This thesis presents a method to quickly determine the optimal battery for an electric vehicle given a set of vehicle characteristics and desired performance metrics. The model is based on four independent design variables: cell count, cell capacity, state-of-charge window, and battery chemistry. Performance is measured in seven categories: cost, all-electric range, maximum speed, acceleration, battery lifetime, lifetime greenhouse gas emissions, and charging time. The performance of each battery is weighted according to a user-defined objective function to determine its overall fitness. The model is informed by a series of battery tests performed on scaled-down battery samples. Seven battery chemistries were tested for capacity at different discharge rates, maximum output power at different charge levels, and performance in a real-world automotive duty cycle. The results of these tests enable a prediction of the performance of the battery in an automobile. Testing was performed at both room temperature and low temperature to investigate the effects of battery temperature on operation. The testing highlighted differences in behavior between lithium, nickel, and lead based batteries. Battery performance decreased with temperature across all samples with the largest effect on nickel-based chemistries. Output power also decreased with lead acid batteries being the least affected by temperature. Lithium-ion batteries were found to be highly efficient (>95%) under a vehicular duty cycle; nickel and lead batteries have greater losses. Low temperatures hindered battery performance and resulted in accelerated failure in several samples. Lead acid, lead tin, and lithium nickel alloy batteries were unable to complete the low temperature testing regime without losing significant capacity and power capability. This is a concern for their applicability in electric vehicles intended for cold climates which have to maintain battery temperature during long periods of inactivity. Three sample optimizations were performed: a compact car, a, truck, and a sports car. The compact car benefits from increased battery capacity despite the associated higher cost. The truck returned the smallest possible battery of each chemistry, indicating that electrification is not advisable. The sports car optimization resulted in the largest possible battery, indicating large performance from increased electrification. These results mirror the current state of the electric vehicle market. / Thesis (Master, Mechanical and Materials Engineering) -- Queen's University, 2013-08-16 15:19:20.333

Nowadays, switching to plug-in hybrid electric vehicles (PHEVs) is a promising way to reduce energy consumption and greenhouse gas (GHG) emissions. This research aims to explore consumers’ attitudes towards adopting PHEVs in the City of Winnipeg. The study attempts to identify social-technical factors affecting car buyers’ intention to purchase PHEVs, along with how attitudes, knowledge and experience affect preference for PHEVs. A further discussion of the Theory of Planned Behavior (TPB) will justify the linkage between attitudes, subjective norms, perceived behavioral control and purchase intentions. Questionnaires were distributed to two groups of people: an expert group familiar with or having experience with electric vehicles and a non-expert group with less knowledge about electric vehicles. Given issues of charging infrastructure and driving range, these vehicles have the potential to alter the urban landscape. Results of the study are expected to provide insight into effective public policy options and PHEV adoption/acceptance by car buyers. / February 2017

abstract: 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. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2016

In today’s world of volatile fuel prices and climate concerns, there is little study on the relation between vehicle ownership patterns and attitudes toward potential policies and vehicle technologies. This work provides new data on ownership decisions and owner preferences under various scenarios, coupled with calibrated models to microsimulate Austin’s household-fleet evolution. Results suggest that most Austinites (63%, population-corrected share) support a feebate policy to favor more fuel efficient vehicles. Top purchase criteria are vehicle purchase price, type/class, and fuel economy (with 30%, 21% and 19% of respondents placing these in their top three). Most (56%) respondents also indicated that they would seriously consider purchasing a Plug-In Hybrid Electric Vehicle (PHEV) if it were to cost $6,000 more than its conventional, gasoline-powered counterpart. And many respond strongly to signals on the external (health and climate) costs of a vehicle’s emissions, more strongly than they respond to information on fuel cost savings. 25-year simulations suggest that 19% of Austin’s vehicle fleet could be comprised of Hybrid Electric Vehicles (HEVs) and PHEVs under adoption of a feebate policy (along with PHEV availability in Year 1 of the simulation, and current gas prices throughout). Under all scenarios vehicle usage levels (in total vehicle miles traveled [VMT]) are predicted to increase overall, along with average vehicle ownership levels (per household, and per capita); and a feebate policy is predicted to raise total regional VMT slightly (just 4.43 percent, by simulation year 25), relative to the trend scenario, while reducing CO2 emissions only slightly (by 3.8 percent, relative to trend). Doubling the trend-case gas price to $5/gallon is simulated to reduce the year-25 vehicle use levels by 17% and CO2 emissions by 22% (relative to trend). Two- and three-vehicle households are simulated to be the highest adopters of HEVs and PHEVs across all scenarios. And HEVs, PHEVs and Smart Cars are estimated to represent a major share of the fleet’s VMT (25%) by year 25 under the feebate scenario. The combined share of vans, pickup trucks, sport utility vehicles (SUVs), and cross over utility vehicles (CUVs) is lowest under the feebate scenario, at 35% (versus 47% in Austin’s current household fleet), yet feebate-policy receipts exceed rebates in each simulation year. A 15% reduction in the usage levels of SUVs, CUVs and minivans is observed in the $5/gallon scenario (relative to trend). Mean use levels per vehicle of HEVs and PHEVs are simulated to have a variation of 753 and 495 across scenarios. In the longer term, gas price dynamics, tax incentives, feebates and purchase prices along with new technologies, government-industry partnerships, and more accurate information on range and recharging times (which increase customer confidence in EV technologies) should have even more significant effects on energy dependence and greenhouse gas emissions. / text

