[1] Piller S, Perrin M, Jossen A.Methods for state-of-charge determination and their applications[J]. Journal of Power Sources, 2001, 96(1):113-120.
[2] 赵徐成, 张磊, 黄卫星.基于动态电子负载的航空蓄电池内阻与容量关系[J].电源技术, 2006, 130(2):149- 151. [ZHAO X C, ZHANG L ,HUANG W X. Study on relation between the capacity and dynamic resistance of aerial storage battery by dynamic electronic load[J]. Chinese Journal of Power Source. 2006, 130(2):149- 151.]
[3] Pop V, Bergveld H J, Notten P H L, et al.Accuracy analysis of the State-of-Charge and remaining run-time determination for lithium-ion batteries[J]. Measurement, 2009, 42(8):1131-1138.
[4] Sheikhan M, Pardis R, Gharavian D.State of charge neural computational models for high energy density batteries in electric vehicles[J].Neural Computing and Applications, 2013, 22(6):1171-1180.
[5] Mastali M,Vazquez-Arenas J,Fraser R,et al. Battery state of the charge estimation using Kalman filtering[J]. Journal of Power Sources, 2013, 239:294-307.
[6] Schwunk S, Armbruster N, Straub S, et al.Particle filter for state of charge and state of health estimation for lithiumiron phosphate batteries[J].Journal of Power Sources, 2013, 239:705-710.
[7] Min Chen, Gabriel A, Rincon-Mora. Accurate electrical battery model capable of predicting runtime and I-V performance[J]. IEEE Transations on Energy Conversion, 2006, 21(2):504-511.
[8] Gregory L Plett. Extended Kalman filtering for battery management systems of LiPB- based HEV battery packs[J]. Power Sources, 2004, 134:252-292.
[9] Moradkhani H, DeChant C M, Sorooshian S.Evolution of ensemble data assimilation for uncertainty quantification using the particle filter-Markov chain Monte Carlo method[J].Water Resources Research, 2012, 48(12).
[10] 刘学,焦淑红,蓝晓宇,等. 拟蒙特卡罗聚合重采样粒子滤波无源定位算法[J]. 西安电子科技大学学报(自然科学版),2012,39(5):154-160. [LIU X, JIAO S H, LAN X Y, et al. Quasi-monte-carlo merging resampling particle filter for passive location[J]. Journal of Xidian University(Natural Science), 2012,39(5):154-160.]
[11] Zhang Zhuhong, Qian Shuqu.Artificial immune system in dynamic environments solving time-varying nonlinear constrained multi-objective problems[J]. Soft Computing, 2011, 15(7):1333-1349.
[12] 常海涛.基于人工免疫粒子滤波的纯电动汽车锂电池 SOC 估计研究[D]. 北京交通大学, 2013. [CHANG H T. Research on estimation for SOC of PEV Li- ion battery based on artificial immune particle filter[D]. Beijing Jiaotong University,2013.]
[13] Sarfraz M,Hussain,et al. Modeling rational spline for visualization of shaped data[J]. Journal of Numerical Mathematics,2013,12:63-67.
[14] 陈涵, 刘会金, 李大路,等.可变遗忘因子递推最小二乘法对时变参数测量[J]. 高电压技术, 2008, 34(7): 1474-1477. [CHEN H, LIU H J, LI D L, et al. Timevarying parameters measurement by least square method with variable forgetting factors[J]. High Voltage Engineering, 2008, 34(7):1474-147.] |