Abstract: A state of charge calculation apparatus and storage battery system improve the estimation accuracy of the state of charge of a secondary battery. A state of charge calculation apparatus (15) for a secondary battery (14) includes a charging/discharging current detector (22) that detects a charging/discharging current of the secondary battery (14), a terminal voltage detector (23) that detects a terminal voltage of the secondary battery (14), a first estimator (24) that integrates the charging/discharging current and estimates a first state of charge, a second estimator (25) that estimates a second state of charge on the basis of the relationship between open circuit voltage and state of charge of the secondary battery (14), and a state of charge calculator (26) that calculates a third state of charge on the basis of the first state of charge and second state of charge respectively weighted by the charging/discharging current.

Abstract: A parameter estimation device using a filter includes a preprocessing computing circuit, a state estimating circuit and a state-of-charge estimating circuit. A low-pass filter of the preprocessing computing circuit transfers the voltage preprocessing value and the current preprocessing value from inputted discharge-and-charge current value and terminal voltage value, respectively. The state estimating circuit estimates parameters of a state equation of a battery equivalent model based on the battery equivalent model containing a resistance and a capacitor from the voltage preprocessing value and the current preprocessing value inputted. The state-of-charge estimating circuit estimates the state of charge from state quantity obtained. The time constant varies in such a way that the higher the temperature and the state of charge becomes the smaller the time constant becomes.

Abstract: An apparatus for battery state estimation can accurately estimate the internal state of a battery by taking into consideration the slow response portion of the battery.

Abstract: In a battery model identification method of the present invention, an M-sequence input electric current production part inputs M-sequence signals with different frequency components as an electric current input into the battery. In this occasion, terminal voltage of the battery is measured by a voltage sensor, and a parameter estimation part executes system identification based on the measured result to calculate frequency characteristics of the battery. Resistance components and capacitance components as parameters of a battery model are identified based on the calculated frequency characteristics.

Abstract: A parameter estimation device using a filter has a preprocessing computing means 6, a state estimating means 7 and a state-of-charge estimating means 9. A low-pass filter 61 of the preprocessing computing means 6 transfers voltage preprocessing value Vp and current preprocessing value Ip from inputted discharge-and-charge current value I and terminal voltage value V, respectively. The state estimating means 7 estimates parameters of a state equation of a battery equivalent model 7A based on the battery equivalent model 7A containing a resistance and a capacitor from the voltage preprocessing value and the current preprocessing value inputted from the means 6. The state-of-charge estimating means 9 estimates the state of charge from state quantity obtained by the means 7. The time constant varies in such a way that the higher the temperature and the state of charge SoC becomes the smaller the time constant becomes.

Abstract: In a battery model identification method of the present invention, an M-sequence input electric current production part 2 inputs M-sequence signals with different frequency components as an electric current input into the battery 4. In this occasion, terminal voltage of the battery is measured by a voltage sensor 5, and a parameter estimation part 3 executes system identification based on the measured result to calculate frequency characteristics of the battery. Resistance components Rb, R1-R3 and capacitance components C1-C3 as parameters of a battery model 7 are identified based on the calculated frequency characteristics.