Prediction of remaining useful life for lithium‐ion battery based on particle filter with residual resampling Article Swipe
Chaofeng Pan
,
Aibao Huang
,
Zhigang He
,
Chunjing Lin
,
Yanyan Sun
,
Shichao Zhao
,
Limei Wang
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1002/ese3.877
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1002/ese3.877
Accurate prediction of the remaining useful life for lithium‐ion battery is beneficial to prolong the life of the battery and increase safety. With the capacity degradation curve obtained from the data of the battery charge and discharge experiment, the remaining useful life of the battery was predicted by using particle filter. In order to improve the prediction accuracy, the particle filter with residual resampling method is used to overcome the lack of particle diversity which has an important effect on the accuracy of state estimation. Compared with the prediction result of the extended Kalman filter, it was found that the precision and stability of particle filter are better than those of extended Kalman filter. The research results presented in this paper provide some suggestions for the health monitoring of power battery for electric vehicles.
Related Topics
Concepts
Battery (electricity)
Residual
Particle filter
Resampling
State of health
Kalman filter
State of charge
Lithium-ion battery
Stability (learning theory)
Extended Kalman filter
Control theory (sociology)
Particle (ecology)
Power (physics)
Computer science
Automotive engineering
Engineering
Algorithm
Artificial intelligence
Machine learning
Physics
Geology
Quantum mechanics
Oceanography
Control (management)
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/ese3.877
- OA Status
- gold
- Cited By
- 32
- References
- 22
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3134333923
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3134333923Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1002/ese3.877Digital Object Identifier
- Title
-
Prediction of remaining useful life for lithium‐ion battery based on particle filter with residual resamplingWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-03-04Full publication date if available
- Authors
-
Chaofeng Pan, Aibao Huang, Zhigang He, Chunjing Lin, Yanyan Sun, Shichao Zhao, Limei WangList of authors in order
- Landing page
-
https://doi.org/10.1002/ese3.877Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1002/ese3.877Direct OA link when available
- Concepts
-
Battery (electricity), Residual, Particle filter, Resampling, State of health, Kalman filter, State of charge, Lithium-ion battery, Stability (learning theory), Extended Kalman filter, Control theory (sociology), Particle (ecology), Power (physics), Computer science, Automotive engineering, Engineering, Algorithm, Artificial intelligence, Machine learning, Physics, Geology, Quantum mechanics, Oceanography, Control (management)Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
32Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 8, 2024: 5, 2023: 6, 2022: 10, 2021: 3Per-year citation counts (last 5 years)
- References (count)
-
22Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W3134333923 |
|---|---|
| doi | https://doi.org/10.1002/ese3.877 |
| ids.doi | https://doi.org/10.1002/ese3.877 |
| ids.mag | 3134333923 |
| ids.openalex | https://openalex.org/W3134333923 |
| fwci | 2.39715949 |
| type | article |
| title | Prediction of remaining useful life for lithium‐ion battery based on particle filter with residual resampling |
| awards[0].id | https://openalex.org/G3260453067 |
| awards[0].funder_id | https://openalex.org/F4320322769 |
| awards[0].display_name | |
| awards[0].funder_award_id | BK20171300 |
| awards[0].funder_display_name | Natural Science Foundation of Jiangsu Province |
| biblio.issue | 8 |
| biblio.volume | 9 |
| biblio.last_page | 1133 |
| biblio.first_page | 1115 |
| topics[0].id | https://openalex.org/T10663 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 1.0 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2203 |
| topics[0].subfield.display_name | Automotive Engineering |
| topics[0].display_name | Advanced Battery Technologies Research |
| topics[1].id | https://openalex.org/T10018 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.9721999764442444 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2208 |
| topics[1].subfield.display_name | Electrical and Electronic Engineering |
| topics[1].display_name | Advancements in Battery Materials |
| topics[2].id | https://openalex.org/T10876 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.9634000062942505 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2207 |
| topics[2].subfield.display_name | Control and Systems Engineering |
| topics[2].display_name | Fault Detection and Control Systems |
| funders[0].id | https://openalex.org/F4320322769 |
| funders[0].ror | https://ror.org/01h0zpd94 |
