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• JI B，SONG X G，CAO W P，et al. Active temperature control of Li-ion batteries in electric vehicles［C］//Hybrid & Electric Vehicles Conference. IET，2013.
• ANGELES CABAÑERO M，ALTMANN J，GOLD L，et al. Investigation of the temperature dependence of lithium plating onset conditions in commercial Li-ion batteries［J］. Energy，2019，171：1217-1228.
• JIANG J，GAO Y，ZHANG C，et al. Lifetime Rapid Evaluation Method for Lithium-Ion Battery with Li（NiMnCo）O2 Cathode［J］. Journal of The Electrochemical Society，2019，166（6）：A1070-A1081.
• THOMAS E V，BLOOM I，CHRISTOPHERSEN J P，et al. Rate-based degradation modeling of lithium-ion cells［J］. Journal of Power Sources，2012，206：378-382.
• BIRKL C R，ROBERTS M R，MCTURK E，et al. Degradation diagnostics for lithium ion cells［J］. Journal of Power Sources，2017，341：373-386.
• LI Y，LIU K，FOLEY A M，et al. Data-driven health estimation and lifetime prediction of lithium-ion batteries：A review［J］. Renewable and Sustainable Energy Reviews，2019，113：109254.
• ITURRONDOBEITIA A，AGUESSE F，GENIES S，et al. Post-Mortem Analysis of Calendar-Aged 16 Ah NMC/Graphite Pouch Cells for EV Application［J］. The Journal of Physical Chemistry C，2017，121（40）：21865-21876.
• RAHE C，KELLY S T，RAD M N，et al. Nanoscale X-ray imaging of ageing in automotive lithium ion battery cells［J］. Journal of Power Sources，2019，433.
• RAUHALA T，JALKANEN K，ROMANN T，et al. Low-temperature aging mechanisms of commercial graphite/LiFePO4 cells cycled with a simulated electric vehicle load profile-A post-mortem study［J］. Journal of Energy Storage，2018，20：344-356.
• 王天鸶. 锂离子电池容量损失预测及健康状态估计研究［D］. 哈尔滨工业大学，2016.
• DOYLE M. Comparison of Modeling Predictions with Experimental Data from Plastic Lithium Ion Cells［J］. Journal of The Electrochemical Society，1996，143（6）：1890.
• LI J，ADEWUYI K，LOTFI N，et al. A single particle model with chemical/mechanical degradation physics for lithium ion battery State of Health （SOH） estimation［J］. Applied Energy，2018，212：1178-1190.
• RAHIMIAN S K，RAYMAN S，WHITE R E. Comparison of single particle and equivalent circuit analog models for a lithium-ion cell［J］. Journal of Power Sources，2011，196（20）：8450-8462.
• SUBRAMANIAN V R，BOOVARAGAVAN V，RAMADESIGAN V，et al. Mathematical Model Reformulation for Lithium-Ion Battery Simulations：Galvanostatic Boundary Conditions［J］. Journal of The Electrochemical Society，2009，156（4）：A260-A271.
• 姜久春，马泽宇，李雪，等. 基于开路电压特性的动力电池健康状态诊断与估计［J］. 北京交通大学学报，2016，40（04）：92-98.
• DUBARRY M，TRUCHOT C，LIAW B Y. Synthesize battery degradation modes via a diagnostic and prognostic model［J］. Journal of Power Sources，2012，219：204-216.
• ANSEÁN D，DUBARRY M，DEVIE A，et al. Operando lithium plating quantification and early detection of a commercial LiFePO4 cell cycled under dynamic driving schedule［J］. Journal of Power Sources，2017，356：36-46.
• 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］. American Control Conference. IEEE，2013.
• 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.
• SEO M，GOH T，PARK M，et al. Detection of Internal Short Circuit in Lithium Ion Battery Using Model-Based Switching Model Method［J］. Energies，2017，10（1）：76.
• ZHANG H，PEI L，SUN J，et al. Online Diagnosis for the Capacity Fade Fault of a Parallel-Connected Lithium Ion Battery Group［J］. Energies，2016，9（5）：387.
• 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.
• KONG X，ZHENG Y，OUYANG M，et al. Fault diagnosis and quantitative analysis of micro-short circuits for lithium-ion batteries in battery packs［J］. Journal of Power Sources，2018，395：358-368.
• NAHA A，KHANDELWAL A，HARIHARAN K S，et al. On-Board Short-Circuit Detection of Li-ion Batteries Undergoing Fixed Charging Profile as in Smartphone Applications［J］. IEEE Transactions on Industrial Electronics，2019，66（11）：8782-8791.
• 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.
• HONG J，WANG Z，YAO Y. Fault prognosis of battery system based on accurate voltage abnormity prognosis using long short-term memory neural networks［J］. Applied Energy，2019，251：113381.
• GAO Y，JIANG J，ZHANG C，et al. Aging mechanisms under different state-of-charge ranges and the multi-indicators system of state-of-health for lithium-ion battery with Li（NiMnCo）O2 cathode［J］. Journal of Power Sources，2018，400：641-651.