Battery Modelling, Applications, and Technology
Batteries, among the various energy storage systems, are electrochemical storage devices that have always been attractive for both stationary and mobile applications. Different kinds of technology have been developed through the years (lead–acid, nickel–cadmium, nickel–metal hydride, lithium ion, et...
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| Формат: | Online |
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| Мова: | Англійська |
| Опубліковано: |
MDPI - Multidisciplinary Digital Publishing Institute
2024
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| Предмети: | |
| Онлайн доступ: | ONIX_20240514_9783725806058_373 |
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| _version_ | 1869514606018297856 |
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| collection | Directory of Open Access Books |
| description | Batteries, among the various energy storage systems, are electrochemical storage devices that have always been attractive for both stationary and mobile applications. Different kinds of technology have been developed through the years (lead–acid, nickel–cadmium, nickel–metal hydride, lithium ion, etc.), and other novel technologies (metal–air, quasi-solid state battery, all-solid state battery, etc.) are still being studied. The most important features for these devices to have include high power, energy density, and efficiency, in addition to a long lifecycle. In particular, the latter can be increased by developing novel technologies in the construction of the batteries themselves and/or in controlling them to operate in their optimal working conditions. To achieve this, the modeling of batteries and the estimation of their parameters becomes a very important challenge. Indeed, through the latter, it is possible to study, analyze, and predict the behavior of single battery cells or whole battery packs with different aims. On the one hand, battery models can be used for analyses of the batteries themselves to improve their efficiency and lifecycle, to build battery management systems, or for sizing battery packs. On the other hand, the same models can be used to analyze the behavior of entire systems in which the battery is one part. This Special Issue collected many articles on battery chemical, electric, thermal, and aging models, integrated battery models and their composition, battery parameter estimation methods, and novel applications and technologies of batteries. |
| format | Online |
| id | doab-20.500.12854ir-137777 |
| 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-1377772024-05-14T14:25:44Z Battery Modelling, Applications, and Technology Barcellona, Simone cable thermal analysis skin and proximity effects battery storage ampacity lithium-ion battery state of charge state of health deep learning cloud field application battery management system machine learning artificial intelligence safety field real-world application SoH battery degradation prognostics lithium-ion batteries calendar aging OCV curve state of charge estimation ICEVs BEVs mobility electricity generation wind energy solar photovoltaic energy renewable energy sources vehicle fleet pollutant emissions second-life battery electricity grid application electrochemical modeling degradation prediction battery operational strategy lithium-ion iron phosphate (LFP) battery hybrid pulse power characterization (HPPC) Thevenin equivalent circuit battery energy storage system renewables market service stacking artificial neural networks data augmentation electrode microstructure heterogeneous physical model mechanical degradation electrochemical impedance spectroscopy battery fuel-cell vehicle load capacity hybrid powertrain electric propulsion system energy balance assessment external load chassis dynamometer lithium batteries Kalman filters sliding innovation filter interacting multiple model battery monitoring system B005 battery dataset thema EDItEUR::2 Language qualifiers::2A Indo-European languages::2AC Germanic and Scandinavian languages::2ACG German Batteries, among the various energy storage systems, are electrochemical storage devices that have always been attractive for both stationary and mobile applications. Different kinds of technology have been developed through the years (lead–acid, nickel–cadmium, nickel–metal hydride, lithium ion, etc.), and other novel technologies (metal–air, quasi-solid state battery, all-solid state battery, etc.) are still being studied. The most important features for these devices to have include high power, energy density, and efficiency, in addition to a long lifecycle. In particular, the latter can be increased by developing novel technologies in the construction of the batteries themselves and/or in controlling them to operate in their optimal working conditions. To achieve this, the modeling of batteries and the estimation of their parameters becomes a very important challenge. Indeed, through the latter, it is possible to study, analyze, and predict the behavior of single battery cells or whole battery packs with different aims. On the one hand, battery models can be used for analyses of the batteries themselves to improve their efficiency and lifecycle, to build battery management systems, or for sizing battery packs. On the other hand, the same models can be used to analyze the behavior of entire systems in which the battery is one part. This Special Issue collected many articles on battery chemical, electric, thermal, and aging models, integrated battery models and their composition, battery parameter estimation methods, and novel applications and technologies of batteries. 2024-05-14T14:25:40Z 2024-05-14T14:25:40Z 2024 book ONIX_20240514_9783725806058_373 9783725806058 9783725806065 https://directory.doabooks.org/handle/20.500.12854/137777 eng application/octet-stream Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/9010 https://mdpi.com/books/pdfview/book/9010 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-0606-5 10.3390/books978-3-7258-0606-5 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725806058 9783725806065 252 open access |
