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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chenguang Jiang Taylor, A. Chen Duan Bai, K. |
| Copyright Year | 2013 |
| Description | Author affiliation: Dept. of Electr. & Comput. Eng., Kettering Univ., Flint, MI, USA (Chenguang Jiang; Taylor, A.; Chen Duan; Bai, K.) |
| Abstract | This paper proposed a battery state of charge (SOC) estimation methodology utilizing the Extended Kalman Filter. First, Extended Kalman Filter for Li-ion battery SOC was mathematically designed. Next, simulation models were developed in MATLAB/Simulink, which indicated that the battery SOC estimation with Extended Kalman filter is much more accurate than that from Coulomb Counting method. This is coincident with the mathematical analysis. At the end, a test bench with Lithium-Ion batteries was set up to experimentally verify the theoretical analysis and simulation. Experimental results showed that the average SOC estimation error using Extended Kalman Filter is <;1%. |
| Sponsorship | IEEE |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 1130597 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781479901463 |
| e-ISBN | 9781479901487 |
| DOI | 10.1109/ITEC.2013.6573477 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-06-16 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Software packages Kalman Filter Electric Vehicles State of Charge(SOC) Li-ion Battery System-on-chip Kalman filters Indexes |
| Content Type | Text |
| Resource Type | Article |
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