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  "description": "An approach to control or monitoring of battery operation makes use of an artificial neural network (ANN), which receives one or more battery attributes for a Lithium ion (Li-ion) battery, and determines, based on the received one or more battery attributes, a state-of-charge (SOC) and/or a…",
  "path": "/patents/1350469",
  "publishedAt": "2023-09-07T00:00:00.000Z",
  "site": "at://did:plc:oql6ds5vnff4ugar6rruliwd/site.standard.publication/3mn3ohu7oxx5w",
  "tags": [
    "G01R31/392",
    "The Trustees of Columbia University in the City of New York"
  ],
  "textContent": "An approach to control or monitoring of battery operation makes use of an artificial neural network (ANN), which receives one or more battery attributes for a Lithium ion (Li-ion) battery, and determines, based on the received one or more battery attributes, a state-of-charge (SOC) and/or a state-of-health (SOH) estimate for the Li-ion battery. The ANN includes at least one of a recurrent neural network (RNN) and a convolutional neural network (CNN), and the series of values of the battery attributes includes at one of battery voltage values, battery current values, and battery temperature values.",
  "title": "NEURAL-NETWORK STATE-OF-CHARGE AND STATE OF HEALTH ESTIMATION"
}