KR20220036701A - Battery system diagnosis apparatus - Google Patents

Abstract

Disclosed is an apparatus for diagnosing a battery system capable of simply diagnosing a defective battery module among a plurality of battery modules included in a battery system. A battery system diagnosis apparatus according to an aspect of the present invention is an apparatus for diagnosing a battery system including a plurality of battery modules, and for each of the battery modules, a voltage configured to measure voltages of a plurality of battery cells included therein measuring unit; a deviation calculating unit configured to calculate a voltage deviation between a plurality of battery cells included therein, for each of the battery modules, based on a result measured by the voltage measuring unit; and a diagnosis unit configured to diagnose a defective module by comparing the change state of the voltage deviation of each battery module calculated by the deviation calculating unit.

Description

Battery system diagnosis apparatus

The present invention relates to a battery diagnosis technology, and more particularly, to a battery diagnosis technology for diagnosing a bad battery module in a battery system including a plurality of battery modules.

Currently commercialized secondary batteries include nickel cadmium batteries, nickel hydride batteries, nickel zinc batteries, and lithium secondary batteries. Among them, lithium secondary batteries have almost no memory effect compared to nickel-based secondary batteries, so charging and discharging are free, The self-discharge rate is very low and the energy density is high, attracting attention.

Such a lithium secondary battery mainly uses a lithium-based oxide and a carbon material as a positive electrode active material and a negative electrode active material, respectively. A lithium secondary battery includes an electrode assembly in which a positive electrode plate and a negative electrode plate to which the positive electrode active material and the negative electrode active material are applied, respectively, are disposed with a separator interposed therebetween, and a casing for sealing and housing the electrode assembly together with an electrolyte, that is, a battery case.

In recent years, secondary batteries have been widely used for driving or energy storage not only in small devices such as portable electronic devices, but also in medium and large devices such as automobiles and energy storage systems (ESS). The secondary battery is included in the battery system in the form provided in the battery module and mounted on a medium or large device. or connected in parallel.

However, while the battery system is in use, a defect may occur in some battery modules. In this case, if the bad battery module is not properly diagnosed, the overall performance and reliability of the battery system may be deteriorated. Therefore, it is necessary to quickly and accurately diagnose a defective battery module included in the battery system.

Until now, several technologies for diagnosing a bad battery module have been developed and proposed. A typical example is a technique for diagnosing a defective battery module by calculating the state of health (SOH) of a battery module or a battery cell (secondary battery) included therein through current integration or internal resistance estimation.

However, according to the SOH-based fault diagnosis method, in the process of calculating voltage, current, and temperature, it is easy to generate a measurement error or a logic error. Therefore, due to such an error, an accurate diagnosis of a defective module may not be performed. In addition, according to the conventional method as described above, the calculation process is complicated, and in the process of performing the calculation, it takes a long time, and a problem such as a large load of a processor may occur.

In addition, according to the conventional method as described above, when replacing some battery modules, it is difficult to compare the SOH between the battery modules, so accurate fault diagnosis may not be made. In particular, in the case of a power storage system used in a power grid such as a smart grid, since numerous battery modules may be included, there may be many cases in which a specific battery module is replaced. However, according to the prior art, due to the replacement of some of these battery modules, the diagnosis of the defective battery module may be complicated or difficult.

The present invention has been devised to solve the above problems, and includes a battery system diagnostic device capable of diagnosing a defective battery module among a plurality of battery modules included in a battery system, a power storage device including the same, a battery pack, etc. is intended to provide

Other objects and advantages of the present invention may be understood by the following description, and will become more clearly understood by the examples of the present invention. It will also be readily apparent that the objects and advantages of the present invention may be realized by the means and combinations thereof indicated in the appended claims.

A battery system diagnosis apparatus according to an aspect of the present invention for achieving the above object is an apparatus for diagnosing a battery system including a plurality of battery modules, and for each of the battery modules, a plurality of batteries included therein a voltage measuring unit configured to measure the voltage of the cell; a deviation calculating unit configured to calculate a voltage deviation between a plurality of battery cells included therein, for each of the battery modules, based on a result measured by the voltage measuring unit; and a diagnosis unit configured to diagnose a defective module by comparing the change state of the voltage deviation of each battery module calculated by the deviation calculating unit.

Here, the deviation calculating unit may be configured to calculate a voltage difference between the highest cell voltage and the lowest cell voltage in each battery module as a voltage deviation of the corresponding battery module.

In addition, the diagnosis unit may be configured to diagnose a defective module by comparing a change state of a voltage deviation of each battery module measured and calculated at two different time points.

In addition, the two different time points may include an installation time of the battery module and a time point after a predetermined period has elapsed from the installation time.

Also, the diagnosis unit may be configured to calculate a deviation ratio of voltage deviation over time for each battery module and diagnose a defective module using the calculated deviation ratio.

In addition, the diagnosis unit derives a ratio of the deviation ratio of the voltage deviation calculated for each battery module to the deviation ratio of the voltage deviation calculated with respect to the other battery modules as a relative ratio, and the relative ratio derived for each battery module may be configured to diagnose a bad module by comparing them with each other.

Also, the diagnosis unit may be configured to select a battery module having the largest relative relativization ratio and diagnose it as a defective module.

In addition, the diagnosis unit may be configured to determine whether the derived relative ratio of the selected battery module exceeds a reference ratio, and if it exceeds the reference ratio, diagnose the selected battery module as a defective module.

In addition, a power storage system according to another aspect of the present invention for achieving the above object includes the battery system diagnosis apparatus according to the present invention.

In addition, a battery pack according to another aspect of the present invention for achieving the above object includes the battery system diagnosis apparatus according to the present invention.

According to the present invention, in a battery pack including a plurality of battery modules, it is possible to effectively diagnose a defective battery module.

In particular, according to one aspect of the present invention, it is possible to diagnose a defective battery module through a relatively simple calculation without going through a complicated calculation process.

Moreover, in the case of the present invention, it is not necessary to calculate the SOH or the like of the battery cell. Accordingly, it is possible to prevent an error in the process of measuring the voltage, current, temperature, etc. of each battery cell to calculate the SOH or the like, or in the process of calculating using the measured values.

