Sention’s technology leverages Machine Learning (ML) to detecting anomalies in battery’s acoustic signals. These anomalies have been demonstrated as strong indicators of a cell’s State-of-Health (SoH).
Sention’s acoustic imaging techniques can identify structural defects in lithium-ion cell electrode stacks, such as wrinkles, which may indicate manufacturing issues.
Global lithium-ion battery demand is projected to grow 30% annually, requiring larger, more efficient gigafactories to meet production and quality challenges.
The electric vehicle industry faces a surge in retiring lithium-ion battery packs, with most currently sent for destructive recycling despite retaining usable capacity.
Accurate and early detection of lithium plating in lithium-ion batteries is crucial for ensuring safety and longevity. In this study, acoustic heatmap imaging was used to monitor the evolution of internal battery changes over 200 charge-discharge cycles. A distinct deformation pattern was identified, later confirmed by teardown analysis at the National Physical Laboratory (NPL) to be lithium plating.
Sention Technologies, based in Hackney Wick, London, develops measurement and data solutions for battery development using ultrasound, X-ray computed tomography, electrochemical testing, and artificial intelligence.
