Abstract: An electronic device, including a memory; a processor; and a remaining useful life (RUL) prediction controller configured to: identify at least one parameter corresponding to at least one of a physical composition and a chemical composition of a plurality of used batteries during at least one of a charging and a discharging of the plurality of used batteries; determine a pattern of variations in at least one of a voltage, a current, a temperature, and a resistance during every cycle of the charging and the discharging of the plurality of used batteries until a failure; generate an artificial intelligence (AI) model which is trained based on a correlation between the determined pattern of variations and the at least one of the physical composition and the chemical composition; and evaluate a RUL of the plurality of used batteries using the AI model.

Abstract: Disclosed is an electronic device including a battery, a charging circuit configured to charge the battery, a measurement circuit configured to measure a state of the battery, and a processor configured to be electrically connected with the battery, the charging circuit, and the measurement circuit, to charge the battery using the charging circuit set by a first charging parameter, determine state information corresponding to a state of the battery based on data associated with the state of the battery obtained using the measurement circuit, determine a second charging parameter for reducing loss of a capacity of the battery based on the state information, and charge the battery using the charging circuit set by the second charging parameter.

Abstract: Embodiments herein provide a method for real time adaptive charging of a battery. The method includes receiving at least one battery parameter. Further, the method includes determining a present battery condition. Further, the method includes correcting the at least one battery parameter based on the present battery condition. Further, the method includes determining a real time optimal current used for charging the battery based on the at least one corrected battery parameter. Further, the method includes charging the battery based on the determined real time optimal current, where a battery management system configures a charger integrated circuit to charge the battery. Further, the method includes updating and storing the at least one battery parameter in real time in a memory after charging the battery at the optimal current.

Abstract: Disclosed is a method of predicting a remaining useful life (RUL) including measuring an operating current during a charging cycle and a discharging cycle of a battery, calculating a capacity fade of a plurality of cycles of the battery based on degradation parameters and the measured operating currents, and predicting an RUL of the battery based on the calculated capacity fade.

Abstract: A method of estimating a remaining useful life (RUL) of a battery includes: identifying a class of data of the battery in real time; determining whether a second level RUL estimation is set for the class; estimating a gross RUL by performing a first level RUL estimation in response to the second level RUL estimation not being set for the class; and estimating a fine RUL of the battery in response to the second level RUL estimation being set for the class.

Abstract: Embodiments herein provide a method and electronic device for detecting an internal short circuit in a battery. The method includes obtaining, by a battery management system, battery gauge data. Further, the method includes estimating, by the battery management system, an internal resistance of the battery using the battery gauge data. Furthermore, the method includes detecting, by the battery management system, the internal short circuit in the battery by comparing a change in the internal resistance with a pre-defined resistance change threshold value.

Abstract: A method includes estimating an average concentration of ions in electrodes of a battery and estimating a state-of-charge (SOC) of the battery by Coulomb counting, correcting the ion concentration based on a difference in predicted and measured cell voltages, and correcting the Coulomb counting SOC based on a relation between SOC estimated by Coulomb counting and the average concentration, and the difference in the predicted and measured cell voltages.

Abstract: Disclosed is an electronic device including a battery, a charging circuit configured to charge the battery, a measurement circuit configured to measure a state of the battery, and a processor configured to be electrically connected with the battery, the charging circuit, and the measurement circuit, to charge the battery using the charging circuit set by a first charging parameter, determine state information corresponding to a state of the battery based on data associated with the state of the battery obtained using the measurement circuit, determine a second charging parameter for reducing loss of a capacity of the battery based on the state information, and charge the battery using the charging circuit set by the second charging parameter.

Abstract: Embodiments herein provide a method and electronic device for detecting an internal short circuit in a battery. The method includes obtaining, by a battery management system, battery gauge data. Further, the method includes estimating, by the battery management system, an internal resistance of the battery using the battery gauge data. Furthermore, the method includes detecting, by the battery management system, the internal short circuit in the battery by comparing a change in the internal resistance with a pre-defined resistance change threshold value.

Abstract: Embodiments herein disclose a method and system of charging a battery. The method includes identifying a state of the battery and a plurality of current levels corresponding to the state of the battery. Furthermore, the method includes charging the battery by applying the plurality of current levels corresponding to a pre-defined sequence to attain a cut-off voltage of the battery.

Abstract: A method includes estimating an average concentration of ions in electrodes of a battery and estimating a state-of-charge (SOC) of the battery by Coulomb counting, correcting the ion concentration based on a difference in predicted and measured cell voltages, and correcting the Coulomb counting SOC based on a relation between SOC estimated by Coulomb counting and the average concentration, and the difference in the predicted and measured cell voltages.

Abstract: Disclosed is a method of predicting a remaining useful life (RUL) including measuring an operating current during a charging cycle and a discharging cycle of a battery, calculating a capacity fade of a plurality of cycles of the battery based on degradation parameters and the measured operating currents, and predicting an RUL of the battery based on the calculated capacity fade.

Abstract: A method of estimating a remaining useful life (RUL) of a battery includes: identifying a class of data of the battery in real time; determining whether a second level RUL estimation is set for the class; estimating a gross RUL by performing a first level RUL estimation in response to the second level RUL estimation not being set for the class; and estimating a fine RUL of the battery in response to the second level RUL estimation being set for the class.

Abstract: Embodiments herein disclose a method and system of charging a battery. The method includes identifying a state of the battery and a plurality of current levels corresponding to the state of the battery. Furthermore, the method includes charging the battery by applying the plurality of current levels corresponding to a pre-defined sequence to attain a cut-off voltage of the battery.