CPC G01R 31/367 (2019.01) [F02N 11/0818 (2013.01); F02N 11/0862 (2013.01); G01R 31/3835 (2019.01); G01R 31/389 (2019.01); H01M 10/0525 (2013.01); H01M 10/48 (2013.01); B60W 20/13 (2016.01); B60W 30/192 (2013.01); B60W 2510/244 (2013.01); F02N 2200/062 (2013.01); H01M 2220/20 (2013.01); H02J 7/0047 (2013.01)] | 16 Claims |
1. A system identification method executed by a system identification device configured to estimate a response of a system that has a current flowing in a battery as input and an overvoltage of the battery as output, the system identification method comprising:
a first step of identifying the system by applying a model of the battery including a finite impulse response (FIR) model and an auto regressive exogenous (ARX) model to the system, based on time series data of each of the current flowing in the battery and the overvoltage of the battery in a predetermined period;
a second step of estimating, based on the model of the battery applied to identify the system in the first step, the overvoltage of battery output from the system at an estimation target time in a case where no current is input to the system before an input start time and the current is input to the system from the input start time onwards, the estimation target time being after the input start time;
a third step of calculating a t-second value resistance based on the overvoltage at the estimation target time and a predetermined current to the battery at the estimation target time; and
a fourth step of controlling an engine to perform an idling stop when the t-second value resistance is less than a determination reference value,
wherein a number of sets of data applied to the FIR model in the time series data is greater than or equal to a number obtained by adding 1 to a number obtained by dividing a period from the input start time to the estimation target time by a sampling cycle.
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