Overview of Fault Diagnosis in New Energy Vehicle Power Battery System

doi:10.3901/JME.2021.14.087

Abstract

Abstract: To achieve significant fuel consumption and carbon emission reductions, new energy vehicles have become a transport development trend throughout the world. However, new energy vehicle safety issues are increasingly prominent with the increase of new energy vehicle, which seriously threatens the life and property of drivers, and restricts the development of new energy vehicles industry. According to statistics, 60% of fire accidents in new energy vehicles are caused by power batteries. The development of advanced fault diagnosis technology for power battery system has become a hot spot in the field of safety protection. In order to fill the gap in the latest Chinese review, the faults of power battery system are classified into internal faults and external faults based on the difference of fault location, and the failure mechanisms of over-charge, over-discharge, external short circuit, internal short circuit, sensor fault, connector fault and cooling system fault are described. From the perspectives of internal faults and external faults, the research status and latest progress of three types of fault diagnosis methods are summarized including knowledge-based, model-based and data driven for lithium-ion power batteries. The main problems in the current research and future development on power battery fault diagnosis technology are discussed. In this way, accurate diagnosis and early prevention of power battery system faults can be realized, the life and property safety of drivers can be guaranteed, and the safety and the further development of the new energy vehicle can be promoted.

Key words: new energy vehicle, power battery, fault mechanism, fault diagnosis

CLC Number:

TM912

SUN Zhenyu, WANG Zhenpo, LIU Peng, ZHANG Zhaosheng, CHEN Yong, QU Changhui. Overview of Fault Diagnosis in New Energy Vehicle Power Battery System[J]. Journal of Mechanical Engineering, 2021, 57(14): 87-104.

References

[1] ZHU X,WANG H,WANG X,et al. Internal short circuit and failure mechanisms of lithium-ion pouch cells under mechanical indentation abuse conditions:An experimental study[J]. Journal of Power Sources,2020,455:227939.
[2] 中华人民共和国公安部,全国私家车保有量首次突破2亿,66个城市汽车保有量超过百万辆[EB/OL].[2020-01-08]. https://app.mps.gov.cn/gdnps/pc/content.jsp?id=7478950. Ministry of Public Security of the People's Republic of China,The number of private cars in China exceeded 200 million for the first time,and the number of cars in 66 cities exceeded one million[EB/OL].[2020-01-08]. https://app.mps.gov.cn/gdnps/pc/content.jsp?id=7478950.
[3] 陈泽宇,熊瑞,孙逢春. 电动汽车电池安全事故分析与研究现状[J]. 机械工程学报,2019,55(24):93-104,116. CHEN Zeyu,XIONG Rui,SUN Fengchun. Research status and analysis for battery safety accidents in electric vehicles[J]. Journal of mechanical engineering,2019,55(24):93-104,116.
[4] 刘真通. 基于模型的纯电动车辆动力系统故障诊断研究[D]. 北京:北京理工大学,2016. LIU Zhentong. Model-based fault diagnosis of electrified driven powertrains in pure electric vehicles[D]. Beijing:Beijing Institute of Technology,2016.
[5] 佘承其,张照生,刘鹏,等. 大数据分析技术在新能源汽车行业的应用综述-基于新能源汽车运行大数据[J]. 机械工程学报,2019,55(20):3-16. SHE Chengqi,ZHANG Zhaosheng,LIU Peng,et al. Overview of the application of big data analysis technology in new energy vehicle industry:Based on operating big data of new energy vehicle[J]. Journal of Mechanical Engineering,2019,55(20):3-16.
[6] 魏晓宾,马小平,李亚朋. 故障诊断技术综述[J]. 煤矿机电,2019(1):68-70. WEI Xiaobin,MA Xiaoping,LI Yapeng. Survey of fault diagnosis technology[J]. Coal Mine Electromechanical,2019(1):68-70.
[7] 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,2013,226:272-288.