| funders[0].display_name | Natural Science Foundation of Jiangsu Province |
| is_xpac | False |
| apc_list.value | 1875 |
| apc_list.currency | USD |
| apc_list.value_usd | 1875 |
| apc_paid.value | 1875 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 1875 |
| concepts[0].id | https://openalex.org/C555008776 |
| concepts[0].level | 3 |
| concepts[0].score | 0.7488349080085754 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q267298 |
| concepts[0].display_name | Battery (electricity) |
| concepts[1].id | https://openalex.org/C155512373 |
| concepts[1].level | 2 |
| concepts[1].score | 0.7380996346473694 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q287450 |
| concepts[1].display_name | Residual |
| concepts[2].id | https://openalex.org/C52421305 |
| concepts[2].level | 3 |
| concepts[2].score | 0.7170333862304688 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q1151499 |
| concepts[2].display_name | Particle filter |
| concepts[3].id | https://openalex.org/C150921843 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5892051458358765 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q1170431 |
| concepts[3].display_name | Resampling |
| concepts[4].id | https://openalex.org/C2777294910 |
| concepts[4].level | 4 |
| concepts[4].score | 0.5459290742874146 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q4050070 |
| concepts[4].display_name | State of health |
| concepts[5].id | https://openalex.org/C157286648 |
| concepts[5].level | 2 |
| concepts[5].score | 0.5440593957901001 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q846780 |
| concepts[5].display_name | Kalman filter |
| concepts[6].id | https://openalex.org/C2776582896 |
| concepts[6].level | 4 |
| concepts[6].score | 0.5175089836120605 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q5368536 |
| concepts[6].display_name | State of charge |
| concepts[7].id | https://openalex.org/C2779197387 |
| concepts[7].level | 4 |
| concepts[7].score | 0.5174975395202637 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q2822895 |
| concepts[7].display_name | Lithium-ion battery |
| concepts[8].id | https://openalex.org/C112972136 |
| concepts[8].level | 2 |
| concepts[8].score | 0.4897603988647461 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q7595718 |
| concepts[8].display_name | Stability (learning theory) |
| concepts[9].id | https://openalex.org/C206833254 |
| concepts[9].level | 3 |
| concepts[9].score | 0.4841078519821167 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q5421817 |
| concepts[9].display_name | Extended Kalman filter |
| concepts[10].id | https://openalex.org/C47446073 |
| concepts[10].level | 3 |
| concepts[10].score | 0.43783900141716003 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q5165890 |
| concepts[10].display_name | Control theory (sociology) |
| concepts[11].id | https://openalex.org/C2778517922 |
| concepts[11].level | 2 |
| concepts[11].score | 0.4369845390319824 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q7140482 |
| concepts[11].display_name | Particle (ecology) |
| concepts[12].id | https://openalex.org/C163258240 |
| concepts[12].level | 2 |
| concepts[12].score | 0.40013939142227173 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q25342 |
| concepts[12].display_name | Power (physics) |
| concepts[13].id | https://openalex.org/C41008148 |
| concepts[13].level | 0 |
| concepts[13].score | 0.39583301544189453 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[13].display_name | Computer science |
| concepts[14].id | https://openalex.org/C171146098 |
| concepts[14].level | 1 |
| concepts[14].score | 0.3566538691520691 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q124192 |
| concepts[14].display_name | Automotive engineering |
| concepts[15].id | https://openalex.org/C127413603 |
| concepts[15].level | 0 |
| concepts[15].score | 0.2803446054458618 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[15].display_name | Engineering |
| concepts[16].id | https://openalex.org/C11413529 |
| concepts[16].level | 1 |
| concepts[16].score | 0.20666363835334778 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[16].display_name | Algorithm |
| concepts[17].id | https://openalex.org/C154945302 |
| concepts[17].level | 1 |
| concepts[17].score | 0.14958789944648743 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[17].display_name | Artificial intelligence |
| concepts[18].id | https://openalex.org/C119857082 |
| concepts[18].level | 1 |
| concepts[18].score | 0.08751240372657776 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q2539 |
| concepts[18].display_name | Machine learning |
| concepts[19].id | https://openalex.org/C121332964 |
| concepts[19].level | 0 |
| concepts[19].score | 0.08383077383041382 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[19].display_name | Physics |
| concepts[20].id | https://openalex.org/C127313418 |
| concepts[20].level | 0 |
