Method and device for diagnosing defective assembly of battery pack

Abstract

To provide a method and a device thereof for diagnosing defective assembly of a battery pack.SOLUTION: A method for diagnosing defective assembly of a battery pack includes: a step of calculating an internal resistance value of a battery module which is provided in a battery pack and contains a plurality of battery cells; a step of calculating an internal resistance value of a BCU (battery control unit) which is provided in the battery pack and controls electric charge / discharge of the battery module; and a step of diagnosing defective assembly of the battery pack by comparing a first voltage value of the battery pack calculated based on the internal resistance value of the battery module and the internal resistance value of the BCU, and a second voltage value being a measured voltage value of the battery pack.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a method and an apparatus for diagnosing assembly defects in a battery pack, and more specifically, to a method, computer program, and an apparatus for diagnosing assembly defects in a battery that can effectively diagnose assembly defects in the process of diagnosing assembly defects in a battery pack. [Background technology]

[0002] Recently, the demand for portable electronic products such as laptops, video cameras, and mobile phones has increased dramatically, and the development of energy storage batteries, robots, satellites, etc. has been fully underway. As a result, research into high-performance secondary batteries that can be repeatedly charged and discharged is being actively conducted.

[0003] Currently, the secondary batteries that are commercially available include nickel-cadmium batteries, nickel-metal hydride batteries (NiMH), nickel-zinc batteries, and lithium secondary batteries. Of these, lithium secondary batteries are attracting attention due to their advantages over nickel-based secondary batteries, such as almost no memory effect, freedom in charging and discharging, extremely low self-discharge rate, and high energy density.

[0004] In particular, as carbon energy is gradually depleted and environmental concerns are growing, the demand for hybrid and electric vehicles is gradually increasing worldwide, including the United States, Europe, Japan, and Korea. Hybrid and electric vehicles use the charging and discharging energy of a battery pack to obtain vehicle driving force, and have been well received by many consumers because they are more fuel efficient and do not emit pollutants or emit less pollutants than vehicles that use only engines. Therefore, more attention and research is being focused on vehicle batteries, which are a core component of hybrid and electric vehicles.

[0005] A battery pack includes various components including a battery module including a plurality of battery cells. In addition, the battery module and the components are connected to each other by welding, bolting, connecting, etc. during assembly, and therefore assembly defects may occur during the connection. Summary of the Invention [Problem to be solved by the invention]

[0006] The problem to be solved by the present invention is to overcome the above-mentioned problems, and to provide a method, computer program, and device for diagnosing battery assembly defects that can effectively diagnose assembly defects in the process of diagnosing assembly defects in a battery pack.

[0007] However, such assignments are illustrative and are not intended to limit the scope of the invention. [Means for solving the problem]

[0008] As a technical means for achieving the above-mentioned technical object, there is provided a method for diagnosing assembly defects in a battery pack, the method including the steps of: calculating an internal resistance value of a battery module provided in the battery pack and including a plurality of battery cells; calculating an internal resistance value of a BCU (battery control unit) provided in the battery pack and controlling charging and discharging of the battery module; and comparing a first voltage value of the battery pack calculated based on the internal resistance value of the battery module and the internal resistance value of the BCU with a second voltage value which is a measured voltage value of the battery pack, thereby diagnosing assembly defects in the battery pack.

[0009] According to an example, calculating the internal resistance value of the battery module may include obtaining a pre-measured internal resistance value by setting both ends of the battery module as measurement points.

[0010] According to another example, the step of calculating the internal resistance value of the battery module may include a step of calculating the internal resistance value of the battery module based on a change in the internal resistance value due to a battery degradation state that is previously stored using a model of the battery cell.

[0011] According to yet another example, the step of diagnosing a defective assembly of the battery pack includes a step of calculating an internal resistance value of the battery pack by combining an internal resistance value of the battery module, in which a change in internal resistance value due to the battery degradation state is reflected, and an internal resistance value of the BCU based on a current degradation state; a step of multiplying the internal resistance value of the battery pack by a value of a current flowing between both ends of the battery pack to calculate the first voltage value; and a step of comparing the magnitude of the first voltage value with the second voltage value obtained by measuring the voltage between both ends of the battery pack.