[8] 肖云魁. 汽车故障诊断学[M]. 2版. 北京:北京理工大学出版社,2006. XIAO Yunkui. Automotive fault diagnosis[M]. 2nd ed. Beijing:Beijing Institute of Technology Press,2006.
[9] 周东华. 动态系统的故障诊断技术[J]. 自动化学报,2009,35(6):748-758. ZHOU Donghua. Fault diagnosis techniques for dynamic systems[J]. Acta Automatica Sinica,2009,35(6):748-758.
[10] 刘鹏鹏,左洪福,苏艳,等. 基于图论模型的故障诊断方法研究进展综述[J]. 中国机械工程,2013,24(5):696-703. LIU Pengpeng,ZUO Hongfu,SU Yan,et al. Review of research progresses for graph-based models in fault diagnosis method[J]. China Mechanical Engineering,2013,24(5):696-703.
[11] FILIPPETTI F,MARTELLI M,FRANCESCHINI G,et al. Development of expert system knowledge base to on-line diagnosis of rotor electrical faults of induction motors[C]//Conference Record of the 1992 IEEE Industry Applications Society Annual Meeting,October 4-9,1992. Houston,Texas,USA:IEEE,1992:92-99.
[12] YANG F,XIAO D. Model and fault inference with the framework of probabilistic SDG[C]//2006 9th International Conference on Control,Automation Control,December 5-8,2006,Singapore:IEEE,2006:1-6.
[13] PATÉ-CORNELL M E. Fault trees vs. event trees in reliability analysis[J]. Risk Analysis,1984,4(3):177-186.
[14] 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(3):272-288.
[15] CHEN J,PATTON R. Robust model-based fault diagnosis for dynamic systems[M]. New York:Springer US,1999.
[16] ISERMANN R. Model-based fault detection and diagnosis-status and applications[J]. IFAC Proceedings Volumes,2004,37(6):49-60.
[17] ISERMANN R. Process fault detection based on modeling and estimation methods:A survey[J]. Automatica,1984,20(4):387-404.
[18] BAGHERI F,KHALOOZADED H,ABBASZADEH K. Stator fault detection in induction machines by parameter estimation,using adaptive kalman filter[C]//2007 Mediterranean Conference on Control & Automation,June 27-29,2007. Athens,Greece:IEEE,2007:1-6.
[19] LIU X,ZHANG H,LIU J,et al. Fault detection and diagnosis of permanent-magnet DC motor based on parameter estimation and neural network[J]. IEEE Transactions on Industrial Electronics,2000,47(5):1021-1030.
[20] ODENDAAL H M,JONES T. Actuator fault detection and isolation:An optimised parity space approach[J]. Control Engineering Practice,2014,26:222-232.
[21] STAROSWIECKI M,COMTET-VARGA G. Analytical redundancy relations for fault detection and isolation in algebraic dynamic systems[J]. Automatica,2001,37(5):687-699.
[22] SAMANTA B,AL-BALUSHI K R. Artificial neural network based fault diagnostics of rolling element bearings using time-domain features[J]. Mechanical Systems & Signal Processing,2003,17(2):317-328.
[23] YOU G,PARK S,OH D. Real-time state-of-health estimation for electric vehicle batteries:A data-driven approach[J]. Applied Energy,2016,176:92-103.
[24] WIDODO A,YANG B. Support vector machine in machine condition monitoring and fault diagnosis[J]. Mechanical Systems & Signal Processing,2008,21(6):2560-2574.
[25] HE S,XIAO L,WANG Y,et al. A novel fault diagnosis method based on optimal relevance vector machine[J]. Neurocomputing,2017,267:651-663.
[26] WIDODO A,YANG B. Machine health prognostics using survival probability and support vector machine[J]. Expert Systems with Applications,2011,38(7):8430-8437.
[27] LIU Z,YIN X,ZHANG Z,et al. Online rotor mixed fault diagnosis way based on spectrum analysis of instantaneous power in squirrel cage induction motors[J]. IEEE Transactions on Energy Conversion,2004,19(3):485-490.