| concepts[20].score | 0.0 |
| concepts[20].wikidata | https://www.wikidata.org/wiki/Q1069 |
| concepts[20].display_name | Geology |
| concepts[21].id | https://openalex.org/C62520636 |
| concepts[21].level | 1 |
| concepts[21].score | 0.0 |
| concepts[21].wikidata | https://www.wikidata.org/wiki/Q944 |
| concepts[21].display_name | Quantum mechanics |
| concepts[22].id | https://openalex.org/C111368507 |
| concepts[22].level | 1 |
| concepts[22].score | 0.0 |
| concepts[22].wikidata | https://www.wikidata.org/wiki/Q43518 |
| concepts[22].display_name | Oceanography |
| concepts[23].id | https://openalex.org/C2775924081 |
| concepts[23].level | 2 |
| concepts[23].score | 0.0 |
| concepts[23].wikidata | https://www.wikidata.org/wiki/Q55608371 |
| concepts[23].display_name | Control (management) |
| keywords[0].id | https://openalex.org/keywords/battery |
| keywords[0].score | 0.7488349080085754 |
| keywords[0].display_name | Battery (electricity) |
| keywords[1].id | https://openalex.org/keywords/residual |
| keywords[1].score | 0.7380996346473694 |
| keywords[1].display_name | Residual |
| keywords[2].id | https://openalex.org/keywords/particle-filter |
| keywords[2].score | 0.7170333862304688 |
| keywords[2].display_name | Particle filter |
| keywords[3].id | https://openalex.org/keywords/resampling |
| keywords[3].score | 0.5892051458358765 |
| keywords[3].display_name | Resampling |
| keywords[4].id | https://openalex.org/keywords/state-of-health |
| keywords[4].score | 0.5459290742874146 |
| keywords[4].display_name | State of health |
| keywords[5].id | https://openalex.org/keywords/kalman-filter |
| keywords[5].score | 0.5440593957901001 |
| keywords[5].display_name | Kalman filter |
| keywords[6].id | https://openalex.org/keywords/state-of-charge |
| keywords[6].score | 0.5175089836120605 |
| keywords[6].display_name | State of charge |
| keywords[7].id | https://openalex.org/keywords/lithium-ion-battery |
| keywords[7].score | 0.5174975395202637 |
| keywords[7].display_name | Lithium-ion battery |
| keywords[8].id | https://openalex.org/keywords/stability |
| keywords[8].score | 0.4897603988647461 |
| keywords[8].display_name | Stability (learning theory) |
| keywords[9].id | https://openalex.org/keywords/extended-kalman-filter |
| keywords[9].score | 0.4841078519821167 |
| keywords[9].display_name | Extended Kalman filter |
| keywords[10].id | https://openalex.org/keywords/control-theory |
| keywords[10].score | 0.43783900141716003 |
| keywords[10].display_name | Control theory (sociology) |
| keywords[11].id | https://openalex.org/keywords/particle |
| keywords[11].score | 0.4369845390319824 |
| keywords[11].display_name | Particle (ecology) |
| keywords[12].id | https://openalex.org/keywords/power |
| keywords[12].score | 0.40013939142227173 |
| keywords[12].display_name | Power (physics) |
| keywords[13].id | https://openalex.org/keywords/computer-science |
| keywords[13].score | 0.39583301544189453 |
| keywords[13].display_name | Computer science |
| keywords[14].id | https://openalex.org/keywords/automotive-engineering |
| keywords[14].score | 0.3566538691520691 |
| keywords[14].display_name | Automotive engineering |
| keywords[15].id | https://openalex.org/keywords/engineering |
| keywords[15].score | 0.2803446054458618 |
| keywords[15].display_name | Engineering |
| keywords[16].id | https://openalex.org/keywords/algorithm |
| keywords[16].score | 0.20666363835334778 |
| keywords[16].display_name | Algorithm |
| keywords[17].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[17].score | 0.14958789944648743 |
| keywords[17].display_name | Artificial intelligence |
| keywords[18].id | https://openalex.org/keywords/machine-learning |
| keywords[18].score | 0.08751240372657776 |
| keywords[18].display_name | Machine learning |
| keywords[19].id | https://openalex.org/keywords/physics |
| keywords[19].score | 0.08383077383041382 |
| keywords[19].display_name | Physics |
| language | en |
| locations[0].id | doi:10.1002/ese3.877 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S2737327489 |
| locations[0].source.issn | 2050-0505 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2050-0505 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Energy Science & Engineering |
| locations[0].source.host_organization | https://openalex.org/P4310320595 |
| locations[0].source.host_organization_name | Wiley |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310320595 |
| locations[0].source.host_organization_lineage_names | Wiley |
| locations[0].license | cc-by |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Energy Science & Engineering |
| locations[0].landing_page_url | https://doi.org/10.1002/ese3.877 |
| locations[1].id | pmh:oai:doaj.org/article:7fa7d9226c374438b27d49ab94a25800 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306401280 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[1].source.host_organization | |
