Modeling and simulation of high energy density lithium-ion battery for multiple fault detection
Abstract Lithium-ion battery, a high energy density storage device has extensive applications in electrical and electronic gadgets, computers, hybrid electric vehicles, and electric vehicles. This paper presents multiple fault detection of lithium-ion battery using two non-linear Kalman filters. A d...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-06-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-13771-4 |
| _version_ | 1811343698243354624 |
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| author | Chandrani Sadhukhan Swarup Kumar Mitra Suvanjan Bhattacharyya Eydhah Almatrafi Bahaa Saleh Mrinal Kanti Naskar |
| author_facet | Chandrani Sadhukhan Swarup Kumar Mitra Suvanjan Bhattacharyya Eydhah Almatrafi Bahaa Saleh Mrinal Kanti Naskar |
| author_sort | Chandrani Sadhukhan |
| collection | DOAJ |
| description | Abstract Lithium-ion battery, a high energy density storage device has extensive applications in electrical and electronic gadgets, computers, hybrid electric vehicles, and electric vehicles. This paper presents multiple fault detection of lithium-ion battery using two non-linear Kalman filters. A discrete non-linear mathematical model of lithium ion battery has been developed and Unscented Kalman filter (UKF) is employed to estimate the model parameter. Occurrences of multiple faults such as over-charge, over-discharge and short circuit faults between inter cell power batteries, affects the parameter variation of system model. Parallel combinations of some UKF (bank of filters) compare the model parameter variation between the normal and faulty situation and generates residual signal indicating different fault. Simulation results of multiple numbers of statistical tests have been performed for residual based fault diagnosis and threshold calculation. The performance of UKF is then compared with Extended Kalman filter (EKF) with same battery model and fault scenario. The simulation result proves that UKF model responses better and quicker than that of EKF for fault diagnosis. |
| first_indexed | 2024-04-13T19:33:23Z |
| format | Article |
| id | doaj.art-81738cbb68fa4a27a2e875be5d1fadad |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-13T19:33:23Z |
| publishDate | 2022-06-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-81738cbb68fa4a27a2e875be5d1fadad2022-12-22T02:33:06ZengNature PortfolioScientific Reports2045-23222022-06-0112111310.1038/s41598-022-13771-4Modeling and simulation of high energy density lithium-ion battery for multiple fault detectionChandrani Sadhukhan0Swarup Kumar Mitra1Suvanjan Bhattacharyya2Eydhah Almatrafi3Bahaa Saleh4Mrinal Kanti Naskar5Electrical Engineering Department, MCKV Institute of Engineering, LiluahElectronic & Telecommunication Engineering Department, MCKV Institute of Engineering, LiluahDepartment of Mechanical Engineering, Birla Institute of Technology & Science, PilaniMechanical Engineering Department, College of Engineering Rabigh, King Abdulaziz UniversityMechanical Engineering Department, College of Engineering, Taif UniversityElectronic & Telecommunication Engineering Department, Jadavpur UniversityAbstract Lithium-ion battery, a high energy density storage device has extensive applications in electrical and electronic gadgets, computers, hybrid electric vehicles, and electric vehicles. This paper presents multiple fault detection of lithium-ion battery using two non-linear Kalman filters. A discrete non-linear mathematical model of lithium ion battery has been developed and Unscented Kalman filter (UKF) is employed to estimate the model parameter. Occurrences of multiple faults such as over-charge, over-discharge and short circuit faults between inter cell power batteries, affects the parameter variation of system model. Parallel combinations of some UKF (bank of filters) compare the model parameter variation between the normal and faulty situation and generates residual signal indicating different fault. Simulation results of multiple numbers of statistical tests have been performed for residual based fault diagnosis and threshold calculation. The performance of UKF is then compared with Extended Kalman filter (EKF) with same battery model and fault scenario. The simulation result proves that UKF model responses better and quicker than that of EKF for fault diagnosis.https://doi.org/10.1038/s41598-022-13771-4 |
| spellingShingle | Chandrani Sadhukhan Swarup Kumar Mitra Suvanjan Bhattacharyya Eydhah Almatrafi Bahaa Saleh Mrinal Kanti Naskar Modeling and simulation of high energy density lithium-ion battery for multiple fault detection Scientific Reports |
| title | Modeling and simulation of high energy density lithium-ion battery for multiple fault detection |
| title_full | Modeling and simulation of high energy density lithium-ion battery for multiple fault detection |
| title_fullStr | Modeling and simulation of high energy density lithium-ion battery for multiple fault detection |
| title_full_unstemmed | Modeling and simulation of high energy density lithium-ion battery for multiple fault detection |
| title_short | Modeling and simulation of high energy density lithium-ion battery for multiple fault detection |
| title_sort | modeling and simulation of high energy density lithium ion battery for multiple fault detection |
| url | https://doi.org/10.1038/s41598-022-13771-4 |
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