Development and validation of a real time flow control integrated MPPT charger for solar PV applications of vanadium redox flow battery

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.

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A Flexible 5-In-1 Microsensor for Internal Microscopic Diagnosis of Vanadium Redox Flow Battery Charging Process

Sensors ◽

10.3390/s19051030 ◽

2019 ◽

Vol 19 (5) ◽

pp. 1030 ◽

Cited By ~ 2

Author(s):

Chi-Yuan Lee ◽

Chin-Lung Hsieh ◽

Chia-Hung Chen ◽

Yen-Pu Huang ◽

Chong-An Jiang ◽

...

Keyword(s):

Real Time ◽

Vanadium Redox Flow Battery ◽

Optimum Operating ◽

Physical Parameters ◽

Redox Flow Battery ◽

Flow Battery ◽

Mems Technology ◽

Microscopic Diagnosis ◽

Vanadium Redox ◽

Physical Quantities

Multiple important physical parameters in the vanadium redox flow battery are difficult to measure accurately, and the multiple important physical parameters (e.g., temperature, flow, voltage, current, pressure, and electrolyte concentration) are correlated with each other; all of them have a critical influence on the performance and life of vanadium redox flow battery. In terms of the feed of fuel to vanadium redox flow battery, the pump conveys electrolytes from the outside to inside for reaction. As the performance of vanadium redox flow battery can be tested only by an external machine—after which, the speed of pump is adjusted to control the flow velocity of electrolyte—the optimum performance cannot be obtained. There is a demand for internal real-time microscopic diagnosis of vanadium redox flow batteries, and this study uses micro-electro-mechanical systems (MEMS) technology to develop a flexible five-in-one (temperature, flow, voltage, current, and pressure) microsensor, which is embedded in vanadium redox flow battery, for real-time sensing. Its advantages include: (1) Small size and the simultaneous measurement of five important physical quantities; (2) elastic measurement position and accurate embedding; and (3) high accuracy, sensitivity, and quick response time. The flexible five-in-one microsensor embedded in the vanadium redox flow battery can instantly monitor the changes in different physical quantities in the vanadium redox flow battery during charging; as such, optimum operating parameters can be found out so that performance and life can be enhancec.

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Internal real-time microscopic diagnosis of vanadium redox flow battery

Sensors and Actuators A Physical ◽

10.1016/j.sna.2020.112259 ◽

2020 ◽

Vol 314 ◽

pp. 112259

Author(s):

Chi-Yuan Lee ◽

Shuo-Jen Lee ◽

Chia-Hung Chen ◽

Chin-Lung Hsieh ◽

Shih-Hao Wen ◽

...

Keyword(s):

Real Time ◽

Vanadium Redox Flow Battery ◽

Redox Flow Battery ◽

Flow Battery ◽

Microscopic Diagnosis ◽

Vanadium Redox

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Application of flexible integrated microsensor to internal real-time measurement of vanadium redox flow battery

Sensors and Actuators A Physical ◽

10.1016/j.sna.2017.10.011 ◽

2017 ◽

Vol 267 ◽

pp. 135-141 ◽

Cited By ~ 2

Author(s):

Chi-Yuan Lee ◽

Chong-An Jiang ◽

Chin-Lung Hsieh ◽

Chia-Hung Chen ◽

Kin-Fu Lin ◽

...

Keyword(s):

Real Time ◽

Time Measurement ◽

Vanadium Redox Flow Battery ◽

Redox Flow Battery ◽

Flow Battery ◽

Real Time Measurement ◽

Vanadium Redox

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Real-time monitoring of capacity loss for vanadium redox flow battery

Journal of Power Sources ◽

10.1016/j.jpowsour.2018.04.063 ◽

2018 ◽

Vol 390 ◽

pp. 261-269 ◽

Cited By ~ 51

Author(s):

Zhongbao Wei ◽

Arjun Bhattarai ◽

Changfu Zou ◽

Shujuan Meng ◽

Tuti Mariana Lim ◽

...

