Improved Battery State Estimation Using Novel Sensing Techniques.
dc.contributor.author | Abdul Samad, Nassim | |
dc.date.accessioned | 2016-06-10T19:32:13Z | |
dc.date.available | NO_RESTRICTION | |
dc.date.available | 2016-06-10T19:32:13Z | |
dc.date.issued | 2016 | |
dc.date.submitted | 2016 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/120815 | |
dc.description.abstract | Lithium-ion batteries have been considered a great complement or substitute for gasoline engines due to their high energy and power density capabilities among other advantages. However, these types of energy storage devices are still yet not widespread, mainly because of their relatively high cost and safety issues, especially at elevated temperatures. This thesis extends existing methods of estimating critical battery states using model-based techniques augmented by real-time measurements from novel temperature and force sensors. Typically, temperature sensors are located near the edge of the battery, and away from the hottest core cell regions, which leads to slower response times and increased errors in the prediction of core temperatures. New sensor technology allows for flexible sensor placement at the cell surface between cells in a pack. This raises questions about the optimal locations of these sensors for best observability and temperature estimation. Using a validated model, which is developed and verified using experiments in laboratory fixtures that replicate vehicle pack conditions, it is shown that optimal sensor placement can lead to better and faster temperature estimation. Another equally important state is the state of health or the capacity fading of the cell. This thesis introduces a novel method of using force measurements for capacity fade estimation. Monitoring capacity is important for defining the range of electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs). Current capacity estimation techniques require a full discharge to monitor capacity. The proposed method can complement or replace current methods because it only requires a shallow discharge, which is especially useful in EVs and PHEVs. Using the accurate state estimation accomplished earlier, a method for downsizing a battery pack is shown to effectively reduce the number of cells in a pack without compromising safety. The influence on the battery performance (e.g. temperature, utilization, capacity fade, and cost) while downsizing and shifting the nominal operating SOC is demonstrated via simulations. The contributions in this thesis aim to make EVs, HEVs and PHEVs less costly while maintaining safety and reliability as more people are transitioning towards more environmentally friendly means of transportation. | |
dc.language.iso | en_US | |
dc.subject | Battery controls and modeling | |
dc.subject | Novel temperature sensors for better battery temperature estimation | |
dc.subject | Capacity estimation using novel force measurments | |
dc.subject | Battery pack downsizing | |
dc.title | Improved Battery State Estimation Using Novel Sensing Techniques. | |
dc.type | Thesis | en_US |
dc.description.thesisdegreename | PhD | |
dc.description.thesisdegreediscipline | Mechanical Engineering | |
dc.description.thesisdegreegrantor | University of Michigan, Horace H. Rackham School of Graduate Studies | |
dc.contributor.committeemember | Stefanopoulou, Anna G | |
dc.contributor.committeemember | Sun, Jing | |
dc.contributor.committeemember | Epureanu, Bogdan | |
dc.contributor.committeemember | Siegel, Jason B | |
dc.subject.hlbsecondlevel | Mechanical Engineering | |
dc.subject.hlbtoplevel | Engineering | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/120815/1/nassimab_1.pdf | |
dc.owningcollname | Dissertations and Theses (Ph.D. and Master's) |
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