Design of a Wireless Charging System for Online Battery Spectroscopy

Edoardo Locorotondo, Fabio Corti, Luca Pugi, Lorenzo Berzi, Alberto Reatti and Giovanni Lutzemberger
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Edoardo Locorotondo: Department of Industrial Engineering, University of Florence, 50139 Florence, Italy
Fabio Corti: Department of Information Engineering, University of Florence, 50139 Florence, Italy
Luca Pugi: Department of Industrial Engineering, University of Florence, 50139 Florence, Italy
Lorenzo Berzi: Department of Industrial Engineering, University of Florence, 50139 Florence, Italy
Alberto Reatti: Department of Information Engineering, University of Florence, 50139 Florence, Italy
Giovanni Lutzemberger: Department of Energy, Systems, Territory and Constructions Engineering, University of Pisa, 56122 Pisa, Italy

Energies, 2021, vol. 14, issue 1, 1-17

Abstract: This paper presents the design procedure of an electric circuit that can perform the battery state diagnosis and, simultaneously, provide its charging. A fast and embedded impedance measurement method is also proposed; this is based on a broadband current signal excitation on the battery during the constant current charging phase. The proposed solution performs the electrochemical impedance spectroscopy (EIS), which is known to provide useful information about battery chemical–physical property changes due to aging or failure events. To demonstrate the functionalities of the proposed method, the spectroscopy is implemented in the control in the wireless charging system. An EIS charging test is simulated on an equivalent circuit model, which emulates the battery impedance properties in a specified frequency band. Circuit parameters are evaluated by experimental data. According to the obtained results, the proposed method allows us to reach an accurate estimation of the battery state and represents a promising solution for an embedded diagnostic of battery health thanks to its simplicity and speed.

Keywords: wireless power transfer; battery; electrochemical impedance spectroscopy; pseudo-random binary sequence; CLC filter; state of health (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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