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Routing and scheduling of electric and alternative-fuel vehicles

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Vehicles powered by electricity and alternative-fuels are becoming a more popular form of transportation since they have less of an environmental impact than standard gasoline vehicles. Unfortunately, their success is currently inhibited by the sparseness of locations where the vehicles

Vehicles powered by electricity and alternative-fuels are becoming a more popular form of transportation since they have less of an environmental impact than standard gasoline vehicles. Unfortunately, their success is currently inhibited by the sparseness of locations where the vehicles can refuel as well as the fact that many of the vehicles have a range that is less than those powered by gasoline. These factors together create a "range anxiety" in drivers, which causes the drivers to worry about the utility of alternative-fuel and electric vehicles and makes them less likely to purchase these vehicles. For the new vehicle technologies to thrive it is critical that range anxiety is minimized and performance is increased as much as possible through proper routing and scheduling. In the case of long distance trips taken by individual vehicles, the routes must be chosen such that the vehicles take the shortest routes while not running out of fuel on the trip. When many vehicles are to be routed during the day, if the refueling stations have limited capacity then care must be taken to avoid having too many vehicles arrive at the stations at any time. If the vehicles that will need to be routed in the future are unknown then this problem is stochastic. For fleets of vehicles serving scheduled operations, switching to alternative-fuels requires ensuring the schedules do not cause the vehicles to run out of fuel. This is especially problematic since the locations where the vehicles may refuel are limited due to the technology being new. This dissertation covers three related optimization problems: routing a single electric or alternative-fuel vehicle on a long distance trip, routing many electric vehicles in a network where the stations have limited capacity and the arrivals into the system are stochastic, and scheduling fleets of electric or alternative-fuel vehicles with limited locations to refuel. Different algorithms are proposed to solve each of the three problems, of which some are exact and some are heuristic. The algorithms are tested on both random data and data relating to the State of Arizona.

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2014

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An Environmental and Economic Analysis of The Near Future of Lithium Ion Batteries

Description

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

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.

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2021-05

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Profitability and environmental benefit of providing renewable energy for electric vehicle charging

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This study evaluates the potential profitability and environmental benefit available by providing renewable energy from solar- or wind-generated sources to electric vehicle drivers at public charging stations, also known as electric vehicle service equipment (EVSE), in the U.S. Past

This study evaluates the potential profitability and environmental benefit available by providing renewable energy from solar- or wind-generated sources to electric vehicle drivers at public charging stations, also known as electric vehicle service equipment (EVSE), in the U.S. Past studies have shown above-average interest in renewable energy by drivers of plug-in electric vehicles (PEVs), though no study has evaluated the profitability and environmental benefit of selling renewable energy to PEV drivers at public EVSE. Through an online survey of 203 U.S.-wide PEV owners and lessees, information was collected on (1) current PEV and EVSE usage, (2) potential willingness to pay (WTP) for upgrading their charge event to renewable energy, and (3) usage of public EVSE if renewable energy was offered. The choice experiment survey method was used to avoid bias known to occur when directly asking for WTP. Sixty percent of the participants purchased their PEVs due to environmental concerns. The survey results indicate a 506% increase in the usage of public pay-per-use EVSE if renewable energy was offered and a mean WTP to upgrade to renewable energy of $0.61 per hour for alternating current (AC) Level 2 EVSE and $1.82 for Direct Current (DC) Fast Chargers (DCFC). Based on data from the 2013 second quarter (2Q) report of The EV Project, which uses the Blink public EVSE network, this usage translates directly to an annual gross income increase of 668% from the original $1.45 million to $11.1 million. Blink would see an annual cost of $16,005 per year for the acquisition of the required renewable energy as renewable energy credits (RECs). Excluding any profit seen purely from the raise in usage, $3.8 million in profits would be gained directly from the sale of renewable energy. Relative to a gasoline-powered internal combustion engine passenger vehicle, greenhouse gas (GHG) emissions are 42% less for the U.S. average blend grid electricity-powered electric vehicle and 99.997% less when wind energy is used. Powering all Blink network charge events with wind energy would reduce the annualized 2Q 2013 GHG emissions of 1,589 metric tons CO2 / yr to 125 kg CO2 / yr, which is the equivalent of removing 334 average U.S. gasoline passenger cars from the road. At the increased usage, 8,031 metric tons CO2 / yr would be prevented per year or the equivalent of the elimination of 1,691 average U.S. passenger cars. These economic and environmental benefits will increase as PEV ownership increases over time.

