Abstract
| Language | English |
|---|---|
| Pages | 205-217 |
| Number of pages | 13 |
| Journal | Energy |
| Volume | 171 |
| DOIs | |
| Publication status | Published - 15 Mar 2019 |
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Keywords
- Hybride deal
- Li-poly battery
- LiFePo battery
- State-of-Charge Prediction
- Energy management
- Pb-acid battery
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A realistic model for battery state of charge prediction in energy management simulation tools. / Homan, Bart (Corresponding Author); Ten Kortenaar, Marnix; Hurink, Johann L.; Smit, Gerard J.M.
In: Energy, Vol. 171, 15.03.2019, p. 205-217.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - A realistic model for battery state of charge prediction in energy management simulation tools
AU - Homan, Bart
AU - Ten Kortenaar, Marnix
AU - Hurink, Johann L.
AU - Smit, Gerard J.M.
N1 - Elsevier deal
PY - 2019/3/15
Y1 - 2019/3/15
N2 - In this paper, a comprehensive model for the prediction of the state of charge of a battery is presented. This model has been specifically designed to be used in simulation tools for energy management in (smart) grids. Hence, this model is a compromise between simplicity, accuracy and broad applicability. The model is verified using measurements on three types of Lead-acid (Pb-acid) batteries, a Lithium-ion Polymer (Li-Poly) battery and a Lithium Iron-phosphate (LiFePo) battery. For the Pb-acid batteries the state of charge is predicted for typical scenarios, and these predictions are compared to measurements on the Pb-acid batteries and to predictions made using the KiBaM model. The results show that it is possible to accurately model the state of charge of these batteries, where the difference between the model and the state of charge calculated from measurements is less than 5%. Similarly the model is used to predict the state of charge of Li-Poly and LiFePo batteries in typical scenarios. These predictions are compared to the state of charge calculated from measurements, and it is shown that it is also possible to accurately model the state of charge of both Li-Poly and LiFePo batteries. In the case of the Li-Poly battery the difference between the measured and predicted state of charge is less than 5% and in the case of the LiFePo battery this difference is less than 3%.
AB - In this paper, a comprehensive model for the prediction of the state of charge of a battery is presented. This model has been specifically designed to be used in simulation tools for energy management in (smart) grids. Hence, this model is a compromise between simplicity, accuracy and broad applicability. The model is verified using measurements on three types of Lead-acid (Pb-acid) batteries, a Lithium-ion Polymer (Li-Poly) battery and a Lithium Iron-phosphate (LiFePo) battery. For the Pb-acid batteries the state of charge is predicted for typical scenarios, and these predictions are compared to measurements on the Pb-acid batteries and to predictions made using the KiBaM model. The results show that it is possible to accurately model the state of charge of these batteries, where the difference between the model and the state of charge calculated from measurements is less than 5%. Similarly the model is used to predict the state of charge of Li-Poly and LiFePo batteries in typical scenarios. These predictions are compared to the state of charge calculated from measurements, and it is shown that it is also possible to accurately model the state of charge of both Li-Poly and LiFePo batteries. In the case of the Li-Poly battery the difference between the measured and predicted state of charge is less than 5% and in the case of the LiFePo battery this difference is less than 3%.
KW - Hybride deal
KW - Li-poly battery
KW - LiFePo battery
KW - State-of-Charge Prediction
KW - Energy management
KW - Pb-acid battery
UR - http://www.scopus.com/inward/record.url?scp=85059818514&partnerID=8YFLogxK
U2 - 10.1016/j.energy.2018.12.134
DO - 10.1016/j.energy.2018.12.134
M3 - Article
VL - 171
SP - 205
EP - 217
JO - Energy
T2 - Energy
JF - Energy
SN - 0360-5442
ER -