| locations[1].source.host_organization_name | |
| locations[1].license | cc-by-sa |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | article |
| locations[1].license_id | https://openalex.org/licenses/cc-by-sa |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | Energy Science & Engineering, Vol 9, Iss 8, Pp 1115-1133 (2021) |
| locations[1].landing_page_url | https://doaj.org/article/7fa7d9226c374438b27d49ab94a25800 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5032415040 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-2185-7970 |
| authorships[0].author.display_name | Chaofeng Pan |
| authorships[0].countries | CN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I115592961 |
| authorships[0].affiliations[0].raw_affiliation_string | Automotive engineering research institute, Jiangsu University, Zhenjiang, China |
| authorships[0].institutions[0].id | https://openalex.org/I115592961 |
| authorships[0].institutions[0].ror | https://ror.org/03jc41j30 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I115592961 |
| authorships[0].institutions[0].country_code | CN |
| authorships[0].institutions[0].display_name | Jiangsu University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Chaofeng Pan |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Automotive engineering research institute, Jiangsu University, Zhenjiang, China |
| authorships[1].author.id | https://openalex.org/A5090653805 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-1320-9597 |
| authorships[1].author.display_name | Aibao Huang |
| authorships[1].countries | CN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I115592961 |
| authorships[1].affiliations[0].raw_affiliation_string | Automotive engineering research institute, Jiangsu University, Zhenjiang, China |
| authorships[1].institutions[0].id | https://openalex.org/I115592961 |
| authorships[1].institutions[0].ror | https://ror.org/03jc41j30 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I115592961 |
| authorships[1].institutions[0].country_code | CN |
| authorships[1].institutions[0].display_name | Jiangsu University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Aibao Huang |
| authorships[1].is_corresponding | True |
| authorships[1].raw_affiliation_strings | Automotive engineering research institute, Jiangsu University, Zhenjiang, China |
| authorships[2].author.id | https://openalex.org/A5101142438 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | Zhigang He |
| authorships[2].countries | CN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I115592961 |
| authorships[2].affiliations[0].raw_affiliation_string | College of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang, China |
| authorships[2].institutions[0].id | https://openalex.org/I115592961 |
| authorships[2].institutions[0].ror | https://ror.org/03jc41j30 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I115592961 |
| authorships[2].institutions[0].country_code | CN |
| authorships[2].institutions[0].display_name | Jiangsu University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Zhigang He |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | College of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang, China |
| authorships[3].author.id | https://openalex.org/A5102368178 |
| authorships[3].author.orcid | |
| authorships[3].author.display_name | Chunjing Lin |
| authorships[3].countries | CN |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I4210094894 |
| authorships[3].affiliations[0].raw_affiliation_string | China Automotive Technology and Research Center Co., Ltd., Tianjin, China |
| authorships[3].institutions[0].id | https://openalex.org/I4210094894 |
| authorships[3].institutions[0].ror | https://ror.org/00r5r6807 |
| authorships[3].institutions[0].type | other |
| authorships[3].institutions[0].lineage | https://openalex.org/I4210094894 |
| authorships[3].institutions[0].country_code | CN |
| authorships[3].institutions[0].display_name | China Automotive Technology and Research Center |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Chunjing Lin |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | China Automotive Technology and Research Center Co., Ltd., Tianjin, China |
| authorships[4].author.id | https://openalex.org/A5086124785 |
| authorships[4].author.orcid | https://orcid.org/0009-0005-0378-823X |
| authorships[4].author.display_name | Yanyan Sun |
| authorships[4].countries | CN |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I4210124559 |
| authorships[4].affiliations[0].raw_affiliation_string | Zhengzhou Yutong Bus Co. Ltd., Zhenjiang, China |
| authorships[4].institutions[0].id | https://openalex.org/I4210124559 |
| authorships[4].institutions[0].ror | https://ror.org/02shrfh49 |
| authorships[4].institutions[0].type | company |
| authorships[4].institutions[0].lineage | https://openalex.org/I4210124559 |
| authorships[4].institutions[0].country_code | CN |