Transportation fleet emissions have a dominant role in air quality because of their significant contribution to ozone precursor and greenhouse gas emissions. Regulatory policies have emphasized improvements in vehicle fuel economy, alternative fuel use, and engine and vehicle technologies as approaches for obtaining transportation systems that support sustainable development. This study examined the air quality impacts of the partial electrification of the transportation fleet and the use of biofuels for the Austin Metropolitan Statistical Area under a 2030 vision of regional population growth and urban development using the Comprehensive Air Quality Model with extensions (CAMx). Different strategies were considered including the use of Plug-in Hybrid Electric Vehicles (PHEVs) with nighttime charging using excess capacity from electricity generation units and the replacement of conventional petroleum fuels with different percentages of the biofuels E85 and B100 along or in combination. Comparisons between a 2030 regional vision of growth assuming a continuation of current development trends (denoted as Envision Central Texas A or ECT A) in the Austin MSA and the electrification and biofuels scenarios were evaluated using different metrics, including changes in daily maximum 1-hour and 8-hour ozone concentrations, total area, time integrated area and total daily population exposure exceeding different 1-hour ozone concentration thresholds. Changes in ozone precursor emissions and predicted carbon monoxide and aldehyde concentrations were also determined for each scenario. Maximum changes in hourly ozone concentration from the use of PHEVs ranged from -8.5 to 2.2 ppb relative to ECT A. Replacement of petroleum based fuels with E85 had a lesser effect than PHEVs on maximum daily ozone concentrations. The maximum reduction due to replacement of 100% of gasoline fuel in light and heavy duty gasoline vehicles by E85 ranged from -2.1 to 2.8 ppb. The magnitude of the effect was sensitive to the biofuel penetration level. Unlike E85, B100 negatively impacted hourly ozone concentrations relative to the 2030 ECT A case. As the replacement level of petroleum-diesel fuel with B100 in diesel vehicles increased, hourly ozone concentrations increased as well. However, changes due to the penetration of B100 were relatively smaller than those due to E85 since the gasoline fraction of the fleet is larger than the diesel fraction. Because of the reductions in NOx emissions associated with E85, the results for the biofuels combination scenario were similar to those for the E85 scenario. Also, the results showed that as the threshold ozone concentration increased, so too did the percentage reductions in total daily population exposure for the PHEV, E85, and biofuel combination scenarios relative to ECT A. The greatest reductions in population exposure under higher threshold ozone concentrations were achieved with the E85 100% and 17% PHEV with EGU controls scenarios, while the B100 scenarios resulted in greater population exposure under higher threshold ozone concentrations. / text

