System and method for diagnosing internal resistance of lithium-ion batteries of kwh class or higher

Abstract

The present invention relates to a system for diagnosing the internal resistance of lithium-ion batteries of a kWh class or higher and, more specifically, to a system and a method for diagnosing the internal resistance of lithium-ion batteries of kWh class or higher in which the state of lithium-on batteries of kWh class or higher for an ESS is diagnosed from an electrical point of view. The present invention comprises: an internal resistance measurement unit for measuring the AC internal resistance of batteries in the frequency domain and setting a reference value of the internal resistance; a battery module-specific state diagnosis unit for evaluating the state of battery modules by using the internal resistance reference value set by the internal resistance measurement unit, and analyzing the deviation in the internal resistance values, thereby identifying battery modules in abnormal states; a module replacement determination unit for performing precise analysis, via electrochemical impedance spectroscopy, of the battery modules classified as being in abnormal states on the basis of the result of internal resistance measurements to determine whether or not to replace the battery modules; and a control unit for monitoring normal and abnormal battery modules by using the result of internal resistance measurements and battery module state diagnosis information. The present invention diagnoses the state of lithium-ion batteries of kWh class or higher for an ESS from an electrical point of view in consideration of the structural characteristics of lithium-ion batteries of kWh class or higher, and can assure improved reliability of internal resistance measurements and safety of measurement workers due to remote measurements.

Description

System and method for diagnosing internal resistance of lithium-ion batteries of KWH or higher

[0001] The present invention relates to a system for diagnosing the internal resistance of a kWh or higher lithium-ion battery, and more particularly, to a system for diagnosing the internal resistance of a kWh or higher lithium-ion battery for ESS and a method therefor for diagnosing the electrical status of a kWh or higher lithium-ion battery for ESS.

[0002] Currently, diagnostic systems related to the use of lithium-ion battery-based ESS are being installed and operated in large quantities exceeding kWh for purposes such as linking with renewable energy, frequency regulation, and peak load reduction.

[0003] Measuring internal resistance is one of the key factors in determining the health of a lithium-ion battery. Methods for measuring internal resistance include Direct Current Internal Resistance (DCIR), Alternating Current Internal Resistance (ACIR), and Electrochemical Impedance Spectroscopy (EIS). Each of these methods has its own advantages and disadvantages. In particular, it is difficult to capture the series-parallel structural characteristics of lithium-ion batteries of the kWh or higher class and ensure measurement reliability using a single, existing method.

[0004] The Direct Current Inductive Resistive Resistance (DCIR) method calculates the battery's internal resistance through a ratio of a given voltage and current, making it suitable for battery manufacturing at the cell and module levels. However, lithium-ion battery-based ESS systems require a series / parallel battery configuration and large capacity (kWh or higher), along with auxiliary equipment such as charging and discharging facilities to match the high capacity. The Direct Current Inductive Resistive Resistance (DCIR) method is not applicable to ESS systems connected to the power grid. Since DCIR measurements require the ESS equipment to be in operation (charge and discharge), equipment problems may arise.

[0005] The ACIR method currently measures internal resistance centered on a specific frequency range (1 kHz). While simple, the measurement itself lacks accuracy. In the field, lithium-ion battery-based ESS capacities range from one million to ten thousand kWh, with diverse electrical circuits. Therefore, simply interpreting internal resistance measurements based on a specific frequency range can be problematic. Furthermore, utilizing traditional ACIR-based measurement methods requires direct measurement of hundreds of modules, which requires considerable time and results in discrepancies between individual measurements.

[0006] Electrochemical impedance spectroscopy (EIS) is used for single-cell condition analysis. While EIS offers precision analysis capabilities, its measurement speed is slow due to variations in current and voltage application methods and its ability to analyze liquid and solid components. Currently, applying EIS to large-capacity lithium-ion batteries requires separate applications (measurement jigs, power system data analysis, etc.), and related equipment is currently unavailable.

[0007] Therefore, a diagnostic system for determining the status of lithium-ion batteries requires an internal resistance measurement and interpretation method that reflects the field characteristics of lithium-ion battery-based ESS, and technology is needed to ensure measurement reliability and protect equipment and human bodies in fields where large-capacity (kWh to MWh) lithium-ion batteries are installed.

[0008] [Prior Art Literature]

[0009] [Patent Document]

[0010] Korean Patent Publication No. 10-2022-0104949 (July 26, 2022)

[0011] The present invention aims to solve the above-described problem by proposing a kWh-class or higher lithium-ion battery internal resistance diagnosis system and method for diagnosing the electrical state of a kWh-class or higher lithium-ion battery for ESS by reflecting the structural characteristics of the kWh-class or higher lithium-ion battery.

