Battery smart sensing via a virtual reference electrode

Area of Science:

• Electrochemistry
• Materials Science
• Battery Technology

Background:

• Battery management systems rely on current and voltage, which can miss critical failure modes like lithium metal plating.
• Direct measurement of negative electrode potential, a key indicator, requires impractical physical reference electrodes in practical cells.

Purpose of the Study:

• To introduce a virtual reference electrode for estimating negative electrode potential without physical sensors.
• To enable early detection of lithium metal plating and improve battery safety and longevity.

Main Methods:

• A predictive model was trained on measured negative electrode potentials from three-electrode cells.
• The model estimates internal battery states using only standard two-electrode cell signals.
• Electron microscopy was used to validate predictions against plating phenomena.

Main Results:

• The virtual reference electrode achieved high accuracy, with root-mean-squared error of 0.023 V and mean absolute error of 0.018 V.
• Predictions accurately identified the transition to lithium metal plating.
• Adaptive charging using the virtual reference electrode extended cycle life by 8.25 times compared to baseline methods.

Conclusions:

• The virtual reference electrode framework enables non-invasive monitoring of critical internal battery states.
• This approach enhances battery safety by detecting potential failure modes like lithium plating.
• The technology offers a pathway for virtual sensing in batteries without altering chemistry or architecture.