TECHNICAL FIELD

The present invention relates to a device and a method for rapidly predicting the SOH of a battery.

More particularly, the present invention relates to a device and method for rapidly predicting the SOH of a battery by predicting the SOH of the battery by dividing it by sections.

BACKGROUND ART

As the use of portable electrical appliances such as notebooks, video cameras is activated, the importance of the secondary battery, which is mainly used as a driving power source, is increasing.

In addition, there is a growing need for an energy storage system (ESS) for supplying a large capacity of power by connecting secondary batteries in series and in parallel.

On the other hand, the importance of the technology related to the management system for more efficiently using and managing the ESS is increasing. Especially, in order to properly adjust the charging or discharging output and the State of Charge (SOC) usage strategy of the ESS, the management system must be able to accurately predict the State of Health (SOH) of the ESS.

Generally, in order to predict the SOH in the ESS, ESS charging/discharging experiment data of about 4000 cycles or more were required. Conventionally, SOH experiments were performed while charging/discharging the entire battery capacity under actual use conditions. In this experiment, since only data of an average of 4 to 5 cycles are obtained per day, approximately 900 days were required to obtain about 4000 charging/discharging test data.

Since the above-described conventional method obtains experimental data for predicting the SOH of the ESS over 30 months, it takes a long time to develop ESS, so that it was difficult to produce desired ESS in the market.

To solve this problem, there was a method of predicting the SOH using extrapolation, but there is a problem that the reliability is worse due to a large error as compared with the actual SOH of the ESS.

Therefore, the present invention proposes a device and method for maintaining the reliability of SOH prediction while reducing the time required to predict the SOH of the ESS.

(Prior art document) Korean Patent Application Publication No. 10-2013-0089360

DISCLOSURE OF THE INVENTION

Technical Problem

The present invention attempts to solve the problem that it takes a long time to obtain data for predicting the SOH of the ESS of the prior art, and the SOH prediction of the ESS takes a long time.

More specifically, the present invention provides a device and method for predicting the SOH of an ESS by dividing the capacity of the ESS into a plurality of capacity ranges to obtain charging/discharging cycle data of the ESS.

Technical Solution

According to an embodiment of the present invention, an energy storage system (ESS) state of health (SOH) prediction method includes: a capacity virtual division step of virtually dividing a capacity of a measurement target ESS into two or more; each capacity range-dependent charging/discharging cycle data measurement step of measuring charging/discharging cycle data of each capacity range divided in the capacity virtual division step; and a measurement target ESS SOH prediction step of predicting an SOH of the measurement target ESS based on charging/discharging cycle data of each actual ESS measured in the each capacity range-dependent charging/discharging cycle data measurement step.

The capacity virtual division step may include: a division range number setting step of setting a number of ranges a total capacity of the measurement target ESS is divided; and an actual ESS preparation step of preparing an actual ESS for each capacity range of the measurement target ESS, wherein a range of the actual ESS may be set based on an output voltage to match the divided range, wherein the divided range of the actual ESS may be overlapped with ranges adjacent to each other by a predetermined range.

The each capacity range-dependent charging/discharging cycle data measurement step may repeat the charging/discharging of the actual ESS corresponding to each capacity range divided in the capacity virtual division step to measure charging/discharging cycle data of the actual ESS corresponding to the each capacity range.

The method of the repeating charging/discharging of the actual ESS may include: a first reference voltage setting step of setting a first reference voltage matching an upper limit capacity in each capacity range corresponding to the actual ESS; a second reference voltage setting step of setting a second reference voltage matching a lower limit capacity in each capacity range corresponding to the actual ESS; an output voltage measurement step of measuring an output voltage of the actual ESS; a comparison step of comparing the measured output voltage of the actual ESS with the first and second reference voltages; and a charging/discharging determination step of determining charging or discharging of the actual ESS according to a comparison result of the comparison step.

The charging/discharging determination step may include performing charging when the output voltage of the actual ESS is less than or equal to the first reference voltage according to the comparison result of the comparison step and stopping charging and performing discharging when the output voltage of the actual ESS exceeds the first reference voltage.

The charging/discharging determination step may include performing discharging when the output voltage of the actual ESS is greater than or equal to the second reference voltage according to the comparison result of the comparison step and stopping discharging and performing charging when the output voltage of the actual ESS is less than the second reference voltage.

The ESS SOH prediction step may predict an SOH of an ESS through at least one of: a first method for predicting the SOH of the ESS by summing each capacity range-dependent charging/discharging cycle data measured in the each capacity range-dependent charging/discharging cycle data measurement step; a second method for predicting the ESS SOH by a combination sum of each capacity range-dependent charging/discharging cycle data measured in the each capacity range-dependent charging/discharging cycle data measurement step; and a third method for predicting the ESS SOH using a multiplicative probability of each capacity range-dependent charging/discharging cycle data measured in the each capacity range-dependent charging/discharging cycle data measurement step.