Therefore, according to the aspect of the present invention, the diagnosis of the defective battery module can be made quickly and accurately.

Moreover, according to an embodiment of the present invention, the SOC of the battery cell does not need to be calculated either.

Further, according to another aspect of the present invention, even when some battery modules among a plurality of battery modules included in the battery system are replaced, a defective battery module can be effectively diagnosed.

Therefore, according to this aspect of the present invention, when used in a power storage system including a large number of battery modules, even when some battery modules are replaced, it is possible to effectively diagnose a defective module.

The following drawings attached to this specification illustrate preferred embodiments of the present invention, and together with the detailed description of the present invention serve to further understand the technical spirit of the present invention, the present invention is should not be construed as being limited only to
1 is a block diagram schematically illustrating a functional configuration of an apparatus for diagnosing a battery system according to an embodiment of the present invention.
2 is a table showing a cell voltage measurement result for one battery module by a voltage measurement unit according to an embodiment of the present invention.
3 is a table schematically illustrating a configuration in which deviation ratios of voltage deviations of a plurality of battery modules are calculated by the diagnostic unit according to an embodiment of the present invention.
4 is a table showing relativization ratios for a plurality of battery modules derived by the diagnostic unit according to an embodiment of the present invention.
5 is a table schematically illustrating a configuration in which a bad module and a warning module are diagnosed by the diagnostic unit according to an embodiment of the present invention.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. Prior to this, the terms or words used in the present specification and claims should not be construed as being limited to conventional or dictionary meanings, and the inventor should properly understand the concept of the term in order to best describe his invention. Based on the principle that it can be defined, it should be interpreted as meaning and concept consistent with the technical idea of the present invention.

Accordingly, the configuration shown in the embodiments and drawings described in the present specification is only the most preferred embodiment of the present invention and does not represent all of the technical spirit of the present invention, so at the time of the present application, various It should be understood that there may be equivalents and variations.

1 is a block diagram schematically illustrating a functional configuration of an apparatus for diagnosing a battery system according to an embodiment of the present invention.

1 , the battery system may include a plurality of battery modules 10 . Although only ten battery modules 10 are illustrated in FIG. 1 , the present invention is not necessarily limited by the specific number of such battery modules 10 .

These battery modules 10 may be electrically connected to each other in series and/or in parallel. In addition, a plurality of battery cells, that is, a plurality of secondary batteries, may be provided inside each battery module 10 . In this case, a plurality of secondary batteries may be connected to each other in series and/or in parallel within the battery module 10 . Also, the battery module 10 may be expressed in other terms such as a battery pack or a cell assembly. For example, each battery module 10 may include a control unit such as a BMS like a general battery pack. The present invention is not limited by the specific embodiment or type of the battery module 10, and the present invention may be applied to various battery modules known at the time of filing of the present invention. The apparatus for diagnosing a battery system according to the present invention may be an apparatus for diagnosing a battery system including a plurality of battery modules 10 as described above.

Referring to FIG. 1 , an apparatus for diagnosing a battery system according to the present invention may include a voltage measuring unit 100 , a deviation calculating unit 200 , and a diagnosis unit 300 .

The voltage measuring unit 100 may be configured to measure a voltage for each of the battery modules 10 . In particular, each of the plurality of battery modules 10 may include a plurality of battery cells therein. In this case, the voltage measuring unit 100 may be configured to measure the voltage of each cell included therein with respect to each battery module 10 .

For example, when ten battery modules 10 shown in FIG. 1 are Module 1 to Module 10, and each of the ten battery modules 10 includes 12 battery cells, the voltage measuring unit 100 is , may be configured to measure the voltage across the battery cells as the cell voltage for each of the 120 battery cells. Here, the voltage measuring unit 100 may measure the OCV (Open Circuit Voltage) of each battery cell as a voltage. Alternatively, the voltage measuring unit 100 may measure the voltage across the cells during charging or discharging of each battery cell.

The voltage measuring unit 100 may employ various voltage measuring configurations known at the time of filing of the present invention, and the present invention is not limited by the specific shape of the voltage measuring unit 100 . For example, the voltage measuring unit 100 may be implemented as a voltage sensor.

Also, in FIG. 1 , only one of the voltage measuring unit 100 is included and all voltages are measured for the entire battery module 10 , but the present invention is not necessarily limited to this embodiment. For example, the battery system diagnosing apparatus according to the present invention may include the voltage measuring unit 100 in the number corresponding to the battery module 10 to measure the cell voltage included in the corresponding battery module. there is.

The deviation calculating unit 200 may be connected to the voltage measuring unit 100 to receive a voltage measurement result of a battery cell included in each of the battery modules 10 from the voltage measuring unit 100 . In addition, the deviation calculating unit 200, based on the cell voltage measurement result measured by the voltage measuring unit 100, for each of the battery modules 10, a voltage deviation between a plurality of battery cells included therein may be configured to compute

For example, in the configuration shown in FIG. 1 , the deviation calculating unit 200 may receive a voltage measurement result of an internal cell for each of the ten battery modules 10 from the voltage measuring unit 100 . In addition, the deviation calculating unit 200 may calculate a voltage deviation for each battery module 10 . More specifically, when the ten battery modules 10 are Modules 1 to 10, respectively, the deviation calculating unit 200 calculates the voltage deviation of Module 1, the voltage deviation of Module 2, ..., and the voltage deviation of Module 10. Each can be calculated. Here, the voltage deviation of each battery module 10 may mean a voltage deviation of cells included in each battery module 10 . For example, the voltage deviation of Module 1 may mean a voltage deviation between a plurality of battery cells included in Module 1 .

The diagnosis unit 300 may be connected to the deviation calculating unit 200 and configured to receive the voltage deviation calculation result of each battery module 10 from the deviation calculating unit 200 . In addition, the diagnosis unit 300 may be configured to compare the change state of the voltage deviation of each battery module 10 calculated by the deviation calculating unit 200 . In addition, the diagnosis unit 300 may be configured to diagnose whether there is a defective module that is not normal among the plurality of battery modules 10 and which battery module 10 is defective based on the comparison result. .

