The distribution of relaxation times (DRT) analysis of impedance spectra is a proven method to determine the number of occurring polarization processes in lithium-ion batteries (LIBs), their polarization contributions and characteristic time constants. Direct measurement of a spectrum by means of electrochemical impedance spectroscopy (EIS), however, suffers from a high expenditure of time for low-frequency impedances and a lack of general availability in most online applications. In this study, a method is presented to derive the DRT by evaluating the relaxation voltage after a current pulse. The method was experimentally validated using both EIS and the proposed pulse evaluation to determine the DRT of automotive pouch-cells and an aging study was carried out. The DRT derived from time domain data provided improved resolution of processes with large time constants and therefore enabled changes in low-frequency impedance and the correlated degradation mechanisms to be identified. One of the polarization contributions identified could be determined as an indicator for the potential risk of plating. The novel, general approach for batteries was tested with a sampling rate of 10 Hz and only requires relaxation periods. Therefore, the method is applicable in battery management systems and contributes to improving the reliability and safety of LIBs.

Fast-switching semiconductors induce ripple currents on the high-voltage DC bus in the electric vehicle (EV). This paper describes the methods used in the project SiCWell and a new approach to investigate the influence of these overlaid ripples on the battery in EVs. The ripple current generated by the main inverter is demonstrated with a measurement obtained from an electric vehicle. A simulation model is presented which is based on an artificial reference DC bus, according to ISO 21498-2, and uses driving cycles in order to obtain current profiles relevant for battery cycling. A prototype of a battery cycling tester capable of high frequency and precise ripple current generation was developed and is used to cycle cells with superimposed ripple currents within an aging study. To investigate the impact of the frequency and the amplitude of the currents on the battery’s lifetime, these ripple parameters are varied between different test series. Cell parameters such as impedance and capacity are regularly characterized and the aging of the cells is compared to standard DC cycled reference cells. The aging study includes a total of 60 automotive-sized pouch cells. The evaluation of ripple currents and their impact on the battery can improve the state-of-health diagnosis and remaining-useful life prognosis. For the development and validation of such methods, the cycled cells are monitored with a measurement system that regularly measures current and voltage with a sampling rate of 2 MHz. The resulting dataset is suitable for the design of future ripple current aging studies as well as for the development and validation of aging models and methods for battery diagnosis.