Through controlled stimulation of the battery, Qnovo’s software diagnoses a cell's electrochemical processes in real time using established scientific analytical methods. Qnovo’s innovation includes an effective implementation of Electrochemical Impedance Spectroscopy (EIS) on the device itself.
Qnovo's advanced battery models interpret the measured real time diagnostics, then determines an optimal course of action for each individual battery. These learning models rely on years of battery know-how at Qnovo and a wealth of battery test data.
The adaptive charging software closes the feedback loop and dynamically modifies the charge profile in response to the model's output. The software performs a multi-dimensional optimization to ensure that the battery meets its best performance and safety specifications.
Qnovo’s adaptive charging software has an execeptional performance and safety record, with zero safety failures. Qnovo recognizes that on extremely rare occasions, a rogue battery may pose a safety hazard. Qnovo’s adaptive charging software monitors the integrity of the battery's internal materials, then predicts its future health and safety risk.
Qnovo’s patented Adaptive Charging algorithms scan the battery using the charging signal to diagnose in real time its true health, then close the loop on the charging parameters for a healthier battery.
Through controlled stimulation of the battery throughout a charge cycle, Qnovo’s software continually diagnoses a cell's electrochemical processes in real-time using an efficient implementation of Electrochemical Impedance Spectroscopy (EIS).