For example, in the configuration shown in FIG. 1 , the diagnosis unit 300 may compare the change state of how the voltage deviation changes with respect to each of the ten battery modules 10 . And, the diagnosis module may diagnose the defective module based on the comparison result.

According to this configuration of the present invention, the defective battery module 10 can be effectively diagnosed through simple calculation and comparison. In particular, according to the above configuration, since the defective module can be diagnosed using only the voltage measurement value, there is no need to go through a complicated calculation process as in the conventional method using the SOH. Therefore, there is little possibility of an error occurring in the calculation process, and time and processing load can be reduced. In addition, according to this configuration of the present invention, since there is no need to use a parameter other than the voltage, the configuration is simple, and there is little risk of errors due to measurement or calculation of other parameters.

Meanwhile, at least one of the deviation calculating unit 200 and the diagnosis unit 300 includes a processor, an application-specific integrated circuit (ASIC), another chipset, and a logic circuit known in the art to execute various control logics performed in the present invention. , registers, communication modems, data processing devices, and the like may optionally be included. In addition, when the control logic is implemented as software, at least one of the deviation calculating unit 200 and the diagnosis unit 300 may be implemented as a set of program modules. In this case, the program module may be stored in the memory and executed by the processor. The memory may be internal or external to the processor, and may be coupled to the processor by various well-known means. Moreover, the battery system or battery pack often includes a control unit referred to by terms such as Micro Controller Unit (MCU) or Battery Management System (BMS). At least one of the deviation calculating unit 200 and the diagnosis unit 300 may be implemented by a component such as an MCU or a BMS provided in the conventional battery pack.

On the other hand, in the present invention, when each component is implemented as a processor, etc., the contents 'configured to' with respect to the operation or function of each component will be understood as contents that are programmed to perform the corresponding operation or function. may be

In the above configuration, the deviation calculating unit 200 may be configured to calculate the voltage difference between the highest cell voltage and the lowest cell voltage inside each battery module 10 as a voltage deviation of the corresponding battery module 10 . . This will be described in more detail with reference to FIG. 2 .

2 is a table showing a cell voltage measurement result for one battery module 10 by the voltage measurement unit 100 according to an embodiment of the present invention.

In the embodiment of FIG. 2 , one battery module 10 , for example, 12 battery cells (Cell 1 to Cell 12) are included in the first module, and the voltage is measured for each battery cell at a certain point in time. is appearing

Such a voltage measurement result may be performed by the voltage measurement unit 100 and transmitted to the deviation calculating unit 200 . In addition, the deviation calculating unit 200 may select the highest cell voltage and the lowest cell voltage in the battery module 10 . In the embodiment of FIG. 2 , the deviation calculating unit 200 may select 4.128 V of Cell 5 as the highest cell voltage and 4.112 V of Cell 9 as the lowest cell voltage. In addition, the deviation calculating unit 200 may calculate the difference between the cell voltage of Cell 5 and the voltage of Cell 9, 0.016 V, that is, 16 mV, as the voltage deviation of the battery module 10 , for example, the first module.

Also, the deviation calculating unit 200 may calculate a voltage deviation at a specific time of each battery module 10 in this way for each of the plurality of battery modules 10 included in the battery system.

Here, the deviation calculating unit 200 may calculate the voltage deviation for each battery module 10 at the same time point or at a time point within a predetermined period having no significant difference. Moreover, the deviation calculating unit 200 may calculate a voltage deviation in the same SOC situation for each battery module 10 . For example, the deviation calculating unit 200 calculates a voltage deviation based on the cell voltage measured in January 2021 for each battery module 10, but the SOC of the battery module or battery cell is 100% In a situation, that is, in a fully charged situation, the voltage deviation can be calculated. In particular, in the case of the power storage system, since each battery module 10 may be used at a different time, the SOC may vary at the same time. Therefore, even if there is a slight difference in time points, voltage deviation is calculated in the same SOC situation, so that voltage deviation can be compared more accurately.

Also, the diagnosis unit 300 may be configured to diagnose a defective module by comparing the change state of the voltage deviation of each battery module 10 measured and calculated at two different time points.

For example, when the deviation calculating unit 200 calculates the voltage deviations for the plurality of battery modules 10 at the first time point T1 and the second time point T2, respectively, the calculated result is returned to the diagnosis unit ( 300) may be transmitted. Then, for each battery module 10 , the diagnosis unit 300 may compare the voltage deviation calculation result at the first time point T1 and the voltage deviation calculation result at the second time point T2 with each other. In addition, by comparing the voltage deviation calculation results at the two different time points T1 and T2 , the change state of the voltage deviation for each battery module 10 may be determined. In addition, the diagnosis unit 300 may compare the change state of the voltage deviation of each battery module 10 identified as described above with each other. Also, by comparing the change state of the voltage deviation of each battery module 10 , the diagnosis unit 300 may diagnose the defective module.

As a more specific example, with respect to Module 1, Module 2, Module 3, ..., Module 10, the voltage deviation calculation result at the first time point T1 by the deviation calculating unit 200 is AT1, AT2, AT3, . .., AT10, and when the voltage deviation calculation result at the second time point T2 by the deviation calculating unit 200 is BT1, BT2, BT3, ..., BT10, the diagnosis unit 300 is configured for each battery module Based on the change state of the voltage deviation in (10), a defective module can be diagnosed. That is, the diagnosis unit 300 compares the state change results of AT1 → BT1, AT2 → BT2, AT3 → BT3, ..., AT10 → BT10, which are the changed states of each battery module 10 with each other, can be diagnosed

According to this configuration of the present invention, if the voltage deviation calculation result at two different time points T1 and T2 is known, the defective module can be identified relatively simply and accurately through the change amount.

Here, the two different viewpoints may mean two different viewpoints according to the passage of time, or may mean two different viewpoints according to use. For example, two different time points may be one time point and a time point when one year has elapsed therefrom. As another example, two different time points may be one time point and a time point when 100 cycles have elapsed therefrom. In this case, the cycle may be calculated based on a time when the battery system or battery module 10 is fully charged and then fully discharged, or is calculated based on a time when the battery system or battery module 10 is turned on and then turned off. it might be

In particular, the two different time points may be configured to include an installation time of each battery module 10 and a time point after a predetermined period has elapsed from the installation time.

