A battery control system includes a plurality of battery cells that are separately controllable as units of individual cells or groups of cells. Each controllable unit may be switchably activated or deactivated in the overall battery circuit, and one or more conditions of each controllable unit may be individually measured. Various techniques are disclosed for operating the battery control system to optimize or improve system performance and longevity.

A battery control system includes a plurality of battery cells that are separately controllable as units of individual cells or groups of cells. Each controllable unit may be switchably activated or deactivated in the overall battery circuit, and one or more conditions of each controllable unit may be individually measured. Various techniques are disclosed for operating the battery control system to optimize or improve system performance and longevity.

A method for estimating a battery power percentage of a battery includes: performing a first fuel gauge operation upon the battery; and using the first fuel gauge operation to generate the battery power percentage of the battery by referring to information measured by a second fuel gauge operation performed upon the battery wherein the second fuel gauge operation is different from the first fuel gauge operation.

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).

The invention provides methods, devices and non-transitory tangible computer-readable storage media for estimating a state of charge of a battery and extracting a charging curve of the battery. The method for estimating the state of charge of the battery includes estimating a first state of charge of the battery; determining a charging curve that conforms to the present charging scenario, wherein the present charging scenario is characterized by at least one of parameters including an ambient temperature, a charging rate, an internal resistance, a state of health, a lifespan, and an open circuit voltage of the battery; and correcting the first state of charge according to the charging curve to obtain a final state of charge of the battery.

The invention provides methods, devices and non-transitory tangible computer-readable storage media for estimating a state of charge of a battery and extracting a charging curve of the battery. The method for estimating the state of charge of the battery includes estimating a first state of charge of the battery; determining a charging curve that conforms to the present charging scenario, wherein the present charging scenario is characterized by at least one of parameters including an ambient temperature, a charging rate, an internal resistance, a state of health, a lifespan, and an open circuit voltage of the battery; and correcting the first state of charge according to the charging curve to obtain a final state of charge of the battery.

Processing circuitry functionally includes: an internal resistance calculation unit; a reference value obtaining unit configured to obtain a reference value for internal resistance; a correction coefficient calculation unit configured to calculate a correction coefficient indicating how great difference between the internal resistance and the reference value is: a correction value calculation unit configured to calculate a correction value by correcting the reference value using the correction coefficient; and an estimation unit configured to calculate estimated internal resistance, based on the correction value and present voltage. The processing circuitry is configured to control charge and/or discharge of the battery, based on the internal resistance or the estimated internal resistance. The correction value calculation unit is configured to calculate the correction value by correcting the reference value using the correction coefficient calculated in the past when the internal resistance calculation unit is unable to calculate the internal resistance.

Processing circuitry functionally includes: an internal resistance calculation unit; a reference value obtaining unit configured to obtain a reference value for internal resistance; a correction coefficient calculation unit configured to calculate a correction coefficient indicating how great difference between the internal resistance and the reference value is: a correction value calculation unit configured to calculate a correction value by correcting the reference value using the correction coefficient; and an estimation unit configured to calculate estimated internal resistance, based on the correction value and present voltage. The processing circuitry is configured to control charge and/or discharge of the battery, based on the internal resistance or the estimated internal resistance. The correction value calculation unit is configured to calculate the correction value by correcting the reference value using the correction coefficient calculated in the past when the internal resistance calculation unit is unable to calculate the internal resistance.