lithium-ion battery degradation pathways, 2) engineering new features that are correlated with physics- and electrochemical-based insights, 3) accurately estimating remaining useful life to within 5% of total cycle life, and 4) implementing data-driven model in a scalable cloud environment._x000D_ _x000D_ This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Topic Code
AA
Solicitation Number
NSF 22-552
Status
(Ongoing)
Last Modified 12/18/24
Period of Performance
10/1/23
Start Date
3/31/26
End Date
Funding Split
$1.2M
Federal Obligation
$0.0
Non-Federal Obligation
$1.2M
Total Obligated
Activity Timeline
Transaction History
Modifications to 2243671
Additional Detail
Award ID FAIN
2243671
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
T6S1Y4JY4BM7
Awardee CAGE
861W8
Performance District
WA-07
Senators
Maria Cantwell
Patty Murray
Patty Murray
Budget Funding
Federal Account | Budget Subfunction | Object Class | Total | Percentage |
---|---|---|---|---|
Research and Related Activities, National Science Foundation (049-0100) | General science and basic research | Grants, subsidies, and contributions (41.0) | $991,095 | 100% |
Modified: 12/18/24