[28] ZHENG H,LI Z,CHEN X. Gear fault diagnosis based on continuous wavelet transform[J]. Mechanical Systems & Signal Processing,2002,16(2-3):447-457.
[29] 孙振宇. 基于数据驱动的纯电动汽车动力电池故障诊断方法研究[D]. 北京:北京理工大学,2018. SUN Zhenyu. Data driven-based fault diagnosis of power battery for pure electric vehicles[D]. Beijing:Beijing Institute of Technology,2018.
[30] BARONTI F,RONCELLA R,SALETTI R. Performance comparison of active balancing techniques for lithium-ion batteries[J]. Journal of Power Sources,2014,267:603-609.
[31] YUAN Q,ZHAO F,WANG W,et al. Overcharge failure investigation of lithium-ion batteries[J]. Electrochimica Acta,2015,178:682-688.
[32] REN D,FENG X,LU L,et al. Overcharge behaviors and failure mechanism of lithium-ion batteries under different test conditions[J]. Applied Energy,2019,250:323-332.
[33] LIU Y,XIE J. Failure study of commercial LiFePO₄ cells in overcharge conditions using electrochemical impedance spectroscopy[J]. Journal of The Electrochemical Society,2015,162(10):A2208-A2217.
[34] HUANG L,ZHANG Z,WANG Z,et al. Thermal runaway behavior during overcharge for large-format lithium-ion batteries with different packaging patterns[J]. Journal of Energy Storage,2019,25:10018.
[35] LARSSON F,ANDERSSON P,BLOMQVIST P,et al. Toxic fluoride gas emissions from lithium-ion battery fires[J]. Scientific Reports,2017,7(1):100811.
[36] CHAO W,SUN J,ZHU C,et al. Research on overcharge and overdischarge effect on lithium-ion batteries[C]//2015 IEEE Vehicle Power and Propulsion Conference (VPPC),October 19-22,2015,Montreal,QC,Canada:IEEE,2015:1-6.
[37] MALEKI H,HOWARD J. Effects of overdischarge on performance and thermal stability of a Li-ion cell[J]. Journal of Power Sources,2006,160(2):1395-1402.
[38] CHAO W,CHUNBO Z,JINLEI S,et al. Fault mechanism study on Li-ion battery at over-discharge and its diagnosis approach[J]. IET Electrical Systems in Transportation,2017,7(1):48-54.
[39] ABAZA A,FERRARI S,WONG H,et al. Experimental study of internal and external short circuits of commercial automotive pouch lithium-ion cells[J]. Journal of Energy Storage,2018,16:211-217.
[40] WANG H,SIMUNOVIC S,MALEKI H,et al. Internal configuration of prismatic lithium-ion cells at the onset of mechanically induced short circuit[J]. Journal of Power Sources,2016,306:424-430.
[41] ORENDORFF C J,LAMBERT T N,CHAVEZ C A,et al. Polyester separators for lithium-ion cells:Improving thermal stability and abuse tolerance[J]. Advanced Energy Materials,2013,3(3):314-320.
[42] 何向明,冯旭宁,欧阳明高. 车用锂离子动力电池系统的安全性[J]. 科技导报,2016,34(6):34-40. HE Xiangming,FENG Xuning,OUYANG Minggao. On the safety issues of lithium ion battery[J]. Science & Technology Review,2016,34(6):34-40.
[43] MALEKI H,HOWARD J N. Internal short circuit in Li-ion cells[J]. Journal of Power Sources,2009,191(2):568-574.
[44] HUANG P,WANG Q,LI K,et al. The combustion behavior of large scale lithium titanate battery[J]. Scientific Reports,2015,5:7788.
[45] YANG R,XIONG R,MA S,et al. Characterization of external short circuit faults in electric vehicle Li-ion battery packs and prediction using artificial neural networks[J]. Applied Energy,2020,260:114253.
[46] CHEN Z,XIONG R,LU J,et al. Temperature rise prediction of lithium-ion battery suffering external short circuit for all-climate electric vehicles application[J]. Applied Energy,2018,213:375-383.
