Discussed is a system for managing a state of a battery, the system including: a user terminal to set location information about a location at which the battery is stored and output the set location information; a battery information obtaining device connected to the battery and to obtain battery information including at least one of voltage, SOC, and SOH of the battery and output the obtained battery information; and a performance detecting device connected to the user terminal to receive the set location information, connected to the battery information obtaining device to receive the obtained battery information, and to determine a target location at which the battery is stored, obtain environment information of the determined target location, set reference state information of at least one reference cell stored around the determined target location, and detect performance of the battery.

Discussed is a system for managing a state of a battery, the system including: a user terminal to set location information about a location at which the battery is stored and output the set location information; a battery information obtaining device connected to the battery and to obtain battery information including at least one of voltage, SOC, and SOH of the battery and output the obtained battery information; and a performance detecting device connected to the user terminal to receive the set location information, connected to the battery information obtaining device to receive the obtained battery information, and to determine a target location at which the battery is stored, obtain environment information of the determined target location, set reference state information of at least one reference cell stored around the determined target location, and detect performance of the battery.

The invention relates to a method for estimating the state of an energy store comprising at least one electrochemical battery cell (12, 14, 16, 18, 20, 22, 24, 26, 28) using a battery management system (BMS) which comprises an impedance spectroscopy chip, having at least the following steps: a) determining the frequency-dependent impedance of the at least one electrochemical battery cell (12, 14, 16, 18, 20, 22, 24, 26, 28) using a data set recording taken in real-time, b) training an artificial neural network (60) with temperature-based training spectra as the input and a specification for temperature values belonging to each training spectrum as the output, c) taking into consideration a battery cell-to-battery cell variance (30) between the electrochemical battery cells (12, 14, 16, 18, 20, 22, 24, 26, 28) when testing the artificial neural network (60) using weighting functions ascertained during step b) and test spectra and estimating the temperature values belonging to the test spectra according to the weighting functions ascertained in step b), and d) estimating at least one internal state (SoC, SoH, T.sub.int) of the at least one electrochemical battery cell (12, 14, 16, 18, 20, 22, 24, 26, 28) of the energy store using the trained artificial neural network (6).

The invention relates to a method for estimating the state of an energy store comprising at least one electrochemical battery cell (12, 14, 16, 18, 20, 22, 24, 26, 28) using a battery management system (BMS) which comprises an impedance spectroscopy chip, having at least the following steps: a) determining the frequency-dependent impedance of the at least one electrochemical battery cell (12, 14, 16, 18, 20, 22, 24, 26, 28) using a data set recording taken in real-time, b) training an artificial neural network (60) with temperature-based training spectra as the input and a specification for temperature values belonging to each training spectrum as the output, c) taking into consideration a battery cell-to-battery cell variance (30) between the electrochemical battery cells (12, 14, 16, 18, 20, 22, 24, 26, 28) when testing the artificial neural network (60) using weighting functions ascertained during step b) and test spectra and estimating the temperature values belonging to the test spectra according to the weighting functions ascertained in step b), and d) estimating at least one internal state (SoC, SoH, T.sub.int) of the at least one electrochemical battery cell (12, 14, 16, 18, 20, 22, 24, 26, 28) of the energy store using the trained artificial neural network (6).

A secondary battery diagnosing technology capable of effectively diagnosing a state of a secondary battery using a charge and discharge signal of the secondary battery, including a memory unit configured to store a positive electrode reference profile and a negative electrode reference profile for charge or discharge of a reference battery, a voltage measuring unit configured to measure a voltage of a target battery during a charge or discharge process, and a processor configured to generate a charge and discharge measurement profile based on the voltage, compare a simulation profile obtained from the positive electrode reference profile and the negative electrode reference profile with the generated charge and discharge measurement profile, and determine a positive electrode adjustment profile and a negative electrode adjustment profile so that an error between the simulation profile and the charge and discharge measurement profile is within a predetermined level.

A battery charging method includes during charging of a battery, upon determining that a state of charge (SOC) of the battery reaches an SOC range, adjusting, within a range from a minimum boundary value of the SOC range to a set SOC, a charge rate of the battery from a first charge rate down to a second charge rate; and adjusting, within a range from the set SOC to a maximum boundary value of the first SOC range, the charge rate of the battery from the second charge rate up to the first charge rate or a third charge rate.

A battery charging method includes during charging of a battery, upon determining that a state of charge (SOC) of the battery reaches an SOC range, adjusting, within a range from a minimum boundary value of the SOC range to a set SOC, a charge rate of the battery from a first charge rate down to a second charge rate; and adjusting, within a range from the set SOC to a maximum boundary value of the first SOC range, the charge rate of the battery from the second charge rate up to the first charge rate or a third charge rate.

A battery information management system, comprises: a battery; and a server that establishes communication with the battery via a network. The battery includes: a storage unit configured to store maintenance information for maintenance of the battery, user information related to personal data of a user of the battery, and usage history information of the battery; an information communication unit configured to transmit the user information and the usage history information from the storage unit to the server; and a control unit configured to control the storage unit and the information communication unit.

A battery information management system, comprises: a battery; and a server that establishes communication with the battery via a network. The battery includes: a storage unit configured to store maintenance information for maintenance of the battery, user information related to personal data of a user of the battery, and usage history information of the battery; an information communication unit configured to transmit the user information and the usage history information from the storage unit to the server; and a control unit configured to control the storage unit and the information communication unit.

A method and apparatus for monitoring an internet-of-things (IoT) battery device (IBD). An example IBD includes a radio transceiver to communicate with an IoT charging device (ICD), a battery, and a battery monitor to determine a state of charge for the battery. An alerter is included to send an alert message to the ICD, via the radio transceiver, to indicate that the SoCh is less than an alert threshold.