Design of Piecewise Affine and Linear Time-Varying Model Predictive Control Strategies for Advanced Battery Management Systems
Advanced Battery Management Systems (ABMSs) are necessary for the optimal and safe operation of Li-ion batteries. This article proposes the design of ABMSs based on Model Predictive Control (MPC). In particular, we consider MPC strategies based on piecewise affine approximations (PWAs) of a first-pr...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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The Electrochemical Society
2020
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| Online Access: | https://hdl.handle.net/1721.1/126338 |
| _version_ | 1811082152015560704 |
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| author | Torchio, Marcello Magni, L. Braatz, Richard D Raimondo, D. M. |
| author2 | Massachusetts Institute of Technology. Department of Chemical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Chemical Engineering Torchio, Marcello Magni, L. Braatz, Richard D Raimondo, D. M. |
| author_sort | Torchio, Marcello |
| collection | MIT |
| description | Advanced Battery Management Systems (ABMSs) are necessary for the optimal and safe operation of Li-ion batteries. This article proposes the design of ABMSs based on Model Predictive Control (MPC). In particular, we consider MPC strategies based on piecewise affine approximations (PWAs) of a first-principles electrochemical battery model known in the literature as the pseudo two-dimensional (P2D) model. The use of model approximations is necessary since the P2D model is too complex to be included in the real-time calculations required by MPC. PWAs allow to well describe the electrochemical phenomena occurring inside the battery. On the other side, the accuracy of such models increases with the number of considered partitions, which also increases the model complexity and the online computational cost of MPC. Linear time-varying (LTV) approximations, which are obtained by linearizing accurate PWAs around a nominal trajectory, are proposed as a way to further reduce online computational costs. The obtained results demonstrate the suitability of MPC based on PWARX and LTV model approximations to provide ABMSs with high performance. ©2017 The Electrochemical Society. All rights reserved. |
| first_indexed | 2024-09-23T11:58:24Z |
| format | Article |
| id | mit-1721.1/126338 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T11:58:24Z |
| publishDate | 2020 |
| publisher | The Electrochemical Society |
| record_format | dspace |
| spelling | mit-1721.1/1263382022-09-27T23:12:26Z Design of Piecewise Affine and Linear Time-Varying Model Predictive Control Strategies for Advanced Battery Management Systems Torchio, Marcello Magni, L. Braatz, Richard D Raimondo, D. M. Massachusetts Institute of Technology. Department of Chemical Engineering Advanced Battery Management Systems (ABMSs) are necessary for the optimal and safe operation of Li-ion batteries. This article proposes the design of ABMSs based on Model Predictive Control (MPC). In particular, we consider MPC strategies based on piecewise affine approximations (PWAs) of a first-principles electrochemical battery model known in the literature as the pseudo two-dimensional (P2D) model. The use of model approximations is necessary since the P2D model is too complex to be included in the real-time calculations required by MPC. PWAs allow to well describe the electrochemical phenomena occurring inside the battery. On the other side, the accuracy of such models increases with the number of considered partitions, which also increases the model complexity and the online computational cost of MPC. Linear time-varying (LTV) approximations, which are obtained by linearizing accurate PWAs around a nominal trajectory, are proposed as a way to further reduce online computational costs. The obtained results demonstrate the suitability of MPC based on PWARX and LTV model approximations to provide ABMSs with high performance. ©2017 The Electrochemical Society. All rights reserved. 2020-07-23T14:27:52Z 2020-07-23T14:27:52Z 2017-03 2017-02 2019-08-14T18:09:25Z Article http://purl.org/eprint/type/JournalArticle 1945-7111 https://hdl.handle.net/1721.1/126338 Torchio, Marcello et al., "Design of Piecewise Affine and Linear Time-Varying Model Predictive Control Strategies for Advanced Battery Management Systems." Journal of The Electrochemical Society 164, 4 (March 2017): p. A949-A959 doi. 10.1149/2.0201706jes ©2017 Authors en https://dx.doi.org/10.1149/2.0201706JES Journal of The Electrochemical Society Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf The Electrochemical Society MIT web domain |
| spellingShingle | Torchio, Marcello Magni, L. Braatz, Richard D Raimondo, D. M. Design of Piecewise Affine and Linear Time-Varying Model Predictive Control Strategies for Advanced Battery Management Systems |
| title | Design of Piecewise Affine and Linear Time-Varying Model Predictive Control Strategies for Advanced Battery Management Systems |
| title_full | Design of Piecewise Affine and Linear Time-Varying Model Predictive Control Strategies for Advanced Battery Management Systems |
| title_fullStr | Design of Piecewise Affine and Linear Time-Varying Model Predictive Control Strategies for Advanced Battery Management Systems |
| title_full_unstemmed | Design of Piecewise Affine and Linear Time-Varying Model Predictive Control Strategies for Advanced Battery Management Systems |
| title_short | Design of Piecewise Affine and Linear Time-Varying Model Predictive Control Strategies for Advanced Battery Management Systems |
| title_sort | design of piecewise affine and linear time varying model predictive control strategies for advanced battery management systems |
| url | https://hdl.handle.net/1721.1/126338 |
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