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Virtual Reference Electrode Extends Battery Life 8.25 Times

Researchers created a virtual reference electrode model that estimates internal battery potentials and prevents failure without changing cell hardware.

WHAT YOU NEED TO KNOW
  • The virtual reference electrode predicted negative electrode potential with a root-mean-squared error of 0.023 volts and a mean absolute error of 0.018 volts.
  • Adaptive charging powered by the virtual sensor extended battery cycle life by 8.25 times compared to a constant-current constant-voltage baseline under low negative-to-positive capacity conditions.
  • The machine learning model estimates internal states using only standard two-electrode signals without altering battery chemistry or physical structure.

Researchers have developed a virtual reference electrode that estimates negative electrode potential in operating batteries using standard two-electrode signals, according to a study published in Nature Communications on August 11, 2026. Traditional battery management systems rely on current and cell voltage, which can miss lithium metal plating. While measuring negative electrode potential can reveal this failure mode, physical reference electrodes are difficult to implement in practical cells.

Trained on negative electrode potentials measured in three-electrode cells, the model estimates internal battery states using only signals collected from standard two-electrode cells. Tests showed the virtual reference electrode predicted these potentials with a root-mean-squared error of 0.023 volts and a mean absolute error of 0.018 volts. Electron microscopy validated the predicted transition between lithium intercalation and lithium metal plating near the thermodynamic threshold.

When integrated into an adaptive charging setup, the virtual sensor adjusts current in response to predicted failure risks. Under a tested low negative-to-positive capacity ratio, the method extended battery cycle life by 8.25 times compared to a constant-current constant-voltage baseline. The researchers stated that the framework could enable virtual sensing of internal battery states without modifying battery chemistry or architecture.

Jiayi Yu, Aki Takahashi, Min-Ho Kim, Rishi Upadhyay, Howard Zhang, and Tian-Yu Wang contributed equally to the work. The team included researchers from the University of California, Los Angeles, the Korea Institute of Energy Technology, the Colorado School of Mines, and Stanford University. Research funding was provided by the Office of Naval Research, the National Science Foundation, the Army Young Investigator Program, and the Defense Advanced Research Projects Agency, with facility access provided by the UCLA–CNSI Electron Imaging Center for NanoMachines.

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