Analysis of Dynamic Wireless Power Transfer Systems Based on Behavioral Modeling of Mutual Inductance

Giulia Di Capua, Antonio Maffucci, Kateryna Stoyka, Gennaro Di Mambro, Salvatore Ventre, Vincenzo Cirimele, Fabio Freschi, Fabio Villone and Nicola Femia
Additional contact information
Giulia Di Capua: Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, 03043 Cassino, FR, Italy
Antonio Maffucci: Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, 03043 Cassino, FR, Italy
Kateryna Stoyka: Department of Information and Electrical Engineering and Applied Mathematics, University of Salerno, 84084 Fisciano, SA, Italy
Gennaro Di Mambro: Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, 03043 Cassino, FR, Italy
Salvatore Ventre: Department of Electrical and Information Engineering, University of Cassino and Southern Lazio, 03043 Cassino, FR, Italy
Vincenzo Cirimele: Department of Energy, Politecnico of Torino, 10129 Turin, TO, Italy
Fabio Freschi: Department of Energy, Politecnico of Torino, 10129 Turin, TO, Italy
Fabio Villone: Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, NA, Italy
Nicola Femia: Department of Information and Electrical Engineering and Applied Mathematics, University of Salerno, 84084 Fisciano, SA, Italy

Sustainability, 2021, vol. 13, issue 5, 1-15

Abstract: This paper proposes a system-level approach suitable to analyze the performance of a dynamic Wireless Power Transfer System (WPTS) for electric vehicles, accounting for the uncertainty in the vehicle trajectory. The key-point of the approach is the use of an analytical behavioral model that relates mutual inductance between the coil pair to their relative positions along the actual vehicle trajectory. The behavioral model is derived from a limited training data set of simulations, by using a multi-objective genetic programming algorithm, and is validated against experimental data, taken from a real dynamic WPTS. This approach avoids the massive use of computationally expensive 3D finite element simulations, that would be required if this analysis were performed by means of look-up tables. This analytical model is here embedded into a system-level circuital model of the entire WPTS, thus allowing a fast and accurate analysis of the sensitivity of the performance as the actual vehicle trajectory deviates from the nominal one. The system-level analysis is eventually performed to assess the sensitivity of the power and efficiency of the WPTS to the vehicle misalignment from the nominal trajectory during the dynamic charging process.

Keywords: behavioral modeling; inductive coupling; mutual inductance; wireless power transfer (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/13/5/2556/pdf (application/pdf)
https://www.mdpi.com/2071-1050/13/5/2556/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:13:y:2021:i:5:p:2556-:d:506676

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().