Accurate physics-based State-of-Health estimation of Lithium ion batteries based on ultra-low frequency impedance measurements with stochastic excitation “AccessTOinternalSOH”

Accurate physics-based State-of-Health estimation of Lithium ion batteries based on ultra-low frequency impedance measurements with stochastic excitation, “AccessTOinternalSOH” In the light of the growing ecological awareness, electrochemical energy storage in battery systems is considered one of the most relevant technologies for enabling a gradual transition from the traditional energy sources (fossil fuels) to the renewable ones. Modern Lithium-ion battery systems have been developed over past 3 decades, exhibiting an impressive specific energy and power performance. For the smart grid and transport sector applications there is an additional specific demand for the system: to operate stably at least for 10 years. Batteries are essentially complex electrochemical systems and as such inevitably prone to gradual worsening of performance due to various diverse degradation processes which cannot be categorically solved. Moreover, directly related, and probably even more importantly, the needed high-energy battery systems are during long-term operation exposed to critical safety concerns. It is crucial that the safety-related issues of modern battery systems are properly solved before the massive production and applications are being realized. In order to reduce the safety concerns various approaches have been established in the field of Battery Management Systems (BMSs) with the aim to estimate the State-Of-Health (SOH) of a battery module/pack. Although there are various different methods for estimation of SOH of Li-ion batteries available, there is critically missing a more direct physical relation with the underlying degradation processes, which would enable a more direct insight into the origin(s) of the specific battery degradation scenarios and increase the predictability of the future evolution of a battery performance and occurrence of possible safety issues. In the present project we propose to solve these issues with the introduction of the original method for battery SOH estimation where Electrochemical Impedance Spectroscopy (EIS) will be utilized in a very wide frequency range - down to ultra-low frequencies (below 1 mHz). The full potential of EIS approach will be realized with the help of the novel electrochemical Transmission Line Model (TLM) methodology recently developed within our group (Department of Materials Chemistry) at the National Institute of Chemistry (NIC). The present project relies on our fundamental research hypothesis: The impedance response of a Li-ion battery measured in a frequency range down to 1 mHz gives the complete information about the battery State-of-Health (SOH). In order for the methodology to be transferred into an actual BMS the original technique utilizing a Discrete Random Binary Sequence (DRBS) input excitation, which was recently developed at the project partner from Institut ""Jožef Stefan"" (IJS), will be efficiently applied for measuring of impedance response of Li-ion batteries down to ultra-low frequencies. In this project the highly adaptable DRBS approach will be further developed with the aim to create an innovative, dedicated design which will be implemented by the original hardware of the DRBS-EIS module. Special attention will be devoted to understanding of the cell-to-cell variations and to tackle the key problem of the “weak cell” related issues. The obtained module will enable to establish a unique accurate, physics-based, SOH estimation method for new generation of BMSs. The general goal of the proposed project is to achieve a prolonged lifetime of battery modules/packs based on improved detection of the local variations and providing increased safety during long-term operation. The goal will be achieved by effectively bridging two scientific research fields: electrochemistry and materials science (NIC) with hardware implementation and signal processing (IJS partner).