Battery Management in Electric Vehicles: Current Status and Future Trends
Lithium-ion batteries are an indispensable component of the global transition to zero-carbon energy and are instrumental in achieving COP26's objective of attaining global net-zero emissions by the mid-century. However, their rapid expansion comes with significant challenges. The continuous demand f...
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| Formatua: | Online |
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| Hizkuntza: | ingelesa |
| Argitaratua: |
MDPI - Multidisciplinary Digital Publishing Institute
2024
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| Sarrera elektronikoa: | ONIX_20240704_9783725813452_240 |
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| _version_ | 1869525103976382464 |
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| collection | Directory of Open Access Books |
| description | Lithium-ion batteries are an indispensable component of the global transition to zero-carbon energy and are instrumental in achieving COP26's objective of attaining global net-zero emissions by the mid-century. However, their rapid expansion comes with significant challenges. The continuous demand for lithium-ion batteries in electric vehicles (EVs) is expected to raise global environmental and supply chain concerns, given that the critical materials required for their production are finite and predominantly mined in limited regions worldwide. Consequently, significant battery waste management will eventually become necessary. By implementing appropriate and enhanced battery management techniques in electric vehicles, the performance of batteries can be improved, their lifespan extended, secondary uses enabled, and the recycling and reuse of EV batteries promoted, thereby mitigating global environmental and supply chain concerns. Therefore, this reprint was crafted to update the scientific community on recent advancements and future trajectories in battery management for electric vehicles. The content of this reprint spans a spectrum of EV battery advancements, ranging from fundamental battery studies to the utilization of neural network modeling and machine learning to optimize battery performance, enhance efficiency, and ensure prolonged lifespan. |
| format | Online |
| id | doab-20.500.12854ir-139444 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1394442024-07-04T09:56:14Z Battery Management in Electric Vehicles: Current Status and Future Trends Das, Prodip K. battery storage battery management electric vehicles converter controllers optimizations battery pack design strategies thermal management lithium-ion battery battery Li-ion temperature thermal map parametric equation electric vehicle topographical optimization mechanical stresses circular economy adaptation batteries fuzzy intelligent system iterative Kalman lithium-ion modeling WLTP inductively coupled power transfer EV battery charging misalignment coil design compensation topology mobility battery sharing battery swapping discrete-event simulation orienteering problem reinforcement learning simulation artificial neural network direct oil cooling electrical performance thermal performance state of health estimation machine learning transfer learning n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TD Industrial chemistry and manufacturing technologies::TDC Industrial chemistry and chemical engineering Lithium-ion batteries are an indispensable component of the global transition to zero-carbon energy and are instrumental in achieving COP26's objective of attaining global net-zero emissions by the mid-century. However, their rapid expansion comes with significant challenges. The continuous demand for lithium-ion batteries in electric vehicles (EVs) is expected to raise global environmental and supply chain concerns, given that the critical materials required for their production are finite and predominantly mined in limited regions worldwide. Consequently, significant battery waste management will eventually become necessary. By implementing appropriate and enhanced battery management techniques in electric vehicles, the performance of batteries can be improved, their lifespan extended, secondary uses enabled, and the recycling and reuse of EV batteries promoted, thereby mitigating global environmental and supply chain concerns. Therefore, this reprint was crafted to update the scientific community on recent advancements and future trajectories in battery management for electric vehicles. The content of this reprint spans a spectrum of EV battery advancements, ranging from fundamental battery studies to the utilization of neural network modeling and machine learning to optimize battery performance, enhance efficiency, and ensure prolonged lifespan. 2024-07-04T09:56:10Z 2024-07-04T09:56:10Z 2024 book ONIX_20240704_9783725813452_240 9783725813452 9783725813469 https://directory.doabooks.org/handle/20.500.12854/139444 eng application/octet-stream Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/9447 https://mdpi.com/books/pdfview/book/9447 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-1346-9 10.3390/books978-3-7258-1346-9 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725813452 9783725813469 248 open access |
| spellingShingle | battery storage battery management electric vehicles converter controllers optimizations battery pack design strategies thermal management lithium-ion battery battery Li-ion temperature thermal map parametric equation electric vehicle topographical optimization mechanical stresses circular economy adaptation batteries fuzzy intelligent system iterative Kalman lithium-ion modeling WLTP inductively coupled power transfer EV battery charging misalignment coil design compensation topology mobility battery sharing battery swapping discrete-event simulation orienteering problem reinforcement learning simulation artificial neural network direct oil cooling electrical performance thermal performance state of health estimation machine learning transfer learning n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TD Industrial chemistry and manufacturing technologies::TDC Industrial chemistry and chemical engineering Battery Management in Electric Vehicles: Current Status and Future Trends |
| title | Battery Management in Electric Vehicles: Current Status and Future Trends |
| title_full | Battery Management in Electric Vehicles: Current Status and Future Trends |
| title_fullStr | Battery Management in Electric Vehicles: Current Status and Future Trends |
| title_full_unstemmed | Battery Management in Electric Vehicles: Current Status and Future Trends |
| title_short | Battery Management in Electric Vehicles: Current Status and Future Trends |
| title_sort | battery management in electric vehicles current status and future trends |
| topic | battery storage battery management electric vehicles converter controllers optimizations battery pack design strategies thermal management lithium-ion battery battery Li-ion temperature thermal map parametric equation electric vehicle topographical optimization mechanical stresses circular economy adaptation batteries fuzzy intelligent system iterative Kalman lithium-ion modeling WLTP inductively coupled power transfer EV battery charging misalignment coil design compensation topology mobility battery sharing battery swapping discrete-event simulation orienteering problem reinforcement learning simulation artificial neural network direct oil cooling electrical performance thermal performance state of health estimation machine learning transfer learning n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TD Industrial chemistry and manufacturing technologies::TDC Industrial chemistry and chemical engineering |
| topic_facet | battery storage battery management electric vehicles converter controllers optimizations battery pack design strategies thermal management lithium-ion battery battery Li-ion temperature thermal map parametric equation electric vehicle topographical optimization mechanical stresses circular economy adaptation batteries fuzzy intelligent system iterative Kalman lithium-ion modeling WLTP inductively coupled power transfer EV battery charging misalignment coil design compensation topology mobility battery sharing battery swapping discrete-event simulation orienteering problem reinforcement learning simulation artificial neural network direct oil cooling electrical performance thermal performance state of health estimation machine learning transfer learning n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TD Industrial chemistry and manufacturing technologies::TDC Industrial chemistry and chemical engineering |
| url | ONIX_20240704_9783725813452_240 |