Online state of charge and model parameter co-estimation based on a novel multi-timescale estimator for vanadium redox flow battery

Applied Energy

Volumn 172, Issue , 2016, Pages 169-179

  Wei, Zhongbao ^a   Lim, Tuti Mariana ^b   Skyllas Kazacos, Maria ^c   Wai, Nyunt ^a   Tseng, King Jet ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^c UNIVERSITY OF NEW SOUTH WALES   (Australia)

Author keywords

Battery model; Lithium ion battery; Multi timescale; Parameters identification; State of charge estimation; Vanadium redox flow battery

Indexed keywords

CHARGING (BATTERIES); ELECTRIC BATTERIES; FLOW BATTERIES; INFORMATION MANAGEMENT; LITHIUM ALLOYS; LITHIUM-ION BATTERIES; PARAMETER ESTIMATION; SECONDARY BATTERIES; VANADIUM;

BATTERY MODELING; PARAMETERS IDENTIFICATION; STATE-OF-CHARGE ESTIMATION; TIME-SCALES; VANADIUM REDOX FLOW BATTERIES;

BATTERY MANAGEMENT SYSTEMS;

AGING; CALIBRATION; CHEMICAL COMPOSITION; EXPERIMENTAL STUDY; INFORMATION MANAGEMENT; MODEL TEST; REDOX POTENTIAL; VANADIUM;

EID: 84961894470     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2016.03.103     Document Type: Article

References (35)

