State-of-charge estimation of a Li-ion battery system with nonlinear output function

dc.contributor.advisorQian, Chunjiang
dc.contributor.authorSoundararajan, Dwarakanath
dc.contributor.committeeMemberKrishnaswami, Hariharan
dc.contributor.committeeMemberBhalla, Amar
dc.descriptionThis item is available only to currently enrolled UTSA students, faculty or staff. To download, navigate to Log In in the top right-hand corner of this screen, then select Log in with my UTSA ID.
dc.description.abstractVarious estimation techniques to estimate the State-of-Charge (SOC) for different types of battery models exist today. However, a non-stochastic nonlinear observer has never been implemented. This thesis is an attempt to fill that void by designing several linear and nonlinear observers, which are simple, intuitive and also convenient to analyze. The historical perspective of such techniques is provided so that it is convenient to see how various techniques have evolved over time. Then, a survey of various battery estimation techniques is conducted and it is seen that the battery model based on the voltage-based model is one of the simplest methods. The advantages and disadvantages of different methods are also mentioned. The model used here is based on Open-Circuit Voltage (OCV) model. The relationship between the OCV and SOC is highly nonlinear. In this thesis, it is found that one of the best ways to express this function is to express them as sum of two exponential functions. The parameters of the battery vary with respect to SOC. The system is greatly simplified by assuming that these parameters are constant. First a linear observer for this battery system is designed and analyzed. Then, a nonlinear observer is transformed into a canonical form and the observer is designed in that domain. Then, the nonlinear observers are designed for different variations of input current. The observers designed are simple, globally observable and have several advantages over other observers mentioned above.
dc.description.departmentElectrical and Computer Engineering
dc.format.extent78 pages
dc.subjectLi-ion battery
dc.subjectState of Charge
dc.subject.classificationElectrical engineering
dc.titleState-of-charge estimation of a Li-ion battery system with nonlinear output function
dcterms.accessRightspq_closed and Computer Engineering of Texas at San Antonio of Science


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