참고문헌
- Kim, J., Cho, B.H.: Pattern recognition for temperature-dependent state-of-charge/capacity estimation of a Li-ion cell. IEEE Trans. Energy Convers. 28(1), 1-11 (2013) https://doi.org/10.1109/TEC.2012.2222884
- Cho, H., Choi, W., Go, J., et al.: A study on time-dependent low temperature power performance of a lithium-ion battery. J. Power Sources 198, 273-280 (2012) https://doi.org/10.1016/j.jpowsour.2011.09.111
- Jiang, J., Zhang, C.: Fundamentals and Applications of Lithium-ion Batteries in Electric Drive Vehicles, pp. 4-5. Wiley, Singapore (2015)
- Shouliang, H.: Research on Modular Cascade Motor System for Electric Vehicle Driving. Harbin Institute of Technology, Harbin (2015)
- Farmann, A., Waag, W., Sauer, D.U.: Adaptive approach for on-board impedance parameters and voltage estimation of lithium-ion batteries in electric vehicles. J. Power Sources 299, 176-188 (2015) https://doi.org/10.1016/j.jpowsour.2015.08.087
- Farmann, A., Waag, W., Marongiu, A., et al.: Critical review of on-board capacity estimation techniques for lithium-ion batteries in electric and hybrid electric vehicles. J. Power Sources 281, 114-130 (2015) https://doi.org/10.1016/j.jpowsour.2015.01.129
- Fleischer, C., Waag, W., Heyn, H., et al.: On-line adaptive battery impedance parameter and state estimation considering physical principles in reduced order equivalent circuit battery models. J. Power Sources 260, 276-291 (2014) https://doi.org/10.1016/j.jpowsour.2014.01.129
- Fleischer, C., Waag, W., Heyn, H., et al.: On-line adaptive battery impedance parameter and state estimation considering physical principles in reduced order equivalent circuit battery models part 2. parameter and state estimation. J. Power Sources 262, 457-482 (2014) https://doi.org/10.1016/j.jpowsour.2014.03.046
- Jian, W., Li, T., Zhang, H., Lei, Y., Zhou, G.: Research on modeling and SOC estimation of lithium iron phosphate battery at low temperature. Energy Procedia 152, 556-561 (2018) https://doi.org/10.1016/j.egypro.2018.09.210
- Li, J., Klee Barillas, J., Guenther, C., et al.: Sequential monte carlo filter for state estimation of LiFePO4 batteries based on an online updated model. J. Sources 247, 156-162 (2014) https://doi.org/10.1016/j.jpowsour.2013.08.099
- Hu, M., Li, Y., Li, S., Fu, C., Qin, D., Li, Z.: Lithium-ion battery modeling and parameter identification based on fractional theory. Energy 165, 153-163 (2018)
- Yongyuan, Q., Hongyue, Z., Shuhua, S.: Kalman filter and principle of integrated navigation. Northwest University of Technology, Xi'an (2015)
- Fu, Y., Tippets, C.A., Donev, E.U., et al.: Structural colors: from natural to artificial systems. Wiley Interdiscip. Rev. Nanomed. Nanobiotechnol. 8(5), 758-775 (2016) https://doi.org/10.1002/wnan.1396
- Xing, Y., He, W., Pecht, M., et al.: State of charge estimation of lithium-ion batteries using the open-circuit voltage at various ambient temperature. Appl. Energy 113, 106-115 (2014) https://doi.org/10.1016/j.apenergy.2013.07.008
- Zhang, R., Xia, B., Li, B., Cao, L., Lai, Y., Zheng, W., Wang, H., Wang, W.: State of the art of lithium-ion battery SOC estimation for electrical vehicles. Energies 11(7), 18-20 (2018)
- Xiong, B., Zhao, J., Wei, Z., Skyllas-Kazacos, M.: Extended Kalman filter method for state of charge estimation of vanadium redox flow battery using thermal-dependent electrical model. J. Power Sources 262, 50-61 (2014) https://doi.org/10.1016/j.jpowsour.2014.03.110
- Wang, Y., Zhang, C., Chen, Z., et al.: A novel active equalization method for lithium-ion batteries in electric vehicles. Appl. Energy 145, 36-42 (2015) https://doi.org/10.1016/j.apenergy.2015.01.127
- Zhao, Y., Stein, P., Bai, Y., Al-Siraj, M., Yang, Y., Bai-Xiang, X.: A review on modeling of electro-chemo-mechanics in lithium-ion batteries. J. Power Sources 413, 259-283 (2019) https://doi.org/10.1016/j.jpowsour.2018.12.011
- Zhang, W., Wang, L., Wang, L., Liao, C.: An improved adaptive estimator for state-of-charge estimation of lithium-ion batteries. J. Power Sources 402, 422-433 (2018) https://doi.org/10.1016/j.jpowsour.2018.09.016
- Xiong, R., Sun, F., Gong, X., et al.: A data-driven based adaptive state of charge estimator of lithium-ion polymer battery used in electric vehicles. Appl. Energy 113, 1421-1433 (2013) https://doi.org/10.1016/j.apenergy.2013.09.006
- Pei, L., Wang, T., Lu, R., et al.: Development of a voltage relaxation model for rapid open-circuit voltage prediction in lithium-ion batteries. J. Power Sources 253, 412-418 (2014) https://doi.org/10.1016/j.jpowsour.2013.12.083
- Khan, M.R., Mulder, G., Van Mierlo, J.: An online framework for state of charge determination of battery systems using combined system identification approach. J. Power Sources 246, 629-641 (2014) https://doi.org/10.1016/j.jpowsour.2013.07.092
- Wang, Y., Zhang, C., Chen, Z.: A method for state-of-charge estimation of LiFePO4 batteries at dynamic currents and temperatures using p filter. J. Power Sources 279, 306-311 (2015) https://doi.org/10.1016/j.jpowsour.2015.01.005
- Plett, G.L.: Extended Kalman filtering for battery management systems of Li PB-based HEV battery packs. J. Power Sources 134(2), 262-276 (2004) https://doi.org/10.1016/j.jpowsour.2004.02.032
피인용 문헌
- Online full-parameter identification and SOC estimation of lithium-ion battery pack based on composite electrochemical - dual circuit polarization modeling vol.675, pp.1, 2020, https://doi.org/10.1088/1755-1315/675/1/012192
- On-line adaptive asynchronous parameter identification of lumped electrical characteristic model for vehicle lithium-ion battery considering multi-time scale effects vol.517, 2020, https://doi.org/10.1016/j.jpowsour.2021.230725