A method for calculating the process capacity at a specific temperature of a lithium secondary battery includes a correction to a process capacity (Q.sub.3) at a specific temperature (T.sub.2) is performed using a value (Q.sub.1−Q.sub.2) obtained by subtracting the charge capacity (Q.sub.2) at the time of the shipping charge from the discharge capacity (Q.sub.1) measured at a discharge temperature (T.sub.1). A system for calculating a process capacity of a lithium secondary battery is provided.

A method for calculating the process capacity at a specific temperature of a lithium secondary battery includes a correction to a process capacity (Q.sub.3) at a specific temperature (T.sub.2) is performed using a value (Q.sub.1−Q.sub.2) obtained by subtracting the charge capacity (Q.sub.2) at the time of the shipping charge from the discharge capacity (Q.sub.1) measured at a discharge temperature (T.sub.1). A system for calculating a process capacity of a lithium secondary battery is provided.

The present disclosure relates to a method for predicting battery consumption of an electric vehicle and a device for the same. An electronic device includes an input unit which obtains destination information from a user, a memory, and at least one processor which is operatively connected to the input unit and the memory. The at least one processor may obtain a travel path of an electric vehicle, which is derived based on the destination information and may predict battery consumption when the electric vehicle travels along the travel path.

The present disclosure relates to a method for predicting battery consumption of an electric vehicle and a device for the same. An electronic device includes an input unit which obtains destination information from a user, a memory, and at least one processor which is operatively connected to the input unit and the memory. The at least one processor may obtain a travel path of an electric vehicle, which is derived based on the destination information and may predict battery consumption when the electric vehicle travels along the travel path.

A device with battery model optimization includes: a processor configured to perform optimization on a battery model for determining optimized parameter values of parameters of the battery model, wherein, to perform the optimization, the processor is configured to: select target parameters from among parameters of a battery model; set a current boundary condition for each of the target parameters; determine an optimized parameter value of each of the target parameters based on the set current boundary condition; set a subsequent boundary condition reduced from the current boundary condition based on the determined optimized parameter value; and determine a subsequent optimized parameter value of each of the target parameters based on the subsequent boundary condition.

A device with battery model optimization includes: a processor configured to perform optimization on a battery model for determining optimized parameter values of parameters of the battery model, wherein, to perform the optimization, the processor is configured to: select target parameters from among parameters of a battery model; set a current boundary condition for each of the target parameters; determine an optimized parameter value of each of the target parameters based on the set current boundary condition; set a subsequent boundary condition reduced from the current boundary condition based on the determined optimized parameter value; and determine a subsequent optimized parameter value of each of the target parameters based on the subsequent boundary condition.

A diagnostic device includes: a receiver that receives data of only some of battery cells constituting a storage battery system; and a controller that diagnoses the storage battery system based on the received data. The data has a voltage value and an integrated current amount value. The some of the battery cells include: a low-state MIN battery cell; a low-state MAX battery cell; a high-state MIN battery cell; and a high-state MAX battery cell. The controller executes at least one of: determining whether the battery cells are in a balanced state or an imbalance state; calculating an imbalance amount between capacities of the battery cells; or calculating a value related to a capacity of a battery cell.

A vehicle that is configured to: acquire information relating to a remaining charge of a battery of a terminal configured to act as a digital key employed in control of a vehicle; and perform a predetermined notification in response to both of a determination being made that the remaining charge of the battery of the terminal is a predetermined threshold or lower based on the acquired information, and the vehicle being in a preset vehicle state.

A vehicle that is configured to: acquire information relating to a remaining charge of a battery of a terminal configured to act as a digital key employed in control of a vehicle; and perform a predetermined notification in response to both of a determination being made that the remaining charge of the battery of the terminal is a predetermined threshold or lower based on the acquired information, and the vehicle being in a preset vehicle state.

A battery management system (BMS) and method for determining an active material content in an electrode includes determining a first peak in an inverse-differential capacity analysis curve of a the battery, determining a second peak in an incremental capacity analysis (ICA) curve associated with the at least one electrode, mapping the first peak of the inverse-differential capacity analysis curve to the second peak of the ICA curve, determining an active material content in the at least one electrode of the battery based on the mapping, and optimizing a performance of the battery based on the active material content in the at least one electrode.