Equivalent hysteresis model based SOC estimation with variable parameters considering temperature
Tóm tắt
Từ khóa
Tài liệu tham khảo
Cheng, M., Tong, M.H.: Development status and trend of electric vehicles in China. Chin. J. Electr. Eng. 3(2), 1–13 (2017)
Liu, K.L., Kang, L.I., Peng, Q., Zhang, C.: A brief review on key technologies in the battery management system of electric vehicles. Front. Mech. Eng. 14(1), 47–64 (2018)
Wang, Y.S., Yang, S.Z., You, Y.: High-capacity and long-cycle life aqueous rechargeable lithium-ion battery with the FePO4 anode. ACS Appl. Mater. Interfaces. 10(8), 7061–7068 (2018)
Jiao, X.X., Liu, Y.Y., Li, B., Zhang, W.X.: Amorphous phosphorus-carbon nanotube hybrid anode with ultralong cycle life and high-rate capability for lithium-ion battery. Carbon 148, 518–524 (2019)
Yang, F.F., Xing, Y.J., Wang, D.: 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 164, 387–399 (2016)
He, Y., Zhang, C.B., Liu, X.T., Chen, Z.H.: SOC estimation for LiFePO4 high-power batteries based on information fusion. Control Decision 29(01), 188–192 (2014)
Deng, Z.W., Hu, X.S., Lin, X.K., Che, Y.H., Guo, W.C.: Data-driven state of charge estimation for lithium-ion battery packs based on Gaussian process regression. Energy 205, 118000 (2020)
Zhang, X., Wang, X., Zhang, W., Lei, G.: A simplified li-ion battery SOC estimating method. Trans. Electr. Electron. Mater. 17(1), 13–17 (2016)
Eziani, S., Ouassaid, M.:State of charge estimation of supercapacitor using artificial neural network for onboard railway applications. In: International Renewable and Sustainable Energy Conference (IRSEC). (2019)
Misyris, G.S., Doukas, D.I., Papadopoulos, T.A.: State-of-charge estimation for li-ion batteries: a more accurate hybrid approach. IEEE Trans. Energy. Convers. 34(1), 109–119 (2019)
Xi, Z.M., Dahmardeh, M., Xia, B.: Learning of battery model bias for effective state of charge estimation of lithium-ion batteries. IEEE Trans. Veh. Technol. 68(9), 8613–8628 (2019)
Li, Y., Xiong, B. Y., Vilathgamuwa, D. M., Wei, Z. B., Zou, C. F.: Constrained ensemble Kalman filter for distributed electrochemical state estimation of lithium-ion batteries. IEEE Trans. Ind. Informat. PP(99) (2020)
Sturm, J., Ennifar, H., Erhard, S.V., Rheinfeld, A., Kosch, S., Jossen, A.: State estimation of lithium-ion cells using a physicochemical model based extended Kalman filter. Appl. Energy 223, 103–123 (2018)
Susanna, S., Dewangga, B. R., Wahyungoro, O., Cahyadi, A. I.: Comparison of simple battery model and thevenin battery model for SOC estimation based on OCV method. In: International Conference on Information and Communications Technology (ICOIACT), pp. 738–743 (2019)
Liu, D., Wang, X. C., Zhang, M., Gong, M. X.: SOC estimation of lithium battery based on N-2RC model in electric vehicle. In: Chinese Control And Decision Conference (CCDC), pp. 2916–2921 (2019)
Du, J., Wang, Y. Y., Wen, C. Y.: Li-ion battery SOC estimation using particle filter based on an equivalent circuit model. In: IEEE International Conference on Control and Automation (IEEE ICCA), pp. 580–585 (2013)
Zhang, L., Wang, S.L., Stroe, D.I., Zou, C.Y., Fernandez, C.: An accurate time constant parameter determination method for the varying condition equivalent circuit model of lithium batteries. Energies 13(8), 2057 (2020)
Luo, M.J., Guo, Y.Z., Kang, J.Q., She, L.Y.: Ternary-material lithium-ion battery SOC estimation under various ambient temperature. Ionics 24(7), 1907–1917 (2018)
Zhu, J.G., Knapp, M., Darma, M.S.D., Fang, Q.H., Wang, X.Y.: An improved electro-thermal battery model complemented by current dependent para-meters for vehicular low temperature application. Appl. Energy 248, 149–161 (2019)
He, Y., Cao, C.Y., Liu, X.T., Zheng, X.X., Zeng, G.J.: SOC estimation of lithium battery based on variable temperature model. Electr. Machines Control 22(01), 43–52 (2018)
Liu, X.T., Li, H., He, Y., Zheng, X.X., Zeng, G.J.: SOC estimation method based on IUPF algorithm and variable para-meter battery model. J. Southeast Univ. (Natural Science Edition) 48(01), 54–62 (2018)
Li, Y.W., Wang, C., Gong, J.F.: A wavelet transform-adaptive unscented Kalman filter approach for state of charge estimation of LiFePo4 battery. Int. J. Energy Res. 42(2), 587–600 (2018)
Chin, C.S., Gao, Z.C., Chiew, J.H.K., Zhang, C.Z.: Nonlinear temperature-dependent state model of cylindrical LiFePO4 battery for open-circuit voltage, terminal voltage and state-of-charge estimation with extended Kalman filter. Energies 11(9), 2467 (2018)
Tan, X. J.: Design of electric vehicle power battery management system. Sun Yatsen University press (2011)
Deng, Z.W., Yang, L., Cai, Y.S., Deng, H., Sun, L.: Online available capacity prediction and state of charge estimation based on advanced data-driven algorithms for lithium iron phosphate battery. Energy 112, 469–480 (2016)
National Automobile Standardization Technical Committee.: QC/T743—2006 Lithium ion batteries for electric vehicles. Beijing: Standards Press of China (2006)
Liu, X.T., He, Y., Zeng, G.J., Zhang, J.F., Zheng, X.X.: A method for state-of-power estimation of li-ion battery considering battery surface temperature. Energy Technol. 6(7), 1352–1360 (2018)
Liu, X.T., Chen, Z.H., Zhang, C.B., He, Y.: A novel temperature-compensated model for power Li-ion batteries with dual-particle-filter state of charge estimation. Appl. Energy 123, 263–272 (2014)
Zhang, R.F., Xia, B.Z., Li, B.H., Cao, L.B., Lai, Y.Z., Zheng, W.W.: A study on the open circuit voltage and state of charge characterization of high capacity lithium-ion battery under different temperature. Energies 11(9), 2408 (2018)
Chen, Y.J., Yang, G., Liu, X., He, Z.C.: A time-efficient and accurate open circuit voltage estimation method for lithium-ion batteries. Energies 12(9), 1803 (2019)
Heo, S., Park, C.G.: Consistent EKF-based visual-inertial odometry on matrix lie group. IEEE Sens. 18(9), 3780–3788 (2018)