Abstract— Typically, the electrochemical model and Equivalent Circuit Model-based (ECM) algorithms of Vanadium Redox Flow Batteries (VRFB) are complex and require high computation-time, thus not suitable to be used in the Battery Management Systems (BMS). Therefore, two simplified fast ECM-based estimation algorithms are proposed for the VRFB’s State of Charge (SoC) estimation. The methods are proposed based on two different parameter identification algorithms, namely discharge pulse response and the optimization-based parameter identification for the first-order ECM. The proposed approaches are further extended by an innovative, simplified mathematical model for the capacity fade of VRFBs based on the battery's electrochemical model. The simplified capacity loss model facilitates non-complex and fast estimation of VRFB’s State of Health (SoH), useful for modeling in the BMS. This has been led to a more accurate SoC estimation in the long-term use of the battery when the VRFB’s capacity fades due to electrolyte volume loss. Although the proposed joint estimation of VRFB’s SoC and SoH estimations are simpler to be modeled in the BMS, the proposed estimations are still accurate since the models consider enough electrochemical details of VRFBs. The accuracy, less complexity, reduced computation-time, and lower BMS memory storage highlight the proposed algorithms.
Keywords—Battery Management System; Battery Parameter Estimation; Energy Storage Systems; Capacity Fade; State of Charge; State of Health; Vanadium Redox Flow Batteries.
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This content will become publicly available on November 1, 2922
Sensorless parameter estimation of vanadium redox flow batteries in charging mode considering capacity fading
ABSTRACT State of Charge (SoC) and discharge capacity of the batteries are parameters that cannot be determined directly from the battery monitoring and control system and requires estimation. Current and voltage sensors have inherent error and delay leading to inaccurate measurements leading to inaccurate SoC and discharge capacity estimations. These sensors also have an additional cost to the battery system. This paper proposes a sensorless approach to estimate parameters of Vanadium Redox Flow Batteries (VRFBs) for both CC and CV charging methods by estimating battery current in CV mode and terminal voltage in CC mode. The results of estimations by the sensorless approach show a maximum relative error of 0.0035 in estimating terminal voltage in CC charging and a maximum relative error of 0.045 in estimating charging current in CV mode. Furthermore, long- term operation of vanadium redox flow batteries causes ion diffusions across the membrane and the depletion of active materials, which leads to capacity fading in VRFBs and inaccurate SoC estimation. To address the inaccuracy of SoC estimation in the long-term use of the battery, the capacity fading model is also considered for VRFBs in this paper. Experimental results show a 19% electrolyte volume change in the positive and negative tanks after 200 cycles of charge/discharge due to the bulk electrolyte transfer between the positive and negative sides of the battery system. This change of electrolyte volume results in 13.73% capacity fading after 200 cycles of charging/discharging. The SoC also changes by 7.1% after 200 cycles, due to the capacity and electrolyte volume loss, which shows the necessity of considering capacity fading in long-term use of the battery.
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- Award ID(s):
- 2039564
- NSF-PAR ID:
- 10229165
- Editor(s):
- Uwe Sauer, Dirk
- Date Published:
- Journal Name:
- Journal of energy storage
- ISSN:
- 2352-152X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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