For example, when the battery system includes ten battery modules 10 and the battery system is provided by installing the ten battery modules 10 at the same time, the first time point for each of the ten battery modules 10 (T1) may be a time point at which ten battery modules 10 are installed. In addition, after the battery system is used, the installation time, that is, the time when one year has elapsed from the first time point T1 may be referred to as a second time point T2. Accordingly, the diagnosis unit 300, for each of the ten battery modules 10, is measured and calculated at the voltage deviation measured and calculated at the installation time T1, and measured and calculated at the time T2 when one year has elapsed from the installation time. voltage deviations can be compared with each other. In addition, the diagnosis unit 300 may determine the change state of the voltage deviation of each battery module 10 by comparing the voltage deviation at different time points. Also, the diagnosis unit 300 may diagnose a defective module by comparing changes in voltage deviation among the plurality of battery modules 10 with each other.

According to this configuration of the present invention, after the battery system is installed, the defective module can be diagnosed simply. More specifically, as long as the voltage deviation of each battery module 10 at the time when the battery system is installed is basically stored, then the voltage deviation of each battery module 10 is calculated at any one time point, compared to the time of installation. , it is possible to determine how the voltage deviation of each battery module 10 is changed. And, with respect to this change state, a defective module may be diagnosed through comparison between each battery module 10 . In particular, according to an exemplary embodiment of the present invention, even after the first diagnosis, subsequent diagnosis such as secondary, tertiary, quaternary, ... may be continuously performed whenever time elapses. In addition, by comparing the voltage deviation calculated when the subsequent diagnosis is performed with the voltage deviation at the time of initial installation, the change state can be grasped, and the defective module can be diagnosed.

On the other hand, two different time points T1 and T2, which are criteria for determining the change state of the voltage deviation, may have the same SOC. For example, for each battery module 10, when the voltage deviation is calculated in a situation where the SOC is 100% at the time T1, the voltage deviation is calculated in the situation where the SOC is also 100% at the time T2, so that the voltage deviation is A change state can be grasped. According to this configuration, the SOC standard is set to be the same, and a more accurate change state of the voltage deviation can be grasped.

In addition, when ten battery modules 10 are included in the battery system, and some battery modules 10 of the ten battery modules 10 are installed at different times to provide a battery system, The installation time, that is, the first time point T1 may be set differently.

For example, it is assumed that the first battery system is installed in January 2020, and at this time, the battery system includes six modules (Module 1 to 6). Then, in June 2020, it is assumed that the other four modules (Module 7 to 10) are added and a total of ten battery modules 10 are installed in the battery system. In this case, for each battery module 10 , a first time point T1 may be set based on an installation time point. That is, for Modules 1 to 6, January 2020 may be set as the first time point T1, and for Modules 7 to 10, June 2020 may be set as the first time point T1.

In this case, the diagnostic unit 300, for Modules 1 to 6, may consider the voltage deviation calculated by the deviation calculating unit 200 at the time of installation in January 2020 as the voltage deviation at the first time point T1. . In addition, the diagnostic unit 300, for Modules 7 to 10, may consider the voltage deviation calculated by the deviation calculating unit 200 at the time of installation in June 2020 as the voltage deviation at the first time point T1.

As such, even if the first time point T1 is different because the installation time is different among at least some of the battery modules 10 among the plurality of battery modules 10 , the second time point T2 may be set to be the same.

For example, in the case of the embodiment, even if the first time point T1 between the two groups is different from among Modules 1 to 10, the second time point T2 may all be set to be the same as January 2021. .

According to this configuration of the present invention, even if there is a difference in the installation timing between the plurality of battery modules 10, the calculation timing of the voltage deviation only changes at the initial installation time, and thereafter, for each battery module 10, the voltage deviation There is no need to manage the calculation timing differently. That is, since the voltage deviation can be calculated at the same time point T2 for all battery modules 10 from time points after the first point, the defective module can be easily diagnosed regardless of the installation time point of the battery module 10 . there is. Accordingly, it is possible to diagnose a defective module by considering the change state of the voltage deviation without considering the usage period of each battery module 10 .

Moreover, during operation of the battery system, some battery modules 10 may be replaced due to a cause such as a failure. According to one aspect of the present invention, when some battery modules 10 are replaced, the first time point T1 is set based on the replacement time for the replaced module, and for the remaining modules, the first time point is set based on the initial installation time. The first time point T1 may be set as .

For example, it is assumed that the first battery system is installed in January 2020, and at this time, the battery system includes 10 modules (Module 1 to 10). And, it is assumed that while operating the battery system, Module 10 malfunctioned in August 2021, and Module 10 was replaced with Module 11. At this time, for Module 11, August 2021 is set as the first time point (T1), and for the other 9 modules (Module 1 to 9), January 2020, the initial installation time, is set as the first time point (T1). can be set.

In this situation, the second time point T2 may be set the same for all the battery modules 10 irrespective of whether or not they are replaced. For example, in the above embodiment, the second time point T2 of both Modules 1 to 9 and Module 11 may be equally set to January 2022.

Accordingly, in the case of Modules 1 to 9, the diagnostic unit 300 may determine a state changed from the voltage deviation of January 2020 to the voltage deviation of January 2022. In addition, the diagnostic unit 300 may grasp a state changed from the voltage deviation in August 2021 to the voltage deviation in January 2022, with respect to Module 11 . In addition, by comparing the voltage deviation change state of each module, a defective module in the battery system can be diagnosed.

As such, according to this aspect of the present invention, even if some battery modules 10 are replaced, the first time point T1 is set differently only for the corresponding battery module 10, and the remaining battery modules 10 that are not replaced. As for the first time point T1, the first time point T1 may be maintained. That is, when some battery modules 10 are replaced, management of other battery modules 10 (in particular, calculation of voltage deviation and understanding of its change state) may not be affected due to such replacement. Therefore, even when some battery modules 10 are replaced, a faulty module diagnosis can be made easily, and the maintenance of the overall battery system can be easily made. Therefore, only for the battery module 10 that has been replaced, only the voltage deviation at the time of the initial replacement is required, and thereafter, the defective module can be diagnosed by identifying the change state of the voltage deviation regardless of whether the replacement is made or the period of use.