[47] LYU D,REN B,LI S. Failure modes and mechanisms for rechargeable Lithium-based batteries:A state-of-the-art review[J]. Acta Mechanica,2018,230(3):701-727.
[48] KRISTON A,PFRANG A,DÖRING H,et al. External short circuit performance of Graphite-LiNi1/3Co1/3Mn1/3O2 and Graphite-LiNi0.8Co0.15Al0.05O2 cell at different external resistances[J]. Journal of Power Sources,2017,361:170-181.
[49] 熊瑞,马骕骁,杨瑞鑫,等. 动力电池外部短路故障热-力影响与分析[J]. 机械工程学报,2019,55(2):115-125. XIONG Rui,MA Suxiao,YANG Ruixin. et al. Thermo-mechanical influence and analysis of external short circuit faults in lithium-ion battery[J]. Journal of Mechanical Engineering. 2019,55(2):115-125.
[50] PANCHAL S,DINCER I,AGELIN-CHAAB M,et al. Thermal modeling and validation of temperature distributions in a prismatic lithium-ion battery at different discharge rates and varying boundary conditions[J]. Applied Thermal Engineering,2016,96:190-199.
[51] PANCHAL S,DINCER I,AGELIN-CHAAB M,et al. Experimental and theoretical investigations of heat generation rates for a water cooled LiFePO₄ battery[J]. International Journal of Heat and Mass Transfer,2016,101:1093-1102.
[52] PANCHAL S,MATHEW M,FRASER R,et al. Electrochemical thermal modeling and experimental measurements of 18650 cylindrical lithium-ion battery during discharge cycle for an EV[J]. Applied Thermal Engineering,2018,135:123-132.
[53] WANG Q,MAO B,STOLIAROV S I,et al. A review of lithium ion battery failure mechanisms and fire prevention strategies[J]. Progress in Energy And Combustion Science,2019,73:95-131.
[54] FENG X,OUYANG M,LIU X,et al. Thermal runaway mechanism of lithium ion battery for electric vehicles:A review[J]. Energy Storage Materials,2018,10:246-267.
[55] WANG Q,PING P,ZHAO X,et al. Thermal runaway caused fire and explosion of lithium ion battery[J]. Journal of Power Sources,2012,208:210-224.
[56] LIU Z,HE H. Sensor fault detection and isolation for a lithium-ion battery pack in electric vehicles using adaptive extended Kalman filter[J]. Applied Energy,2017,185:2033-2044.
[57] MIKOLAJCZAK C,KAHN P M,WHITE K,et al. Lithium-ion batteries hazard and use Assessment[M]. Boston:Springer,2011.
[58] XU J,WANG J,LI S,et al. A method to simultaneously detect the current sensor fault and estimate the state of energy for batteries in electric vehicles[J]. Sensors,2016,16(8):1328.
[59] HU X,JIANG H,FENG F,et al. An enhanced multi-state estimation hierarchy for advanced lithium-ion battery management[J]. Applied Energy,2020,257:114019.
[60] DEY S,MOHON S,PISU P,et al. Sensor fault detection,isolation,and estimation in lithium-ion batteries[J]. IEEE Transactions on Control Systems Technology,2016,24(6):2141-2149.
[61] YAO L,WANG Z,MA J. Fault detection of the connection of lithium-ion power batteries based on entropy for electric vehicles[J]. Journal of Power Sources,2015,293:548-561.
[62] LIU G,OUYANG M,LU L,et al. Analysis of the heat generation of lithium-ion battery during charging and discharging considering different influencing factors[J]. Journal of Thermal Analysis and Calorimetry,2014,116(2):1001-1010.
[63] FENG X,SUN J,OUYANG M,et al. Characterization of large format lithium-ion battery exposed to extremely high temperature[J]. Journal of Power Sources,2014,272:457-467.
[64] TOBISHIMA S I,YAMAKI J I. A consideration of lithium cell safety[J]. Journal of Power Sources,1999,81/82:882-886.
