[1] HANNAN M A,LIPU M S H,HUSSAIN A,et al. A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications:challenges and recommendations [J]. Renewable & Sustainable Energy Reviews,2017,78(1):834-854.
[2] YONG J Y, RAMACHANDARAMURTHY V K,TAN K M,et al. A review on the state-of-the-art technologies of electric vehicle,its impacts and prospects [J]. Renewable and Sustainable Energy Reviews,2015,49(1):365-385.
[3] SUN F,XIONG R,HE H. A systematic state-of-charge estimation framework for multi-cell battery pack in electric vehicles using bias correction technique [J]. Applied Energy,2016,162(1):1399-1409.
[4] 唐偲,鲁丽娟. 磷酸铁锂电池在电力系统中的应用研究 [J]. 南方能源建设,2016,3(增刊1):39-42.
[5] CONTE F V. Battery and battery management for hybrid electric vehicles:a review [J]. E & I Elektrotechnik and Informationstechnik,2006,123(10):424-431.
[6] XIONG R,TIAN J,MU H,et al. A systematic model-based degradation behavior recognition and health monitoring method for lithium-ion batteries [J]. Applied Energy,2017,207(1):372-383.
[7] 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):309-316.
[8] LU L,HAN X,LI J,et al. A review on the key issues for lithium-ion battery management in electric vehicles [J]. Journal of Power Sources,2013,226(1):272-288.
[9] SCROSATI B,JÜRGEN G. Lithium batteries:Status,prospects and future [J]. Journal of Power Sources,2010,195(9):2419-2430.
[10] NAGPURE S C,BHUSHAN B. Atomic force microscopy studies of aging mechanisms in Lithium-ion batteries [M]. Applied Scanning Probe Methods XIII. Springer Berlin Heidelberg,2009:203-233.
[11] WOHLFAHRT-MEHRENS M,VOGLER C,GARCHE J. Aging mechanisms of Lithium cathode materials [J]. Journal of Power Sources,2004,127(1):58-64.
[12] VETTER J,NOVáK P,WAGNER M R,et al. Ageing mechanisms in Lithium-ion batteries[J]. Journal of Power Sources,2005,147(1):269-281.
[13] 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(1):793-803.
[14] CHEN Z,CHUNTING CHRIS M I,et al. Online battery state of health estimation based on genetic algorithm for electric and hybrid vehicle applications [J]. Journal of Power Sources,2013,240(31):184-192.
[15] ZHENG Y,HAN X,LU L,et al. Lithium ion battery pack power fade fault identification based on Shannon entropy in electric vehicles [J]. Journal of Power Sources,2013,223(1):136-146.
[16] WIDODO A,SHIM M C,CAESARENDRA W,et al. Intelligent prognostics for battery health monitoring based on sample entropy [J]. Expert Systems with Applications,2011,38(9):11763-11769.
[17] CHEN Y,BAO J,XIANG Z,et al. Predictability analysis of lithium-ion battery remaining useful life with multiscale entropy [C] //IEEE.org. 2013 Fifth international conference on computational and information sciences (ICCIS 2013),Hubei,China,June 21-23,2013,Hubei:IEEE.org,2013.
[18] 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(1):953-960.
[19] DUBARRY M,TRUCHOT C,LIAW B Y. Synthesize battery degradation modes via a diagnostic and prognostic model [J]. Journal of Power Sources,2012,219(1):204-216.
[20] KASSEM M,BERNARD J,REVEL R,et al. Calendar aging of a graphite/LiFePO4 cell [J]. Journal of Power Sources,2012,208(1):296-305.
[21] WENG C,CUI Y,SUN J,et al. On-board state of health monitoring of lithium-ion batteries using incremental capacity analysis with support vector regression [J]. Journal of Power Sources,2013,235(4):36-44.
[22] HAN X,OUYANG M,LU L,et al. A comparative study of commercial lithium ion battery cycle life in electrical vehicle:Aging mechanism identification [J]. Journal of Power Sources,2014,251(1):38-54.
[23] REZVANIZANIANI S M,LIU Z,CHEN Y,et al. Review and recent advances in battery health monitoring and prognostics technologies for electric vehicle(EV)safety and mobility [J]. Journal of Power Sources,2014,256(12):110-124.