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Increasing demand for reducing the stress on fossil fuels has motivated automotive industries to shift towards sustainable modes of transport through electric and hybrid electric vehicles. Most fuel efficient cars of year 2016 are hybrid vehicles as reported by environmental protection agency. Hybrid vehicles operate with internal combustion engine and

Increasing demand for reducing the stress on fossil fuels has motivated automotive industries to shift towards sustainable modes of transport through electric and hybrid electric vehicles. Most fuel efficient cars of year 2016 are hybrid vehicles as reported by environmental protection agency. Hybrid vehicles operate with internal combustion engine and electric motors powered by batteries, and can significantly improve fuel economy due to downsizing of the engine. Whereas, Plug-in hybrids (PHEVs) have an additional feature compared to hybrid vehicles i.e. recharging batteries through external power outlets. Among hybrid powertrains, lithium-ion batteries have emerged as a major electrochemical storage source for propulsion of vehicles.

In PHEVs, batteries operate under charge sustaining and charge depleting mode based on torque requirement and state of charge. In the current article, 26650 lithium-ion cells were cycled extensively at 25 and 50 oC under charge sustaining mode to monitor capacity and cell impedance values followed by analyzing the Lithium iron phosphate (LiFePO4) cathode material by X-ray diffraction analysis (XRD). High frequency resistance measured by electrochemical impedance spectroscopy was found to increase significantly under high temperature cycling, leading to power fading. No phase change in LiFePO4 cathode material is observed after 330 cycles at elevated temperature under charge sustaining mode from the XRD analysis. However, there was significant change in crystallite size of the cathode active material after charge/discharge cycling with charge sustaining mode. Additionally, 18650 lithium-ion cells were tested under charge depleting mode to monitor capacity values.
ContributorsBadami, Pavan Pramod (Author) / Kannan, Arunachala Mada (Thesis advisor) / Huang, Huei Ping (Thesis advisor) / Ren, Yi (Committee member) / Arizona State University (Publisher)
Created2016
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Description
Tolerance specification for manufacturing components from 3D models is a tedious task and often requires expertise of “detailers”. The work presented here is a part of a larger ongoing project aimed at automating tolerance specification to aid less experienced designers by producing consistent geometric dimensioning and tolerancing (GD&T). Tolerance specification

Tolerance specification for manufacturing components from 3D models is a tedious task and often requires expertise of “detailers”. The work presented here is a part of a larger ongoing project aimed at automating tolerance specification to aid less experienced designers by producing consistent geometric dimensioning and tolerancing (GD&T). Tolerance specification can be separated into two major tasks; tolerance schema generation and tolerance value specification. This thesis will focus on the latter part of automated tolerance specification, namely tolerance value allocation and analysis. The tolerance schema (sans values) required prior to these tasks have already been generated by the auto-tolerancing software. This information is communicated through a constraint tolerance feature graph file developed previously at Design Automation Lab (DAL) and is consistent with ASME Y14.5 standard.

The objective of this research is to allocate tolerance values to ensure that the assemblability conditions are satisfied. Assemblability refers to “the ability to assemble/fit a set of parts in specified configuration given a nominal geometry and its corresponding tolerances”. Assemblability is determined by the clearances between the mating features. These clearances are affected by accumulation of tolerances in tolerance loops and hence, the tolerance loops are extracted first. Once tolerance loops have been identified initial tolerance values are allocated to the contributors in these loops. It is highly unlikely that the initial allocation would satisfice assemblability requirements. Overlapping loops have to be simultaneously satisfied progressively. Hence, tolerances will need to be re-allocated iteratively. This is done with the help of tolerance analysis module.

The tolerance allocation and analysis module receives the constraint graph which contains all basic dimensions and mating constraints from the generated schema. The tolerance loops are detected by traversing the constraint graph. The initial allocation distributes the tolerance budget computed from clearance available in the loop, among its contributors in proportion to the associated nominal dimensions. The analysis module subjects the loops to 3D parametric variation analysis and estimates the variation parameters for the clearances. The re-allocation module uses hill climbing heuristics derived from the distribution parameters to select a loop. Re-allocation Of the tolerance values is done using sensitivities and the weights associated with the contributors in the stack.