[65] HU X,XU L,LIN X,et al. Battery lifetime prognostics[J]. Joule,2020,4(2):310-346.
[66] YOSHIO M. BRODD R J,KOZAWA A. Lithium-ion batteries science and technology[M]. New York:Springer,2009.
[67] 彭影,黄瑞,俞小莉,等. 电动汽车锂离子动力电池冷却方案的对比研究[J]. 机电工程,2015,32:101-107. PENG Ying,HUANG Rui,YU Xiao li,et al. Comparison of the cooling methods on LiFePO₄ power battery for electrical vehicle[J]. Journal of Mechanical & Electrical Engineering,2015,32:101-107.
[68] 金鑫,任献彬,周亮. 智能故障诊断技术研究综述[J]. 国外电子测量技术,2009,28(7):30-32. JIN Xin,REN Xianbin,ZHOU Liang. Overview on intelligent technology of fault diagnosis[J] Foreign Electronic Measurement Technology,2009,28(7):30-32.
[69] 郑杭波,齐国光. 电池组故障诊断模糊专家系统的研究[J]. 高技术通讯,2004,14(6):70-74. ZHENG Hangbo,QI Guoguang. The research of the battery pack fuzzy diagnostic expert system[J]. Chinese High Technology Letters,2004,14(6):70-74.
[70] 刘晓俊. 电池故障智能诊断系统的研究与实现[D]. 北京:北京邮电大学,2010. LIU Xiaojun. Research and application of intelligent battery fault diagnosis system[D]. Beijing:Beijing University of Postsand Telecommunications,2010.
[71] 吴建荣. 纯电动汽车远程监控系统设计及故障诊断方法研究[D]. 长春:吉林大学,2011. WU Jianrong. Design of remote monitoring system and study on fault diagnosis method for electric vehicle[D]. Changchun:Jilin University,2011.
[72] 檀斐. 车用动力锂离子电池系统故障诊断研究与实现[D]. 北京:北京理工大学,2015. TAN Fei. Fault diagnosis and implementation of electric vehicle lithium-ion battery system[D]. Beijing:Beijing Institute of Technology,2015.
[73] 周旸. 电动汽车动力电池系统故障诊断策略与方法研究[D]. 北京:北京理工大学,2013. ZHOU Yang. Research of failure diagnosis strategies and methods for power battery system of electric vehicles[D]. Beijing:Beijing Institute of Technology,2013.
[74] 黄嫄. 电动汽车动力电池在线监测技术研究[D]. 北京:华北电力大学,2015. HUANG Yuan. Study on on-line contamination monitoring method of electric vehicle batteries[D]. Beijing:North China Electric Power University,2015.
[75] 夏淑英. 基于模糊故障树的汽车故障诊断方法及其应用研究[D]. 武汉:湖北工业大学,2017. XIA Shuying. Research on the automobile fault diagnosis its methods and application based on the fuzzy fault tree[D]. Wuhan:Hubei university of technology,2017.
[76] 钱强. 新能源汽车动力电池压差故障与维修技术研究[J]. 电子测试,2020(5):139-140,18. QIAN Qiang. Research on differential pressure fault and maintenance technology of new energy vehicle power battery[J]. Electronic Test,2020(5):139-140,18.
[77] ZHU X,WANG Z,WANG Y,et al. Overcharge investigation of large format lithium-ion pouch cells with Li(Ni0.6Co0.2Mn0.2)O₂ cathode for electric vehicles:Thermal runaway features and safety management method[J]. Energy,2019,169:868-880.
[78] 王震坡,刘鹏,孙逢春. 工作状态下的电动汽车中成组电池的单体电池的检测装置:中国,CN201220725080.3[P]. 2013-06-05. WANG Zhenpo,LIU Peng,SUN Fengchun. Detecting device for battery cell of group battery in electric vehicle during working state:China,CN201220725080.3[P]. 2013-06-05.
