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dc.contributor.authorBehjati, Hamiden_US
dc.date.accessioned2014-03-12T23:49:23Z
dc.date.available2014-03-12T23:49:23Z
dc.date.issued2014-03-12
dc.date.submittedJanuary 2013en_US
dc.identifier.otherDISS-12403en_US
dc.identifier.urihttp://hdl.handle.net/10106/24087
dc.description.abstractSustainable energy sources and power electronic systems for utilizing such energy sources are becoming indispensible components of the modern power grid. The ability of multiport converters to mitigate the intermittency issues associated with these energy sources have made them attractive candidates for renewable energy conversion systems. Two single-stage multiport dc-dc converters, with independent and series outputs, are proposed in this dissertation. The advantages and applications of the proposed topologies are discussed. The ability of the proposed converters to regulate the input powers, coming from different energy sources, in addition to regulating the output voltages stands out. Specific switching schemes are presented for the proposed converters and the dynamic models of the converters are developed based on the designated switching scheme. Appropriate control algorithms are presented for regulating the input powers and output voltages.Proper design and development of digital controllers for multiport dc energy conversion systems requires exact discrete-time modeling of such systems. An exact discrete-time modeling framework is set forth for direct digital-control design of multiport dc-dc converters. The proposed modeling technique addresses the peculiar aspects of multiport dc-dc converters, which make the use of conventional continuous-time modeling for such converters prone to failure. Time-multiplexing switching schemes are accommodated by considering multiple propagation paths during each switching period. Sampling effects, modulator effects, and the propagation delays due to multiple propagation paths are included. The proposed model can accommodate both leading and trailing edge PWM schemes. The approximations inherent in the averaging techniques are avoided by using Floquet theory.A cooperative control method is also proposed for multiphase dc-dc converters. The proposed cooperative control scheme enjoys structural modularity, plug-and-play capability, fault tolerance against random failures in the converters and/or communication links, and satisfactory dynamic performance. A general analytical framework is provided to study modular dc-dc converters with an arbitrary communication graph. Hence, the designer has the freedom to choose among the various types of graphs based on the available communication resources and the desired level of reliability and fault tolerance. The dynamic model of the cooperative multi-phase converter system is developed and analyzed.Semiconductor switches are, arguably, among the reliability bottlenecks in power electronic converters and, especially, multiport converters. Redundant switch structures are proposed for reliability improvement in such systems. Parallel and standby configurations are applied to semiconductor switches to this aim. The reliability models of both configurations are developed based on Markov process. Mean Time to Failure (MTTF) of each configuration is derived in terms of the underlying parameters. It is demonstrated that there is a boundary condition in which both configurations have the same MTTF. This boundary condition is expressed in terms of the junction temperature of the semiconductor switch in the steady state. The temperature range in which the parallel configuration is more reliable is formulated for different types of power semiconductor switches.en_US
dc.description.sponsorshipDavoudi, Alien_US
dc.language.isoenen_US
dc.publisherElectrical Engineeringen_US
dc.titleMultiport DC Energy Conversion Systemsen_US
dc.typePh.D.en_US
dc.contributor.committeeChairDavoudi, Alien_US
dc.degree.departmentElectrical Engineeringen_US
dc.degree.disciplineElectrical Engineeringen_US
dc.degree.grantorUniversity of Texas at Arlingtonen_US
dc.degree.leveldoctoralen_US
dc.degree.namePh.D.en_US


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