In particular, in the case of a power storage system (ESS), since a myriad of battery modules 10 are included and are often used for a long period of time, replacement and repair of the battery module 10 may occur frequently. However, according to the aspect of the present invention, even if some battery modules 10 are replaced, since the calculation of voltage deviation for other battery modules 10 and understanding of the change state are not affected, the maintenance of the power storage system is reduced The advantage of being easily accomplished can be further improved.

As shown in FIG. 1 , the battery diagnosis apparatus according to an embodiment of the present invention may further include a memory unit 400 .

The memory unit 400 may store programs and data necessary for the voltage measuring unit 100 , the deviation calculating unit 200 , and/or the diagnosis unit 300 to perform its functions. That is, the memory unit 400 stores data required for each component of the battery system diagnosis apparatus according to an embodiment of the present invention to perform an operation and function, or data generated in the process of performing a program or operation and function. can For example, the memory unit 400 may store the voltage deviation at the first time point T1 , particularly at the installation time point of each battery module 10 .

The memory unit 400 is not particularly limited in its type as long as it is a known information storage means capable of writing, erasing, updating, and reading data. As an example, the information storage means may include RAM, flash memory, ROM, EEPROM, registers, and the like. Also, the memory unit 400 may store program codes in which processes executable by the voltage measuring unit 100 , the deviation calculating unit 200 , and/or the diagnosis unit 300 are defined.

The diagnosis unit 300 may be configured to calculate a deviation ratio of voltage deviation over time for each battery module 10 . That is, the diagnosis unit 300 may calculate a ratio of the voltage deviation at the second time point T2 to the voltage deviation at the first time point T1 as a deviation ratio. Also, the diagnosis unit 300 may be configured to diagnose a defective module using the calculated deviation ratio. This will be described in more detail with reference to FIG. 3 .

3 is a table schematically illustrating a configuration in which a deviation ratio of voltage deviations of a plurality of battery modules 10 is calculated by the diagnosis unit 300 according to an embodiment of the present invention.

Referring to FIG. 3 , ten battery modules 10 ( Modules 1 to 10 ) are included in the battery system. In addition, the voltage deviation at the first time point T1 and the voltage deviation at the second time point T2 are described for each battery module 10 . This voltage deviation may be calculated by the deviation calculating unit 200 .

The diagnosis unit 300, for each battery module 10, a voltage deviation at a relatively recently calculated second time point T2, a past time point (for example, the installation time of each battery module 10) By dividing by the voltage deviation at the first time point T1 , the change ratio of the voltage deviation for each battery module 10 may be calculated.

For example, in the case of Module 1, since the voltage deviation at time T2 is 18 mV and the voltage deviation at time T1 is 15 mV, the deviation ratio (deviation ratio) can be calculated as 1.20 as 18/15. As another example, in the case of Module 4, since the voltage deviation at time T2 is 24 mV and the voltage deviation at time T1 is 14 mV, the deviation ratio can be calculated as 1.71 as 24/14. In addition, other battery modules 10 may also calculate the deviation ratio in the same manner.

That is, the deviation ratio of each battery module 10 may be calculated in the following manner.

Deviation ratio = voltage deviation at time T2/voltage deviation at time T1

And, the diagnosis unit 300 may diagnose the defective module through the deviation ratio calculated for each battery module 10 as described above. For example, in the embodiment of FIG. 3 , the diagnosis unit 300 may diagnose Module 4 having the largest deviation ratio (1.71) as a defective module.

According to this embodiment of the present invention, the diagnosis of the defective module can be made simply and quickly. In particular, in the case of the embodiment of the present invention, a defective module is not diagnosed only with a voltage deviation at a certain point in time T2, and by taking the voltage deviation of the past time point T1 into consideration, normal degradation and abnormal degradation are easier can be distinguished

For example, in the embodiment of FIG. 3 , the voltage deviation at time T2 is greater in Module 4 of 24 mV and Module 9 of 25 mV. However, according to the embodiment of the present invention, it is possible to diagnose Module 4 as a bad module without diagnosing Module 9 as a bad module. In the case of Module 9, it can be said that the voltage deviation at T1 was 19 mV, which was higher than that of Module 4. For example, in the case of Module 9, since it was installed in the battery system with a high voltage deviation from the beginning, even if the voltage deviation at the time T2 is calculated to be relatively high, it can be said that the degradation rate or the degradation rate itself is not high. In particular, in the case of a power storage system, battery modules 10 having various performances may be installed together, or a recycled battery module 10 may be installed. In this case, there may be a difference in voltage deviation between the battery modules 10 from the time of initial installation in the battery system. In the present invention, in consideration of such a difference, the battery module 10 that is relatively deteriorated can be diagnosed as a bad module without diagnosing the bad module with the absolute value of the voltage deviation at a specific time point.

That is, according to the exemplary configuration of the present invention, a defective module is not determined by comparing the magnitude of the voltage deviation at any one time point, but the voltage deviation at at least two time points is looked at, and the change of the voltage deviation at the two time points is not determined. Based on the ratio, a bad module can be diagnosed. For example, in the exemplary configuration of FIG. 3 , the diagnostic unit 300 may determine the deviation ratio of the voltage deviation at the time T2 to the voltage deviation at the time T1, and diagnose the defective module based on the deviation ratio. .

The diagnosis unit 300 may select the battery module 10 having the highest deviation ratio among the deviation ratios of each battery module 10 . For example, in the embodiment of FIG. 3 , by comparing each deviation ratio of Modules 1 to 10, Module 4 having a deviation ratio of 1.71 may be selected.

Furthermore, the diagnosis unit 300 may diagnose the module having the highest deviation ratio in the entire battery module 10 (Module 4 in the embodiment of FIG. 3 ) as a defective module. In this case, the diagnosis unit 300 may be configured to determine whether the deviation ratio determined to be the highest is equal to or greater than a reference value, and diagnose the battery module 10 as a defective module only when the deviation ratio is equal to or greater than the reference value.

