The implementation of a voltage-based tunneling mechanism in aging models for lithium-ion batteries

Abstract

Precise explanation and prediction of the aging behavior of lithium-ion batteries (LIBs) is essential for improving battery management systems. It is quickly becoming a hotspot in battery research. Solid electrolyte interphase (SEI) growth is regarded as the dominant factor of capacity losses in LIBs. However, the growth of SEI is yet to be understood in more detail due to its complexity. In the present paper, an advanced voltage-based aging model using an electron tunneling mechanism is proposed and validated by experiments. This model employs the electrode voltage as an input parameter for the first time with a tunneling mechanism, which is more flexible than existing energy-based approaches and can be used to predict the electron tunneling (dis)charge cycles. The proposed model is used to simulate tunneling current profiles during (dis)charging of graphite, LTO, and blend Si/C negative electrodes. The simulation results prove and explain that lower states-of-charge of LIBs mitigate electron tunneling and SEI growth, further reducing calendar aging. That work can be used to describe battery capacity losses better and it is crucial for predicting the state-of-health of LIBs.