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Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/8B41F561-DB68-40C7-8D22-CD22BEBC9061 | ||
| Year | 2022 | ||
| Type of Item | Diploma Work | ||
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| Bibliographic Citation | Konstantinos Leontsinis, "Electric vehicles’ energy consumption estimation through aerial traffic supervision", Diploma Work, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2022 https://doi.org/10.26233/heallink.tuc.91450 | ||
| Appears in Collections |
The enhanced greenhouse effect and climate change, which has taken place inrecent years, are due to the gaseous pollutants, which are released into the atmosphere from the burning of mineral resources, such as oil and its derivatives. The usage of the above resources is mainly made by the cars because of the internal combustion engines, which mostly accept gasoline and diesel as fuel. The urgent need of changing theengine’s car, without polluting the environment, has motivated the car industries to design and produce electric cars, that uses an electric motor and powers from batteries.The most important disadvantage of the electric cars is the increased powerconsumption of the battery when traveling at high speeds. Therefore, for the smooth transition of the car’s fleet, it is essential to estimate cars’ speeds on highways and expressways, in order to properly place charging stations along them.In the present diploma thesis, a speed recording method is analyzed by the cars,that are traveling along the Northern Road Axis of Crete. First of all, the video recording of the cars took place at three points along the Northern Road Axis of Crete around the city of Chania and at a distance of 7 kilometers from each other. Moreover, the videos were record with a civilian drone, in order to avoid possible interference in front of the camera. Furthermore, the identification of the cars and estimation of their speed is implemented by the object detection algorithm YOLO (You Only Look Once) and the Mixture of Gaussian 2 (MOG2) method, which is provided by the Opencv library.YOLO algorithm is used to record only the speeds of cars and not all vehicles, such as trucks and buses.Subsequently, the speeds are used to estimate the power consumption of fourelectric cars, that cover the routes Chania-Rethymno and Chania-Hraklion. Inconclusion, a fuzzy logic system is used to derive the possibility a driver of an electric car is searching for a charging station along the Northern Road Axis of Crete.In summary, the aim of this thesis is a recommendation about the placement of the charging stations on the highway from Chania to Hraklion, which is based upon the fuzzy logic system’s results.
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