International Energy Agency. Global EV Outlook 2023[R/OL]. (2023-04-30)[2024-09-15]. https://www.iea.org/reports/global-ev-outlook-2023.
巩浩, 钟洪伟, 孙梦凯, 等. 新能源电动汽车节能减排效应及发展[J]. 能源与节能, 2023(12): 80-84. doi: 10.3969/j.issn.2095-0802.2023.12.022
万广伟, 张强. 锂离子电池SOC评估方法研究进展[J]. 电源技术, 2023, 47(9): 1122-1125. doi: 10.3969/j.issn.1002-087X.2023.09.004
ZHANG S Z, GUO X, DOU X X, et al. A Data-Driven Coulomb Counting Method for State of Charge Calibration and Estimation of Lithium-Ion Battery[J]. Sustainable Energy Technologies and Assessments, 2020, 40: 100752. doi: 10.1016/j.seta.2020.100752
王义军, 左雪. 锂离子电池荷电状态估算方法及其应用场景综述[J]. 电力系统自动化, 2022, 46(14): 193-207. doi: 10.7500/AEPS20211124005
YU Q Q, WAN C J, LI J F, et al. An Open Circuit Voltage Model Fusion Method for State of Charge Estimation of Lithium-Ion Batteries[J]. Energies, 2021, 14(7): 1797. doi: 10.3390/en14071797
李清波, 张懋慧, 罗英, 等. 基于等效电路模型融合电化学原理的锂离子电池荷电状态估计[J]. 储能科学与技术, 2024, 13(9): 3072-3083.
ZHAO H Y, ZHANG C Z, LIAO C L, et al. An Improved Electrochemical Equivalent Circuit Model and Precise State-of-Charge Estimation Comparative Study for Lithium-Rich Manganese-Based Battery[J]. Journal of Energy Storage, 2024, 94: 112354. doi: 10.1016/j.est.2024.112354
PENG J K, LUO J Y, HE H W, et al. An Improved State of Charge Estimation Method Based on Cubature Kalman Filter for Lithium-Ion Batteries[J]. Applied Energy, 2019, 253: 113520. doi: 10.1016/j.apenergy.2019.113520
DOU J M, MA H Y, ZHANG Y D, et al. Extreme Learning Machine Model for State-of-Charge Estimation of Lithium-Ion Battery Using Salp Swarm Algorithm[J]. Journal of Energy Storage, 2022, 52: 104996. doi: 10.1016/j.est.2022.104996
于仲安, 邵昊晖, 陈可怡. 基于IGWO-BP神经网络的锂离子电池SOC估计[J]. 电源技术, 2023, 47(9): 1153-1157. doi: 10.3969/j.issn.1002-087X.2023.09.011
张越. 基于GWO-SVM算法的锂动力电池状态在线联合估计方法研究[D]. 哈尔滨: 哈尔滨理工大学, 2023.
郭鹏. 数据—模型联合驱动的锂电池SOC稳健估计方法研究[D]. 西安: 西安理工大学, 2024.
JIA K, GAO Z, MA R C, et al. An Adaptive Optimization Algorithm in LSTM for SOC Estimation Based on Improved Borges Derivative[J]. IEEE Transactions on Industrial Informatics, 2024, 20(2): 1907-1919. doi: 10.1109/TII.2023.3280340
王尔申, 王欢, 雷虹, 等. 基于麻雀搜索算法的ARAIM故障子集优化算法[J]. 北京航空航天大学学报, 2024, 50(7): 2066-2073.
EYAD A, SALEH A, EMAD A, et al. State of Charge Estimation for a Group of Lithium-Ion Batteries Using Long Short-Term Memory Neural Network[J]. Journal of Energy Storage, 2022, 52(PA): 104761.
潘思源, 张伟. 基于改进LSTM算法的锂电池SOC估计[J]. 计算机与现代化, 2023(8): 25-30. doi: 10.3969/j.issn.1006-2475.2023.08.005
YANG F F, ZHANG S H, LI W H, et al. State-of-Charge Estimation of Lithium-Ion Batteries Using LSTM and UKF[J]. Energy, 2020, 201: 117664. doi: 10.1016/j.energy.2020.117664
洪吉超, 张昕阳, 徐晓明, 等. 基于多熵融合的动力电池故障诊断与应用研究[J]. 机械工程学报, 2024, 60(12): 301-312.
雷亦鸣. 基于数据驱动的稳健SOC估计融合方法研究[D]. 西安: 西安理工大学, 2024.