A Mixed Continuous-Discrete Approach to Fast Charging of Li-ion Batteries While Maximizing Lifetime
Fast charging studies for lithium-ion batteries aim to minimize charging time while maximizing battery lifetime. Real-time optimal control problems are typically solved using empirical or simplified physical models with constraint-based model predictive control (MPC). In this article, we derive phys...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Elsevier BV
2024
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| Online Access: | https://hdl.handle.net/1721.1/157617 |
| _version_ | 1824458068310622208 |
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| author | Berliner, Marc D Cogswell, Daniel A Bazant, Martin Z Braatz, Richard D |
| author2 | Massachusetts Institute of Technology. Department of Chemical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Chemical Engineering Berliner, Marc D Cogswell, Daniel A Bazant, Martin Z Braatz, Richard D |
| author_sort | Berliner, Marc D |
| collection | MIT |
| description | Fast charging studies for lithium-ion batteries aim to minimize charging time while maximizing battery lifetime. Real-time optimal control problems are typically solved using empirical or simplified physical models with constraint-based model predictive control (MPC). In this article, we derive physics-based operating modes based on degradative governing equations, which are used to ensure safe use and minimal degradation during long-term cycling. The fast-charging protocols are efficiently and deterministically simulated using a mixed continuous-discrete (aka hybrid) approach to fast charging. This simultaneously solves the battery system of equations and the constraint-based control problem. The approach is evaluated using a Porous Electrode Theory-based model that includes solid-electrolyte interface (SEI) capacity fade. Three physics-based charging protocols are compared to a conventional constant current-constant voltage (CC-CV) protocol. Given identical levels of capacity fade after 500 cycles, the physics-based protocols uniformly reach a greater charge capacity compared to CC-CV after charging for 10 and 15 minutes. The computational cost of simulating physics-based charging protocols is only about 30% greater than the CC-CV method. The fast charging framework is easily extendable to other battery models, irrespective of model complexity. |
| first_indexed | 2025-02-19T04:20:01Z |
| format | Article |
| id | mit-1721.1/157617 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2025-02-19T04:20:01Z |
| publishDate | 2024 |
| publisher | Elsevier BV |
| record_format | dspace |
| spelling | mit-1721.1/1576172024-12-21T05:47:57Z A Mixed Continuous-Discrete Approach to Fast Charging of Li-ion Batteries While Maximizing Lifetime Berliner, Marc D Cogswell, Daniel A Bazant, Martin Z Braatz, Richard D Massachusetts Institute of Technology. Department of Chemical Engineering Fast charging studies for lithium-ion batteries aim to minimize charging time while maximizing battery lifetime. Real-time optimal control problems are typically solved using empirical or simplified physical models with constraint-based model predictive control (MPC). In this article, we derive physics-based operating modes based on degradative governing equations, which are used to ensure safe use and minimal degradation during long-term cycling. The fast-charging protocols are efficiently and deterministically simulated using a mixed continuous-discrete (aka hybrid) approach to fast charging. This simultaneously solves the battery system of equations and the constraint-based control problem. The approach is evaluated using a Porous Electrode Theory-based model that includes solid-electrolyte interface (SEI) capacity fade. Three physics-based charging protocols are compared to a conventional constant current-constant voltage (CC-CV) protocol. Given identical levels of capacity fade after 500 cycles, the physics-based protocols uniformly reach a greater charge capacity compared to CC-CV after charging for 10 and 15 minutes. The computational cost of simulating physics-based charging protocols is only about 30% greater than the CC-CV method. The fast charging framework is easily extendable to other battery models, irrespective of model complexity. 2024-11-20T14:41:09Z 2024-11-20T14:41:09Z 2022 2024-11-19T21:06:38Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/157617 Berliner, Marc D, Cogswell, Daniel A, Bazant, Martin Z and Braatz, Richard D. 2022. "A Mixed Continuous-Discrete Approach to Fast Charging of Li-ion Batteries While Maximizing Lifetime." IFAC-PapersOnLine, 55 (30). en 10.1016/j.ifacol.2022.11.070 IFAC-PapersOnLine Creative Commons Attribution-NonCommercial-NoDerivs https://creativecommons.org/licenses/by-nc-nd/4.0/ application/pdf Elsevier BV Elsevier BV |
| spellingShingle | Berliner, Marc D Cogswell, Daniel A Bazant, Martin Z Braatz, Richard D A Mixed Continuous-Discrete Approach to Fast Charging of Li-ion Batteries While Maximizing Lifetime |
| title | A Mixed Continuous-Discrete Approach to Fast Charging of Li-ion Batteries While Maximizing Lifetime |
| title_full | A Mixed Continuous-Discrete Approach to Fast Charging of Li-ion Batteries While Maximizing Lifetime |
| title_fullStr | A Mixed Continuous-Discrete Approach to Fast Charging of Li-ion Batteries While Maximizing Lifetime |
| title_full_unstemmed | A Mixed Continuous-Discrete Approach to Fast Charging of Li-ion Batteries While Maximizing Lifetime |
| title_short | A Mixed Continuous-Discrete Approach to Fast Charging of Li-ion Batteries While Maximizing Lifetime |
| title_sort | mixed continuous discrete approach to fast charging of li ion batteries while maximizing lifetime |
| url | https://hdl.handle.net/1721.1/157617 |
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