Real-time monitoring of the state of charge (SOC) in vanadium redox-flow batteries using UV–Vis spectroscopy in operando mode

Shin, Kyoung-Hee; Jin, Chang-Soo; So, Jae-Young; Park, Se-Kook; Kim, Dong-Ha; Yeon, Sun-Hwa

doi:10.1016/j.est.2019.101066

Cited by 48 publications

(21 citation statements)

References 35 publications

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“…Capacity loss due to side reactions (e.g.,

oxidation) must be corrected via chemical or electrochemical rebalancing of the oxidation states [ 31 , 35 , 36 ]. Accounting for these losses allows the electrolyte to be used and its indefinite life to be maintained [ 36 ]. To achieve this, a suitable monitoring method is required to detect state of charge imbalances.…”

Section: Introductionmentioning

confidence: 99%

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A High-Resolution Reflective Microwave Planar Sensor for Sensing of Vanadium Electrolyte

Kazemi

Schofield

Musilek

2021

Sensors

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Microwave planar sensors employ conventional passive complementary split ring resonators (CSRR) as their sensitive region. In this work, a novel planar reflective sensor is introduced that deploys CSRRs as the front-end sensing element at fres=6 GHz with an extra loss-compensating negative resistance that restores the dissipated power in the sensor that is used in dielectric material characterization. It is shown that the S11 notch of −15 dB can be improved down to −40 dB without loss of sensitivity. An application of this design is shown in discriminating different states of vanadium redox solutions with highly lossy conditions of fully charged V5+ and fully discharged V4+ electrolytes.

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“…Capacity loss due to side reactions (e.g.,

Section: Introductionmentioning

confidence: 99%

“…To achieve this, a suitable monitoring method is required to detect state of charge imbalances. Open-circuit voltage is one of the most widely used techniques; however, this produces inaccuracies due to the incomplete representation of the electrode potential, and is only accurate in a balanced system [ 35 , 36 , 37 ].…”

Section: Introductionmentioning

confidence: 99%

A High-Resolution Reflective Microwave Planar Sensor for Sensing of Vanadium Electrolyte

Kazemi

Schofield

Musilek

2021

Sensors

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“…The peak at 380 nm was assigned to Cr (III) [37], which corresponds to the FeCr 2 O 4 phase. The peak at 482 nm was assigned to V=O stretching, which confirmed the existence of V (IV) and V (V) [38,39].…”

Section: Direct-acid-leaching Processmentioning

confidence: 69%

Efficient Recovery of Vanadium from High-Chromium Vanadium Slag with Calcium-Roasting Acidic Leaching

Peng

Shi

et al. 2022

Minerals

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High-chromium vanadium slag (HCVS) is an important by-product generated during the smelting process of high-chromium-vanadium-titanium-magnetite. Direct acid leaching and calcium-roasting acid leaching technology were applied to recover vanadium and chromium from HCVS. The effects of experimental parameters on the leaching process, including concentration of H2SO4, reaction temperature, reaction time, and liquid-to-solid ratio, were investigated. The XRD and UV-Vis DRS results showed that vanadium and chromium existed in low valence with a spinel structure in the HCVS. The Cr-spinel was too stable to leach out; no more than 8% of the chromium could be leached out both in the direct acid leaching process and calcium-roasting acid-leaching process. Most low valence vanadium could be oxidized to high valence with calcium-roasting technology, and the leaching efficiency could be increased from 33.89% to 89.12% at the selected reaction conditions: concentration of H2SO4 at 40 vt.%, reaction temperature of 90 °C, reaction time of 3 h, liquid-to-solid ratio of 4:1 mL/g, and stirring rate of 500 rpm. The kinetics analysis indicated that the leaching behavior of vanadium followed the shrinking core model well, and the leaching process was controlled by the surface chemical reaction, with an Ea of 58.95 kJ/mol and 62.98 kJ/mol for direct acid leaching and roasting acid leaching, respectively.

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“…Three statistical measures are used to evaluate our method, including the absolute mean error (MAE), the root mean squared error (RMSE) and mean absolute percentage error (MAPE). These values are calculated by formula (15), (16), (17) respectively. RMSE and MAPE describe how close the prediction value and the true value are.…”

Section: Experiments and Discussionmentioning

confidence: 99%

“…The latter is typically represented by the SOC. Nevertheless, battery degradation makes it difficult to create a direct linkage between remaining energy and SOC [17,22]. Though the Coulomb counting is developed widespread for SOC estimation in commercial battery management systems (BMSs), this method is sensitive to noise, parameter uncertainties, and deviation in initialization [23].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning-Based Method for Remaining Range Prediction of Electric Vehicles

et al. 2020

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Limited driving range is one of the major obstacles to the widespread application of electric vehicles (EVs). Accurately predicting the remaining driving range can effectively reduce the range anxiety of drivers. In this paper, a blended machine learning model was proposed to predict the remaining driving range of EVs based on real-world historical driving data. The blended model fuses two advanced machine learning algorithms of Extreme Gradient Boosting Regression Tree (XGBoost) and Light Gradient Boosting Regression Tree (LightGBM). The proposed model was trained to "learn" the relationship between the driving distance and the proposed features such as cumulative output energy of the motor and the battery, different driving patterns, and temperature of the battery). In addition, an "anchor (baseline) based" strategy was proposed and was seen to be able to effectively eliminate the unbalance distribution of dataset. The results of experiments suggest that our proposed anchor-based blended model has better performances with a smaller prediction error range of [-0.8, 0.8] as compared with previous methods. INDEX TERMS electric vehicle, remaining driving range estimation, machine learning, data mining.

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Real-time monitoring of the state of charge (SOC) in vanadium redox-flow batteries using UV–Vis spectroscopy in operando mode

Cited by 48 publications

References 35 publications

A High-Resolution Reflective Microwave Planar Sensor for Sensing of Vanadium Electrolyte

A High-Resolution Reflective Microwave Planar Sensor for Sensing of Vanadium Electrolyte

Efficient Recovery of Vanadium from High-Chromium Vanadium Slag with Calcium-Roasting Acidic Leaching

Machine Learning-Based Method for Remaining Range Prediction of Electric Vehicles

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