Data driven health and life prognosis management of supercapacitor and lithium-ion battery storage systems: Developments, implementation aspects, limitations, and future directions
Health and life prognosis research contributes to the development of next-generation energy storage solutions with enhanced performance, longer lifespans, and improved sustainability. Nonetheless, energy storage systems experience a range of deterioration processes over time, such as chemical reacti...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Other Authors: | |
| Format: | Review |
| Published: |
Elsevier Ltd
2025
|
| Subjects: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1833410239643254784 |
|---|---|
| author | Hossain Lipu M.S. Rahman M.S.A. Mansor M. Rahman T. Ansari S. Fuad A.M. Hannan M.A. |
| author2 | 58562396100 |
| author_facet | 58562396100 Hossain Lipu M.S. Rahman M.S.A. Mansor M. Rahman T. Ansari S. Fuad A.M. Hannan M.A. |
| author_sort | Hossain Lipu M.S. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Health and life prognosis research contributes to the development of next-generation energy storage solutions with enhanced performance, longer lifespans, and improved sustainability. Nonetheless, energy storage systems experience a range of deterioration processes over time, such as chemical reactions, mechanical strain, and degradation of electrode materials, posing difficulties in precise modeling and prediction. Additionally, the performance of energy storage systems can be influenced by factors such as temperature, operating conditions, and usage patterns, further complicating prognosis accuracy. In this paper, the developments made in the field of data-driven health and life prognosis management with regard to state of health (SOH) and remaining useful life (RUL) of supercapacitor and lithium-ion battery storage systems has been reviewed. Accordingly, this paper investigates the advancements in the SOH and RUL estimation of supercapacitors and lithium-ion battery storage systems through data-driven approaches involves analyzing significant findings, contributions, benefits, drawbacks, and research gaps. Moreover, the various implementation aspects of these approaches, including data processing, feature extraction, computation capacity, experiments, and validation are discussed. In addition, the paper outlines the limitations and challenges of data-driven approaches for assessing the SOH and RUL of supercapacitor and lithium-ion battery storage systems, as well as proposing future research paths and opportunities aimed at improving this prognosis using data-driven methods. Overall, data-driven approaches empower precise SOH estimation and RUL prognosis, significantly contributing to reliability, efficiency, and cost-effectiveness in for diverse energy storage needs. ? 2024 Elsevier Ltd |
| format | Review |
| id | my.uniten.dspace-36305 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2025 |
| publisher | Elsevier Ltd |
| record_format | dspace |
| spelling | my.uniten.dspace-363052025-03-03T15:41:52Z Data driven health and life prognosis management of supercapacitor and lithium-ion battery storage systems: Developments, implementation aspects, limitations, and future directions Hossain Lipu M.S. Rahman M.S.A. Mansor M. Rahman T. Ansari S. Fuad A.M. Hannan M.A. 58562396100 58811982000 6701749037 57912369500 57218906707 58010487300 7103014445 Battery management systems Cost effectiveness Data handling Deterioration Digital storage Energy storage Information management Ions Storage management Supercapacitor Battery storage system Data driven Data-driven approach Energy Health and life prognose management Implementation aspects Performance Remaining useful lives State of health Storage systems Lithium-ion batteries Health and life prognosis research contributes to the development of next-generation energy storage solutions with enhanced performance, longer lifespans, and improved sustainability. Nonetheless, energy storage systems experience a range of deterioration processes over time, such as chemical reactions, mechanical strain, and degradation of electrode materials, posing difficulties in precise modeling and prediction. Additionally, the performance of energy storage systems can be influenced by factors such as temperature, operating conditions, and usage patterns, further complicating prognosis accuracy. In this paper, the developments made in the field of data-driven health and life prognosis management with regard to state of health (SOH) and remaining useful life (RUL) of supercapacitor and lithium-ion battery storage systems has been reviewed. Accordingly, this paper investigates the advancements in the SOH and RUL estimation of supercapacitors and lithium-ion battery storage systems through data-driven approaches involves analyzing significant findings, contributions, benefits, drawbacks, and research gaps. Moreover, the various implementation aspects of these approaches, including data processing, feature extraction, computation capacity, experiments, and validation are discussed. In addition, the paper outlines the limitations and challenges of data-driven approaches for assessing the SOH and RUL of supercapacitor and lithium-ion battery storage systems, as well as proposing future research paths and opportunities aimed at improving this prognosis using data-driven methods. Overall, data-driven approaches empower precise SOH estimation and RUL prognosis, significantly contributing to reliability, efficiency, and cost-effectiveness in for diverse energy storage needs. ? 2024 Elsevier Ltd Final 2025-03-03T07:41:52Z 2025-03-03T07:41:52Z 2024 Review 10.1016/j.est.2024.113172 2-s2.0-85200540481 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200540481&doi=10.1016%2fj.est.2024.113172&partnerID=40&md5=2b2121d02b4b93c610ad94bd792dc765 https://irepository.uniten.edu.my/handle/123456789/36305 98 113172 Elsevier Ltd Scopus |
| spellingShingle | Battery management systems Cost effectiveness Data handling Deterioration Digital storage Energy storage Information management Ions Storage management Supercapacitor Battery storage system Data driven Data-driven approach Energy Health and life prognose management Implementation aspects Performance Remaining useful lives State of health Storage systems Lithium-ion batteries Hossain Lipu M.S. Rahman M.S.A. Mansor M. Rahman T. Ansari S. Fuad A.M. Hannan M.A. Data driven health and life prognosis management of supercapacitor and lithium-ion battery storage systems: Developments, implementation aspects, limitations, and future directions |
| title | Data driven health and life prognosis management of supercapacitor and lithium-ion battery storage systems: Developments, implementation aspects, limitations, and future directions |
| title_full | Data driven health and life prognosis management of supercapacitor and lithium-ion battery storage systems: Developments, implementation aspects, limitations, and future directions |
| title_fullStr | Data driven health and life prognosis management of supercapacitor and lithium-ion battery storage systems: Developments, implementation aspects, limitations, and future directions |
| title_full_unstemmed | Data driven health and life prognosis management of supercapacitor and lithium-ion battery storage systems: Developments, implementation aspects, limitations, and future directions |
| title_short | Data driven health and life prognosis management of supercapacitor and lithium-ion battery storage systems: Developments, implementation aspects, limitations, and future directions |
| title_sort | data driven health and life prognosis management of supercapacitor and lithium-ion battery storage systems: developments, implementation aspects, limitations, and future directions |
| topic | Battery management systems Cost effectiveness Data handling Deterioration Digital storage Energy storage Information management Ions Storage management Supercapacitor Battery storage system Data driven Data-driven approach Energy Health and life prognose management Implementation aspects Performance Remaining useful lives State of health Storage systems Lithium-ion batteries |
| url_provider | http://dspace.uniten.edu.my/ |