[0012] According to yet another example, the step of diagnosing a faulty assembly of the battery pack also includes a step of diagnosing a faulty assembly of the battery pack if the magnitude of the second voltage value is greater than the magnitude of the first voltage value.

[0013] According to yet another example, the step of calculating the internal resistance value of the BCU also includes a step of calculating the internal resistance value of the BCU based on the internal resistance value measured in advance using a measurement point set in advance for each component incorporated and equipped in the BCU.

[0014] As a technical means for achieving the above technical object, a computer program stored on a recording medium is provided for making a computing device execute the above method.

[0015] As a technical means for achieving the above-mentioned technical object, there is provided an apparatus for diagnosing assembly defects in a battery pack, the apparatus including a battery module provided in the battery pack and including a plurality of battery cells, a BCU (battery control unit) provided in the battery pack and controlling charging and discharging of the battery module, and a processor that calculates an internal resistance value of the battery module, calculates an internal resistance value of the BCU, and compares a first voltage value of the battery pack calculated based on the internal resistance value of the battery module and the internal resistance value of the BCU with a second voltage value which is a measured voltage value of the battery pack, and diagnoses assembly defects of the battery pack.

[0016] According to one example, the processor may use both ends of the battery module as measurement points and obtain a pre-measured internal resistance value.

[0017] According to another example, the processor may calculate the internal resistance value of the battery module based on a change in the internal resistance value due to a battery degradation state that is stored in advance using a model of the battery cell.

[0018] According to yet another example, the processor may combine the internal resistance value of the battery module, which reflects the amount of change in internal resistance due to the battery degradation state, with the internal resistance value of the BCU based on the current degradation state, to calculate the internal resistance value of the battery pack, multiply the internal resistance value of the battery pack by the value of the current flowing between both ends of the battery pack to calculate the first voltage value, and compare the magnitude of the first voltage value with the second voltage value obtained by measuring the voltage between both ends of the battery pack.

[0019] According to yet another example, the processor may diagnose that the battery pack is improperly assembled if the magnitude of the second voltage value is greater than the magnitude of the first voltage value.

[0020] According to yet another example, the processor may use pre-established measurement points for each component incorporated in the BCU and calculate the internal resistance value of the BCU based on the pre-measured internal resistance values. Effect of the Invention

[0021] According to the present invention, a method, a computer program, and an apparatus for diagnosing a battery assembly defect that can effectively diagnose an assembly defect in a process of diagnosing an assembly defect in a battery pack can be provided, although it goes without saying that the scope of the present invention is not limited by such effects. [Brief description of the drawings]

[0022] [Figure 1] FIG. 1 is a diagram illustrating a battery pack according to an embodiment of the present invention. [Diagram 2] 1 is an exemplary diagram for explaining a method for diagnosing an assembly error of a battery pack according to an embodiment of the present invention; [Diagram 3] 4 is a flowchart illustrating a method for diagnosing a battery pack assembly error according to an embodiment of the present invention. [Figure 4] 4 is an exemplary diagram illustrating a change in internal resistance value depending on a deterioration state of a battery according to an embodiment of the present invention; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0023] Hereinafter, various embodiments will be described in detail with reference to the accompanying drawings so that a person having ordinary skill in the art to which the present disclosure pertains can easily carry out the present disclosure. However, the technical idea of ​​the present disclosure may be embodied in various forms and is not limited to the embodiments described herein. In the description of the embodiments disclosed herein, if it is determined that a detailed description of a related known technology may make the gist of the technical idea of ​​the present disclosure unclear, the detailed description of the known technology will be omitted. Identical or similar components are denoted by the same reference numerals, and duplicate descriptions thereof will be omitted.

[0024] In this specification, when an element is described as being "connected" to another element, this does not only mean that it is "directly connected" to another element, but also means that it is "indirectly connected" to another element through another element in between. When an element "includes" another element, this does not mean that it excludes other elements in addition to the other elements, but also means that it includes other elements.

