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- Creators: Arizona State University
- Member of: Theses and Dissertations
Currently, several hard-switching topologies have been employed such as conventional boost DC/DC, interleaved step-up DC/DC, and full-bridge DC/DC converter. These converters face respective limitations in achieving high step-up conversion ratio, size and weight issues, or high component count. In this work, a bi-directional synchronous boost DC/DC converter with easy interleaving capability is proposed with a novel ZVT mechanism. This converter steps up the EV battery voltage of 200V-300V to a wide range of variable output voltages ranging from 310V-800V. High power density and efficiency are achieved through high switching frequency of 250kHz for each phase with effective frequency doubling through interleaving. Also, use of wide bandgap high voltage SiC switches allows high efficiency operation even at high temperatures.
Comprehensive analysis, design details and extensive simulation results are presented. Incorporating ZVT branch with adaptive time delay results in converter efficiency close to 98%. Experimental results from a 2.5kW hardware prototype validate the performance of the proposed approach. A peak efficiency of 98.17% has been observed in hardware in the boost or motoring mode.
Lithium-ion battery (LIB) packs were subjected to room and high temperature settings while being cycled under a current profile created from a drive cycle. The Federal Urban Driving Schedule (FUDS) was selected and modified to simulate normal city driving situation using an electric only drive mode. Capacity and impedance fade of the LIB packs were monitored over the lifetime of the pack to determine the overall performance through the variables of energy and power fade. Regression analysis was done on the energy and power fade of the LIB pack to determine the duration life of LIB packs for HEV applications. This was done by comparing energy and power fade with the average lifetime mileage of a vehicle.
The collected capacity and impedance data was used to create an electrical equivalent model (EEM). The model was produced through the process of a modified Randles circuit and the creation of the inverse constant phase element (ICPE). Results indicated the model had a potential for high fidelity as long as a sufficient amount of data was gathered. X-ray powder diffraction (XRD) and a scanning electron microscope (SEM) was performed on a fresh and cycled LFP battery. SEM results suggested a dramatic growth on LFP crystals with a reduction in carbon coating after cycling. XRD effects showed a slight uniformed strain and decrease in size of LFP olivine crystals after cycling.
Lithium ion batteries are quintessential components of modern life. They are used to power smart devices — phones, tablets, laptops, and are rapidly becoming major elements in the automotive industry. Demand projections for lithium are skyrocketing with production struggling to keep up pace. This drive is due mostly to the rapid adoption of electric vehicles; sales of electric vehicles in 2020 are more than double what they were only a year prior. With such staggering growth it is important to understand how lithium is sourced and what that means for the environment. Will production even be capable of meeting the demand as more industries make use of this valuable element? How will the environmental impact of lithium affect growth? This thesis attempts to answer these questions as the world looks to a decade of rapid growth for lithium ion batteries.
The major emphasis in this dissertation is the development of theories and associated algorithms for a new set of location problems defined on continuous network space related to siting multiple RPs for range limited vehicles.
This dissertation covers three optimization problems: locating multiple RPs on a line network, locating multiple RPs on a comb tree network, and locating multiple RPs on a general tree network. For each of the three problems, finding the minimum number of RPs needed to refuel all Origin-Destination (O-D) flows is considered as the first objective. For this minimum number, the location objective is to locate this number of RPs to minimize weighted sum of the travelling distance for all O-D flows. Different exact algorithms are proposed to solve each of the three algorithms.
In the first part of this dissertation, the simplest case of locating RPs on a line network is addressed. Scenarios include single one-way O-D pair, multiple one-way O-D pairs, round trips, etc. A mixed integer program with linear constraints and quartic objective function is formulated. A finite dominating set (FDS) is identified, and based on the existence of FDS, the problem is formulated as a shortest path problem. In the second part, the problem is extended to comb tree networks. Finally, the problem is extended to general tree networks. The extension to a probabilistic version of the location problem is also addressed.