Box–Jenkins Black-Box Modeling of a Lithium-Ion Battery Cell Based on Automotive Drive Cycle Data
The Box–Jenkins model is a polynomial model that uses transfer functions to express relationships between input, output, and noise for a given system. In this article, we present a Box–Jenkins linear model for a lithium-ion battery cell for use in electric vehicles. The model parameter identificatio...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-07-01
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| Series: | World Electric Vehicle Journal |
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| Online Access: | https://www.mdpi.com/2032-6653/12/3/102 |
| _version_ | 1797516933803802624 |
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| author | Jaouad Khalfi Najib Boumaaz Abdallah Soulmani El Mehdi Laadissi |
| author_facet | Jaouad Khalfi Najib Boumaaz Abdallah Soulmani El Mehdi Laadissi |
| author_sort | Jaouad Khalfi |
| collection | DOAJ |
| description | The Box–Jenkins model is a polynomial model that uses transfer functions to express relationships between input, output, and noise for a given system. In this article, we present a Box–Jenkins linear model for a lithium-ion battery cell for use in electric vehicles. The model parameter identifications are based on automotive drive-cycle measurements. The proposed model prediction performance is evaluated using the goodness-of-fit criteria and the mean squared error between the Box–Jenkins model and the measured battery cell output. A simulation confirmed that the proposed Box–Jenkins model could adequately capture the battery cell dynamics for different automotive drive cycles and reasonably predict the actual battery cell output. The goodness-of-fit value shows that the Box–Jenkins model matches the battery cell data by 86.85% in the identification phase, and 90.83% in the validation phase for the LA-92 driving cycle. This work demonstrates the potential of using a simple and linear model to predict the battery cell behavior based on a complex identification dataset that represents the actual use of the battery cell in an electric vehicle. |
| first_indexed | 2024-03-10T07:07:47Z |
| format | Article |
| id | doaj.art-79c076f662fb4678b6861109f32072fc |
| institution | Directory Open Access Journal |
| issn | 2032-6653 |
| language | English |
| last_indexed | 2024-03-10T07:07:47Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj.art-79c076f662fb4678b6861109f32072fc2023-11-22T15:42:01ZengMDPI AGWorld Electric Vehicle Journal2032-66532021-07-0112310210.3390/wevj12030102Box–Jenkins Black-Box Modeling of a Lithium-Ion Battery Cell Based on Automotive Drive Cycle DataJaouad Khalfi0Najib Boumaaz1Abdallah Soulmani2El Mehdi Laadissi3Laboratory of Electrical Systems, Energy Efficiency and Telecommunications, Department of Physics, Faculty of Sciences and Technology, Cadi Ayyad University, Marrakech 40000, MoroccoLaboratory of Electrical Systems, Energy Efficiency and Telecommunications, Department of Physics, Faculty of Sciences and Technology, Cadi Ayyad University, Marrakech 40000, MoroccoLaboratory of Electrical Systems, Energy Efficiency and Telecommunications, Department of Physics, Faculty of Sciences and Technology, Cadi Ayyad University, Marrakech 40000, MoroccoLaboratory of Engineering Sciences for Energy (LabSIPE), National School of Applied Sciences, Chouaib Doukkali University, El Jadida 24000, MoroccoThe Box–Jenkins model is a polynomial model that uses transfer functions to express relationships between input, output, and noise for a given system. In this article, we present a Box–Jenkins linear model for a lithium-ion battery cell for use in electric vehicles. The model parameter identifications are based on automotive drive-cycle measurements. The proposed model prediction performance is evaluated using the goodness-of-fit criteria and the mean squared error between the Box–Jenkins model and the measured battery cell output. A simulation confirmed that the proposed Box–Jenkins model could adequately capture the battery cell dynamics for different automotive drive cycles and reasonably predict the actual battery cell output. The goodness-of-fit value shows that the Box–Jenkins model matches the battery cell data by 86.85% in the identification phase, and 90.83% in the validation phase for the LA-92 driving cycle. This work demonstrates the potential of using a simple and linear model to predict the battery cell behavior based on a complex identification dataset that represents the actual use of the battery cell in an electric vehicle.https://www.mdpi.com/2032-6653/12/3/102Box–Jenkins modellithium-ion battery cellelectric vehiclesautomotive drive-cycle measurements |
| spellingShingle | Jaouad Khalfi Najib Boumaaz Abdallah Soulmani El Mehdi Laadissi Box–Jenkins Black-Box Modeling of a Lithium-Ion Battery Cell Based on Automotive Drive Cycle Data World Electric Vehicle Journal Box–Jenkins model lithium-ion battery cell electric vehicles automotive drive-cycle measurements |
| title | Box–Jenkins Black-Box Modeling of a Lithium-Ion Battery Cell Based on Automotive Drive Cycle Data |
| title_full | Box–Jenkins Black-Box Modeling of a Lithium-Ion Battery Cell Based on Automotive Drive Cycle Data |
| title_fullStr | Box–Jenkins Black-Box Modeling of a Lithium-Ion Battery Cell Based on Automotive Drive Cycle Data |
| title_full_unstemmed | Box–Jenkins Black-Box Modeling of a Lithium-Ion Battery Cell Based on Automotive Drive Cycle Data |
| title_short | Box–Jenkins Black-Box Modeling of a Lithium-Ion Battery Cell Based on Automotive Drive Cycle Data |
| title_sort | box jenkins black box modeling of a lithium ion battery cell based on automotive drive cycle data |
| topic | Box–Jenkins model lithium-ion battery cell electric vehicles automotive drive-cycle measurements |
| url | https://www.mdpi.com/2032-6653/12/3/102 |
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