Several test cases have been run with this software and the desired user input acceptance rates are achieved. Three test cases are presented and output of each module is discussed.
ContributorsBiswas, Deepanjan (Author) / Shah, Jami J. (Thesis advisor) / Davidson, Joseph (Committee member) / Ren, Yi (Committee member) / Arizona State University (Publisher)
Created2016
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Description
Commercial Li-ion cells (18650: Li4Ti5O12 anodes and LiCoO2 cathodes) were subjected to simulated Electric Vehicle (EV) conditions using various driving patterns such as aggressive driving, highway driving, air conditioning load, and normal city driving. The particular drive schedules originated from the Environment Protection Agency (EPA), including the SC-03, UDDS, HWFET,

Commercial Li-ion cells (18650: Li4Ti5O12 anodes and LiCoO2 cathodes) were subjected to simulated Electric Vehicle (EV) conditions using various driving patterns such as aggressive driving, highway driving, air conditioning load, and normal city driving. The particular drive schedules originated from the Environment Protection Agency (EPA), including the SC-03, UDDS, HWFET, US-06 drive schedules, respectively. These drive schedules have been combined into a custom drive cycle, named the AZ-01 drive schedule, designed to simulate a typical commute in the state of Arizona. The battery cell cycling is conducted at various temperature settings (0, 25, 40, and 50 °C). At 50 °C, under the AZ-01 drive schedule, a severe inflammation was observed in the cells that led to cell failure. Capacity fading under AZ-01 drive schedule at 0 °C per 100 cycles is found to be 2%. At 40 °C, 3% capacity fading is observed per 100 cycles under the AZ-01 drive schedule. Modeling and prediction of discharge rate capability of batteries is done using Electrochemical Impedance Spectroscopy (EIS). High-frequency resistance values (HFR) increased with cycling under the AZ-01 drive schedule at 40 °C and 0 °C. The research goal for this thesis is to provide performance analysis and life cycle data for Li4Ti5O12 (Lithium Titanite) battery cells in simulated Arizona conditions. Future work involves an evaluation of second-life opportunities for cells that have met end-of-life criteria in EV applications.
ContributorsAbdelhay, Reem (Author) / Kannan, Arunachala Mada (Thesis advisor) / Wishart, Jeffrey (Committee member) / Nam, Changho (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Photocatalytic activity of titanium dioxide (titania or TiO2) offers enormous potential in solving energy and environmental problems. Immobilization of titania nanoparticles on inert substrates is an effective way of utilizing its photocatalytic activity since nanoparticles enable high mass-transport, and immobilization avoids post-treatment separation. For competitive photocatalytic performance, the morphology of

Photocatalytic activity of titanium dioxide (titania or TiO2) offers enormous potential in solving energy and environmental problems. Immobilization of titania nanoparticles on inert substrates is an effective way of utilizing its photocatalytic activity since nanoparticles enable high mass-transport, and immobilization avoids post-treatment separation. For competitive photocatalytic performance, the morphology of the substrate can be engineered to enhance mass-transport and light accessibility. In this work, two types of fiber architectures (i.e., dispersed polymer/titania phase or D-phase, and multi-phase polymer-core/composite-shell fibers or M-phase) were explored as effective substrate solutions for anchoring titania. These fibers were fabricated using a low-cost and scalable fiber spinning technique. Polymethyl methacrylate (PMMA) was selected as the substrate material due to its ultraviolet (UV) transparency and stability against oxidative radicals. The work systematically investigates the influence of the fiber porosity on mass-transport and UV light scattering. The properties of the fabricated fiber systems were characterized by scanning electron microscopy (SEM), Brunauer–Emmett–Teller (BET), UV-vis spectrophotometry (UV-vis), and mechanical analysis. The photocatalytic performance was characterized by monitoring the decomposition of methylene blue (MB) under UV (i.e., 365 nm) light. Fabrication of photocatalytic support structures was observed to be an optimization problem where porosity improved mass transport but reduced UV accessibility. The D-phase fibers demonstrated the highest MB degradation rate (i.e., 0.116 min-1) due to high porosity (i.e., 33.2 m2/g). The M-phase fibers reported a better degradation rate compared to a D-phase fibers due to higher UV accessibility efficiency.
ContributorsKanth, Namrata (Author) / Song, Kenan (Thesis advisor) / Tongay, Sefaattin (Thesis advisor) / Kannan, Arunachala Mada (Committee member) / Arizona State University (Publisher)
Created2020