GB202020829D0 - Method for predicting condition parameter degradation of a cell - Google Patents
Method for predicting condition parameter degradation of a cellInfo
- Publication number
- GB202020829D0 GB202020829D0 GBGB2020829.4A GB202020829A GB202020829D0 GB 202020829 D0 GB202020829 D0 GB 202020829D0 GB 202020829 A GB202020829 A GB 202020829A GB 202020829 D0 GB202020829 D0 GB 202020829D0
- Authority
- GB
- United Kingdom
- Prior art keywords
- cell
- condition parameter
- parameter degradation
- predicting condition
- predicting
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Ceased
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/392—Determining battery ageing or deterioration, e.g. state of health
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
Priority Applications (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
GBGB2020829.4A GB202020829D0 (en) | 2020-12-31 | 2020-12-31 | Method for predicting condition parameter degradation of a cell |
PCT/GB2021/053437 WO2022144542A1 (en) | 2020-12-31 | 2021-12-24 | Method for predicting condition parameter degradation of a cell |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
GBGB2020829.4A GB202020829D0 (en) | 2020-12-31 | 2020-12-31 | Method for predicting condition parameter degradation of a cell |
Publications (1)
Publication Number | Publication Date |
---|---|
GB202020829D0 true GB202020829D0 (en) | 2021-02-17 |
Family
ID=74566505
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
GBGB2020829.4A Ceased GB202020829D0 (en) | 2020-12-31 | 2020-12-31 | Method for predicting condition parameter degradation of a cell |
Country Status (2)
Country | Link |
---|---|
GB (1) | GB202020829D0 (en) |
WO (1) | WO2022144542A1 (en) |
Families Citing this family (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113839107B (en) * | 2021-09-22 | 2023-03-21 | 北京航空航天大学 | Early warning method for soft package lithium ion battery diving degradation mode |
CN115508711B (en) * | 2022-10-10 | 2023-06-30 | 南京工程学院 | Electric vehicle power lithium battery residual life prediction method based on deep network model |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US11226374B2 (en) * | 2017-10-17 | 2022-01-18 | The Board Of Trustees Of The Leland Stanford Junior University | Data-driven model for lithium-ion battery capacity fade and lifetime prediction |
-
2020
- 2020-12-31 GB GBGB2020829.4A patent/GB202020829D0/en not_active Ceased
-
2021
- 2021-12-24 WO PCT/GB2021/053437 patent/WO2022144542A1/en active Application Filing
Non-Patent Citations (3)
Title |
---|
ATTIA, P. M. ET AL.: "Closed-loop optimization of fast-charging protocols for batteries with machine learning", NATURE, vol. 578, 2020, pages 397 - 402, XP037035978, DOI: 10.1038/s41586-020-1994-5 |
FERMIN, P ET AL.: "Identification and machine learning prediction of knee-point and knee-onset in capacity degradation curves of lithium-ion cells", ENERGY AND AL, 2020, pages 100006, Retrieved from the Internet <URL:https://doi.Org/10.1016/j.egyai.2020.100006> |
SEVERSON, K ET AL.: "Data-driven prediction of battery cycle life before capacity degradation", NATURE ENERGY, vol. 4, 2019, pages 1 - 9 |
Also Published As
Publication number | Publication date |
---|---|
WO2022144542A1 (en) | 2022-07-07 |
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Legal Events
Date | Code | Title | Description |
---|---|---|---|
AT | Applications terminated before publication under section 16(1) |