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2014

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Performance, modeling, and characteristics of LFP pack for HEV using FUDS (depleting) in hot and arid conditions

Description

There was a growing trend in the automotive market on the adoption of Hybrid Electric Vehicles (HEVs) for consumers to purchase. This was partially due to external pressures such as the effects of global warming, cost of petroleum, governmental

There was a growing trend in the automotive market on the adoption of Hybrid Electric Vehicles (HEVs) for consumers to purchase. This was partially due to external pressures such as the effects of global warming, cost of petroleum, governmental regulations, and popularity of the vehicle type. HEV technology relied on a variety of factors which included the powertrain (PT) of the system, external driving conditions, and the type of driving pattern being driven. The core foundation for HEVs depended heavily on the battery pack and chemistry being adopted for the vehicle performance and operations. This paper focused on the effects of hot and arid temperatures on the performance of LiFePO4 (LFP) battery packs and presented a possible modeling method for overall performance.

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.

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2016

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High Frequency Power Converter with ZVT for Variable DC-link in Electric Vehicles

Description

The most important metrics considered for electric vehicles are power density, efficiency, and reliability of the powertrain modules. The powertrain comprises of an Electric Machine (EM), power electronic converters, an Energy Management System (EMS), and an Energy Storage System (ESS).

The most important metrics considered for electric vehicles are power density, efficiency, and reliability of the powertrain modules. The powertrain comprises of an Electric Machine (EM), power electronic converters, an Energy Management System (EMS), and an Energy Storage System (ESS). The power electronic converters are used to couple the motor with the battery stack. Including a DC/DC converter in the powertrain module is favored as it adds an additional degree of freedom to achieve flexibility in optimizing the battery module and inverter independently. However, it is essential that the converter is rated for high peak power and can maintain high efficiency while operating over a wide range of load conditions to not compromise on system efficiency. Additionally, the converter must strictly adhere to all automotive standards.

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.

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2018

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EV battery performance in the desert area and development of a new drive cycle for Arizona

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

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.

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2018

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Thermal cycling of LTO-LCO batteries subjected to electric vehicle schedule and its second life evaluation

Description

Lithium titanium oxide (LTO), is a crystalline (spinel) anode material that has recently been considered as an alternative to carbon anodes in conventional lithium-ion batteries (LIB), mainly due to the inherent safety and durability of this material. In this paper

Lithium titanium oxide (LTO), is a crystalline (spinel) anode material that has recently been considered as an alternative to carbon anodes in conventional lithium-ion batteries (LIB), mainly due to the inherent safety and durability of this material. In this paper commercial LTO anode 18650 cells with lithium cobalt oxide (LCO) cathodes have been cycled to simulate EV operating condition (temperature and drive profiles) in Arizona. The capacity fade of battery packs (pack #1 and pack#2), each consisting 6 such cells in parallel was studied. While capacity fades faster at the higher temperature (40°C), fading is significantly reduced at the lower temperature limit (0°C). Non-invasive techniques such as Electrochemical Impedance Spectroscopy (EIS) show a steady increase in the high-frequency resistance along with capacity fade indicating Loss of Active Material (LAM) and formation of co-intercalation products like Solid Electrolyte Interface (SEI). A two-stage capacity fade can be observed as previously reported and can be proved by differential voltage curves. The first stage is gradual and marks the slow degradation of the anode while the second stage is marked by a drastic capacity fade and can be attributed to the fading cathode. After an effective capacity fading of ~20%, the battery packs were disassembled, sorted and repackaged into smaller packs of 3 cells each for second-life testing. No major changes were seen in the crystal structure of LTO, establishing its electrochemical stability. However, the poor built of the 18650-cell appears to have resulted in failures like gradual electrolytic decomposition causing prominent swelling and failure in a few cells and LAM from the cathode along with cation dissolution. This result is important to understand how LTO batteries fail to better utilize the batteries for specific secondary-life applications.

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2019

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A Novel Location-Allocation-Routing Model for Siting Multiple Recharging Points on the Continuous Network Space

Description

Due to environmental and geopolitical reasons, many countries are embracing electric vehicles (EVs) as an alternative to gasoline powered automobiles. Other alternative-fuel vehicles (AFVs) powered by compressed gas, hydrogen or biodiesel have also been tested for replacing gasoline powered vehicles.

Due to environmental and geopolitical reasons, many countries are embracing electric vehicles (EVs) as an alternative to gasoline powered automobiles. Other alternative-fuel vehicles (AFVs) powered by compressed gas, hydrogen or biodiesel have also been tested for replacing gasoline powered vehicles. However, since the associated refueling infrastructure of AFVs is sparse and is gradually being built, the distance between recharging points (RPs) becomes a crucial prohibitive attribute in attracting drivers to use such vehicles. Optimally locating RPs will both increase demand and help in developing the refueling infrastructure.

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.

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2020