Predicting the Market Potential of Plug-in Electric Vehicles Using Multiday GPS Data
By Mobashwir Khan, Kara M. Kockelman. 2012
186 citations recorded by the source corpus.
Subfields: Automotive Engineering, Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment
View Paper: https://www.semanticscholar.org/paper/cbf76fbe8e181f80858d023a9ac298d299bb58bd
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Automotive Engineering
In Electrical and Electronic Engineering
- T. Gnann
- F. Sprei
- L. Noel
- Roxana J. Javid
- Ali Nejat
- Benjamin Sovacool
- Johannes Kester
- Chien-fei Chen
In Renewable Energy, Sustainability and the Environment
Citations in the corpus
- Are multi-car households better suited for battery electric vehicles? Driving patterns and economics in Sweden and Germany (2016, methodology): “In relation to Khan and Kockelman (2012), we make the same choice of which car in the household to replace with a BEV.”
- A comprehensive model of regional electric vehicle adoption and penetration (2017, background): “In terms of dataset, either small (Egbue and Long, 2012; Khan and Kockelman, 2012; Türnau, 2015) or large (Higgins et al., 2012; Tamor et al., 2013) surveys or questionnaires from conventional car buyers are used.”
- Assessing the socio-demographic, technical, economic and behavioral factors of Nordic electric vehicle adoption and the influence of vehicle-to-grid preferences (2020, background): “For instance, a study found that an EV with a range of 100 miles would satisfy 50% of one-vehicle households and 80% of multi-vehicle households [53].”