Authors:
Zonggen Yi
and
Peter H. Bauer
Affiliation:
University of Notre Dame, United States
Keyword(s):
Electric Vehicle(EV), Energy Consumption Model, Charging Station Placement, Reachable Range Estimation, Energy Constraint, Google Maps Api.
Related
Ontology
Subjects/Areas/Topics:
Economic Models of Energy Efficiency
;
Energy and Economy
;
Energy-Aware Systems and Technologies
;
Greener Systems Planning and Design
;
Optimization Techniques for Efficient Energy Consumption
;
Planning and Design Challenges for Smart Cities
;
Service Innovation and Design to Support Smart Cities
;
Smart Cities
Abstract:
A detailed energy consumption model is introduced for electric vehicles (EVs), that takes into account all
tractive effort components, regenerative braking, and parasitic power users. Based on this model a software
tool for EV reachable range estimation (EVRE) is developed and implemented. This software tool uses real
driving distances and elevation data from Google Maps and can therefore much more accurate predict the
reachable range of a given EV than the typical Euclidean distance models. Furthermore, an optimization
model for the placement of charging stations to maximize the number of reachable households under energy
constraints is established using EVRE. These results are illustrated by a number of examples involving the
cities of New York City, Boulder Colorado, and South Bend, Indiana. The developed methodology can easily
incorporate additional constraints such as popular destinations, preferred parking, driver habits, available
power infrastructure, etc. to initially reduce
the search space for optimal charging station placement.
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