| authorships[4].institutions[0].display_name | Yutong (China) |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Yanyan Sun |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Zhengzhou Yutong Bus Co. Ltd., Zhenjiang, China |
| authorships[5].author.id | https://openalex.org/A5041046693 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-6170-7072 |
| authorships[5].author.display_name | Shichao Zhao |
| authorships[5].countries | CN |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I4210124559 |
| authorships[5].affiliations[0].raw_affiliation_string | Zhengzhou Yutong Bus Co. Ltd., Zhenjiang, China |
| authorships[5].institutions[0].id | https://openalex.org/I4210124559 |
| authorships[5].institutions[0].ror | https://ror.org/02shrfh49 |
| authorships[5].institutions[0].type | company |
| authorships[5].institutions[0].lineage | https://openalex.org/I4210124559 |
| authorships[5].institutions[0].country_code | CN |
| authorships[5].institutions[0].display_name | Yutong (China) |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Shichao Zhao |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | Zhengzhou Yutong Bus Co. Ltd., Zhenjiang, China |
| authorships[6].author.id | https://openalex.org/A5100695797 |
| authorships[6].author.orcid | https://orcid.org/0000-0001-7166-5278 |
| authorships[6].author.display_name | Limei Wang |
| authorships[6].countries | CN |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I115592961 |
| authorships[6].affiliations[0].raw_affiliation_string | Automotive engineering research institute, Jiangsu University, Zhenjiang, China |
| authorships[6].institutions[0].id | https://openalex.org/I115592961 |
| authorships[6].institutions[0].ror | https://ror.org/03jc41j30 |
| authorships[6].institutions[0].type | education |
| authorships[6].institutions[0].lineage | https://openalex.org/I115592961 |
| authorships[6].institutions[0].country_code | CN |
| authorships[6].institutions[0].display_name | Jiangsu University |
| authorships[6].author_position | last |
| authorships[6].raw_author_name | Limei Wang |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | Automotive engineering research institute, Jiangsu University, Zhenjiang, China |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.1002/ese3.877 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Prediction of remaining useful life for lithium‐ion battery based on particle filter with residual resampling |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10663 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 1.0 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2203 |
| primary_topic.subfield.display_name | Automotive Engineering |
| primary_topic.display_name | Advanced Battery Technologies Research |
| related_works | https://openalex.org/W2927378857, https://openalex.org/W2406829934, https://openalex.org/W2801696468, https://openalex.org/W2162253570, https://openalex.org/W1824810860, https://openalex.org/W2138381686, https://openalex.org/W1583020711, https://openalex.org/W1486580556, https://openalex.org/W3144709167, https://openalex.org/W2010934810 |
| cited_by_count | 32 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 8 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 5 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 6 |
| counts_by_year[3].year | 2022 |
| counts_by_year[3].cited_by_count | 10 |
| counts_by_year[4].year | 2021 |
| counts_by_year[4].cited_by_count | 3 |
| locations_count | 2 |
| best_oa_location.id | doi:10.1002/ese3.877 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S2737327489 |
| best_oa_location.source.issn | 2050-0505 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2050-0505 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Energy Science & Engineering |
| best_oa_location.source.host_organization | https://openalex.org/P4310320595 |
| best_oa_location.source.host_organization_name | Wiley |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310320595 |
| best_oa_location.source.host_organization_lineage_names | Wiley |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Energy Science & Engineering |
| best_oa_location.landing_page_url | https://doi.org/10.1002/ese3.877 |
| primary_location.id | doi:10.1002/ese3.877 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S2737327489 |
| primary_location.source.issn | 2050-0505 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2050-0505 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Energy Science & Engineering |
| primary_location.source.host_organization | https://openalex.org/P4310320595 |
| primary_location.source.host_organization_name | Wiley |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320595 |
| primary_location.source.host_organization_lineage_names | Wiley |
| primary_location.license | cc-by |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Energy Science & Engineering |