[0025] Some embodiments may be described by functional block configurations and various processing steps. Some or all of such functional blocks may be embodied by various numbers of hardware configurations and / or software configurations performing specific functions. For example, the functional blocks of the present disclosure may be embodied by one or more microprocessors or by circuit configurations for a given function. The functional blocks of the present disclosure may be embodied by various programming languages ​​or scripting languages. The functional blocks of the present disclosure may be realized by algorithms executed by one or more processors. The functions performed by the functional blocks of the present disclosure may be performed by multiple functional blocks, or the functions performed by multiple functional blocks in the present disclosure may be performed by one functional block. In addition, the present disclosure may employ conventional techniques for electronic configuration, signal processing, and / or data processing, etc.

[0026] FIG. 1 illustrates a schematic diagram of a battery pack according to one embodiment of the present invention.

[0027] Referring to FIG. 1, a battery pack according to an embodiment of the present invention includes a battery module 110, a processor 150, a memory 160, a voltage measuring unit 120, a current measuring unit 130, and a temperature measuring unit 140.

[0028] The battery module 110 includes a plurality of battery cells 111, which are also rechargeable secondary batteries. For example, the battery cells 111 may include at least one selected from the group consisting of a nickel-cadmium battery, a lead-acid battery, a nickel metal hydride battery (NiMH), a lithium ion battery, a lithium polymer battery, and the like.

[0029] The number and connection manner of the battery cells 111 included in the battery module 110 may be determined based on the amount of power and voltage required for the battery pack. In FIG. 1, the battery cells 111 included in the battery module 110 are illustrated as being connected in series for conceptual purposes only, but the battery cells 111 may be connected in parallel to each other or in series and parallel. In FIG. 1, the battery pack is illustrated as including one battery module 110 for conceptual purposes only, but the battery pack may include multiple battery modules 110 connected in series, in parallel, or in series and parallel. The battery module 110 may include only one battery cell 111.

[0030] The battery module 110 also includes a plurality of battery modules, each of which is formed by a plurality of battery cells 111. The battery pack also includes a pair of pack terminals 101, 102 to which an electrical load or a charging device can be coupled.

[0031] In this specification, the subject of diagnosis for assembly defects is the battery pack, and also is at least one each of the battery modules 110 included in the battery pack.

[0032] The battery pack according to an embodiment of the present invention also includes a switch. The switch may be coupled between the battery module 110 and one of the pack terminals 101, 102 (e.g., pack terminal 101). The switch may be controlled by the processor 150. Although not shown in FIG. 1, the battery pack may further include a battery protection circuit, a fuse, a current sensor, etc.

[0033] An apparatus for diagnosing a battery pack for misassembly, according to one embodiment of the present invention, includes a processor 150 and a memory 160.

[0034] The processor 150 controls the overall operation of the device for diagnosing assembly defects in a battery pack. For example, the processor 150 may be embodied in a form that selectively includes a processor, an application-specific integrated circuit (ASIC), other chipsets, logic circuits, registers, a communication modem, and / or a data processing device known in the art to perform the above-mentioned operations.

[0035] The processor 150 may perform basic arithmetic, logic, and input / output operations, for example, to execute program code stored in memory 160. The processor 150 may store data in the memory 160 or load data stored in the memory 160.

[0036] The memory 160 is a recording medium readable by the processor 150 and may include a random access memory (RAM), a read-only memory (ROM), and a permanent mass storage device such as a disk drive. An operating system (OS) and at least one program or application code may be stored in the memory 160. The memory 160 may store program code or data according to an embodiment of the present invention. For example, the data may include a charge / discharge current, a terminal voltage, and / or a temperature of the battery.

[0037] The memory 160 may store program code and SOC-OCV (open circuit voltage) data for estimating a state of charge (SOC) of the battery using data generated by measuring at least one parameter of the battery module 110. The memory 160 may also store program code or data for estimating a state of health (SOH) of the battery using data generated by measuring at least one parameter of the battery module 110. Here, the SOH of the battery may indicate the state of health of the battery.

[0038] For example, the at least one parameter of the battery module 110 may include a component or variable, such as a terminal voltage of the battery module 110, a charge / discharge current, and / or an ambient temperature.

[0039] The device for diagnosing an assembly defect of a battery pack according to an embodiment of the present invention further includes a voltage measuring unit 120, a current measuring unit 130, and a temperature measuring unit 140 for measuring at least one parameter of the battery module 110. The device for diagnosing an assembly defect of a battery pack further includes a communication module for communicating with other devices such as an electronic control device of a vehicle and a controller of a charging device.

