US 11,971,454 B2
System and method for determining a battery condition
Evan Murphy, San Francisco, CA (US); Patrick Herring, San Francisco, CA (US); Daniel Vickery, San Francisco, CA (US); Elizabeth Goldberg, San Francisco, CA (US); Jacqueline Maslyn, San Francisco, CA (US); Matthew Bohan, San Francisco, CA (US); Shyam Srinivasan, San Francisco, CA (US); Dustin Summy, San Francisco, CA (US); Zachary Gima, San Francisco, CA (US); Brian Goodall, San Francisco, CA (US); and Mark Tobenkin, San Francisco, CA (US)
Assigned to Zitara Technologies, Inc., San Francisco, CA (US)
Filed by Zitara Technologies, Inc., San Francisco, CA (US)
Filed on Dec. 9, 2022, as Appl. No. 18/078,814.
Claims priority of provisional application 63/287,819, filed on Dec. 9, 2021.
Claims priority of provisional application 63/388,141, filed on Jul. 11, 2022.
Prior Publication US 2023/0184839 A1, Jun. 15, 2023
Int. Cl. G06F 11/30 (2006.01); G01R 31/367 (2019.01); G01R 31/385 (2019.01); G01R 31/396 (2019.01)
CPC G01R 31/367 (2019.01) [G01R 31/385 (2019.01); G01R 31/396 (2019.01)] 19 Claims
OG exemplary drawing
 
1. A system for detecting a battery anomaly in a battery comprising:
at least one of:
a current sensor configured to measure a current dataset associated with the battery;
a voltage sensor configured to measure a voltage dataset associated with the battery; or
a temperature sensor configured to measure a temperature dataset associated with the battery;
a model operable to predict a local property dataset of the battery using the at least one of the current dataset, the voltage dataset, or the temperature dataset;
a classifier configured to classify whether the battery is operating in an anomalous condition based on the estimated local properties of the battery, wherein the classifier is operable in:
a steady state mode wherein the classifier is operable to classify the anomalous condition as a thermal anomaly or an electrical short using a local property dataset derived from steady state readings of the at least one of current, voltage, or temperature; and
a jump change mode wherein the classifier is operable to classify the anomalous condition as a battery cell disconnection or a loss of thermal connection using a local property dataset jump changes in the at least one of current, voltage, or temperature, wherein the jump changes are at least about 0.1 A/s to classify the battery cell disconnection.