<div>Plug-in hybrid electric vehicles (PHEVs) are being considered as an alternative to conventional medium-duty (MD) and heavy-duty (HD) commercial vehicles to reduce fuel consumption and tailpipe emissions. Lithium ion batteries, which are used in PHEVs due to their high energy density, are expensive. The battery contributes significantly towards the life-cycle cost of MD/HD PHEVs, as these vehicles, due to high mass and aggressive battery usage, require multiple battery replacements over their lifetime. Smaller batteries increase the fuel consumption and need more replacements, while bigger batteries increase the initial system cost. Powertrain design from a life-cycle cost perspective is required to explore this trade-off and maximize the economic gains obtained from PHEVs. </div><div><br></div><div>Powertrain design entails component sizing, control strategy selection as well as architecture selection. Different powertrain designs yield different lifetime economic gains. A variety of applications exist for MD/HD vehicles, which differ in their ways of powertrain usage, due to variations in required acceleration, available braking, and average and maximum speeds. Therefore, different powertrain designs are needed depending on the application and usage scenario. The powertrain design space needs to be explored, and solutions that maximize the economic gains within the specified constraints need to be chosen.</div><div><br></div><div>This dissertation compares the economic viability of two PHEV applications (MD Truck and HD Transit Bus), with options of series and parallel hybrid architectures, over multiple drivecycles, for four economic scenarios (years 2015, 2020, 2025 and 2030). It is shown that hybridizing the transit bus achieves payback sooner than hybridizing the truck. Further, the results for the transit bus application, over the Manhattan drivecycle, show that implementation of the parallel architecture is economically viable in the 2015(present) scenario, while the series architecture becomes viable in 2020, due to significantly lower initial costs involved in the parallel architecture.</div><div><br></div><div>A methodology to select a solution out of the explored design space that maximizes the economic gains is demonstrated. Variations in the economic and vehicle usage conditions for which this solution is designed, can be expected. It is therefore necessary to check the robustness of this solution to change in external factors such as vehicle mass, annual vehicle miles travelled (AVMT), component and fuel costs. It is shown that the economic gains are affected by the battery cost, fuel cost, AVMT and vehicle mass, while the number of battery replacements are affected by AVMT and vehicle mass. </div><div><br></div><div>A probability-based approach is demonstrated to obtain confidence in the economic and battery life predictions. Specifically, probability-based variations are provided to variables such as miles traveled between recharge, recharge C-rate and battery temperature. It is shown that battery life is affected the most by battery temperature.</div><div><br></div><div>A battery heating/cooling system is required to maintain constant battery temperature of operation during all seasons, but these systems incur additional fuel costs. A framework that utilizes just the Coefficient of Performance (COP) of the heating/cooling system to calculate the excess fuel cost is proposed and demonstrated. An increase of 0.9-1.8\% in fuel consumption is shown, depending on the drivecycle and ambient temperature.</div><div><br></div><div>Further, the well-to-wheel (WTW) fuel-cycle emissions from conventional and PHEV transit buses operating in Indiana and California are assessed using the ``Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation'' (GREET) Model 2017, developed by Argonne National Labs. It is shown that 59% and 63% greenhouse gas (GHG) reductions can be achieved in Indiana and California respectively, along with reduction in carbon monoxide (CO), nitrogen oxides NOx, particulate matter with diameter less than 2.5 microns PM2.5 and volatile organic compounds (VOC) emissions for both the states. However, an increase in sulfur oxides SOx emissions for both the states, and particulate matter with diameter less than 10 microns PM10 increase for Indiana, are observed. </div><div><br></div>

The new generation of cars are so-called Plug-in Hybrid Electric Vehicles (PHEVs) which has the grid connection capability. By the introduction of these vehicles, the grid issues will be connected to the private car transportation sector for the first time. The cars from the gird perspective can be considered as a regular load with certain power factor. The effects of this type of new load in distribution grid are studied in this thesis. By modelling the cars as regular load, the effects of the cars in three distinct areas in Stockholm are investigated. The car number in each area is estimated based on the population and commercial density of electricity consumption in the three areas. Afterward, the average electricity consumption by the cars in one day is distributed among 24 hours of the day with peak load in the studied year. This distribution is done by two regulated and unregulated methods. The regulated method is based on the desired pattern of electricity consumption of PHEVs by vehicle owners. On the other hand, the regulated pattern is designed based on encouragement of the car owners to consume electricity for charging their car batteries at low-power hours of day (usually midnight hours). The power system from high voltage lines in Sweden down to 11 kV substations in Stockholm simulated in PSS/E software has been used in this study. The automation program (written in Python) is run in order to get the output report (voltage variation and losses) of the load flow calculations for different hours of day by adding the required power for PHEVs both by regulated and unregulated patterns. The results show the possibility of introducing growing number of cars till year 2050 in each area with existing grid infrastructures. Moreover, the number of cars, yearly and daily electric consumption for PHEVs in pure electric mode are shown in this project and the effects of regulated electricity consumption are investigated. It is concluded that since the car number is estimated based on the population, the areas with higher residential characteristics are more problematic for integration of PHEVs from capacity point of view. Moreover, by regulating the charging pattern of PHEVs, the higher number of PHEVs can be integrated to the grid with the existing infrastructures. In addition, the losses have been decreased in regulated pattern in comparison with unregulated pattern with the same power consumption. The voltage in different substations is within the standard boundaries by adding 100 percent of PHEVs load for both regulated and unregulated patterns in all three areas.