[0012] A system for diagnosing the internal resistance of a kWh or higher lithium-ion battery according to one embodiment of the present invention includes an internal resistance measuring unit that measures the AC internal resistance of the battery in a frequency domain and sets a reference value of the internal resistance, a battery module-specific status diagnosis unit that evaluates the status of a battery module using the internal resistance reference value set by the internal resistance measuring unit and analyzes a deviation of the internal resistance value to identify an abnormal battery module, a module replacement determination unit that performs a precise analysis using electrochemical impedance spectroscopy on a battery module classified as being in an abnormal state based on the internal resistance measurement result to determine whether to replace the battery module, and a control unit that performs monitoring of normal and abnormal battery modules using the internal resistance measurement result and battery module status diagnosis information.

[0013] The control unit corrects the error rate of the instantaneous value measured through the internal resistance measurement unit and controls the battery status to be diagnosed through the status diagnosis unit for each battery module based on the internal resistance change rate at a certain period (weekly, monthly, quarterly, yearly).

[0014] The battery module-specific status diagnosis unit compares and analyzes the internal resistance change rate by period (day / month / year) with ESS information such as SOH (battery degradation index), SOC (battery charge rate), and temperature and humidity.

[0015] Meanwhile, a method using a system for diagnosing the internal resistance of a kWh or higher lithium-ion battery, which includes an internal resistance measurement unit, a status diagnosis unit for each battery module, a module replacement determination unit, and a control unit, comprises: a step in which the control unit measures the AC internal resistance of the battery in a frequency domain through the internal resistance measurement unit and sets a reference value of the internal resistance; a step in which the control unit evaluates the status of the battery module using the internal resistance reference value set by the internal resistance measurement unit through the status diagnosis unit for each battery module, and analyzes the deviation of the internal resistance value to identify a battery module in an abnormal state; and a step in which the control unit performs a precise analysis through a separate electrochemical impedance spectroscopy on a battery module classified as in an abnormal state based on the internal resistance measurement result to determine whether to replace the battery module.

[0016] According to the present invention, the electrical state of a kWh or higher lithium-ion battery for ESS can be diagnosed by reflecting the structural characteristics of a kWh or higher lithium-ion battery, and the reliability of internal resistance measurement can be improved and the protection of the measurer can be secured through remote measurement.

[0017] Figure 1 is a configuration diagram of a system for diagnosing the internal resistance of a kWh or higher lithium-ion battery according to one embodiment of the present invention.

[0018] Figure 2 is a remote measurement concept diagram of a system for diagnosing the internal resistance of a kWh or higher lithium-ion battery according to one embodiment of the present invention.

[0019] FIG. 3 is an overall flowchart illustrating a method using a system for diagnosing internal resistance of a kWh or higher lithium ion battery according to one embodiment of the present invention.

[0020] Figure 4 is a schematic flowchart illustrating a method for diagnosing internal resistance of a lithium ion battery of the kWh class or higher according to one embodiment of the present invention.

[0021] A system for diagnosing the internal resistance of a kWh or higher lithium-ion battery according to one embodiment of the present invention is a state diagnosis technology for a kWh or higher lithium-ion battery for ESS from an electrical perspective, and proposes an internal resistance measurement method and an analysis method that reflect the structural characteristics of a kWh or higher lithium-ion battery, and secures improvement in the reliability of internal resistance measurement and protection of the measurer through a remote measurement system according to the method.

[0022] According to this embodiment, the main functions of the alternating current inductive resonance (ACIR) method and electrochemical impedance spectroscopy (EIS) suitable for the structure of a kWh large-capacity lithium-ion battery are combined to evaluate and diagnose the condition of the battery using the internal resistance measurement value of the kWh large-capacity lithium-ion battery.

[0023] In addition, the battery status is diagnosed based on the internal resistance change rate at regular intervals (weekly, monthly, quarterly, yearly) by correcting the error rate of the measured instantaneous value, which is a shortcoming of ACIR during battery diagnosis.

[0024] In addition, in this embodiment, by remotely automating internal resistance measurement, the existing direct measurement method is improved, and not only can ESS equipment and human accidents be prevented through remote measurement, but a battery status diagnosis function can be implemented in real time.

[0025] Hereinafter, one embodiment of the present invention will be described in detail with reference to the drawings.

[0026] FIG. 1 is a configuration diagram of a system for diagnosing internal resistance of a kWh or higher lithium ion battery according to one embodiment of the present invention.

[0027] As illustrated in FIG. 1, a system (10) for diagnosing internal resistance of a kWh or higher lithium ion battery according to one embodiment of the present invention includes an internal resistance measurement unit (110), a battery module-specific status diagnosis unit (120), a module replacement determination unit (130), and a control unit (140).

