C
Chris Gearhart
Researcher at National Renewable Energy Laboratory
Publications - 26
Citations - 491
Chris Gearhart is an academic researcher from National Renewable Energy Laboratory. The author has contributed to research in topics: Renewable energy & Electrification. The author has an hindex of 9, co-authored 24 publications receiving 309 citations. Previous affiliations of Chris Gearhart include Ford Motor Company.
Papers
More filters
Journal ArticleDOI
A statistical approach to estimating acceptance of electric vehicles and electrification of personal transportation
TL;DR: In this paper, the authors use a surrogate metric of acceptance defined as a threshold frequency of need for alternative transportation above which all users would not accept the inconvenience, and show that although the market acceptance and electrification potential of EVs are severely limited by battery cost, it is possible to determine an optimal EV range.
Journal ArticleDOI
The rise of electric vehicles—2020 status and future expectations
Matteo Muratori,Marcus Alexander,Doug Arent,Morgan Bazilian,Pierpaolo Cazzola,Ercan M. Dede,John Farrell,Chris Gearhart,David L. Greene,Alan Jenn,Matthew Keyser,Timothy Lipman,Sreekant Narumanchi,Ahmad Pesaran,Ramteen Sioshansi,Emilia Suomalainen,Gil Tal,Kevin Walkowicz,Jacob W. Ward +18 more
TL;DR: In this article, the authors provide an overview of the status of the light-duty-EV market and current projections for future adoption; insights on market opportunities beyond light duty EVs; cost and performance evolution for batteries, power electronics, and electric machines that are key components of EV success.
Journal ArticleDOI
Future integrated mobility-energy systems: A modeling perspective
Matteo Muratori,Paige Jadun,Brian Bush,David A. Bielen,Laura Vimmerstedt,Jeffrey Gonder,Chris Gearhart,Doug Arent +7 more
TL;DR: Assessment of existing tools used to represent and model future mobility systems and their interactions with other energy systems concludes that out-of-sample extrapolation of emerging trends and future anticipated developments is more important than ever due to the plethora of factors driving disruptive change in mobility systems.
Journal ArticleDOI
Predicting demand for hydrogen station fueling
TL;DR: In this paper, the authors developed a model that simulates future demand at a hydrogen filling station and trained it from actual hydrogen fill count, amount, and frequency data, which can be used for hydrogen station requirements and operation and maintenance strategies.