[0040] The voltage measurement unit 120 may be configured to measure the voltage of the battery module 110. For example, as shown in the configuration of FIG. 1, the voltage measurement unit 120 may be electrically connected to both ends of the battery module 110 and / or the battery cell 111. The voltage measurement unit 120 may also be electrically connected to the processor 150 so as to exchange electrical signals. The voltage measurement unit 120 may also measure the voltages across the battery module 110 and / or the battery cell 111 at time intervals under the control of the processor 150 and output a signal indicating the magnitude of the measured voltage to the processor 150. At this time, the processor 150 may determine the voltages of the battery module 110 and / or the battery cell 111 from the signal output from the voltage measurement unit 120. For example, the voltage measurement unit 120 may be embodied using a voltage measurement circuit commonly used in the art.

[0041] Also, the current measuring unit 130 may be configured to measure the current of the battery. For example, the current measuring unit 130 may be electrically connected to a current sensor provided on a charge / discharge path of the battery module 110 and / or the battery cell 111. Also, the current measuring unit 130 may be electrically connected to the processor 150 so as to exchange electrical signals. Also, the current measuring unit 130 may repeatedly measure the magnitude of the charge current or the discharge current of the battery module 110 and / or the battery cell 111 at time intervals under the control of the processor 150, and output a signal indicating the magnitude of the measured current to the processor 150. At this time, the processor 150 may determine the magnitude of the current from the signal output from the current measuring unit 130. For example, the current sensor may be implemented using a Hall sensor or a sense resistor commonly used in the art.

[0042] The temperature measuring unit 140 may be configured to measure the temperature of the battery. For example, as shown in the configuration of FIG. 1, the temperature measuring unit 140 may be connected to the battery module 110 and / or the battery cell 111 and may measure the temperature of the secondary battery included in the battery module 110 and / or the battery cell 111. The temperature measuring unit 140 may be electrically connected to the processor 150 so as to exchange electrical signals. The temperature measuring unit 140 may repeatedly measure the temperature of the secondary battery at time intervals and output a signal indicating the magnitude of the measured temperature to the processor 150. At this time, the processor 150 may determine the temperature of the secondary battery from the signal output from the temperature measuring unit 140. For example, the temperature measuring unit 140 may be implemented using a thermocouple commonly used in the industry.

[0043] The processor 150 may estimate a state of charge (SOC) of the battery module 110 using at least one of a voltage measurement value, a current measurement value, and a temperature measurement value related to the battery module 110 received from the voltage measurement unit 120, the current measurement unit 130, and the temperature measurement unit 140. Here, the SOC may be calculated to a value corresponding to a remaining capacity of the battery module 110 in a range of 0% to 100%. The processor 150 may estimate a state of health (SOH) of the battery module 110 using at least one of a voltage measurement value, a current measurement value, a temperature measurement value, and SOC data related to the battery module 110 received from the voltage measurement unit 120, the current measurement unit 130, and the temperature measurement unit 140. Here, the SOH may be calculated to a value corresponding to a remaining capacity of the battery module 110 in a range of 0% to 100%. For example, the SOC estimation and SOH estimation of the battery according to the present invention may be performed by a known estimation method.

[0044] In one aspect of the present invention, the processor 150 may estimate the SOC of the battery module 110 by integrating the charging current and discharging current of the battery module 110. Here, when charging or discharging of the battery module 110 starts, an initial value of the state of charge may be determined using an open circuit voltage (OCV) of the battery module 110 measured before charging or discharging starts. To this end, the processor 150 may include an SOC-OCV lookup table that defines the state of charge for each open circuit voltage, and may map the state of charge corresponding to the open circuit voltage of the battery module 110 from the lookup table.

[0045] In another aspect of the present invention, the processor 150 may estimate the SOC of the battery module 110 using an extended Kalman filter. The extended Kalman filter refers to a mathematical algorithm that adaptively estimates the state of charge of the secondary battery using the voltage, current, and temperature of the secondary battery.

