EcoCharge – Charging Electric Vehicles Using Renewable Energy

How it works


How it works



EcoCharge

+ Intelligent hoarding
+ Fast configuration of preference rules
+ Reduces derouting costs
+ Considers chargers' availability
+ Reduces CO2 emissions
+ Integration of renewable sources

About


EcoCharge is an innovative framework, which combines multiple non-conflicting objectives into an optimization task providing user-defined ranking means through an intuitive spatial application. EcoCharge utilizes a Continuous k-Nearest Neighbor query, where the distance function is computed using Estimated Components (ECs). An EC defines a function that can have a fuzzy value based on some estimates. Examples of ECs are: (i) the derouting cost, which is the time to reach the charger depending on estimated traffic; (ii) the (available clean) power at the charger, which depends on the estimated weather; and (iii) the charger availability, which depends on the estimated busy timetables that show when the charger is crowded.

EcoCharge has been developed by researchers and students at the Data Management Systems Laboratory (DMSL), Department of Computer Science at the University of Cyprus.

To get a quote on how to enable, set-up and configure EcoCharge drop us a line here or at ecocharge@cs.ucy.ac.cy.

EcoCharge can be downloaded on Github. To contribute to EcoCharge system development post your "Issue" or "Pull Request" on Github.

Team


SOTERIS CONSTANTINOU

LEAD STUDENT

DIMITRIS PAPAZACHARIOU

STUDENT

Andreas Konstantinidis

EXTERNAL MEMBER

MOHAMED F. MOKBEL

EXTERNAL MEMBER

CONSTANTINOS COSTA

EXTERNAL MEMBER

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