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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01cn69m683b
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dc.contributor.advisorSteingart, Daniel-
dc.contributor.authorDavies, Gregory-
dc.contributor.otherMechanical and Aerospace Engineering Department-
dc.date.accessioned2018-06-12T17:47:06Z-
dc.date.available2018-09-05T08:09:23Z-
dc.date.issued2018-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01cn69m683b-
dc.description.abstractUltrasound has been an invaluable and widely used tool in the medical and non-destructive testing (NDT) sectors. Much of its success is attributable to its low-cost, compact size, the speed and ease of its application, and the useful qualitative information that it provides. However, until recently the technique has not been applied to dynamic and changing material systems. This dissertation explores the application of ultrasonic techniques to characterize batteries - systems that undergo both electrochemical and mechanical changes during the course of their lifetime (charging, discharging, aging). Two battery specific applications are surveyed: (i) the application of ultrasound for accurate predictions of state of charge (SOC) and state of health (SOH), as a method for augmenting traditional battery management systems; and (ii) the application of ultrasound for tomographic imaging. In addition, two more fundamental studies are presented: (i) a computational investigation of the coupled electrochemical-mechanical changes and structural properties of a cycling battery that give rise to the measured, changing ultrasonic signals; and (ii) an in-operando cycling/ultrasound/energy-dispersive x-ray diffraction (EDXRD) study of a battery, investigating the relationships between its internal material structures and its ultrasonic characterization. More specifically, in Chapter 2 ultrasonic measurements were combined with a supervised machine-learning technique, which was used to predict the SOC and SOH of lithium-ion cells that had been operated for several hundred cycles. Excellent results were demonstrated, with the technique showing an accuracy of ~1% for both SOC and SOH prediction. In Chapter 3, to explain the measurable and repeatable ultrasonic signal changes during cycling, a model of ultrasonic propagation through a finely layered lithium-ion battery structure was developed. The model demonstrated that graphite is the primary determinant of the ultrasonic response of a cycling battery, and that finely layered structures can significantly impact wave propagation. Next, in Chapter 4, the combination of ultrasonic measurements with full-waveform inversion techniques originating from geophysics was investigated, demonstrating that using ultrasound for structure and property reconstruction may be feasible. Finally, Chapter 5 presents the in-situ ultrasound/EDXRD experiment, linking specific material properties with previously unexplained behaviors in the ultrasonic signals.-
dc.language.isoen-
dc.publisherPrinceton, NJ : Princeton University-
dc.relation.isformatofThe Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog: <a href=http://catalog.princeton.edu> catalog.princeton.edu </a>-
dc.subjectBatteries-
dc.subjectInversions-
dc.subjectSOC-
dc.subjectSOH-
dc.subjectUltrasound-
dc.subjectXRD-
dc.subject.classificationMechanical engineering-
dc.subject.classificationEnergy-
dc.subject.classificationAcoustics-
dc.titleCharacterization of batteries using ultrasound: applications for battery management and structural determination-
dc.typeAcademic dissertations (Ph.D.)-
pu.projectgrantnumber690-2143-
pu.embargo.terms2018-09-05-
Appears in Collections:Mechanical and Aerospace Engineering

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