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Novel state-of-health diagnostic method for Li-ion battery in service

Mingant, R., Bernard, J., Sauvant-Moynot, V.
Applied energy 2016 v.183 pp. 390-398
algorithms, batteries, case studies, diagnostic techniques, electrochemistry, energy, impedance, prediction, vehicles (equipment)
The development of improved State-of-Health (SoH) diagnostic methods is a current research topic for battery-powered applications. For instance, the current rapid development of Electric Vehicles (EV) creates a strong demand for an accurate and reliable on-board SoH indicator during operation. Such an indicator is a key parameter required to optimize battery energy management and to track the degradation of the system performance. The electrochemical impedance spectrum (EIS) of an electrochemical system is a powerful lab-based diagnostic technique, usually measured using a frequency response analyzer. In this paper, we present an innovative diagnostic technique based on analysis of free voltage and current signals to give a so called “quasi-electrochemical impedance spectrum” (QEIS) and demonstrate its application on a Li-ion battery during a real EV duty cycle. It is worth noting that in our technique no additional signal is applied to the cell, since the current flowing into cells during use on-board is directly processed in the data treatment step.Commercial batteries (1.4Ah cylindrical LiFePO4/graphite cell) were selected in this study to validate the diagnostic method in the framework of an applied case study related to an electric school bus demonstrator. In order to study the capability of QEIS measurements as a diagnostic tool for SoH of Li-ion cells, a test procedure including ageing phases has been defined to characterise Li-ion cells before and during ageing. Voltage and current signals were treated by Fast Fourier Transform (FFT) in order to determine the QEIS spectra of Li-ion cells under study. Then, SoH prediction algorithms have been obtained from a mathematical analysis of the impedance parameters sensitive to SoH.