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

International audienceHighlights • Two modules of 66 cells were aged with two cycling protocols corresponding to the EV cycling of electric school bus demonstrator. • Free charge/discharge signals were used to determine the quasi-EIS (QEIS) spectra during ageing. • These QEIS spectra were fitted with an equivalent circuit model. • The fitted parameters were used to develop a diagnostic tool to estimate the SoH of a battery. • This tool shows good accuracy in the estimation of SoH (2 % uncertainty) for both types of ageing studied. Abstract 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 (1.4 Ah cylindrical LiFePO 4 /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