Abstract
A new battery modelling method is presented based on the simulation error minimization criterion rather than the conventional prediction error criterion. A new integrated optimization method to optimize the model parameters is proposed. This new method is validated on a set of Li ion battery test data, and the results confirm the advantages of the proposed method in terms of the model generalization performance and long-term prediction accuracy.
| Original language | English |
|---|---|
| Title of host publication | PES General Meeting: Conference & Exposition, 2014 IEEE |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Number of pages | 5 |
| ISBN (Electronic) | 9781479964154 |
| DOIs | |
| Publication status | Published - 31 Jul 2014 |
| Event | IEEE Power & Energy Society General Meeting, 2014 (PES 14) - USA, Washington DC, United States Duration: 27 Jul 2014 → 31 Jul 2014 |
Conference
| Conference | IEEE Power & Energy Society General Meeting, 2014 (PES 14) |
|---|---|
| Country/Territory | United States |
| City | Washington DC |
| Period | 27/07/2014 → 31/07/2014 |
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