Delivers time-critical battery management directly within vehicles, using physics-based models that analyze local battery data with minimal latency. The solution works with any lithium-ion battery type without extra hardware, maintaining automotive-grade safety standards while integrating seamlessly as an AUTOSAR application into existing vehicle systems. This architecture ensures continuous battery protection even without connectivity, while still supporting cloud-based analytics and updates.

Extends vehicle-level intelligence through powerful remote analytics. It applies ML/AI to extensive battery datasets while leveraging Qnovo’s proprietary Battery Genome database of cell behaviors. This architecture enables fleet-wide diagnostics that identify trends across entire vehicle populations, providing actionable insights into battery health. Through secure OTA updates, the system continuously evolves, deploying enhanced algorithms to vehicles without requiring service visits.

Responds to chemical battery models in real time, controlling the charging process by adjusting the rate and depth of discharge (DOD) for each battery. This adaptive approach maximizes battery life and compensates for the natural variability in battery manufacturing.