Optimizing the Energy Transfer, With a High System Efficiency in Dynamic Inductive Charging of EVs

Inductive charging is based on the operating principles of a transformer; energy is transferred through an air-gap from a primary coil incorporated in the charging station to a secondary coil incorporated in the electric vehicle (EV). Dynamic inductive charging allows the vehicle to wirelessly receive energy while moving on the road and appears to be an ideal solution for the increase of the limited travel range of EVs. However, currently developed dynamic inductive power transfer (IPT) solutions limit the application of this method when the EV rapidly moves over the charging station. The aim of this paper is to propose a novel optimization procedure, in order to define the values for the variables involved in the electrical operation of a dynamic IPT system. The optimization procedure considers constraints associated with the operational conditions in the primary and secondary sides of the IPT system, in order to define the movement section, where the energy transferred to the EV is maximized at a considerably high system efficiency. The values derived from the optimization method are implemented in the control of the secondary side of the IPT system. Moreover, a control method is proposed that effectively eliminates the need for a detection mechanism and the continuous data transfer between the primary and secondary side. The suggested control scheme requires the operation of the charging station at a low-efficiency movement section without significant energy losses in this specific section. The proposed optimization procedure is applied in the case of a 60-cm-diameter circular pad, and the suggested control scheme is validated by simulating the operation of the dynamic IPT system over the whole EV movement range. An experimental setup has been used to study the application of the optimization procedure and investigate the effective operation of the system.


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  • Accession Number: 01676340
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jun 21 2018 12:02PM