[79] 中华人民共和国工业与信息化部. GB/T 32960-2016电动汽车远程服务与管理系统技术规范[S]. 北京:中国标准出版社,2016. Ministry of Industry and Information Technology in China. GB/T 32960-2016 Technical Specifications of Remote Service and Management System for Electric Vehicles[S]. Beijing:Standards Press of China,2016.
[80] XIE J,CHEN J. Battery early warning and monitoring system:U.S,Patent 8,952,823[P]. 2015-02-10.
[81] 何朴芳. 汽车电池管理的远程监护与故障诊断[D]. 上海:东华大学,2015. HE Pufang. Remote monitoring and fault diagnosis of automobile battery management[D]. Shanghai:Donghua University,2015.
[82] XIONG J,BANVAIT H,LI L,et al. Failure detection for over-discharged li-ion batteries[C]//2012 IEEE International Electric Vehicle Conference,March 4-8,2012,Greenville,SC,USA:IEEE,2012:1-5.
[83] XIA B,CHEN Z,MI C. External short circuit fault diagnosis for lithium-ion batteries[C]//2014 IEEE Transportation Electrification Conference and Expo (ITEC),June 15-18,2014,Dearborn,MI,USA:IEEE,2014:1-6.
[84] 刘兵晓,杨瑞,刘晓康. 一种电池微短路的检测方法及装置:中国,CN108241102A[P]. 2018-07-03. LIU Bingxiao,YANG Rui,LIU Xiaokang. Method and device for detecting battery micro-short circuit:China,CN108241102A[P]. 2018-07-03.
[85] 赵洋. 基于大数据的电动汽车动力电池系统故障诊断方法研究[D]. 北京:北京理工大学,2018. ZHAO Yang. Research on fault diagnosis methods of electric vehicle power battery system based on big data[D]. Beijing:Beijing Institute of Technology,2018.
[86] 王慧,容旭东. 非线性系统故障诊断与容错控制技术综述[J]. 浙江万里学院学报,2010,23(4):43-48. WANG Hui,RONG Xudong. Overview of fault diagnosis and fault-tolerant control for nonlinear systems[J]. Journal of Zhejiang Wanli University,2010,23(4):43-48.
[87] TOMASOV M,KAJANOVA M,BRACINIK P,et al. Overview of battery models for sustainable power and transport applications[J]. Transportation Research Procedia,2019,40:548-555.
[88] 熊瑞. 基于数据模型融合的电动车辆动力电池组状态估计研究[D]. 北京:北京理工大学,2014. XIONG Rui. Estimation of battery pack state for electric vehicles using model-data fusion approach[D]. Beijing:Beijing Institute of Technology,2014.
[89] SINGH A,IZADIAN A,ANWAR S. Fault diagnosis of li-ion batteries using multiple-model adaptive estimation[C]//IECON 2013-39th Annual Conference of the IEEE Industrial Electronics Society,November 10-13,2013. Vienna,Austria:IEEE,2013:3524-3529.
[90] SIDHU A,IZADIAN A,ANWAR S. Adaptive nonlinear model-based fault diagnosis of li-ion batteries[J]. IEEE Transactions on Industrial Electronics,2015,62(2):1002-1011.
[91] ALAVI S M M,SAMADI M F,SAIF M. Plating mechanism detection in lithium-ion batteries,by using a particle-filtering based estimation technique[C]//2013 American Control Conference,June 17-19,2013. Washington,DC,USA:IEEE,2013:4356-4361.
[92] CHEN W,CHEN W,SAIF M,et al. Simultaneous fault isolation and estimation of lithium-ion batteries via synthesized design of luenberger and learning observers[J]. IEEE Transactions on Control Systems Technology,2014,22(1):290-298.
[93] CHEN Z,XIONG R,TIAN J,et al. Model-based fault diagnosis approach on external short circuit of lithium-ion battery used in electric vehicles[J]. Applied Energy,2016,184:365-374.
[94] GAO W,ZHENG Y,OUYANG M,et al. Micro-short-circuit diagnosis for series-connected lithium-ion battery packs using mean-difference model[J]. IEEE Transactions on Industrial Electronics,2019,66(3):2132-2142.
