| dc.contributor.author | Northrop, Paul W. C. | |
| dc.contributor.author | Suthar, Bharatkumar | |
| dc.contributor.author | Ramadesigan, Venkatasailanathan | |
| dc.contributor.author | Santhanagopalan, Shriram | |
| dc.contributor.author | Braatz, Richard D. | |
| dc.contributor.author | Subramanian, Venkat R. | |
| dc.date.accessioned | 2014-10-31T17:08:36Z | |
| dc.date.available | 2014-10-31T17:08:36Z | |
| dc.date.issued | 2014-05 | |
| dc.date.submitted | 2014-04 | |
| dc.identifier.issn | 0013-4651 | |
| dc.identifier.issn | 1945-7111 | |
| dc.identifier.uri | http://hdl.handle.net/1721.1/91252 | |
| dc.description.abstract | Improving the efficiency and utilization of battery systems can increase the viability and cost-effectiveness of existing technologies for electric vehicles (EVs). Developing smarter battery management systems and advanced sensing technologies can circumvent problems arising due to capacity fade and safety concerns. This paper describes how efficient simulation techniques and improved algorithms can alleviate some of these problems to help electrify the transportation industry by improving the range of variables that are predictable and controllable in a battery in real-time within an electric vehicle. The use of battery models in a battery management system (BMS) is reviewed. The effect of different simulation techniques on computational cost and accuracy are also compared, and the validity of implementation in a microcontroller environment for model predictive control (MPC) is addressed. Using mathematical techniques to add more physics without losing efficiency is also discussed. | en_US |
| dc.description.sponsorship | United States. Defense Advanced Research Projects Agency (Energy (ARPA-E) award #DE-AR0000275) | en_US |
| dc.language.iso | en_US | |
| dc.publisher | Electrochemical Society | en_US |
| dc.relation.isversionof | http://dx.doi.org/10.1149/2.018408jes | en_US |
| dc.rights | 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. | en_US |
| dc.source | MIT web domain | en_US |
| dc.title | Efficient Simulation and Reformulation of Lithium-Ion Battery Models for Enabling Electric Transportation | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Northrop, P. W. C., B. Suthar, V. Ramadesigan, S. Santhanagopalan, R. D. Braatz, and V. R. Subramanian. “Efficient Simulation and Reformulation of Lithium-Ion Battery Models for Enabling Electric Transportation.” Journal of the Electrochemical Society 161, no. 8 (January 1, 2014): E3149–E3157. | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Chemical Engineering | en_US |
| dc.contributor.mitauthor | Braatz, Richard D. | en_US |
| dc.relation.journal | Journal of the Electrochemical Society | en_US |
| dc.eprint.version | Final published version | en_US |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
| eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
| dspace.orderedauthors | Northrop, P. W. C.; Suthar, B.; Ramadesigan, V.; Santhanagopalan, S.; Braatz, R. D.; Subramanian, V. R. | en_US |
| dc.identifier.orcid | https://orcid.org/0000-0003-4304-3484 | |
| mit.license | PUBLISHER_POLICY | en_US |
| mit.metadata.status | Complete | |