BattSense is a machine learning project focused on predicting the State of Health (SOH) of lithium-ion batteries using operational parameters such as voltage, current, temperature, and capacity. The model enables accurate, data-driven diagnostics for battery performance monitoring in electric vehicles and portable devices.

Interactive React/TypeScript platform delivering data-driven visualizations and analytics of next-generation battery technologies—from Li-ion variants (NMC, LFP, high-nickel, silicon-anode) and sodium-ion to solid-state, redox-flow & zinc-air chemistries, plus AI-driven BMS, fast-charging, second-life reuse and grid-scale ESS. Try interactive demo!