A Sensor-Fault-Estimation Method for Lithium-Ion Batteries in Electric Vehicles
In recent years, electric vehicles powered by lithium-ion batteries have developed rapidly, and the safety and reliability of lithium-ion batteries have been a paramount issue. Battery management systems are highly dependent on sensor measurements to ensure the proper functioning of lithium-ion batt...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-09-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/18/7737 |
| _version_ | 1827723640208097280 |
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| author | Tianyu Lan Zhi-Wei Gao Haishuang Yin Yuanhong Liu |
| author_facet | Tianyu Lan Zhi-Wei Gao Haishuang Yin Yuanhong Liu |
| author_sort | Tianyu Lan |
| collection | DOAJ |
| description | In recent years, electric vehicles powered by lithium-ion batteries have developed rapidly, and the safety and reliability of lithium-ion batteries have been a paramount issue. Battery management systems are highly dependent on sensor measurements to ensure the proper functioning of lithium-ion batteries. Therefore, it is imperative to develop a suitable fault diagnosis scheme for battery sensors, to realize a diagnosis at an early stage. The main objective of this paper is to establish validated electrical and thermal models for batteries, and address a model-based fault diagnosis scheme for battery sensors. Descriptor proportional and derivate observer systems are applied for sensor diagnosis, based on electrical and thermal models of lithium-ion batteries, which can realize the real-time estimation of voltage sensor fault, current sensor fault, and temperature sensor fault. To verify the estimation effect of the proposed scheme, various types of faults are utilized for simulation experiments. Battery experimental data are used for battery modeling and observer-based fault diagnosis in battery sensors. |
| first_indexed | 2024-03-10T22:03:34Z |
| format | Article |
| id | doaj.art-a1b35ba8ffe645298ebc1c1137000fa3 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T22:03:34Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-a1b35ba8ffe645298ebc1c1137000fa32023-11-19T12:53:30ZengMDPI AGSensors1424-82202023-09-012318773710.3390/s23187737A Sensor-Fault-Estimation Method for Lithium-Ion Batteries in Electric VehiclesTianyu Lan0Zhi-Wei Gao1Haishuang Yin2Yuanhong Liu3Research Centre for Digitalization and Intelligent Diagnosis to New Energies, College of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163000, ChinaResearch Centre for Digitalization and Intelligent Diagnosis to New Energies, College of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163000, ChinaResearch Centre for Digitalization and Intelligent Diagnosis to New Energies, College of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163000, ChinaResearch Centre for Digitalization and Intelligent Diagnosis to New Energies, College of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163000, ChinaIn recent years, electric vehicles powered by lithium-ion batteries have developed rapidly, and the safety and reliability of lithium-ion batteries have been a paramount issue. Battery management systems are highly dependent on sensor measurements to ensure the proper functioning of lithium-ion batteries. Therefore, it is imperative to develop a suitable fault diagnosis scheme for battery sensors, to realize a diagnosis at an early stage. The main objective of this paper is to establish validated electrical and thermal models for batteries, and address a model-based fault diagnosis scheme for battery sensors. Descriptor proportional and derivate observer systems are applied for sensor diagnosis, based on electrical and thermal models of lithium-ion batteries, which can realize the real-time estimation of voltage sensor fault, current sensor fault, and temperature sensor fault. To verify the estimation effect of the proposed scheme, various types of faults are utilized for simulation experiments. Battery experimental data are used for battery modeling and observer-based fault diagnosis in battery sensors.https://www.mdpi.com/1424-8220/23/18/7737lithium-ion batterysensor faultfault diagnosisfault estimationdescriptor observer |
| spellingShingle | Tianyu Lan Zhi-Wei Gao Haishuang Yin Yuanhong Liu A Sensor-Fault-Estimation Method for Lithium-Ion Batteries in Electric Vehicles Sensors lithium-ion battery sensor fault fault diagnosis fault estimation descriptor observer |
| title | A Sensor-Fault-Estimation Method for Lithium-Ion Batteries in Electric Vehicles |
| title_full | A Sensor-Fault-Estimation Method for Lithium-Ion Batteries in Electric Vehicles |
| title_fullStr | A Sensor-Fault-Estimation Method for Lithium-Ion Batteries in Electric Vehicles |
| title_full_unstemmed | A Sensor-Fault-Estimation Method for Lithium-Ion Batteries in Electric Vehicles |
| title_short | A Sensor-Fault-Estimation Method for Lithium-Ion Batteries in Electric Vehicles |
| title_sort | sensor fault estimation method for lithium ion batteries in electric vehicles |
| topic | lithium-ion battery sensor fault fault diagnosis fault estimation descriptor observer |
| url | https://www.mdpi.com/1424-8220/23/18/7737 |
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