| primary_location.landing_page_url | https://doi.org/10.1002/ese3.877 |
| publication_date | 2021-03-04 |
| publication_year | 2021 |
| referenced_works | https://openalex.org/W2905277589, https://openalex.org/W2796379873, https://openalex.org/W2085942406, https://openalex.org/W2994638732, https://openalex.org/W3022412239, https://openalex.org/W2064175677, https://openalex.org/W2906328214, https://openalex.org/W2908039736, https://openalex.org/W2336223670, https://openalex.org/W2056207828, https://openalex.org/W2589111654, https://openalex.org/W2883525675, https://openalex.org/W2096947102, https://openalex.org/W1628954589, https://openalex.org/W2768463855, https://openalex.org/W2038012452, https://openalex.org/W2165344987, https://openalex.org/W2759525351, https://openalex.org/W2012734651, https://openalex.org/W2007655149, https://openalex.org/W2078279667, https://openalex.org/W4249919990 |
| referenced_works_count | 22 |
| abstract_inverted_index.In | 52 |
| abstract_inverted_index.an | 77 |
| abstract_inverted_index.by | 48 |
| abstract_inverted_index.in | 119 |
| abstract_inverted_index.is | 11, 66 |
| abstract_inverted_index.it | 96 |
| abstract_inverted_index.of | 3, 17, 32, 43, 72, 83, 91, 104, 111, 129 |
| abstract_inverted_index.on | 80 |
| abstract_inverted_index.to | 13, 54, 68 |
| abstract_inverted_index.The | 115 |
| abstract_inverted_index.and | 20, 36, 102 |
| abstract_inverted_index.are | 107 |
| abstract_inverted_index.for | 8, 125, 132 |
| abstract_inverted_index.has | 76 |
| abstract_inverted_index.the | 4, 15, 18, 24, 30, 33, 39, 44, 56, 59, 70, 81, 88, 92, 100, 126 |
| abstract_inverted_index.was | 46, 97 |
| abstract_inverted_index.With | 23 |
| abstract_inverted_index.data | 31 |
| abstract_inverted_index.from | 29 |
| abstract_inverted_index.lack | 71 |
| abstract_inverted_index.life | 7, 16, 42 |
| abstract_inverted_index.some | 123 |
| abstract_inverted_index.than | 109 |
| abstract_inverted_index.that | 99 |
| abstract_inverted_index.this | 120 |
| abstract_inverted_index.used | 67 |
| abstract_inverted_index.with | 62, 87 |
| abstract_inverted_index.curve | 27 |
| abstract_inverted_index.found | 98 |
| abstract_inverted_index.order | 53 |
| abstract_inverted_index.paper | 121 |
| abstract_inverted_index.power | 130 |
| abstract_inverted_index.state | 84 |
| abstract_inverted_index.those | 110 |
| abstract_inverted_index.using | 49 |
| abstract_inverted_index.which | 75 |
| abstract_inverted_index.Kalman | 94, 113 |
| abstract_inverted_index.better | 108 |
| abstract_inverted_index.charge | 35 |
| abstract_inverted_index.effect | 79 |
| abstract_inverted_index.filter | 61, 106 |
| abstract_inverted_index.health | 127 |
| abstract_inverted_index.method | 65 |
| abstract_inverted_index.result | 90 |
| abstract_inverted_index.useful | 6, 41 |
| abstract_inverted_index.battery | 10, 19, 34, 45, 131 |
| abstract_inverted_index.filter, | 95 |
| abstract_inverted_index.filter. | 51, 114 |
| abstract_inverted_index.improve | 55 |
| abstract_inverted_index.prolong | 14 |
| abstract_inverted_index.provide | 122 |
| abstract_inverted_index.results | 117 |
| abstract_inverted_index.safety. | 22 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Accurate | 1 |
| abstract_inverted_index.Compared | 86 |
| abstract_inverted_index.accuracy | 82 |
| abstract_inverted_index.capacity | 25 |
| abstract_inverted_index.electric | 133 |
| abstract_inverted_index.extended | 93, 112 |
| abstract_inverted_index.increase | 21 |
| abstract_inverted_index.obtained | 28 |
| abstract_inverted_index.overcome | 69 |
| abstract_inverted_index.particle | 50, 60, 73, 105 |
| abstract_inverted_index.research | 116 |
| abstract_inverted_index.residual | 63 |
| abstract_inverted_index.accuracy, | 58 |
| abstract_inverted_index.discharge | 37 |
| abstract_inverted_index.diversity | 74 |
| abstract_inverted_index.important | 78 |
| abstract_inverted_index.precision | 101 |
| abstract_inverted_index.predicted | 47 |
| abstract_inverted_index.presented | 118 |
| abstract_inverted_index.remaining | 5, 40 |
| abstract_inverted_index.stability | 103 |
| abstract_inverted_index.vehicles. | 134 |
| abstract_inverted_index.beneficial | 12 |
| abstract_inverted_index.monitoring | 128 |
| abstract_inverted_index.prediction | 2, 57, 89 |
| abstract_inverted_index.resampling | 64 |
| abstract_inverted_index.degradation | 26 |
| abstract_inverted_index.estimation. | 85 |
| abstract_inverted_index.experiment, | 38 |
| abstract_inverted_index.suggestions | 124 |
| abstract_inverted_index.lithium‐ion | 9 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 95 |
| corresponding_author_ids | https://openalex.org/A5090653805 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 7 |
| corresponding_institution_ids | https://openalex.org/I115592961 |
| citation_normalized_percentile.value | 0.8697536 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |