A battery diagnosing apparatus, comprising: a voltage measuring circuit configured to generate a voltage signal representing a battery voltage that is a voltage across both ends of each of a plurality of batteries; a database in which a plurality of abnormal patterns, a plurality of reference time series, and a predetermined corresponding relationship between the plurality of abnormal patterns and the plurality of reference time series are recorded; and a control unit configured to generate a plurality of input time series representing a change history of the battery voltage of each of the plurality of batteries, based on the voltage signal, wherein the control unit is configured to extract an abnormal input time series representing an abnormal voltage behavior among the plurality of input time series by comparing the plurality of input time series with each other, and characterised in that: for each of the plurality of reference time series, the control unit is configured to: calculate a first similarity value representing a signal distance between the abnormal input time series and each reference time series by using dynamic time warping, convert the abnormal input time series and each reference time series into a first arranged time series and a second arranged time series having the same time length, respectively, by using the dynamic time warping, calculate a second similarity value representing a Pearson correlation coefficient between the first arranged time series and the second arranged time series, and determine a matching index between the abnormal input time series and each reference time series by combining the first similarity value and the second similarity value, wherein the control unit is configured to identify an abnormal pattern of the abnormal input time series to be identical to an abnormal pattern corresponding to a reference time series associated with one of the plurality of matching indexes determined for the plurality of reference time series. a voltage measuring circuit configured to generate a voltage signal representing a battery voltage that is a voltage across both ends of each of a plurality of batteries; a database in which a plurality of abnormal patterns, a plurality of reference time series, and a predetermined corresponding relationship between the plurality of abnormal patterns and the plurality of reference time series are recorded; and a control unit configured to generate a plurality of input time series representing a change history of the battery voltage of each of the plurality of batteries, based on the voltage signal, wherein the control unit is configured to extract an abnormal input time series representing an abnormal voltage behavior among the plurality of input time series by comparing the plurality of input time series with each other, and characterised in that: for each of the plurality of reference time series, the control unit is configured to: calculate a first similarity value representing a signal distance between the abnormal input time series and each reference time series by using dynamic time warping, convert the abnormal input time series and each reference time series into a first arranged time series and a second arranged time series having the same time length, respectively, by using the dynamic time warping, calculate a second similarity value representing a Pearson correlation coefficient between the first arranged time series and the second arranged time series, and determine a matching index between the abnormal input time series and each reference time series by combining the first similarity value and the second similarity value, wherein the control unit is configured to identify an abnormal pattern of the abnormal input time series to be identical to an abnormal pattern corresponding to a reference time series associated with one of the plurality of matching indexes determined for the plurality of reference time series. calculate a first similarity value representing a signal distance between the abnormal input time series and each reference time series by using dynamic time warping, convert the abnormal input time series and each reference time series into a first arranged time series and a second arranged time series having the same time length, respectively, by using the dynamic time warping, calculate a second similarity value representing a Pearson correlation coefficient between the first arranged time series and the second arranged time series, and determine a matching index between the abnormal input time series and each reference time series by combining the first similarity value and the second similarity value, wherein the control unit is configured to identify an abnormal pattern of the abnormal input time series to be identical to an abnormal pattern corresponding to a reference time series associated with one of the plurality of matching indexes determined for the plurality of reference time series.