In addition, the diagnosis unit 300 is configured to derive the ratio of the deviation ratio of the voltage deviation calculated for each battery module 10 to the deviation ratio of the voltage deviation calculated for the other battery modules 10 as a relative ratio. can be configured. In addition, the diagnosis unit 300 may be configured to diagnose a defective module by comparing the relative ratios derived for each battery module 10 with each other. This will be described in more detail with reference to FIG. 4 .

FIG. 4 is a table showing the relativization ratios for a plurality of battery modules 10 derived by the diagnosis unit 300 according to an embodiment of the present invention.

Referring to FIG. 4 , the deviation ratio for each battery module 10 is indicated, which is the same as the deviation ratio described in FIG. 3 . In addition, when the deviation ratio between the time T1 and the time T2 is calculated for each battery module 10 in this way, the diagnosis unit 300 may compare with the deviation ratio for other battery modules 10 . The deviation ratio of the voltage deviation can be calculated. In FIG. 4 , the deviation ratio of the voltage deviation with respect to the other battery modules 10 is displayed as an average ratio.

Here, the items displayed as the average ratio may not be set identically to each other for each battery module 10 . In particular, the average ratio for each battery module 10 may be an average value of the remaining battery modules 10 except for each battery module 10 . For example, the average ratio of Module 5 can be said to be the average value of the deviation ratio of Modules 1 to 4 and the deviation ratio of Modules 6 to 10. As another example, the average ratio of Module 10 can be said to be the average value of the deviation ratios of Modules 1 to 9. Accordingly, between the battery modules 10 having different deviation ratios, the average ratio may also be different.

In addition, when the average ratio is calculated for each battery module 10 as described above, the diagnosis unit 300 may derive a relative ratio using the average ratio and the deviation ratio. In particular, the diagnosis unit 300 may derive the relative ratio by dividing the deviation ratio of each battery module 10 by the average ratio of each battery module 10 .

For example, as shown in FIG. 4 , in the case of Modules 1 to 3, since the deviation ratio is 1.20 and the average ratio is 1.25, the relativization ratio can be derived as 0.96 as 1.20/1.25. And, in the case of Module 4, since the deviation ratio is 1.71 and the average ratio is 1.19, the relativization ratio can be derived as 1.44. As such, when the relative ratio for all battery modules 10 is derived, the diagnosis unit 300 may be configured to diagnose a defective module by comparing the relative ratio of each battery module 10 with each other.

In particular, the diagnosis unit 300 may be configured to select the battery module 10 having the largest relative relativization ratio and diagnose it as a defective module.

For example, in the embodiment of FIG. 4 , the diagnosis unit 300 may compare the relativization ratios of all battery modules 10 with each other, and determine the highest relativization ratio as 1.44 of Module 4 . And, based on this determination, the diagnosis unit 300 may diagnose Module 4 as a defective module.

According to this embodiment of the present invention, defective modules can be simply and clearly selected. That is, according to the above configuration, a defective module can be clearly diagnosed only by comparing the sizes of the counterpart modules.

In particular, according to the above configuration, the possibility of defectiveness of the corresponding module can be easily grasped only by the absolute value of the relativization ratio. For example, when the value of the relativization ratio is greater than 1.0, it is possible to diagnose as a bad module or a warning module (a module with a high probability of progressing to a bad module).

Moreover, the diagnosis unit 300 may be configured to determine whether the derived relative ratio of the selected battery module 10 exceeds a reference ratio. In addition, the diagnosis unit 300 may be configured to diagnose the selected battery module 10 as a defective module when it is determined that the derived relative ratio exceeds the reference ratio. Here, the reference ratio may be stored as a preset value to be compared with the relative ratio, and may be stored in the memory unit 400 or the like, and may be referred to as a reference value or range for diagnosing a defective module.

For example, when the reference ratio is set to 1.3, the diagnosis unit 300 may detect that the relative ratio (1.44) of Module 4, which is the battery module 10 having the largest relative ratio in FIG. 4 , exceeds the reference ratio (1.3). can be judged whether And, when the relative ratio of Module 4 exceeds the reference ratio, the diagnosis unit 300 may diagnose Module 4 as a defective module. On the other hand, when the relativization ratio of Module 4 is 1.25, the diagnosis unit 300 may not diagnose Module 4 as a bad module even if it is derived with the largest relativization ratio.

According to this configuration, it is easy to predict how different the specific battery module 10 is in the deterioration state or the possibility of failure compared to other battery modules 10 .

In addition, according to the above-described configuration, for all the battery modules 10 , the difference in the degradation rate between each battery module 10 can be easily predicted as a whole. For example, in the embodiment of Figure 4, since only the relativization ratio of Module 9 with Module 4 is confirmed to exceed 1.0, the diagnostic unit 300 sees that there is a defective possibility only for Module 4 and Module 9, and these Only modules can be checked for defects in more depth.

In particular, the diagnosis unit 300 may be configured to compare and review a warning rate, which is a range different from the reference rate, with a relative rate. Here, the warning rate may be set to a value or range lower than the reference rate. For example, when the reference ratio is set to 1.3 as in the above embodiment, the warning ratio may be set to 1.0, which is lower than this.

In this situation, the diagnosis unit 300 may be configured to separately store and manage the battery module 10 having a higher than the warning ratio as a warning module, although it is not determined as a defective module because the relative ratio is lower than the reference ratio.

For example, in the exemplary configuration of FIG. 4 , as in the previous embodiment, when the reference ratio is 1.3 and the warning ratio is preset to 1.0, the diagnostic unit 300 displays Module 4 in which the relativization ratio is higher than the reference ratio (1.3). can be diagnosed as a bad module. In addition, the diagnosis unit 300 may diagnose Module 9, in which the relativization ratio is not higher than the reference ratio (1.3) but higher than the warning ratio (1.0), as a warning module.

In addition, the diagnosis unit 300 regards the battery module 10 diagnosed as a warning module as a module that is not currently defective but has a possibility of failure in the future, and stores this information in the memory unit 400 , etc. It can be configured to be managed separately.

Here, when there is the battery module 10 diagnosed as the warning module, the diagnosis unit 300 may adjust a cycle for the next diagnosis time point. In particular, when there is a battery module 10 diagnosed as a warning module, the diagnosis unit 300 may be configured to shorten a period for a next diagnosis time.