| spellingShingle | cable thermal analysis skin and proximity effects battery storage ampacity lithium-ion battery state of charge state of health deep learning cloud field application battery management system machine learning artificial intelligence safety field real-world application SoH battery degradation prognostics lithium-ion batteries calendar aging OCV curve state of charge estimation ICEVs BEVs mobility electricity generation wind energy solar photovoltaic energy renewable energy sources vehicle fleet pollutant emissions second-life battery electricity grid application electrochemical modeling degradation prediction battery operational strategy lithium-ion iron phosphate (LFP) battery hybrid pulse power characterization (HPPC) Thevenin equivalent circuit battery energy storage system renewables market service stacking artificial neural networks data augmentation electrode microstructure heterogeneous physical model mechanical degradation electrochemical impedance spectroscopy battery fuel-cell vehicle load capacity hybrid powertrain electric propulsion system energy balance assessment external load chassis dynamometer lithium batteries Kalman filters sliding innovation filter interacting multiple model battery monitoring system B005 battery dataset thema EDItEUR::2 Language qualifiers::2A Indo-European languages::2AC Germanic and Scandinavian languages::2ACG German Battery Modelling, Applications, and Technology |
| title | Battery Modelling, Applications, and Technology |
| title_full | Battery Modelling, Applications, and Technology |
| title_fullStr | Battery Modelling, Applications, and Technology |
| title_full_unstemmed | Battery Modelling, Applications, and Technology |
| title_short | Battery Modelling, Applications, and Technology |
| title_sort | battery modelling applications and technology |
| topic | cable thermal analysis skin and proximity effects battery storage ampacity lithium-ion battery state of charge state of health deep learning cloud field application battery management system machine learning artificial intelligence safety field real-world application SoH battery degradation prognostics lithium-ion batteries calendar aging OCV curve state of charge estimation ICEVs BEVs mobility electricity generation wind energy solar photovoltaic energy renewable energy sources vehicle fleet pollutant emissions second-life battery electricity grid application electrochemical modeling degradation prediction battery operational strategy lithium-ion iron phosphate (LFP) battery hybrid pulse power characterization (HPPC) Thevenin equivalent circuit battery energy storage system renewables market service stacking artificial neural networks data augmentation electrode microstructure heterogeneous physical model mechanical degradation electrochemical impedance spectroscopy battery fuel-cell vehicle load capacity hybrid powertrain electric propulsion system energy balance assessment external load chassis dynamometer lithium batteries Kalman filters sliding innovation filter interacting multiple model battery monitoring system B005 battery dataset thema EDItEUR::2 Language qualifiers::2A Indo-European languages::2AC Germanic and Scandinavian languages::2ACG German |
| topic_facet | cable thermal analysis skin and proximity effects battery storage ampacity lithium-ion battery state of charge state of health deep learning cloud field application battery management system machine learning artificial intelligence safety field real-world application SoH battery degradation prognostics lithium-ion batteries calendar aging OCV curve state of charge estimation ICEVs BEVs mobility electricity generation wind energy solar photovoltaic energy renewable energy sources vehicle fleet pollutant emissions second-life battery electricity grid application electrochemical modeling degradation prediction battery operational strategy lithium-ion iron phosphate (LFP) battery hybrid pulse power characterization (HPPC) Thevenin equivalent circuit battery energy storage system renewables market service stacking artificial neural networks data augmentation electrode microstructure heterogeneous physical model mechanical degradation electrochemical impedance spectroscopy battery fuel-cell vehicle load capacity hybrid powertrain electric propulsion system energy balance assessment external load chassis dynamometer lithium batteries Kalman filters sliding innovation filter interacting multiple model battery monitoring system B005 battery dataset thema EDItEUR::2 Language qualifiers::2A Indo-European languages::2AC Germanic and Scandinavian languages::2ACG German |
| url | ONIX_20240514_9783725806058_373 |