Ayman Moawad

Impact of Technology on Electric Drive Fuel Consumption and Cost

In support of the U.S Department of Energy’s Vehicle Technologies Program, numerous vehicle technology combinations have been simulated using Autonomie. Argonne National Laboratory (Argonne) designed and wrote the Autonomie modeling software to serve as a single tool that could be used to meet the requirements of automotive engineering throughout the development process, from modeling to control, offering the ability to quickly compare the performance and fuel efficiency of numerous powertrain configurations. For this study, a multitude of vehicle technology combinations were simulated for many different vehicles classes and configurations, which included conventional, power split hybrid electric vehicle (HEV), power split plug-in hybrid electric vehicle (PHEV), extendedrange EV (E-REV)-capability PHEV, series fuel cell, and battery electric vehicle. In this paper, the results are examined to compare the extent to which each of these technologies reduces fuel consumption and which combination of technologies produces the best trade-off between cost and fuel consumption. The main questions are whether it is cost effective to use advanced technologies, such as PHEVs, and how far we should or could electrify vehicles to obtain fuel consumption improvements at reasonable costs. Several timeframes are considered—2010, 2015, 2020, 2030, and 2045—to track electric drive evolution through time.

Impact of vehicle performance on cost effective way to meet CAFE 2017–2025

In September 2010, the U.S. Environmental Protection Agency (EPA) and the National Highway Traffic Safety Authority (NHTSA) released the Interim Joint Technical Assessment Report, Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy Standards for Model Years 2017–2025. The objective of the study is to determine the most cost-effective technology options to meet the 3 and 6% fuel consumption improvements proposed for different acceleration performances. To take into account uncertainties, three cases have been considered: low (90%), medium (50%), and high (10%). The low case represents “business as usual,” while the high case is based on targets from the U.S. DOE Vehicle Technologies Program. The study, based on Argonnes Autonomie vehicle simulation tool, demonstrates that improving vehicle performance benefits the introduction of electric drive vehicles.