For example, in the battery system diagnosis apparatus according to the present invention, each time one year elapses from the time the first battery module 10 is installed, the voltage is measured, the voltage deviation is calculated, and the change state of the voltage deviation is compared. By doing so, a bad module can be diagnosed. However, as in Module 9 of the previous embodiment, when there is a battery module 10 that is not diagnosed as a bad module but is diagnosed as a warning module, the diagnosis unit 300 may shorten the next diagnosis cycle to 6 months. .

More specifically, for the battery system installed in January 2020, if the defective module is configured to be diagnosed every first year, the battery module 10 diagnosed as a warning module at the time of the first diagnosis in January 2021 is included. Assume there is In this case, the next secondary diagnosis may be set to July 2021 instead of January 2022. Accordingly, the diagnostic unit 300 controls the voltage measuring unit 100 and the deviation calculating unit 200 in July 2021 so that the voltage is measured for each battery module 10 and the voltage deviation is calculated, so that the failure Allows the module to be diagnosed.

According to this configuration of the present invention, when there is a battery module 10 that is not diagnosed as a bad module but is highly likely to be degraded into a bad module, more rapid diagnosis can be made. Accordingly, when a defective module occurs, a faster response can be made.

Also, the diagnosis unit 300 may adjust a cycle for the next diagnosis time based on the number of battery modules 10 diagnosed as warning modules. In particular, the diagnosis unit 300 may be configured such that as the number of battery modules 10 diagnosed with the warning module increases, the period for the diagnosis time becomes shorter.

For example, when the number of battery modules 10 diagnosed with the warning module is one, the diagnosis unit 300 adjusts the period for the diagnosis time to 6 months so that the next faulty module diagnosis time of the battery system is It can be done after 6 months. And, when the number of battery modules 10 diagnosed as warning modules is two, the diagnosis unit 300 adjusts the period for the diagnosis time to 3 months, so that the diagnosis time for the next defective module of the battery system is 3 months can be done later.

According to this configuration of the present invention, as the number of battery modules 10 that are highly likely to be degraded into defective modules increases, the performance of the entire battery system can be greatly affected, so that more rapid diagnosis and response are possible. Accordingly, in this case, it is possible to prevent problems such as shutdown of the entire battery system, in which use is not possible.

Also, the diagnosis unit 300 may adjust a reference ratio with respect to the battery module 10 diagnosed as a warning module. In particular, the diagnosis unit 300 may set a low reference ratio for the battery module 10 diagnosed as a warning module in the previous diagnosis, unlike other battery modules 10 .

For example, in a battery system that includes Modules 1 to 10 and the reference ratio is set to 1.3 in principle, if Module 5 is diagnosed as a warning module, for Module 5 diagnosed as a warning module, the reference ratio at the next diagnosis is 1.2 can be lowered to In addition, for the other battery modules 10 except for Module 5, the reference ratio may be maintained at 1.3 during the next diagnosis. Accordingly, with respect to the battery module 10 diagnosed as the warning module in the previous diagnosis, the probability of being diagnosed as a bad module may be higher than that of other battery modules 10 .

According to this configuration of the present invention, with respect to a module having a high probability of failure, by lowering the criterion for determination of failure, it is possible to more easily diagnose whether or not there is a failure. In particular, when there is no significant numerical difference between some battery modules 10, the battery module 10 diagnosed as a warning module in the previous diagnosis may be more reliably diagnosed as a bad module.

For example, with respect to the battery module 10 determined as a warning module in the secondary diagnosis, even if the relativization ratio at the time of the tertiary diagnosis is slightly lower than that of other battery modules 10, due to the history determined as a warning module in the past , the probability of failure may be higher. Therefore, according to the above-described configuration, it is possible to more reliably diagnose the battery module 10 having a high possibility of failure.

Also, the diagnosis unit 300 may be configured to diagnose a defective module based on the number of warning diagnoses with respect to the battery module 10 diagnosed as a warning module. This will be described in more detail with reference to FIG. 5 .

5 is a table schematically illustrating a configuration in which a bad module and a warning module are diagnosed by the diagnostic unit 300 according to an embodiment of the present invention.

Referring to FIG. 5 , in three diagnoses of the primary diagnosis, the secondary diagnosis, and the tertiary diagnosis, among the various battery modules 10 included in the battery system, the diagnosis unit 300 selects a bad module or a warning module. Identification information of the diagnosed module is described. Such information may be stored in the self-memory of the diagnosis unit 300 or the memory unit 400 . Here, the first to third diagnosis times may be referred to as points in time when a predetermined period has elapsed from the point in time when the battery system is installed. For example, if the initial installation time of the battery system is January 2020, diagnosis can be made in the form of primary diagnosis, secondary diagnosis, tertiary diagnosis, ... every year after that. there is. In this case, the change state may be diagnosed based on the voltage deviation at the time of initial installation, not only at the time of the first diagnosis, but also at the time of the second diagnosis and the time of the third diagnosis, etc. at each diagnosis time.

More specifically, during the first diagnosis, Module 4 was diagnosed as a bad module and Module 9 was diagnosed as a warning module. In this case, the module 4 may be removed from the battery system due to discontinuation of use, and replaced with another battery module 10 . And, Module 9 can continue to be used in the battery system.

Next, in the second diagnosis, Module 9 and Module 10 were diagnosed as warning modules, and in the third diagnosis, Module 7, Module 9 and Module 10 were diagnosed as warning modules. As such, when the first to third diagnostics are diagnosed as the warning module, the battery module 10 diagnosed as the warning module at the time of the corresponding diagnosis is not determined as a defective module and can be used continuously.

However, the diagnosis unit 300 may diagnose whether there is a defect in consideration of the number of times of diagnosis of the warning module. For example, in the embodiment of FIG. 5 , up to the third diagnosis, it can be seen that Module 9 is diagnosed three times with the warning module, and Module 10 is diagnosed twice. Accordingly, in the fourth diagnosis, the diagnosis unit 300 may diagnose whether the modules diagnosed as the warning module are defective based on different criteria according to the number of warnings.

