The aim of this research study is to present a method for analyzing the performance of the wireless inductive charge-while-driving (CWD) electric vehicles, from both traffic and energy points of view. To accurately quantify the electric power required from an energy supplier for the proper management of the charging system, a traffic simulation model is implemented. This model is based on a mesoscopic approach, and it is applied to a freight distribution scenario. Lane changing and positioning are managed according to a cooperative system among vehicles and supported by advanced driver assistance systems (ADAS). From the energy point of view, the analyses indicate that the traffic may have the following effects on the energy of the system: in a low traffic level scenario, the maximum power that should be supplied for the entire road is simulated at approximately 9 MW; and in a high level traffic scenario with lower average speeds, the maximum power required by the vehicles in the charging lane increases by more than 50%.
“Charge while driving” for electric vehicles: road traffic modeling and energy assessment / Deflorio, FRANCESCO PAOLO; Castello, Luca; Pinna, Ivano; Guglielmi, Paolo. - In: JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY. - ISSN 2196-5625. - STAMPA. - 3:2(2015), pp. 277-288. [10.1007/s40565-015-0109-z]
“Charge while driving” for electric vehicles: road traffic modeling and energy assessment
DEFLORIO, FRANCESCO PAOLO;CASTELLO, LUCA;PINNA, IVANO;GUGLIELMI, Paolo
2015
Abstract
The aim of this research study is to present a method for analyzing the performance of the wireless inductive charge-while-driving (CWD) electric vehicles, from both traffic and energy points of view. To accurately quantify the electric power required from an energy supplier for the proper management of the charging system, a traffic simulation model is implemented. This model is based on a mesoscopic approach, and it is applied to a freight distribution scenario. Lane changing and positioning are managed according to a cooperative system among vehicles and supported by advanced driver assistance systems (ADAS). From the energy point of view, the analyses indicate that the traffic may have the following effects on the energy of the system: in a low traffic level scenario, the maximum power that should be supplied for the entire road is simulated at approximately 9 MW; and in a high level traffic scenario with lower average speeds, the maximum power required by the vehicles in the charging lane increases by more than 50%.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2600754
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