[95] DEY S,BIRON Z A,TATIPAMULA S,et al. On-board thermal fault diagnosis of lithium-ion batteries for hybrid electric vehicle application[J]. IFAC-PapersOnLine,2015,48(15):389-394.
[96] DEY S,BIRON Z A,TATIPAMULA S,et al. Model-based real-time thermal fault diagnosis of lithium-ion batteries[J]. Control Engineering Practice,2016,56:37-48.
[97] DEY S,PEREZ H E,MOURA S J. Model-Based battery thermal fault diagnostics:Algorithms,analysis,and experiments[J]. IEEE Transactions on Control Systems Technology,2019,27(2):576-587.
[98] 徐蒙. 磷酸铁锂动力电池放电过程电化学-热耦合模型研究[D]. 北京:北京交通大学,2014. XU Meng. Study Oil Electrochemical and heat transfer model of LiFePO₄ power battery during discharge process[D]. Beijing:Beijing Jiaotong University,2014.
[99] CHEN M,SUN Q,LI Y,et al. A thermal runaway simulation on a lithium titanate battery and the battery module[J]. Energies,2015,8(1):490-500.
[100] FENG X,WENG C,OUYANG M,et al. Online internal short circuit detection for a large format lithium ion battery[J]. Applied Energy,2016,161:168-180.
[101] OUYANG M,ZHANG M,FENG X,et al. Internal short circuit detection for battery pack using equivalent parameter and consistency method[J]. Journal of Power Sources,2015,294:272-283.
[102] XIA B,SHANG Y,NGUYEN T,et al. A correlation based fault detection method for short circuits in battery packs[J]. Journal of Power Sources,2017,337:1-10.
[103] LI X,WANG Z. A novel fault diagnosis method for lithium-Ion battery packs of electric vehicles[J]. Measurement,2018,116:402-411.
[104] KANG Y,DUAN B,ZHOU Z,et al. A multi-fault diagnostic method based on an interleaved voltage measurement topology for series connected battery packs[J]. Journal of Power Sources,2019,417:132-144.
[105] 李晓宇,肖仁鑫,潘二东,等. 基于聚类分析算法电动汽车在线安全性研究[J]. 昆明理工大学学报,2017,42(2):107-112. LI Xiaoyu,XIAO Renxin,PAN Erdong,et al. Research of electric vehicle online security based on clustering analysis algorithm[J]. Journal of Kunming University of Science and Technology,2017,42(2):107-112.
[106] LIU P,WANG J,WANG Z,et al. High-dimensional data abnormity detection based on improved Variance-of-Angle (VOA) algorithm for electric vehicles battery[C]//2019 IEEE Energy Conversion Congress and Exposition (ECCE),September 29-October 3,2019. Baltimore,MD,USA:IEEE,2019:5072-5077.
[107] LI D,ZHANG Z,LIU P,et al. DBSCAN-based thermal runaway diagnosis of battery systems for electric vehicles[J]. Energies,2019,12(15):2977.
[108] ZHAO Y,LIU P,WANG Z,et al. Fault and defect diagnosis of battery for electric vehicles based on big data analysis methods[J]. Applied Energy,2017,207:354-362.
[109] WANG Z,HONG J,LIU P,et al. Voltage fault diagnosis and prognosis of battery systems based on entropy and Z-score for electric vehicles[J]. Applied Energy,2017,196:289-302.
[110] HONG J,WANG Z,LIU P. Big-data-based thermal runaway prognosis of battery systems for electric vehicles[J]. Energies,2017,10(7):919.
[111] LIU P,SUN Z,WANG Z,et al. Entropy-based voltage fault diagnosis of battery systems for electric vehicles[J]. Energies,2018,11(1):136.
[112] LI X,DAI K,WANG Z,et al. Lithium-ion batteries fault diagnostic for electric vehicles using sample entropy analysis method[J]. Journal of Energy Storage,2020,27:101121.
