Abstract
In recent years, lithium iron phosphate batteries have become widespread energy sources for high-power automotive and storage applications. The efficient use of such applications require an accurate information about the battery's state of charge. Unfortunately, the battery's open circuit voltage shows a nonlinear and in wide areas flat dependence on the state of charge and is significantly influenced by hysteresis phenomena. As a result, the unique determination of the state of charge using the open circuit voltage is hampered. This work deals with a dual estimation approach utilizing a sequential Monte-Carlo method in connection with a marginalization technique to provide an accurate estimation of the battery's state of charge. In order to circumvent the hysteresis induced ambiguous mapping between the state of charge and the open circuit voltage, a nonlinear hysteresis state is introduced.
Originalsprache | Deutsch (Österreich) |
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Titel | 2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings |
Seiten | 1-6 |
Seitenumfang | 6 |
DOIs | |
Publikationsstatus | Veröffentlicht - 26 Mai 2016 |
Extern publiziert | Ja |
Veranstaltung | 2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings - Taipei, Taiwan Dauer: 23 Mai 2016 → 26 Mai 2016 |
Konferenz
Konferenz | 2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings |
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Zeitraum | 23/05/16 → 26/05/16 |
Schlagwörter
- Batteries
- Integrated circuit modeling
- State of charge
- Hysteresis
- Voltage measurement
- Estimation
- Kalman filters