Open Access
E3S Web Conf.
Volume 267, 2021
7th International Conference on Energy Science and Chemical Engineering (ICESCE 2021)
Article Number 01017
Number of page(s) 5
Section Energy Development and Utilization and Energy-Saving Technology Application
Published online 04 June 2021
  1. I. U. Khalil, M. Ahsan, I. Ullah, A. Adnan, N. Khan and S. Nawaz, “SOC prediction of Lithium-Ion Battery using Extended Kalman Filter,” 2018 International Symposium on Recent Advances in Electrical Engineering (RAEE), Islamabad, Pakistan, 2018, pp. 1-5. [Google Scholar]
  2. X. Liu et al., “Online identification of power battery parameters for electric vehicles using a decoupling multiple forgetting factors recursive least squares method,” in CSEE Journal of Power and Energy Systems, vol. 6, no. 3, pp. 735-742, Sept. 2020. [Google Scholar]
  3. Li P, Wang H, Xing Z, et al. Joint estimation of SOC and SOH for lithium-ion batteries based on EKF multiple time scales[J]. 2020. [Google Scholar]
  4. D. A. Pola et al., “Particle-Filtering-Based Discharge Time Prognosis for Lithium-Ion Batteries With a Statistical Characterization of Use Profiles,” in IEEE Transactions on Reliability, vol. 64, no. 2, pp. 710720, June 2015. [Google Scholar]
  5. Xu Y, Hu M, Fu C, et al. State of Charge Estimation for Lithium-Ion Batteries Based on Temperature-Dependent Second-Order RC Model[J]. Electronics, 2019, 8(9):1012-. [Google Scholar]
  6. Tian Y, Lai R, Li X, et al. A combined method for state-of-charge estimation for lithium-ion batteries using a long short-term memory network and an adaptive cubature Kalman filter[J]. Applied Energy, 2020, 265. [Google Scholar]
  7. Wang Houlian, Zhou Gongbo. State of charge prediction of supercapacitors via combination of Kalman filtering and backpropagation neural network[J]. IET Electric Power Applications, 2018, 12(4). [Google Scholar]
  8. Aung H, Low K S, Soon J J. State-of-charge estimation using particle swarm optimization with inverse barrier constraint in a nanosatellite[C]// Industrial Electronics & Applications. IEEE, 2015. [Google Scholar]
  9. Chandra Shekar A, Anwar S. Real-Time State-of-Charge Estimation via Particle Swarm Optimization on a Lithium-Ion Electrochemical Cell Model[J]. Batteries, 2019, 5(1). [Google Scholar]
  10. Mao X, Song S, Ding F, et al. SOC Estimation of Lithium Battery Based on IPSO-BP Neural Network[J]. Journal of Physics: Conference Series, 2020, 1684(1):012152 (6pp). [Google Scholar]

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