Name
Title | ||
|---|---|---|
Lebesgue Sampling-Based Li-Ion Battery Simplified First Principle Model for SOC Estimation and RDT Prediction |
Abstract | ||
|---|---|---|
The state-of-charge (SOC) estimation and remaining-dischargeable-time (RDT) prediction are critical and challenging to safe operation of Li-ion batteries. The main challenges are the limited accuracy of traditional equivalent circuit model and computation-inefficiency of electrochemical battery models. To address this problem, this article proposes a Lebesgue-sampling-based extended Kalman filter ... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TIE.2021.3114699 | IEEE Transactions on Industrial Electronics |
Keywords | DocType | Volume |
Batteries,State of charge,Estimation,Computational modeling,Predictive models,Integrated circuit modeling,Prediction algorithms | Journal | 69 |
Issue | ISSN | Citations |
9 | 0278-0046 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Enhui Liu | 1 | 0 | 2.03 |
| Xuan Wang | 2 | 1 | 2.06 |
| Guangxing Niu | 3 | 4 | 4.15 |
| Dongzhen Lyu | 4 | 0 | 0.34 |
| Tao Yang | 5 | 160 | 76.32 |
| Bin Zhang | 6 | 2 | 1.74 |