Abstract
The resulting improved model is both simple and effective, making it specially useful as part of smart control, and energy usage simulations.
| Original language | English |
|---|---|
| Pages | 1-6 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 20 Jul 2017 |
| Event | 12th IEEE PES PowerTech Conference: Towards and Beyond Sustainable Energy Systems - University of Manchester, Manchester, United Kingdom Duration: 18 Jun 2017 → 22 Jul 2017 Conference number: 12 http://ieee-powertech.org/ |
Conference
| Conference | 12th IEEE PES PowerTech Conference |
|---|---|
| Abbreviated title | PowerTech 2017 |
| Country | United Kingdom |
| City | Manchester |
| Period | 18/06/17 → 22/07/17 |
| Internet address |
Fingerprint
Keywords
- Storage
- Predictive model
- Smart grid
- Energy management
Cite this
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A comprehensive model for battery State of Charge prediction. / Homan, Bart ; Smit, Gerardus Johannes Maria; van Leeuwen, Richard Pieter; Ten Kortenaar, Marnix (Contributor).
2017. 1-6 Paper presented at 12th IEEE PES PowerTech Conference, Manchester, United Kingdom.Research output: Contribution to conference › Paper › Academic › peer-review
TY - CONF
T1 - A comprehensive model for battery State of Charge prediction
AU - Homan, Bart
AU - Smit, Gerardus Johannes Maria
AU - van Leeuwen, Richard Pieter
A2 - Ten Kortenaar, Marnix
PY - 2017/7/20
Y1 - 2017/7/20
N2 - In this paper the relatively simple model for State of Charge prediction, based on energy conservation, introduced in [1] is improved and verified. The model as introduced in [1] is verified for Pb-acid, Li-ion and Seasalt batteries. The model is further improved to accommodate the rate capacity effect and the capacity recovery effect, the improvements are verified with lead-acid batteries. For further verification the model is applied on a realistic situation and compared to measurements on the behavior of a real battery in that situation. Furthermore the results are compared to results of the well-established KiBaM model. Predictions on the SoC over time done using the proposed model closely follow the SoC over time calculated from measured data.The resulting improved model is both simple and effective, making it specially useful as part of smart control, and energy usage simulations.
AB - In this paper the relatively simple model for State of Charge prediction, based on energy conservation, introduced in [1] is improved and verified. The model as introduced in [1] is verified for Pb-acid, Li-ion and Seasalt batteries. The model is further improved to accommodate the rate capacity effect and the capacity recovery effect, the improvements are verified with lead-acid batteries. For further verification the model is applied on a realistic situation and compared to measurements on the behavior of a real battery in that situation. Furthermore the results are compared to results of the well-established KiBaM model. Predictions on the SoC over time done using the proposed model closely follow the SoC over time calculated from measured data.The resulting improved model is both simple and effective, making it specially useful as part of smart control, and energy usage simulations.
KW - Storage
KW - Predictive model
KW - Smart grid
KW - Energy management
U2 - 10.1109/PTC.2017.7980943
DO - 10.1109/PTC.2017.7980943
M3 - Paper
SP - 1
EP - 6
ER -