According to a first embodiment of the present invention, an energy storage system (ESS) state of health (SOH) prediction device includes: a plurality of actual energy storage systems (ESSs); and an analysis unit for measuring and analyzing charging/discharging cycle data from each of the plurality of actual ESSs, wherein the analysis unit includes: a virtual capacity division unit for virtually dividing a capacity of the ESS to be measured into two or more capacity ranges; a reference voltage setting unit for setting a first reference voltage and a second reference voltage matching the divided capacitance range; and an ESS SOH prediction unit for predicting the SOH of the ESS from the inputted charging/discharging cycle data, wherein the number of actual ESSs is equal to or greater than the number of capacity ranges divided by the virtual capacity division unit, wherein the analysis unit transmits a first reference voltage and a second reference voltage matching the divided capacity range to the plurality of actual ESSs and repeats the charging or discharging process of each actual ESS to measure divided capacity range-dependent charging/discharging cycle data.

The virtual capacity division unit may set the virtually divided capacity range to overlap ranges adjacent to each other by a predetermined range, wherein the first reference voltage may correspond to an upper limit capacity of each divided capacity range, wherein the second reference voltage may corresponds to a lower limit capacity of each divided capacity range, wherein the first reference voltage may be higher than the second reference voltage.

Each of the plurality of actual ESSs may include a BSC for controlling charging/discharging of an actual ESS, wherein when the initial output voltage of the actual ESS is less than or equal to the first reference voltage, after charging is performed until the output voltage of the actual ESS becomes the first reference voltage, when the output voltage of the actual ESS exceeds the first reference voltage, the BSC may stop charging and perform discharging, wherein when the initial output voltage of the actual ESS is greater than or equal to the second reference voltage, after discharging is performed until the output voltage of the actual ESS becomes the second reference voltage, and when the output voltage of the actual ESS becomes less than the second reference voltage, the BSC may stop discharging and perform charging.

The ESS SOH prediction unit may predict an SOH of an ESS through at least one of: a first method for predicting the SOH of the ESS by summing each capacity range-dependent charging/discharging cycle data measured in each of the plurality of actual ESSs; a second method for predicting the ESS SOH by a combination sum of each capacity range-dependent charging/discharging cycle data measured in each of the plurality of actual ESSs; and a third method for predicting the ESS SOH using a multiplicative probability of each capacity range-dependent charging/discharging cycle data measured in each of the plurality of actual ESSs.

According to a second embodiment of the present invention, an energy storage system (ESS) state of health (SOH) prediction device includes: a plurality of actual Energy Storage Systems (ESSs); and an analysis unit for measuring and analyzing charging/discharging cycle data from each of the plurality of actual ESSs, wherein the analysis unit includes: a virtual capacity division unit for virtually dividing the capacity of the ESS to be measured into two or more capacity ranges; a reference voltage setting unit for setting a first reference voltage and a second reference voltage matching the divided capacitance range; and an ESS SOH prediction unit for predicting the SOH of the ESS from the inputted charging/discharging cycle data, wherein the number of the two or more capacity ranges divided by the virtual capacity division unit is equal to or less than the actual ESS number, and wherein the analysis unit transmits a first reference voltage and a second reference voltage matching the divided capacity range to the plurality of actual ESSs and repeats the charging or discharging process of each actual ESS to measure divided capacity range-dependent charging/discharging cycle data.

The virtual capacity division unit may set the virtually divided capacity range to overlap ranges adjacent to each other by a predetermined range, wherein the first reference voltage may correspond to an upper limit capacity of each divided capacity range, wherein the second reference voltage may correspond to a lower limit capacity of each divided capacity range, and wherein the first reference voltage may be higher than the second reference voltage.

Each of the plurality of actual ESSs may include a BSC for controlling charging/discharging of an actual ESS, wherein when the initial output voltage of the actual ESS is less than or equal to the first reference voltage, after charging is performed until the output voltage of the actual ESS becomes the first reference voltage, when the output voltage of the actual ESS exceeds the first reference voltage, the BSC may stop charging and perform discharging, wherein when the initial output voltage of the actual ESS is greater than or equal to the second reference voltage, after discharging is performed until the output voltage of the actual ESS becomes the second reference voltage, and when the output voltage of the actual ESS becomes less than the second reference voltage, the BSC may stop discharging and perform charging.

The ESS SOH prediction unit may predict an SOH of an ESS through at least one of: a first method for predicting the SOH of the ESS by summing each capacity range-dependent charging/discharging cycle data measured in each of the plurality of actual ESSs; a second method for predicting the ESS SOH by a combination sum of each capacity range-dependent charging/discharging cycle data measured in each of the plurality of actual ESSs; and a third method for predicting the ESS SOH using a multiplicative probability of each capacity range-dependent charging/discharging cycle data measured in each of the plurality of actual ESSs.

Advantageous Effects

The present invention may divide the capacity range of the ESS into several capacity ranges and rapidly collect charging/discharging cycle data of the ESSs for each capacity range.

In addition, by rapidly collecting the charging/discharging cycle data of the ESS for each capacity range, the SOH of the whole ESS may be predicted quickly.