[0046] The SOC of the battery module 110 may be determined by other known methods capable of estimating the state of charge by selectively utilizing the voltage, current, and temperature of the secondary battery, other than the above-mentioned current integration method or extended Kalman filter.

[0047] FIG. 2 is an exemplary diagram for explaining a method for diagnosing an assembly error of a battery pack according to an embodiment of the present invention.

[0048] 1 and 2, a battery pack according to an embodiment of the present invention includes a battery module 110 and a battery control unit (BCU) 100. For example, as shown in FIG. 2, the BCU 100 includes a processor 150, a contactor, a fuse, and a shunt resistor. However, the present invention is not limited thereto, and the BCU 100 according to an embodiment of the present invention may further include a battery protection circuit, a voltage measurement circuit, a current measurement circuit, a temperature measurement circuit, and the like.

[0049] The battery module 110 according to an embodiment of the present invention is provided in a battery pack and includes a plurality of battery cells 111. The BCU 100 according to an embodiment of the present invention is provided in the battery pack and can control charging and discharging of the battery module 110.

[0050] According to an embodiment of the present invention, the processor 150 may calculate an internal resistance value of the battery module 110. The processor 150 may also calculate an internal resistance value of the BCU 100. The processor 150 may also compare a first voltage value of the battery pack with a second voltage value that is a measured voltage value of the battery pack, and diagnose an assembly error of the battery pack. Here, the first voltage value may be calculated based on the internal resistance value of the battery module and the internal resistance value of the BCU.

[0051] The processor 150 may also set both ends of the battery module 110 as measurement points to obtain a pre-measured internal resistance value.

[0052] Furthermore, the processor 150 can calculate the internal resistance value of the battery module 110 based on the amount of change in the internal resistance value due to the battery degradation state that is stored in advance, using a model of the battery cell 111.

[0053] In addition, the processor 150 can calculate the internal resistance value of the battery pack by combining the internal resistance value of the battery module 110, which reflects the amount of change in the internal resistance value due to the battery degradation state, with the internal resistance value of the BCU 100 based on the current degradation state.

[0054] The processor 150 may also multiply the internal resistance value of the battery pack by the value of the current flowing between both ends of the battery pack to calculate a first voltage value. The processor 150 may also compare the first voltage value with a second voltage value obtained by measuring the voltage between both ends of the battery pack. If the second voltage value is greater than the first voltage value, the processor 150 may diagnose that the battery pack is defective in assembly.

[0055] In addition, the processor 150 may use measurement points set in advance for each component incorporated in the BCU 100, and may calculate the internal resistance value of the BCU 100 based on the internal resistance value measured in advance.

[0056] Since the battery pack is connected by welding, bolting, connecting, etc. during assembly, diagnosis of assembly defects of the connection part is necessary. In this specification, the contact resistance of the contact part during connection may be indicated as an internal resistance. For example, as shown in FIG. 2, a battery module 110 or a battery rack may be provided with 300 battery cells 111. Here, the battery rack may include a plurality of battery modules. Although the battery module 110 including 300 battery cells 111 is described in this specification, the present invention is not limited thereto, and may also be described as a battery rack including a plurality of battery modules.

[0057] For example, when a charging current of 300A flows, if there are 300 battery cells 111 with a voltage of 4V, the sum of the cell voltages may be 1,200V. If the contact resistance 115 of the contact parts where the battery cells 111 are assembled is 0.1mΩ, the total contact resistance is 30mΩ due to the 300 contact parts, and the internal resistance value of the battery module 110 is also 30mΩ. In this case, the voltage measured at the input / output terminals 117, 119 at both ends of the battery module 110 may be 1,209V (1,209V=0.0001x300pointsx300A+1,200V).

[0058] If the contact resistance 115 of a normal contact part without any assembly defects is 0.1 mΩ, then in a normal battery pack, if 300 A flows, a voltage difference of 9 V will occur in the battery module, but if there is an assembly defect in the contact part, a voltage difference of 9 V or more will occur. A contact part with an assembly defect may cause a fire, so it is necessary to detect the assembly defect in advance.

[0059] When the battery is charged and discharged, the voltage value of the total cell voltage and the voltage measurement value of the battery module differ from each other depending on the internal resistance value. For example, the internal resistance value of each component of the battery module and the BCU included in the battery pack may be measured using a measurement point designated in advance. Alternatively, the internal resistance value of each component of the battery module and the BCU included in the battery pack may be stored in advance in a memory.