Keyword(s):

Real Time ◽

Vanadium Redox Flow Battery ◽

Redox Flow Battery ◽

Real Time Monitoring ◽

Flow Battery ◽

Capacity Loss ◽

Vanadium Redox

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A Neural Network Based Method for Real-Time Measurement of Capacity and SOC of Vanadium Redox Flow Battery

ASME 2015 13th International Conference on Fuel Cell Science, Engineering and Technology ◽

10.1115/fuelcell2015-49305 ◽

2015 ◽

Author(s):

Hongfei Cao ◽

Xinjian Zhu ◽

Haifeng Shen ◽

Meng Shao

Keyword(s):

Neural Network ◽

Real Time ◽

Probabilistic Neural Network ◽

Average Power ◽

Vanadium Redox Flow Battery ◽

Redox Flow Battery ◽

Flow Battery ◽

Time Operation ◽

Remaining Capacity ◽

Vanadium Redox

The state of charge (SOC) of Vanadium Redox Flow Battery (VRFB) plays an important role in the operation and control of the Battery system. The value of SOC can be defined as the ratio of the remaining capacity to the rated capacity of the battery. Current measurement of SOC of VRFB is limited to one certain charge-discharge circulation so the rated capacity is known and can be regarded as a constant. However, during long time cycling, the capacity of VRFB will reduce gradually to a relatively low level so that the capacity of the battery cannot be seen as the constant value of rated capacity, which makes it difficult to measure the SOC accurately in real-time operation. This work presents a neural network based method of measuring the capacity and SOC for VRFB in real time. The capacity is firstly classified into three levels in terms of the loss degree by a Probabilistic Neural Network (PNN) using the values of the voltage per second and the average power of the cell stack in any period of the circulation. The values of capacity which fall within different levels are then given by different Back Propagation Neural Networks (BPNN) trained by the battery operation values in corresponding level. Finally, the SOC can be obtained by the calculated capacity. All the networks are validated by experimental data and the results indicate that the method is suitable for the measurement of VRFB capacity and SOC in the practical application.

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A Novel State of Charge Estimating Scheme Based on an Air-Gap Fiber Interferometer Sensor for the Vanadium Redox Flow Battery

Energies ◽

10.3390/en13020291 ◽

2020 ◽

Vol 13 (2) ◽

pp. 291 ◽

Cited By ~ 1

Author(s):

Chao-Tsung Ma

Keyword(s):

Real Time ◽

Remote Monitoring ◽

Strong Acid ◽

Air Gap ◽

The State ◽

State Of Charge ◽

Vanadium Redox Flow Battery ◽

Redox Flow Battery ◽

Flow Battery ◽

Vanadium Redox

Real-time and remote monitoring of the state of charge (SOC) of a vanadium redox flow battery (VRFB) is technically desirable for achieving advanced compensation functions of VRFB systems. This paper, for the first time, proposes a novel SOC monitoring scheme based on an air-gap fiber Fabry–Perot interferometer (AGFFPI) sensor for the VRFB. The proposed sensing concept is based on real-time sensing of the refractive index (RI) of the positive electrolyte, which is found closely correlated to the VRFB’s SOC. The proposed SOC estimating scheme using fiber sensor has a number of merits, e.g., being precise, having lightweight, having strong acid resistance, and being easy to incorporate the state-of-the-art fiber communication technology for remote monitoring. It is found that the RI of the positive electrolyte solution exhibits distinct and linear variations in accordance with changes of the VRFB’s SOC value. Using the linear relationship between the electrolyte’s RI and SOC, a real-time SOC monitoring mechanism can be readily realized by the proposed AGFFPI. In this paper, existing SOC detecting methods for VRFB are firstly reviewed. The details concerning the proposed detecting method are then addressed. Typical experimental results are presented to verify the feasibility and effectiveness of the proposed SOC estimating scheme.

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