Abstract
This paper presents new methods for improving state of charge (SOC) estimation accuracy for Lithium Ion battery cells connected in series. The methods benefit from the fact that the cells share a common current trajectory. These methods extend previously studied techniques for SOC estimation, like the Extended Kalman Filter. While the existing literature focuses on estimating SOC for individual cells separately, we consider the cells in a series string collectively. We show that estimation accuracy is increased for cells in series both when they are 1) balanced and 2) un-balanced. We validate these methods against a control case using Monte Carlo simulation.
| Original language | English (US) |
|---|---|
| Title of host publication | 2014 American Control Conference, ACC 2014 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 254-259 |
| Number of pages | 6 |
| ISBN (Print) | 9781479932726 |
| DOIs | |
| State | Published - Jan 1 2014 |
| Event | 2014 American Control Conference, ACC 2014 - Portland, OR, United States Duration: Jun 4 2014 → Jun 6 2014 |
Publication series
| Name | Proceedings of the American Control Conference |
|---|---|
| ISSN (Print) | 0743-1619 |
Other
| Other | 2014 American Control Conference, ACC 2014 |
|---|---|
| Country/Territory | United States |
| City | Portland, OR |
| Period | 6/4/14 → 6/6/14 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering
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