[0060] For example, as shown in FIG. 2, pre-specified measurement points according to one embodiment of the present invention include input / output terminals 117, 119 at both ends of the battery module 110, input / output terminals 101, 102 of the battery pack, measurement point Rack V+ between the positive input / output terminal 117 of the battery module 110 and the contactor, measurement point Rack P+ between the fuse and the positive input / output terminal 101 of the battery pack, and measurement point Rack V- between the shunt resistor and the negative input / output terminal 102 of the battery pack.

[0061] In addition, in the method for diagnosing an assembly defect of a battery pack according to an embodiment of the present invention, the internal resistance value of each component may be measured using a measurement point designated in advance. Also, the assembly defect of each component may be detected using a voltage value measured at the measurement point designated in advance. For example, the assembly defect of a contactor may be detected using the internal resistance value and the voltage value measured at the measurement point Rack V- and the measurement point Rack P+.

[0062] 3 is a flowchart illustrating a method for diagnosing an assembly error of a battery pack according to an embodiment of the present invention. The method for diagnosing an assembly error of a battery pack according to an embodiment of the present invention may be performed by the processor 150 illustrated in FIG.

[0063] First, referring to FIG. 3, in operation S110, the processor 150 may calculate an internal resistance value of a battery module 110 that is included in a battery pack and includes a plurality of battery cells 111.

[0064] In addition, the processor 150 according to an embodiment of the present invention may acquire a pre-measured internal resistance value by setting both ends of the battery module 110 as measurement points.

[0065] In addition, the processor 150 according to an embodiment of the present invention may calculate the internal resistance of the battery module 110 based on the amount of change in the internal resistance due to the deterioration state of the battery that is stored in advance using a model of the battery cell 111.

[0066] In step S120, the processor 150 may calculate an internal resistance value of the BCU 100 that is provided in the battery pack and controls charging and discharging of the battery module 110.

[0067] According to one embodiment of the present invention, the processor 150 may use pre-established measurement points for each component incorporated in the BCU 100 and calculate the internal resistance value of the BCU 100 based on the pre-measured internal resistance values.

[0068] In step S130, the processor 150 may compare a first voltage value of the battery pack calculated based on the internal resistance value of the battery module 110 and the internal resistance value of the BCU 100 with a second voltage value which is a measured voltage value of the battery pack, and diagnose a defective assembly of the battery pack.

[0069] According to one embodiment of the present invention, the processor 150 can calculate the internal resistance value of the battery pack by combining the internal resistance value of the battery module 110, which reflects the amount of change in the internal resistance value due to the battery degradation state, with the internal resistance value of the BCU 100 based on the current degradation state.

[0070] Furthermore, the processor 150 may multiply the internal resistance value of the battery pack by the value of the current flowing between both ends of the battery pack to calculate a first voltage value, and may compare the magnitude of the first voltage value with a second voltage value obtained by measuring the voltage between both ends of the battery pack.

[0071] Furthermore, the processor 150 according to an embodiment of the present invention may diagnose that there is an assembly defect in the battery pack if the magnitude of the second voltage value is greater than the magnitude of the first voltage value.

[0072] An apparatus for diagnosing defective assembly of a battery pack according to one embodiment of the present invention can diagnose defective assembly of the battery pack by comparing a first voltage value of the battery pack calculated based on the internal resistance value of the battery module 110 and the internal resistance value of the BCU 100 with a second voltage value which is the measured voltage value of the battery pack.

[0073] For example, the first voltage value can be calculated as V1 = |(Q1 x (1 + E) + Q2) x (AB)|. Also, the second voltage value can be calculated as V2 = △V(DC). Here, Q1 = internal resistance value of the battery module, Q2 = internal resistance value of the BCU, A = applied current of the battery pack, B = initial current of the battery pack, V(C) = voltage before application of battery pack current, V(D) = voltage 2 seconds after application of battery pack current, and E = rate of change of internal resistance value due to battery degradation state. Here, E will be explained in detail below.

