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It’s broadly believed that frequent DC quick charging stresses a battery, shortening its helpful lifetime. Nevertheless, the long-term results of frequent quick charging may be mitigated with correctly designed charging limits. (Battery information specialist Recurrent not too long ago launched the outcomes of a examine on the topic.)
Can BMS software program eradicate this drawback and push the boundaries of charging pace? Qnovo supplies automotive OEMs with software program designed to mitigate injury to a battery pack from frequent quick charging. Its adaptive algorithms make the most of charging information to diagnose the inner properties of the cells in realtime.
The corporate not too long ago introduced a collaboration with NXP Semiconductors to combine Qnovo’s new SpectralX software program with NXP’s BMS and onboard charger {hardware}.
Qnovo CEO Nadim Maluf spoke with Charged on the latest CES commerce present, and defined how his firm’s software program helps batteries ship protected, superfast, limitless charging.
Qnovo says its information can present steady diagnostics of a battery’s age whereas the algorithms optimize the speed and diploma of charging, decreasing battery put on and maximizing battery life. The adaptive charging algorithms repeat this course of each time the battery is charging.
Qnovo software program stack runs as a regular AUTOSAR software and integrates into non-AUTOSAR RTOS-based BMS architectures by an outlined interface. Its measurement supplies a well being index that displays the final situation of a battery and its capability to ship the required efficiency in comparison with a brand new battery. The well being index of a brand new cell is 100 and 0 when the cell reaches end-of-life. The speed of change in well being is used to foretell the presence of defects, and the Qnovo security indicator will alert if cells require quick consideration.
Qnovo says its well being index and security indicator increase the prevailing BMS’s capacity-based
state-of-health and add predictive capabilities to enhance the BMS’s confidence in delivering rated energy and vary estimations.
Supply: Qnovo
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