[1] 潘海鸿,吕治强,付兵,等.采用极限学习机实现锂离子电池健康状态在线估算[J].汽车工程,2017,39(12):1375-1382. [2] DANG X, YAN L, XU K, et al. Open-circuit voltage-based state of charge estimation of lithium-ion battery using dual neural network fusion battery model[J]. Electrochimica Acta,2016,188:356-366. [3] 王常虹,董汉成,凌明祥,等.车用锂离子电池剩余使用寿命预测[J].汽车工程,2015,37(4):476-479. [4] 刘月峰,赵光权,彭喜元.锂离子电池循环寿命的融合预测方法[J].仪器仪表学报,2015(7):1462-1469. [5] ZHANG L, MU Z, SUN C. Remaining useful life prediction for lithium-ion batteries based on exponential model and particle filter[J]. IEEE Access,2018(6):17729-17740. [6] 苗强,崔恒娟,谢磊,等.粒子滤波在锂离子电池剩余寿命预测中的应用[J].重庆大学学报,2013(8):47-52. [7] 周秀文.电动汽车锂离子电池健康状态估计及寿命预测方法研究[D].长春:吉林大学,2016. [8] CHENG Q, BONDON P. A new unscented particle filter[C].2008 IEEE International Conference on Acoustics, Speech and Signal Processing. Las Vegas, USA: IEEE,2008:3417-3420. [9] DOUCET A. On sequential simulation-based methods for bayesian filtering[J]. Statistics & Computing,1998(8):1-26. [10] DUONG P L T, RAGHAVAN N. Heuristic Kalman optimized particle filter for remaining useful life prediction of lithium-ion battery[J]. Microelectronics Reliability,2018,81:232-243. [11] YU J, MO B, TANG D, et al. Remaining useful life prediction for lithium-ion batteries using a quantum particle swarm optimization-based particle filter[J]. Quality Engineering,2017,29(5):536-546. [12] XIAN W, LONG B, LI M, et al. Prognostics of lithium-ion batteries based on the verhulst model, particle swarm optimization and particle filter[J]. IEEE Transactions on Instrumentation and Measurement,2014,63(1):2-17. [13] LIU Z, SUN G, BU S, et al. Remaining useful life estimation of lithium-ion battery using exemplar-based conditional particle filter[C].2015 IEEE Conference on Prognostics and Health Management. Austin, USA: IEEE,2015:1-8. [14] 邹国辉,敬忠良,胡洪涛.基于优化组合重采样的粒子滤波算法[J].上海交通大学学报,2006(7):1135-1139. [15] SAHA B, GOEBEL K. Battery data set[G]. NASA Ames Prognostics Data Repository. NASA Ames, Moffett Field, CA,2007. http://ti.arc.nasa.gov/tech/dash/groups/pcoe/prognostic-data-repository/#battery. [16] ZOU Y, HU X, MA H, et al. Combined state of charge and state of health estimation over lithium-ion battery cell cycle lifespan for electric vehicles[J]. Journal of Power Sources,2015,273:793-803. [17] HU X, LI S E, JIA Z, et al. Enhanced sample entropy-based health management of Li-ion battery for electrified vehicles[J]. Energy,2014,64:953-960. |