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锂离子电池健康评估及剩余使用寿命预测方法研究-测试计量技术及仪器专业论文.docx

锂离子电池健康评估及剩余使用寿命预测方法研究-测试计量技术及仪器专业论文.docx

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锂离子电池健康评估及剩余使用寿命预测方法研究-测试计量技术及仪器专业论文

ABSTRACTThefunctionalityandreliabilityofLi-ionbatteryasmajorenergystorage devicehas receivedmoreandmoreattentionsfromawidespectrumofstakeholders including federal/state policymakers, business leaders, technicalresearchers,environmentalgroupsandgeneralpublic.FailuresofLi-ionbatterynotonly resultinseriousinconvenienceandenormouscosts,butalsoincreasetheriskofinducingcatastrophic consequences. In order to prevent severe failure from happening and optimize the Li-ion battery maintenance schedules, breakthroughs in prognostics and health monitoring of Li-ion battery must be achieved.The paperpresents as:TheanalysisofLi-ionbatterydatasetsfromNASAAmesResearchCenter.theanalysis involvestheimpactoftemperatureagainstLi-ionbatteryhealth,theimpactofEIStestsagainst Li-ionbatteryhealth, theimpactofdepthofdischargeagainstLi-ionbatteryhealthandtheinvestigation of randomness in batteryhealth degradation.Theresearchof Gaussianmixturemodel.Firstly, PrincipalComponentAnalysis(PCA) isutilizedforfeatureextractionfromtherawdatacollectedundernormalconditon,Then,theGaussianMixtureModel(GMM)isbuiltbasedonthefeatureextraction.Lastlythetestingdata comesinandconstructsanewGMM.ThedistanceorsimilarityofthisGMMandtheonegeneratedinthetrainingprocesswillindicatethecurrenthealthstatusofbattery, asrepresentedbyConfidenceValue(CV).The resultofthe experiment is satisfactory.Theresearchof ARIMA-PFfusionprognosticframework.ItiscomposedofARIMA AlgorithmandPFAlgorithm.Firstly,monitorthelithiumionbatteryonline, thenrunthe correspondingalgorithmbasedonshort-termforecastsorlong-termforecastsRequirements,wegettheforecastmapswhichtransverseandlongitudinalcoordinatesstandforthecycleand capacityrespectively.Theresultoftheexperimentindicatestheproposedprognosticframework can predict lithiumion batteryRULaccuratelyand fast.Keywords:Li-ionbattery, healthassessment,remainingusefullifeanalysis,gaussian mixturemode,autoregressive integrated movingaverage model,particle filter目录第一章绪论....

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