[113] HONG J,WANG Z,CHEN W,et al. Multi-fault synergistic diagnosis of battery systems based on the modified multi-scale entropy[J]. International Journal of Energy Research,2019,43(14):8350-8369.
[114] CHEN Z,XU K,WEI J,et al. Voltage fault detection for lithium-ion battery pack using local outlier factor[J]. Measurement,2019,146:544-556.
[115] 张旭. 动力电池组内短路检测算法研究[D]. 北京:北京理工大学,2019. ZHANG Xu. Investigation on internal short circuit detection algorithm for power battery pack[D]. Beijing:Beijing Institute of Technology,2019.
[116] ZHANG Z,KONG X,ZHENG Y,et al. Real-time diagnosis of micro-short circuit for li-ion batteries utilizing low-pass filters[J]. Energy,2019,166:1013-1024.
[117] YANG R,XIONG R,HE H,et al. A fractional-order model-based battery external short circuit fault diagnosis approach for all-climate electric vehicles application[J]. Journal of Cleaner Production,2018,187:950-959.
[118] 韩冰海,王东梅,李世云. 一种基于直流内阻的电池组连接可靠性的检测方法[J]. 电源技术,2017,41(7):981-983. HAN Binghai,WANG Dongmei,LI Shiyun. Research on battery connection reliability based on DC internal resistanc e[J]. Chinese Journal of Power Sources,2017,41(7):981-983.
[119] MARCICKI J,ONORI S,RIZZONI G. Nonlinear fault detection and isolation for a lithium-ion battery management system[C]//ASME 2010 Dynamic Systems and Control Conference,September 12-15,2010. Cambridge,Massachusetts,USA:ASME. 2010:607-614.
[120] 郑宗豪. 电动汽车传感器的故障诊断研究[D]. 乌鲁木齐:新疆大学,2019. ZHENG Zonghao. Research on fault diagnosis of electric vehicle sensors[D]. Urumqi:Xinjiang University,2019.
[121] LIU Z,AHMED Q,RIZZONI G,et al. Fault detection and isolation for lithium-ion battery system using structural analysis and sequential residual generation[C]//ASME 2014 Dynamic Systems and Control Conference,October 22-24,2014. San Antonio,Texas,USA:ASME,2014:DSCC2014-6101.
[122] LOMBARDI W,ZARUDNIEV M,LESECQ S,et al. Sensors fault diagnosis for a BMS[C]//2014 European Control Conference (ECC),June 24-27,2014. Strasbourg,France:IEEE,2014:952-957.
[123] LIU Z,HE H. Model-based sensor fault diagnosis of a lithium-ion battery in electric vehicles[J]. Energies,2015,8(7):6509-6527.
[124] XIONG R,YU Q,SHEN W,et al. A sensor fault diagnosis method for a lithium-ion battery pack in electric vehicles[J]. IEEE Transactions on Power Electronics,2019,34(10):9709-9718.
[125] 杨洋,杨林,李冬冬,等. 电动汽车电池组连接松脱故障诊断[J]. 汽车技术,2019(5):43-48. YANG Yang,YANG Lin. LI Dongdong. et al. A loose connection fault diagnosis for battery pack of electric vehicle[J]. Automobile Technology,2019(5):43-48.
[126] XIA B,MI C. A fault-tolerant voltage measurement method for series connected battery packs[J]. Journal of Power Sources,2016,308:83-96.
[127] XIA B,NGUYEN T,YANG J,et al. The improved interleaved voltage measurement method for series connected battery packs[J]. Journal of Power Sources,2016,334:12-22.
[128] 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,2013,223:136-146.
[129] SUN Z,LIU P,WANG Z. Real-time fault diagnosis method of battery system based on shannon entropy[J]. Energy Procedia,2017,105:2354-2359.
[130] MA M,WANG Y,DUAN Q,et al. Fault detection of the connection of lithium-ion power batteries in series for electric vehicles based on statistical analysis[J]. Energy,2018,164:745-756.