1. Sum E., Rychcik M., Skyllas-kazacos M. Investigation of the V(V)/V(IV) system for use in the positive half-cell of a redox battery. J Power Sour 1985, 16:85-95.
2. Skyllas-Kazacos M., Rychcik M., Robins R.G., Fane A.G., Green M.A. New all-vanadium redox flow cell. J Electrochem Soc 1986, 133:1057-1058.
3. Skyllas-Kazacos M., Kazacos G., Poon G., Verseema H. Recent advances with UNSW vanadium-based redox flow batteries. Int J Energy Res 2010, 34:182-189.
4. Mohamed M.R., Leung P.K., Sulaiman M.H. Performance characterization of a vanadium redox flow battery at different operating parameters under a standardized test-bed system. Appl Energy 2015, 137:402-412.
5. Roe S., Menictas C., Skyllas-Kazacos M. A high energy density vanadium redox flow battery with 3 M vanadium electrolyte. J Electrochem Soc 2016, 163:A5023-A5028.
6. Wei X., Nie Z., Luo Q., Li B., Chen B., Simmons K., et al. Nanoporous polytetrafluoroethylene/silica composite separator as a high-performance all-vanadium redox flow battery membrane. Adv Energy Mater 2013, 3:1215-1220.
7. Leung P.K., Mohamed M.R., Shah A.A., Xu Q., Conde-Duran M.B. A mixed acid based vanadium-cerium redox flow battery with a zero-gap serpentine architecture. J Power Sour 2015, 274:651-658.
8. Skyllas-Kazacos M., Kazacos M. State of charge monitoring methods for vanadium redox flow battery control. J Power Sour 2011, 196:8822-8827.
9. Corcuera S., Skyllas-Kazacos M. State-of-charge monitoring and electrolyte rebalancing methods for the vanadium redox flow battery. Eur Chem Bull 2012, 1:511-519.
10. Mohamed M.R., Ahmad H., Seman M.N. Estimating the state-of-charge of all-vanadium redox flow battery using a divided. Open-circuit potentiometric cell. Elektron Elektrotech 2013, 19:37-42.
11. Wang Y.J., Zhang C.B., Chen Z.H. A method for state-of-charge estimation of Li-ion batteries based on multi-model switching strategy. Appl Energy 2015, 137:427-434.
12. Zou Y., Hu X.S., Ma H.M., Li S.E. Combined state of charge and state of health estimation over lithium-ion battery cell cycle lifespan for electric vehicles. J Power Sour 2015, 273:793-803.
13. Yang F.F., Xing Y.J., Wang D., Tsui K.L. A comparative study of three model-based algorithms for estimating state-of-charge of lithium-ion batteries under a new combined dynamic loading profile. Appl Energy 2016, 164:387-399.
14. He H.W., Xiong R., Peng J.K. Real-time estimation of battery state-of-charge with unscented Kalman filter and RTOS μCOS-II platform. Appl Energy 2016, 162:1410-1418.
15. 4 batteries at dynamic currents and temperatures using particle filter. J Power Sour 2015, 279:306-311.
16. 4 batteries. Appl Energy 2014, 135:81-87.
17. Wang Y.J., Zhang C.B., Chen Z.H. On-line battery state-of-charge estimation based on an integrated estimator. Appl Energy 2015, 10.1016/j.apenergy.2015.09.015.
18. Zhang C.P., Wang L.Y., Li X., Chen W., Yin G., Jiang J.C. Robust and adaptive estimation of state of charge for lithium-ion batteries. IEEE Trans Ind Electron 2015, 62:4948-4957.
19. Hua Y., Xu M., Li M., Ma C.B., Zhao C. Estimation of state of charge for two types of lithium-ion batteries by nonlinear predictive filter for electric vehicles. Energies 2015, 8:3556-3577.
20. 4 batteries based on a dual-circuit state observer. J Power Sour 2015, 296:23-29.
21. Lin C., Mu H., Xiong R., Shen W.X. A novel multi-model probability battery state of charge estimation approach for electric vehicles using H-infinity algorithm. Appl Energy 2016, 166:76-83.
22. Wei Z.B., Zhao J.Y., Skyllas-Kazacos M., Xiong B.Y. Dynamic thermal-hydraulic modeling and stack flow pattern analysis for all-vanadium redox flow battery. J Power Sour 2014, 260:89-99.
23. Wei Z.B., Zhao J.Y., Xiong B.Y. Dynamic electro-thermal modeling of all-vanadium redox flow battery with forced cooling strategies. Appl Energy 2014, 135:1-10.
24. Xiong B.Y., Zhao J.Y., Wei Z.B., Skyllas-Kazacos M. Extended Kalman filter method for state of charge estimation of vanadium redox flow battery using thermal-dependent electrical model. J Power Sour 2014, 262:50-61.
25. Zhang Y., Zhao J.Y., Wang P., Skyllas-Kazacos M., Xiong B.Y., Badrinarayanan R. A comprehensive equivalent circuit model of all-vanadium redox flow battery for power system analysis. J Power Sour 2015, 290:14-24.
26. Mohamed M.R., Ahmad H., Seman M.N., Razali S., Najib M.S. Electrical circuit model of a vanadium redox flow battery using extended Kalman filter. J Power Sour 2013, 239:284-293.
27. 4 batteries using a novel open-circuit voltage at various ambient temperatures. Energies 2015, 8:2950-2976.
28. Feng T.H., Yang L., Zhao X.W., Zhang H.D., Qiang J.X. Online identification of lithium-ion battery parameters based on an improved equivalent-circuit model and its implementation on battery state-of-power prediction. J Power Sour 2015, 281:192-203.
29. Xiong R., Sun F.C., Chen Z., He H.W. A data-driven multi-scale extended Kalman filtering based parameter and state estimation approach of lithium-ion olymer battery in electric vehicles. Appl Energy 2014, 113:463-476.
30. Xiong R., Sun F.C., Gong X.Z., Gao C.C. A data-driven based adaptive state of charge estimator of lithium-ion polymer battery used in electric vehicles. Appl Energy 2014, 113:1421-1433.
31. 4 battery using invariant imbedding method. Appl Energy 2016, 162:163-171.
32. 4 batteries in electric vehicles. Appl Energy 2012, 89:413-420.
33. Åström K.J., Wittenmark B. Adaptive control 2013, Courier Corporation.
34. Wei Z.B., Li X.L., Xu L.J., Cheng Y.T. Comparative study of computational intelligence approaches for NOx reduction of coal-fired boiler. Energy 2013, 55:683-692.
35. Luo Q., Li L., Wang W., Nie Z., Wei X., Li B., et al. Capacity decay and remediation of Nafion-based all-vanadium redox flow batteries. ChemSusChem 2013, 6:268-274.