Well-to-Wheel Energy, Emissions, and Cost Analysis of Electricity and Fuel Used in Conventional and Electrified Vehicles, and Their Connection to a Sustainable Energy Infrastructure

Abstract

Recent legislation by the United States Environmental Protection Agency (EPA) requires record low vehicle tailpipe emissions, necessitating research and development in the areas of lowering conventional (i.e., internal combustion engine) vehicle emissions rates while facilitating the widespread introduction of electrified vehicles. Currently, the EPA views Battery Electric Vehicles as having zero emissions. However, a number of studies illustrate this is not the case when considering the emissions produced in creating the electricity through a full Life Cycle Analysis. As a result, proper comparison of electrified and conventional vehicles must include a complete Well-to-Wheel (WtW) study including the emissions generated through production and use of liquid petroleum and biofuels. As a result, this work provides a full WtW investigation into fuel, electricity, and production analysis of conventional and electrified vehicles. This is supported by a thorough literature review of current and projected future technology, extrapolating to a fleet analysis, as well as applying the technology to an advanced electricity infrastructure. In the following effort, the first chapter simply provides a background into these different areas in order to help set the stage. Chapter 2 explores conventional vehicle emissions profiles predicting future requirements of engine and catalytic exhaust aftertreatment technologies. Findings illustrate that low temperature climates and aging both adversely affect a vehicle's ability to perform proper emissions reductions. This chapter additionally demonstrates an improvement in the fuel use emissions profiles of Argonne National Laboratories' Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model through the update of embedded time-sheet emissions lookup tables using EPA's Motor Vehicle Emissions Simulator (MOVES). This simulation package utilizes a statistical database of over 3000 counties in the continental United States in calculating the emissions profile of various vehicle and fuel type combinations, updating the current tables utilized in GREET. Chapter 3 utilizes these efforts in performing a life cycle analysis of a 1974 Volkswagen Super Beetle converted to a plug-in series hybrid. This work utilizes GREET in exploring the WtW fuel use emissions profile, as well as estimating the energy and emissions savings through reusing a number of stock vehicle components in the conversion. A vehicle dynamics model supports this analysis, calculating the average fuel use in a typical city/highway drive cycle. The fourth chapter expands upon this work, analyzing an 800+ vehicle fleet in a comparative analysis between electrified vehicles and their conventional counterparts. This work utilizes four simplified vehicle dynamics models, focusing on ten vehicles with various powertrains and fuel use algorithms. These models calculate the average fuel consumption of these vehicles, employing the GREET model in calculating the emissions profiles on a per-mile and yearly total basis. Furthermore, a full cost analysis of fuel and vehicle combinations demonstrates the economic impacts of electrifying the vehicle fleet. Finally, Chapter 5 seeks to support future research into electrified vehicles for vehicle-to-grid technology, energy storage, and infrastructure control through the design and construction of a small-scale smart grid in collaboration with a previous University of Kansas EcoHawks senior design team. This design consists of a renewable and conventional energy source, a grid load, bulk and dynamic grid storage, and a full sensory and control system. The final design meets the two requirements of a smart grid set forth by the Department of Energy: decentralization of energy production and storage, and providing two-way communication from end users or appliances and the energy network.