Impedance-based forecasting of lithium-ion battery performance amid uneven usage

Abstract

Accurate forecasting of lithium-ion battery performance is essential for easing consumer concerns about the safety and reliability of electric vehicles. Most research on battery health prognostics focuses on the research and development setting where cells are subjected to the same usage patterns. However, in practical operation, there is great variability in use across cells and cycles, thus making forecasting challenging. To address this challenge, here we propose a combination of electrochemical impedance spectroscopy measurements with probabilistic machine learning methods. Making use of a dataset of 88 commercial lithium-ion coin cells generated via multistage charging and discharging (with currents randomly changed between cycles), we show that future discharge capacities can be predicted with calibrated uncertainties, given the future cycling protocol and a single electrochemical impedance spectroscopy measurement made immediately before charging, and without any knowledge of usage history. The results are robust to cell manufacturer, the distribution of cycling protocols, and temperature. The research outcome also suggests that battery health is better quantified by a multidimensional vector rather than a scalar state of health.

Health prognostics for lithium-ion batteries: mechanisms, methods, and prospects

“…It is very helpful to make the data and code open access so that researchers can easily follow the research and develop their own studies based on the shared data and code. The common way to share the data and code related to the work is to add the access link in the supplementary information of the published paper [111][112][113][114] , which makes it easy to find for the readers. To share the data, a public data-sharing platform can be chosen, such as Zenodo 111,113,114 , Mendeley 115 , and OSF 116 , or the personal website is also popular to share the data from the research group 35,[117][118][119] .…”

“…The common way to share the data and code related to the work is to add the access link in the supplementary information of the published paper [111][112][113][114] , which makes it easy to find for the readers. To share the data, a public data-sharing platform can be chosen, such as Zenodo 111,113,114 , Mendeley 115 , and OSF 116 , or the personal website is also popular to share the data from the research group 35,[117][118][119] . For code sharing, it is convenient for readers to access when it is shared together with the related datasets 35,118,119 , or the public code sharing platform can be chosen, such as Github 111,115 .…”

“…The time series data of voltage and temperature were used directly as inputs. Jones et al 113 integrate the loading profile and the EIS measurement to achieve the SoH estimation under random charging/discharging conditions, where historical information is not required. Gong et al 173 adopted the encoder-decoder modelbased deep learning method for battery SoH estimation using the charging curves.…”

“…It is very helpful to make the data and code open access so that researchers can easily follow the research and develop their own studies based on the shared data and code. A common way to share the data and code related to the work is to provide the access link in the supplementary information of the published paper, [111][112][113][114] which makes it easy to find for the readers.…”

Flower-Shaped CoS-Co2O3/G-C3N4 Nanocomposite for Two-Symmetric-Electrodes Supercapacitor of High Capacitance Efficiency Examined in Basic and Acidic Mediums

“…The relation between the real (Z) and imaginary (Z − ) impedance (Nyquist plot) is shown in Figure 4d for the supercapacitor in 6 M NaOH. Moreover, the impedance circuit represents the electrochemical contact of the prepared supercapacitor (see insert Figure 4d), in which the series and charge transfer resistance represent the electrolyte and electrolyte/electrode resistances, respectively, while the Warburg impedance represents the resistance of the electrode material [29,30]. Moreover, the capacitance appears in the cir- The relation between the real (Z) and imaginary (Z − ) impedance (Nyquist plot) is shown in Figure 4d for the supercapacitor in 6 M NaOH.…”