The Battery Management Software combines comprehensive, on-the-phone predictive health management and real-time monitoring with cloud-based dashboards, without costly infrastructure. The core engine is built on an adaptive layer that prevents most health issues and a predictive layer that identifies devices with the potential for battery failure.
The Adaptive Layer consists of algorithms, models, data and policies to measure ion diffusion in real time, determine if the battery is operating in a safe zone, and adapt charge parameters for optimal performance. This layer interfaces with the fuel gauge to monitor cell conditions and send suitable charge parameters to control charging in real time. Available as QNS (software only) or QNI (software with hardware assist), our system always works within cell specification limits and never impacts pre-defined safety or thermal controls (including JEITA and max voltage/current).
The Predictive Layer consists of models and policies to interpret millions of real-time computations by the adaptive layer and generate four predictive values (shown above), available as Qnovo-defined Android properties on the phone. This data (less than 10 bytes) summarizes complete understanding of device health and helps predict defects like lithium plating, excessive swelling, and mechanical defects before they turn into catastrophic failures.