Model-Based Condition Monitoring of a Vanadium Redox Flow Battery

Abstract

The safe, efficient and durable utilization of a vanadium redox flow battery (VRB) requires accurate monitoring of its state of charge (SOC) and capacity decay. This paper focuses on the unbiased model parameter identification and model-based monitoring of both the SOC and capacity decay of a VRB. Specifically, a first-order resistor-capacitance (RC) model was used to simulate the dynamics of the VRB. A recursive total least squares (RTLS) method was exploited to attenuate the impact of external disturbances and accurately track the change of model parameters in realtime. The RTLS-based identification method was further integrated with an H-infinity filter (HIF)-based state estimator to monitor the SOC and capacity decay of the VRB in real-time. Experiments were carried out to validate the proposed method. The results suggested that the proposed method can achieve unbiased model parameter identification when unexpected noises corrupt the current and voltage measurements. SOC and capacity decay can also be estimated accurately in real-time without requiring additional open-circuit cells.Energies 2019, 12, 3005 2 of 16 the SOC [9]. This method, albeit accurate, is ex-situ and not suitable for real-time application. In a recent study, the electrolyte viscosity-determined by measuring the pressure drop across the VRB cell-was used to estimate the SOC [10]. This method demonstrated good potential for online SOC monitoring, although the quantitative relationships among SOC, viscosity, and pressure drop have to be calibrated accurately to ensure a reliable estimate. Uncertainties associated with other environmental or operating conditions also have to be ruled out.A new category of methods for SOC estimation of VRBs is the model-based observers. Firstly, a battery model is established to describe the inner physical processes and electrochemical reactions [11,12]. A typical model-based observer then links the measurable input and output to the internal state via a nonlinear state-space model [13]. This can provide a closed-loop and robust solution, which is favourable for online application, although a highly accurate battery model is a prerequisite. Different types of models have been proposed for VRBs. Numerical models [14][15][16] can describe the complicated electrochemical processes and multi-physics feature of a VRB well, but the high computing cost restricts their use in real-time application. Tang et al. developed a simplified mathematical model to describe the key processes of a VRB [17]. However, the model parameters involved had to be determined empirically based on extensive testing and knowledge of the VRB's dynamics. In contrast to mechanism-based models, equivalent circuit models (ECMs) show an expected trade-off between the computing complexity and the model accuracy. A simple ECM has been proposed for system-level integration, although this overlooks the dynamic variability of VRBs [18][19][20]. More recently, first-order [21-23] and second-order [24,25] RC models were developed to take into account the ...

Transient Modeling of a Vanadium Redox Flow Battery and Real-Time Monitoring of Its Capacity and State of Charge

“…As the voltage measurement, especially for the range considered in this work, is a matured technology, uncertainty in its measurement is low. It is assumed that the cell voltage measurement has a standard deviation of 10 mV . For both capacity and SOC models, the process noise is assumed to be 1%.…”

“…It is assumed that the cell voltage measurement has a standard deviation of 10 mV. 72 For both capacity and SOC models, the process noise is assumed to be 1%. The identified model used in KF is ∼25 times faster compared to the nonlinear 2D model.…”

“…Tang et al proposed a simplified mathematical model by considering the key processes of VRFB, where the model parameters are to be determined analytically based on factors like SOC, current, and operating temperature. One popular approach is to use equivalent-circuit models (ECMs) overlooking the physics and chemistry of battery systems. − First-order ,, and second-order ,, RC (resistance capacitance) ECMs were developed by taking into account the polarization effects in VRFBs. Skyllas-Kazacos and Wei developed an extended Kalman filter (EKF) approach to estimate SOC using ECM.…”

Redox Flow Batteries: A Literature Review Oriented to Automatic Control

“…Table 6 contains a classification of most relevant RFB models. Equivalent circuit [118][119][120] A VRFB system, can be mainly separated in three different physical models, which are the electrochemical, the thermal and the hydraulic. All of them are interconnected.…”

“…An electric circuit model is used in [118,119] to model the state of charge. Another study that uses this type of model to monitor the capacity decay of the VRFB is [120].…”