Print Email Facebook Twitter IoT Based Online Harmonic Emission Estimation of DC Fast Chargers Title IoT Based Online Harmonic Emission Estimation of DC Fast Chargers Author LIANG, YAWEN (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Bauer, P. (mentor) Qin, Z. (mentor) Lekic, A. (graduation committee) Degree granting institution Delft University of Technology Programme Electrical Engineering | Electrical Power Engineering Date 2022-07-11 Abstract Nowadays, electric vehicles (EVs) in the market only travel short distance and are usually charged at home which can be the obstacle in the way of EVs development. As a result, fast charging that can ensure long-distance drive with shorter charging time draws more and more attention.In emerging fast-charging stations, DC fast chargers (DCFCs) are employed which rely on power electronics and control to achieve the required performance. Harmonic current emission induced by the complex system behavior is of great concern in the DC fast charger (DCFC) system. This thesis proposes a harmonic emission model for the typical DCFC design, i.e., the two-level active front end. The technique is based on the Fourier series method and the impedance model which is able to reveal the harmonic current emission of DCFCs under different grid conditions. Time-domain simulations and experiments are presented subsequently to validate the proposed model.The analytical model can be implemented in cloud-based charging, which is a popular topic right now because of the lower overall cost. Besides, cloud-based systems have a larger storage capacity and are easier to maintain. Another reason for the appealing cloud-based charging is that all of these Internet of things (IoT) devices are interconnected, and vehicle data are shared. Therefore, an IoT based online harmonic emission estimation tool for DCFC is built based on the aforementioned proposed model in this thesis. Subject DC Fast ChargerHarmonic EmissionIoTElectrical Vehicle To reference this document use: http://resolver.tudelft.nl/uuid:ec624cac-a3fe-42ec-a699-c5c81ec4adb1 Part of collection Student theses Document type master thesis Rights © 2022 YAWEN LIANG Files PDF MScThesisYawen.pdf 11.17 MB Close viewer /islandora/object/uuid:ec624cac-a3fe-42ec-a699-c5c81ec4adb1/datastream/OBJ/view