Author: Roberta Ramilli, University of Bologna (IUNET)
Batteries are transforming the technology of mobility and transport in all modes (airborne, naval, rail, road, by heavy vehicles, and off-road). Many research directions are aimed at allowing for full supervision and control of the battery system. In the publication “Binary Sequences for Online Electrochemical Impedance Spectroscopy of Battery Cells” is presented a technique to perform the online diagnosis of the battery at cell level, devoted to monitor the performance and state of each cell and improve its safety, reliability, and lifetime.
Electrochemical Impedance Spectroscopy (EIS) is considered the most appropriate and informative technique for battery diagnostics, as it allows for the inference of several key battery state parameters so as to have a comprehensive overview of the battery functionality, but the time scale associated with its implementation should be shortened with respect to the measurement times typical of laboratory set-ups, if it has to be applied in real-time operation on-board of the vehicle. Thus, binary excitation signals are explored to reduce the measurement time of EIS investigation: more precisely, the publication proposes two alternative methods to synthesize multisine sequences that allow for the excitation of many frequencies of the cell equivalent impedance concurrently.
Today, battery sensing/control basically takes place only at the battery pack-level (or module-level, at best) via a Battery Management System (BMS), losing the possibility to locally investigate on a single cell: another challenge faced in this publication was the miniaturization of the measurement architecture, with the aim of exploiting VLSI technology to carry out EIS at the very cell-level.
An impedance measurement architecture relying on binary sequences suitable was designed to be implemented in a system on a chip. A prototype was realized on a PCB board (Fig. 1) and validated in the online monitoring of the impedance spectra of a lithium-ion battery cell during the discharge process with promising results.
This work is a preliminary solution towards the implementation of smart sensing at cell-level, capable of monitoring “in operando” and “in situ” the performance and control the state of every single battery cell. This will also open to smart functionalities of the battery cell that, in conjunction with sophisticated prediction models, could provide a more reliable, safe and longer-life battery system, and thus foster the electrification process in all transport modes, promoting the sustainable development of the mobility and energy sectors.
Fig.1 Prototype of the impedance measurement system realized on a PCB board.
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