In particular, the diagnosis unit 300 may configure different reference ratios for modules diagnosed as a warning module according to the number of warnings. For example, the diagnosis unit 300 may be configured such that the reference ratio decreases as the number of times of diagnosis of defective modules increases.

For example, in the embodiment of FIG. 5 , the diagnostic unit 300 sets the reference ratio to 1.2 for Module 9 diagnosed three times with the warning module in the first to third diagnostic processes, and sets the reference ratio to 1.2 with the warning module twice. It can be configured to set the reference ratio to 1.25 for the diagnosed Module 10, and to set the reference ratio to 1.3 for Module 7 diagnosed once with the warning module. Therefore, in the fourth diagnosis, the diagnostic unit 300 diagnoses as a bad module when the relativization ratio exceeds 1.2 for Module 9, and diagnoses it as a bad module when the relativity ratio exceeds 1.25 for Module 10, For 7, if the relativization ratio exceeds 1.3, it can be diagnosed as a bad module.

According to this configuration of the present invention, since the reference ratio is adaptively changed according to the number of diagnoses of the warning module, the failure diagnosis of the battery module 10 can be made more reliably.

Also, the diagnosis unit 300 may be configured to change the reference ratio according to the usage period or usage of the battery system. In particular, the diagnosis unit 300 may be configured such that the reference ratio decreases as the period of use of the battery system increases or the amount of use of the battery system increases.

For example, the diagnosis unit 300 may set the reference ratio to be 1.25 when 5 years have passed since the initial installation of the battery system, and set the reference ratio to be 1.20, which is lower when 10 years have passed since the initial installation of the battery system. can

According to this embodiment of the present invention, as the battery system ages, the possibility of deterioration or failure of the battery module 10 included therein increases, so that the defective module can be more reliably diagnosed. In addition, according to this embodiment, due to the overall deterioration of the battery system, a problem that a defective module that is difficult to use among several battery modules 10 is not easily discriminated can be reduced.

Also, as shown in FIG. 1 , the battery system diagnosis apparatus according to the present invention may further include a notification unit 500 .

The notification unit 500 may be configured to deliver a diagnosis result by the diagnosis unit 300 to a user or the like. For example, the notification unit 500 may include a display monitor, a speaker, a warning lamp, and the like, and display the diagnosis to the user in various ways, such as visual and auditory methods.

The battery system diagnosis apparatus according to the present invention may be applied to a power storage system. That is, the power storage system according to the present invention may include the battery system diagnosis apparatus according to the present invention. In addition, the power storage system according to the present invention may further include components typically included in the power storage system.

Also, the apparatus for diagnosing a battery system according to the present invention may be applied to a battery pack. That is, the battery pack according to the present invention may include the battery system diagnosis apparatus according to the present invention. In addition, the battery pack according to the present invention may further include components normally included in the battery pack. For example, the battery pack according to the present invention may further include electronic components such as a current sensor, a relay, a fuse, or control devices such as a BMS.

Also, the apparatus for diagnosing a battery system according to the present invention may be applied to a vehicle, particularly an electric vehicle. That is, the vehicle according to the present invention may include the battery system diagnosis apparatus according to the present invention. In addition, the vehicle according to the present invention may further include components such as a vehicle body, a motor, and a drive shaft, which are typically included in the vehicle.

Meanwhile, in this specification, the term '~bu' is used, such as 'cell voltage measuring unit 100', 'deviation calculating unit 200', and 'diagnosing unit 300', and these components must be physically It can be understood as functionally differentiated elements rather than separated elements. For example, each component may be selectively integrated with other components or each component may be divided into sub-components for efficient execution of control logic(s). In addition, it is apparent to those skilled in the art that even if each component is integrated or divided, if the same function can be recognized, it should be interpreted that the integrated or divided components are also within the scope of the present application.

As described above, although the present invention has been described with reference to limited embodiments and drawings, the present invention is not limited thereto, and the technical idea of the present invention and the following by those of ordinary skill in the art to which the present invention pertains. Of course, various modifications and variations are possible within the scope of equivalents of the claims to be described.

10: battery module
100: voltage measuring unit
200: deviation calculator
300: diagnostic unit
400: memory unit
500: notification unit

Claims (10)

An apparatus for diagnosing a battery system including a plurality of battery modules, the apparatus comprising:
a voltage measuring unit configured to measure voltages of a plurality of battery cells included therein for each of the battery modules;
a deviation calculating unit configured to calculate a voltage deviation between a plurality of battery cells included therein, for each of the battery modules, based on a result measured by the voltage measuring unit; and
A diagnosis unit configured to diagnose a defective module by comparing the change state of the voltage deviation of each battery module calculated by the deviation calculating unit
Battery system diagnostic device comprising a. According to claim 1,
The deviation calculating unit is configured to calculate a voltage difference between the highest cell voltage and the lowest cell voltage in each battery module as a voltage deviation of the corresponding battery module. According to claim 1,
The diagnosis unit is configured to diagnose the defective module by comparing the change state of the voltage deviation of each battery module measured and calculated at two different time points. 4. The method of claim 3,
The two different time points include a time point at which the battery module is installed and a time point after a predetermined period has elapsed from the time of installation. 5. The method of claim 4,
The diagnosis unit is configured to calculate a deviation ratio of voltage deviation over time for each battery module and diagnose a defective module using the calculated deviation ratio. 6. The method of claim 5,
The diagnosis unit derives a ratio of the deviation ratio of the voltage deviation calculated for each battery module to the deviation ratio of the voltage deviation calculated for the other battery modules as a relative ratio, and compares the relative ratio derived for each battery module with each other. A battery system diagnostic device, characterized in that configured to diagnose a bad module by comparison. 7. The method of claim 6,
The diagnosis unit is configured to select a battery module having the largest relative relativization ratio and diagnose it as a defective module. 8. The method of claim 7,
The diagnosis unit is configured to determine whether the derived relative ratio of the selected battery module exceeds a reference ratio, and if it exceeds the reference ratio, diagnose the selected battery module as a defective module . A power storage system comprising the battery system diagnostic device according to any one of claims 1 to 8. A battery pack comprising the battery system diagnostic device according to any one of claims 1 to 8.

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