Multiband Multisine Excitation Signal for Online Impedance Spectroscopy of Battery Cells
Source abstract
Abstract
Multisine electrochemical impedance spectroscopy (EIS) represents a highly promising technique for the online characterization of battery functional states, offering the potential to monitor, in real-time, key degradation phenomena such as aging, internal resistance variation, and state of health (SoH) evolution. However, its widespread adoption in embedded systems is currently limited by the need to balance measurement accuracy with strict energy constraints and the requirement for short acquisition times. This work proposes a novel broadband EIS approach based on a multiband multisine excitation strategy in which the excitation signal spectrum is divided into multiple sub-bands that are sequentially explored. This enables the available energy to be concentrated on a limited portion of the spectrum at a time, thereby significantly improving the signal-to-noise ratio (SNR) without substantially increasing the total measurement time. The result is a more energy-efficient method that maintains high diagnostic precision. We further investigated the optimal design of these multiband multisine sequences, taking into account realistic constraints imposed by the sensing hardware such as limitations in excitation amplitude and noise level. The effectiveness of the proposed method was demonstrated within a comprehensive simulation framework implementing a complete impedance measurement system. Compared with conventional excitation techniques (i.e., the sine sweep and the classical single-band multisine methods), the proposed strategy is an optimal trade-off solution both in terms of energy efficiency and measurement time. Therefore, the technique is a valuable solution for real-time, embedded, and in situ battery diagnostics, with direct implications for the development of intelligent battery management systems (BMS), predictive maintenance, and enhanced safety in energy storage applications.
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Research context
OpenAlex topics: Advanced Battery Technologies Research · Advancements in Battery Materials · Advanced Battery Materials and Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Electrical, Electronic, and Information Engineering (DEI), University of Bologna, 40136 Bologna, Italy
Advanced Research Center on Electronic Systems (ARCES), University of Bologna, 40123 Bologna, Italy
Funding
Italian Ministry of University
References (47)
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