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Application of MMAE to the Fault Detection of Lithium-Ion Battery
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| Zeitschriftentitel: | Applied Mechanics and Materials |
|---|---|
| Personen und Körperschaften: | , |
| In: | Applied Mechanics and Materials, 598, 2014, S. 342-346 |
| Format: | E-Article |
| Sprache: | Unbestimmt |
| veröffentlicht: |
Trans Tech Publications, Ltd.
|
| Schlagwörter: |
| author_facet |
Liu, Zhao Sohel, Anwar Liu, Zhao Sohel, Anwar |
|---|---|
| author |
Liu, Zhao Sohel, Anwar |
| spellingShingle |
Liu, Zhao Sohel, Anwar Applied Mechanics and Materials Application of MMAE to the Fault Detection of Lithium-Ion Battery General Engineering |
| author_sort |
liu, zhao |
| spelling |
Liu, Zhao Sohel, Anwar 1662-7482 Trans Tech Publications, Ltd. General Engineering http://dx.doi.org/10.4028/www.scientific.net/amm.598.342 <jats:p>With the advantage of high energy density, long cycle life and environmental friendliness, Lithium-ion battery has become a promising power source for hybrid and electric vehicles, which are liable to two kinds of failure, overcharge and overdischarge. Because of the capability of detecting multiple faults, Multiple Model Adaptive Estimation (MMAE) method was applied to a model-based fault detection of a lithium-ion battery with a two-order linear electrical model. Parameters that represent normal-mode and faulty-mode of the battery were obtained by a series of experiments, and three Kalman filters were designed thereafter. Finally, simulation verified the performance of the MMAE algorithm on fault detection of these two kinds of fault and it is shown that this technique is able to discern these faults rapidly and accurately.</jats:p> Application of MMAE to the Fault Detection of Lithium-Ion Battery Applied Mechanics and Materials |
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Trans Tech Publications, Ltd., 2014 |
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Trans Tech Publications, Ltd., 2014 |
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2014 |
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Trans Tech Publications, Ltd. |
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Applied Mechanics and Materials |
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49 |
| title |
Application of MMAE to the Fault Detection of Lithium-Ion Battery |
| title_unstemmed |
Application of MMAE to the Fault Detection of Lithium-Ion Battery |
| title_full |
Application of MMAE to the Fault Detection of Lithium-Ion Battery |
| title_fullStr |
Application of MMAE to the Fault Detection of Lithium-Ion Battery |
| title_full_unstemmed |
Application of MMAE to the Fault Detection of Lithium-Ion Battery |
| title_short |
Application of MMAE to the Fault Detection of Lithium-Ion Battery |
| title_sort |
application of mmae to the fault detection of lithium-ion battery |
| topic |
General Engineering |
| url |
http://dx.doi.org/10.4028/www.scientific.net/amm.598.342 |
| publishDate |
2014 |
| physical |
342-346 |
| description |
<jats:p>With the advantage of high energy density, long cycle life and environmental friendliness, Lithium-ion battery has become a promising power source for hybrid and electric vehicles, which are liable to two kinds of failure, overcharge and overdischarge. Because of the capability of detecting multiple faults, Multiple Model Adaptive Estimation (MMAE) method was applied to a model-based fault detection of a lithium-ion battery with a two-order linear electrical model. Parameters that represent normal-mode and faulty-mode of the battery were obtained by a series of experiments, and three Kalman filters were designed thereafter. Finally, simulation verified the performance of the MMAE algorithm on fault detection of these two kinds of fault and it is shown that this technique is able to discern these faults rapidly and accurately.</jats:p> |
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| author | Liu, Zhao, Sohel, Anwar |
| author_facet | Liu, Zhao, Sohel, Anwar, Liu, Zhao, Sohel, Anwar |
| author_sort | liu, zhao |
| container_start_page | 342 |
| container_title | Applied Mechanics and Materials |
| container_volume | 598 |
| description | <jats:p>With the advantage of high energy density, long cycle life and environmental friendliness, Lithium-ion battery has become a promising power source for hybrid and electric vehicles, which are liable to two kinds of failure, overcharge and overdischarge. Because of the capability of detecting multiple faults, Multiple Model Adaptive Estimation (MMAE) method was applied to a model-based fault detection of a lithium-ion battery with a two-order linear electrical model. Parameters that represent normal-mode and faulty-mode of the battery were obtained by a series of experiments, and three Kalman filters were designed thereafter. Finally, simulation verified the performance of the MMAE algorithm on fault detection of these two kinds of fault and it is shown that this technique is able to discern these faults rapidly and accurately.</jats:p> |
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| imprint | Trans Tech Publications, Ltd., 2014 |
| imprint_str_mv | Trans Tech Publications, Ltd., 2014 |
| institution | DE-D275, DE-Bn3, DE-Brt1, DE-D161, DE-Gla1, DE-Zi4, DE-15, DE-Pl11, DE-Rs1, DE-105, DE-14, DE-Ch1, DE-L229 |
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| issn_str_mv | 1662-7482 |
| language | Undetermined |
| last_indexed | 2024-03-01T11:17:34.369Z |
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| physical | 342-346 |
| publishDate | 2014 |
| publishDateSort | 2014 |
| publisher | Trans Tech Publications, Ltd. |
| record_format | ai |
| recordtype | ai |
| series | Applied Mechanics and Materials |
| source_id | 49 |
| spelling | Liu, Zhao Sohel, Anwar 1662-7482 Trans Tech Publications, Ltd. General Engineering http://dx.doi.org/10.4028/www.scientific.net/amm.598.342 <jats:p>With the advantage of high energy density, long cycle life and environmental friendliness, Lithium-ion battery has become a promising power source for hybrid and electric vehicles, which are liable to two kinds of failure, overcharge and overdischarge. Because of the capability of detecting multiple faults, Multiple Model Adaptive Estimation (MMAE) method was applied to a model-based fault detection of a lithium-ion battery with a two-order linear electrical model. Parameters that represent normal-mode and faulty-mode of the battery were obtained by a series of experiments, and three Kalman filters were designed thereafter. Finally, simulation verified the performance of the MMAE algorithm on fault detection of these two kinds of fault and it is shown that this technique is able to discern these faults rapidly and accurately.</jats:p> Application of MMAE to the Fault Detection of Lithium-Ion Battery Applied Mechanics and Materials |
| spellingShingle | Liu, Zhao, Sohel, Anwar, Applied Mechanics and Materials, Application of MMAE to the Fault Detection of Lithium-Ion Battery, General Engineering |
| title | Application of MMAE to the Fault Detection of Lithium-Ion Battery |
| title_full | Application of MMAE to the Fault Detection of Lithium-Ion Battery |
| title_fullStr | Application of MMAE to the Fault Detection of Lithium-Ion Battery |
| title_full_unstemmed | Application of MMAE to the Fault Detection of Lithium-Ion Battery |
| title_short | Application of MMAE to the Fault Detection of Lithium-Ion Battery |
| title_sort | application of mmae to the fault detection of lithium-ion battery |
| title_unstemmed | Application of MMAE to the Fault Detection of Lithium-Ion Battery |
| topic | General Engineering |
| url | http://dx.doi.org/10.4028/www.scientific.net/amm.598.342 |