Apparatus and method for estimating a state of charge of a battery

An apparatus for estimating a state of charge of a battery, the apparatus comprising:

• a sensing unit configured to:
• measure a voltage of the battery via a voltage sensor of the sensing unit;
• and
• measure a current of the battery via a current sensor of the sensing unit;
• a current integrating unit is a coulomb counter configured to calculate a current integration value for a predetermined period, based on the measured current;
• and
• a processor operably coupled to the sensing unit and the current integrating unit, the processor includes a chipset, wherein the processor is configured to:
• read out, from a memory, a first initial value representing a previously estimated state of charge of the battery, a second initial value representing a previously estimated overpotential of the battery, and a third initial value representing a previously estimated error covariance matrix of an extended Kalman filter;
• assign the first initial value and the second initial value respectively to a first state variable and a second state variable of a first state equation of the extended Kalman filter;
• predict a next value of the first state variable and predict a next value of the second state variable based on the current integration value, by using the first state equation;
• determine a process noise covariance matrix of the extended Kalman filter, based on any one of the first initial value and the predicted first state variable;
• predict the error covariance matrix based on the third initial value and the determined process noise covariance matrix, by using a second state equation of the extended Kalman filter;
• determine a Kalman gain of the extended Kalman filter, based on the predicted error covariance matrix;
• and
• correct each of the predicted first state variable and the predicted second state variable, based on the determined Kalman gain and the measured voltage,
• wherein the processor is further configured to:
• convert an open circuit voltage curve indicating a relationship between a SOC and an open circuit voltage of the battery to an open circuit voltage change rate curve indicating a relationship between the SOC and a rate of change of the open circuit voltage of the battery;
• when the first initial value is within a first section, assign a predetermined first value and a predetermined second value respectively to a first process noise and to a second process noise of the determined process noise covariance matrix, the first section is a first SOC range where the rate of change of the open circuit voltage is equal to or greater than a threshold value;
• set a second section, the second section is a second SOC range, separate from the first SOC range of the first section, where the rate of change of the open circuit voltage is smaller than the threshold value, and
• wherein the processor is further configured to, when the first initial value is in the second section, assign the first value to the first process noise and assign a fourth value greater than the second value to the second process noise.

An apparatus for estimating a state of charge of a battery, the apparatus comprising:

• a sensing unit configured to:
• measure a voltage of the battery via a voltage sensor of the sensing unit, and
• measure a current of the battery via a current sensor of the sensing unit;
• a current integrating unit is a coulomb counter configured to calculate a current integration value for a predetermined period, based on the measured current;
• and
• a processor operably coupled to the sensing unit and the current integrating unit, the processor includes a chipset,
• wherein the processor is configured to:
• read out, from a memory, a first initial value representing a previously estimated state of charge of the battery, a second initial value representing a previously estimated overpotential of the battery, and a third initial value representing a previously estimated error covariance matrix of an extended Kalman filter;
• assign the first initial value and the second initial value respectively to a first state variable and a second state variable of a first state equation of the extended Kalman filter;
• predict a next value of the first state variable and predict a next value of the second state variable based on the current integration value, by using the first state equation;
• determine a process noise covariance matrix of the extended Kalman filter, based on any one of the first initial value and the predicted first state variable;
• predict the error covariance matrix based on the third initial value and the determined process noise covariance matrix, by using a second state equation of the extended Kalman filter;
• determine a Kalman gain of the extended Kalman filter, based on the predicted error covariance matrix;
• and
• correct each of the predicted first state variable and the predicted second state variable, based on the determined Kalman gain and the measured voltage,
• wherein the processor is further configured to:
• convert an open circuit voltage curve indicating a relationship between a SOC and an open circuit voltage of the battery to an open circuit voltage change rate curve indicating a relationship between the SOC and a rate of change of the open circuit voltage of the battery;
• when the first initial value is within a first section, assign a predetermined first value and a predetermined second value respectively to a first process noise and to a second process noise of the determined process noise covariance matrix, the first section is a first SOC range where the rate of change of the open circuit voltage is equal to or greater than a threshold value;
• set a second section, the second section is a second SOC range, separate from the first SOC range of the first section, where the rate of change of the open circuit voltage is smaller than the threshold value;
• and
• wherein the processor is further configured to, when the first initial value is in the second section, assign a fifth value smaller than the first value to the first process noise and assign a sixth value greater than the second value to the second process noise.