[0074] In addition, the device for diagnosing assembly defects in a battery pack according to an embodiment of the present invention may diagnose that the battery pack is assembled incorrectly when the second voltage value is greater than the first voltage value, for example, when V2>V1, the battery pack may be diagnosed as assembled incorrectly, and when V2≦V1, the battery pack may be diagnosed as not assembled incorrectly and as normal.

[0075] The device for diagnosing an assembly defect of a battery pack according to an embodiment of the present invention may calculate an internal resistance value of the battery module 110 based on a change in internal resistance value due to a deterioration state of the battery that is stored in advance using a model of the battery cell 111. For example, referring to FIG 4, an exemplary diagram for explaining a change in internal resistance value due to a deterioration state of the battery according to an embodiment of the present invention is shown.

[0076] In order to accurately diagnose an assembly defect in the battery module 110, it is necessary to reflect an increase in the internal resistance value due to a deterioration state of the battery cell 111. The rate of change in the internal resistance value due to the battery deterioration state may be indicated differently for each model of the battery cell 111. In addition, data related to the rate of change in the internal resistance value due to the battery deterioration state for each model of the battery cell 111 may be stored in advance in a memory.

[0077] For example, referring to Fig. 4, the rate of change of the internal resistance value due to the battery charge / discharge cycle is illustrated for battery cell model 1 and battery cell model 2. For example, the battery cycle may be expressed as one cycle in which the SOC is discharged from 100% to 0%. In addition, the more the battery cycle increases, the more the battery deteriorates, so the deterioration state of the battery may be estimated based on the battery cycle.

[0078] For example, referring to Fig. 4, it is shown that the internal resistance value of the battery increases to 130% at 1,500 cycles for battery cell model 2. The rate of increase in the internal resistance value due to the battery cycle increases linearly, so it can be predicted as a trend line.

[0079] In the present invention, the first voltage value is calculated as V1=|(Q1×(1+E)+Q2)×(AB)|, where E represents the rate of change in the internal resistance value due to the battery degradation state. In this case, for battery cell model 2, if the internal resistance value of the battery increases to 130% in the state of 1,500 cycles, the value of E may be 0.3.

[0080] According to the present invention, the internal resistance of the battery is more accurately estimated by applying the increase rate of the internal resistance depending on the deterioration state of the battery, and thus it is possible to more accurately diagnose defective assembly of the battery pack.

[0081] The various embodiments described above are merely examples, and are not to be separated from one another and implemented independently. The embodiments described in this specification may be implemented in a form in which they are combined with one another.

[0082] The various embodiments described above may be embodied in the form of a computer program that can be executed by various components on a computer, and such a computer program may be recorded on a computer-readable medium. In this case, the medium may continuously store the computer-executable program or may temporarily store it for execution or download. The medium may be various recording or storage means in the form of a single or multiple pieces of hardware combined, and is not limited to a medium directly connected to a computer system, but may also be distributed on a network. Examples of the medium include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as compact disc read only memory (CD-ROM) and digital versatile disc (DVD); magneto-optical media such as floptical disks; and media configured to store program instructions, including ROM, RAM, and flash memory. Examples of other media include recording media or storage media managed by app stores that distribute applications, and sites and servers that supply or distribute various other software.

[0083] In this specification, a "module" or "unit" may be a hardware component such as a processor or a circuit, and / or a software component executed by a hardware component such as a processor. For example, a "module" or "unit" may be embodied by a software component, an object-oriented software component, a component such as a class component, and a task component, as well as a process, a function, an attribute, a procedure, a subroutine, a segment of program code, a driver, firmware, microcode, a circuit, data, a database, a data structure, a table, an array, and a variable.

[0084] The above description of the present invention is for illustrative purposes only, and those skilled in the art will understand that the present invention can be easily modified into other specific forms without changing the technical idea or essential features of the present invention. Therefore, the above-described embodiments should be understood to be illustrative in all respects and not limiting. For example, each component described as a single type may be implemented in a distributed form, and similarly, each component described as distributed may be implemented in a combined form.

