[1] 唐葆君,刘江鹏.中国新能源汽车产业发展展望[J].北京理工大学学报(社会科学版),2015,17(2):1-6. [2] 付天照,盖旗涛.常用可充电电池的性能比较[J].通信电源技术,2013,30(3):51-52. [3] 沈佳妮,贺益君,马紫峰.基于模型的锂离子电池SOC及SOH估计方法研究进展[J].化工学报,2018,69(1):317-324. [4] 汪奂伶,侯朝勇,贾学翠,等.电化学储能电池荷电状态(SOC)估算技术对比分析[J].电器与能效管理技术,2017(5):76-83. [5] 杨立. 基于二阶离散滑模观测器的锂电池SOC估计[J].电器与能效管理技术,2018(3):43-46,52. [6] ZHANG C P,JIANG J C,ZHANG L J,et al.A generalized SOC-OCV model for lithium-ion batteries and the SOC estimation for LNMCO battery[J].Energies,2016,9(11):900. [7] 杨文荣,朱赛飞,陈阳,等.基于改进安时积分法估计锂离子电池组SOC[J].电源技术,2018,42(2):183-184,246. [8] SHEN W X,CHAN C C,LO E W C,et al.A new battery available capacity indicator for ele-ctric vehicles using neural network[J].Energy Conversion and Management,2002,43(6):817-826. [9] 高昂,郭梦蕾,徐珂雅,等.卡尔曼滤波算法在锂电池荷电状态估计中的应用[J].电子设计工程,2019,27(18):33-37. [10] URBAIN M,STÉPHANE RAEL,DAVAT B,et al.State estimation of a lithium-ion battery through Kalman filter in IEEE Power Electronics Specialists Conference[C].2007. [11] PLETT G L.Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs:Part 2.Modeling and idenpngycation[J].Journal of Power Sources,2004,134(2):262-276. |