Apparatus and method for determining state of change (SOC) and state of health (SOH) of electrical cells
Abstract
Systems and methods for prediction of state of charge (SOH), state of health (SOC) and other characteristics of batteries using acoustic signals, includes determining acoustic data at two or more states of charge and determining a reduced acoustic data set representative of the acoustic data at the two or more states of charge. The reduced acoustic data set includes time of flight (TOF) shift, total signal amplitude, or other data points related to the states of charge. Machine learning models use at least the reduced acoustic dataset in conjunction with non-acoustic data such as voltage and temperature for predicting the characteristics of any other independent battery.
- Inventors:
- Issue Date:
- Research Org.:
- Princeton Univ., NJ (United States)
- Sponsoring Org.:
- USDOE Advanced Research Projects Agency - Energy (ARPA-E)
- OSTI Identifier:
- 1651019
- Patent Number(s):
- 10684262
- Application Number:
- 16/150,655
- Assignee:
- The Trustees of Princeton University (Princeton, NJ)
- Patent Classifications (CPCs):
-
G - PHYSICS G01 - MEASURING G01N - INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
Y - NEW / CROSS SECTIONAL TECHNOLOGIES Y02 - TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE Y02E - REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- DOE Contract Number:
- AR0000400
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 10/03/2018
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 25 ENERGY STORAGE
Citation Formats
Steingart, Daniel Artemis, Bhadra, Shoham, Hsieh, Andrew Gaheem, Hertzberg, Benjamin, Gjeltema, Peter James, Rowley, III, Clarence Worth, Goy, Alexandre S. R., and Fleischer, Jason Wolf. Apparatus and method for determining state of change (SOC) and state of health (SOH) of electrical cells. United States: N. p., 2020.
Web.
Steingart, Daniel Artemis, Bhadra, Shoham, Hsieh, Andrew Gaheem, Hertzberg, Benjamin, Gjeltema, Peter James, Rowley, III, Clarence Worth, Goy, Alexandre S. R., & Fleischer, Jason Wolf. Apparatus and method for determining state of change (SOC) and state of health (SOH) of electrical cells. United States.
Steingart, Daniel Artemis, Bhadra, Shoham, Hsieh, Andrew Gaheem, Hertzberg, Benjamin, Gjeltema, Peter James, Rowley, III, Clarence Worth, Goy, Alexandre S. R., and Fleischer, Jason Wolf. Tue .
"Apparatus and method for determining state of change (SOC) and state of health (SOH) of electrical cells". United States. https://www.osti.gov/servlets/purl/1651019.
@article{osti_1651019,
title = {Apparatus and method for determining state of change (SOC) and state of health (SOH) of electrical cells},
author = {Steingart, Daniel Artemis and Bhadra, Shoham and Hsieh, Andrew Gaheem and Hertzberg, Benjamin and Gjeltema, Peter James and Rowley, III, Clarence Worth and Goy, Alexandre S. R. and Fleischer, Jason Wolf},
abstractNote = {Systems and methods for prediction of state of charge (SOH), state of health (SOC) and other characteristics of batteries using acoustic signals, includes determining acoustic data at two or more states of charge and determining a reduced acoustic data set representative of the acoustic data at the two or more states of charge. The reduced acoustic data set includes time of flight (TOF) shift, total signal amplitude, or other data points related to the states of charge. Machine learning models use at least the reduced acoustic dataset in conjunction with non-acoustic data such as voltage and temperature for predicting the characteristics of any other independent battery.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Jun 16 00:00:00 EDT 2020},
month = {Tue Jun 16 00:00:00 EDT 2020}
}
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