[0085] The scope of the present invention is indicated by the claims rather than the above detailed description, and all modifications and variations that fall within the meaning, scope, and equivalent concepts of the claims should be construed as being included within the scope of the present invention. [Explanation of symbols]

[0086] 100 BCH 101,102 Pack terminal 110 Battery Module 111 Battery Cell 115 Contact resistance 117,119 Input / Output Terminal 120 Voltage measurement section 130 Current measurement section 130 Temperature measurement section 150 processors 160 Memory

Claims

1. 1. A method for diagnosing a battery pack assembly defect, comprising: calculating an internal resistance value of a battery module including a plurality of battery cells provided in the battery pack; Calculating an internal resistance value of a battery control unit (BCU) provided in the battery pack and controlling charging and discharging of the battery module; a step of comparing a first voltage value of the battery pack calculated based on the internal resistance value of the battery module and the internal resistance value of the BCU with a second voltage value which is a measured voltage value of the battery pack, and diagnosing an assembly defect of the battery pack.

2. The assembly defect diagnosis method of claim 1 , wherein the step of calculating the internal resistance value of the battery module includes the step of acquiring a pre-measured internal resistance value by setting both ends of the battery module as measurement points.

3. 3. The assembly defect diagnosis method of claim 2, wherein the step of calculating the internal resistance value of the battery module includes a step of calculating the internal resistance value of the battery module based on a change in the internal resistance value due to a battery deterioration state that is previously stored using a battery cell model.

4. The step of diagnosing an assembly error of the battery pack includes: calculating an internal resistance value of the battery pack by combining an internal resistance value of the battery module, in which a change in the internal resistance value due to the battery degradation state is reflected, and an internal resistance value of the BCU based on a current degradation state; multiplying an internal resistance value of the battery pack by a value of a current flowing through both ends of the battery pack to calculate the first voltage value; The assembly fault diagnosis method according to claim 3 , further comprising: comparing the magnitude of the first voltage value with the magnitude of the second voltage value obtained by measuring a voltage across the battery pack.

5. 5. The method of claim 4, wherein the step of diagnosing an assembly defect of the battery pack includes the step of diagnosing an assembly defect of the battery pack when the magnitude of the second voltage value is greater than the magnitude of the first voltage value.

6. 2. The assembly defect diagnosis method of claim 1, wherein the step of calculating the internal resistance value of the BCU includes a step of calculating the internal resistance value of the BCU based on the internal resistance value measured in advance using a measurement point set in advance for each component incorporated in the BCU.

7. A computer program stored on a recording medium for causing a computing device to carry out the method according to any one of claims 1 to 6.

8. 1. A device for diagnosing assembly defects in a battery pack, comprising: a battery module provided in the battery pack and including a plurality of battery cells; A battery control unit (BCU) provided in the battery pack for controlling charging and discharging of the battery module; a processor that calculates an internal resistance value of the battery module, calculates an internal resistance value of the BCU, compares a first voltage value of the battery pack calculated based on the internal resistance value of the battery module and the internal resistance value of the BCU with a second voltage value that is a measured voltage value of the battery pack, and diagnoses an assembly defect of the battery pack.

9. The assembly defect diagnosis device according to claim 8 , wherein the processor uses both ends of the battery module as measurement points and obtains a pre-measured internal resistance value.

10. The assembly defect diagnosis device according to claim 9 , wherein the processor calculates the internal resistance value of the battery module based on a change in the internal resistance value due to a battery deterioration state that is stored in advance using a battery cell model.

11. The processor calculates an internal resistance value of the battery pack by combining an internal resistance value of the battery module, in which a change in the internal resistance value due to the battery degradation state is reflected, with an internal resistance value of the BCU based on a current degradation state; multiplying an internal resistance value of the battery pack by a value of a current flowing through both ends of the battery pack to calculate the first voltage value; The assembly defect diagnosis device according to claim 10 , further comprising: a step of comparing a magnitude of the first voltage value with a magnitude of the second voltage value obtained by measuring a voltage across the battery pack.

12. The assembly defect diagnosis device according to claim 11 , wherein the processor diagnoses that there is an assembly defect in the battery pack when the magnitude of the second voltage value is greater than the magnitude of the first voltage value.

13. 9. The assembly defect diagnosis device according to claim 8, wherein the processor uses pre-established measurement points for each component incorporated in the BCU and calculates an internal resistance value of the BCU based on the pre-measured internal resistance values.

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