Date of Award
Master of Science in Mechanical Engineering (MSME)
Douglas E. Adams
Douglas E. Adams
Committee Member 1
James Eric Dietz
With their superior advantages of high capacity and low percentage of self-discharge, lithium-ion batteries, which are most commonly used as power sources for hand-held electronic devices, have become the most popular choice for power storage in electric vehicles. Due to the increased potential for long life of lithium-ion batteries in vehicle applications, manufacturers are pursuing methodologies to increase the reliability of their batteries. Methods are now being developed to monitor the health of lithium-ion batteries throughout their life cycle. The work in this thesis is focused on utilizing non-destructive vibration diagnostic testing methods to monitor changes in the physical properties of the lithium-ion battery electrodes, which dictate the states of charge (SOCs) and states of health (SOHs) of the battery cell. Inside a lithium-ion battery cell, lithium ions travel from cathodes to anodes during charge and reverse during discharge; these processes transfer matter from one electrode to another causing mechanical properties such as thickness, mass, and stiffness of the electrodes inside a battery cell to change at different states of charge; therefore, the detection of these changes will serve to determine the state of charge of the battery cell. As mass and stiffness of the electrodes change during charge and discharge, they will respond to the excitation input differently. An automated vibration diagnostic test is developed to characterize the state of charge of a lithium-ion battery cell by measuring the amplitude and phase of the kinematic response as a function of excitation frequency at different states of charge of the battery cell and at different times in the life of the cell. Also, the mechanical properties of the electrodes are obtained by direct measurements to estimate the thickness change at different SOCs and to develop a first-principles frequency response model for the battery cell. The correlation between the vibration test results and the model will be used to determine exact the state of charge of the cell.
Pham, Huan Le, "Health Diagnosis of Lithium-ion Battery Cell Using Vibration-based Test and Analysis" (2013). Open Access Theses. 123.