A battery management apparatus, comprising: a memory unit configured to store first to p th observational data sets and first to n th desired data sets, wherein each of p and n is an integer of 2 or greater; and a control unit operably coupled to the memory unit, wherein the first to p th observational data sets are respectively associated with p external variables that are observable outside a battery cell, each of the first to p th observational data sets includes a predetermined number of input values, the first to n th desired data sets are associated with first to n th internal variables, respectively, wherein the first to n th internal variables are dependent on an internal chemical state of the battery cell and unobservable outside the battery cell, each of the first to n th desired data sets includes the same number of target values as the predetermined number, and the control unit is configured to: set m observational data sets extracted by data filtering from the first to p th observational data sets as first to m th input data sets, wherein m is an integer with 1 ≤ m ≤ p, by determining a multiple correlation coefficient between the q th observational data set and the q+1 th observational data set, when q is an integer of 1 to p-1, and setting the q th observational data set as one of the first to m th input data sets when an absolute value of the multiple correlation coefficient is less than a predetermined filtering value, and set at least one of the first to m th external variables as a valid external variable for each of the first to n th internal variables based on the first to m th input data sets and the first to n th desired data sets by analyzing a correlation between the internal variables and the external variables, and wherein the first to m th external variables are m external variables associated with the m observational data sets, among the p external variables. a memory unit configured to store first to p th observational data sets and first to n th desired data sets, wherein each of p and n is an integer of 2 or greater; and a control unit operably coupled to the memory unit, wherein the first to p th observational data sets are respectively associated with p external variables that are observable outside a battery cell, each of the first to p th observational data sets includes a predetermined number of input values, the first to n th desired data sets are associated with first to n th internal variables, respectively, wherein the first to n th internal variables are dependent on an internal chemical state of the battery cell and unobservable outside the battery cell, each of the first to n th desired data sets includes the same number of target values as the predetermined number, and the control unit is configured to: set m observational data sets extracted by data filtering from the first to p th observational data sets as first to m th input data sets, wherein m is an integer with 1 ≤ m ≤ p, by determining a multiple correlation coefficient between the q th observational data set and the q+1 th observational data set, when q is an integer of 1 to p-1, and setting the q th observational data set as one of the first to m th input data sets when an absolute value of the multiple correlation coefficient is less than a predetermined filtering value, and set at least one of the first to m th external variables as a valid external variable for each of the first to n th internal variables based on the first to m th input data sets and the first to n th desired data sets by analyzing a correlation between the internal variables and the external variables, and wherein the first to m th external variables are m external variables associated with the m observational data sets, among the p external variables. set m observational data sets extracted by data filtering from the first to p th observational data sets as first to m th input data sets, wherein m is an integer with 1 ≤ m ≤ p, by determining a multiple correlation coefficient between the q th observational data set and the q+1 th observational data set, when q is an integer of 1 to p-1, and setting the q th observational data set as one of the first to m th input data sets when an absolute value of the multiple correlation coefficient is less than a predetermined filtering value, and set at least one of the first to m th external variables as a valid external variable for each of the first to n th internal variables based on the first to m th input data sets and the first to n th desired data sets by analyzing a correlation between the internal variables and the external variables, and wherein the first to m th external variables are m external variables associated with the m observational data sets, among the p external variables.