[0028] The internal resistance measuring unit (110) measures the internal resistance based on the AC method to determine the basic information of the lithium-ion battery in the field and the resonant frequency range, and upon confirming the resonant frequency range, measures again to set a reference value for the internal resistance. In other words, the first internal resistance value becomes the reference value for the internal resistance in the field, and based on this, a status diagnosis is performed for each battery module.

[0029] The ACIR measurement (hereinafter, ACIR measurement) based on the internal resistance measurement unit (110) according to this embodiment applies battery AC current in the frequency domain and measures the voltage response thereto. This ACIR measurement represents the real part of the impedance value according to frequency and can be expressed in mΩ (milli-ohm units).

[0030] This frequency response analysis allows us to see how the internal resistance of the battery changes with frequency, and the frequency response reflects the electrolyte condition of the battery, the chemical reaction state, and the structure of the electrodes and electrolyte.

[0031] At this time, ACIR measurements may include errors due to contact resistance between the measuring equipment and the battery module and other external factors. It is important to obtain accurate ACIR values ​​by diagnosing the battery condition based on the internal resistance change rate over a certain period (weekly, monthly, quarterly, or yearly) by compensating for the error rate of the instantaneous ACIR measurement.

[0032] The operation of the internal resistance measuring unit (110) according to the present embodiment will be described as an example. A battery module is selected to initiate ACIR measurement, and an AC current is applied to the battery module using a frequency set in the frequency domain. The battery module reacts to the AC current according to the given frequency and generates a voltage response thereto. The internal resistance measuring unit measures and records the voltage response of the battery module, calculates an ACIR value using the measured voltage response data, and displays this value in milliohms.

[0033] In addition, the internal resistance measurement unit performs error correction on the ACIR measurement results to obtain an accurate ACIR value, and the measured ACIR value is recorded and analyzed and used to evaluate the internal resistance status of the battery module. The ACIR value obtained from the first measurement is set as the internal resistance reference value of the corresponding module and is used for comparison in subsequent measurements. Afterwards, the status diagnosis unit for each battery module compares the ACIR value with the internal resistance reference value to diagnose the status of the battery module, detect changes in the status, and transmits the ACIR measurement results and the status diagnosis information of the battery module to the control unit so that they can be reported to the system manager or operator.

[0034] The battery module-specific status diagnosis unit (120) diagnoses the status of each battery module based on the internal resistance reference value set by the internal resistance measurement unit and classifies it into a normal state and an abnormal state. At this time, a battery module with a significant deviation from the internal resistance reference value is classified as abnormal. In particular, a battery module corresponding to a high resistance value with a significant deviation from the internal resistance reference value is classified as abnormal.

[0035] The operation of the status diagnosis unit (120) for each battery module is described as follows.

[0036] The internal resistance value obtained through the initial ACIR measurement in the internal resistance measurement unit (110) becomes the internal resistance reference value at the site. This reference value is used as a standard for evaluating the condition of the battery module.

[0037] The battery module-specific status diagnosis unit (120) compares the ACIR measurement results with the internal resistance reference value to diagnose the status of each battery module. The status diagnosis is performed by checking whether the internal resistance value deviates from the reference value. If the deviation between the internal resistance value and the reference value is large, the corresponding battery module is classified as abnormal. In particular, a battery module that has a large deviation between the internal resistance value and the internal resistance reference value and corresponds to a high resistance value is classified as abnormal. Battery modules classified as abnormal in the status diagnosis results are reported to the control unit, and this information is later used in the step of determining whether to replace the module.

[0038] The module replacement determination unit (130) determines whether to replace the battery module by conducting a separate, precise analysis through EIS on the battery module classified as abnormal through the status diagnosis unit for each battery module.

[0039] The operation of the module replacement determination unit (130) is described as follows.

[0040] Information on battery modules classified as abnormal is received from the battery module-specific status diagnosis unit (120). These battery modules are likely to have internal resistance values ​​that deviate significantly from the reference value or have high resistance values.

[0041] The module replacement determination unit (130) performs a separate, precise analysis using Electrochemical Impedance Spectroscopy (EIS) on battery modules classified as abnormal. EIS is used to analyze the physical and electrochemical properties of the battery module in more detail. The EIS analysis results are then used to determine whether the module needs to be replaced. EIS provides in-depth information, which helps identify the actual condition of the battery module and the cause of the problem. The results of the module replacement determination can be reported to the control unit to identify modules requiring replacement and adjust operations accordingly.

[0042] The following is an explanation of the decision regarding whether to replace the battery module according to this embodiment.

[0043] The module replacement determination unit measures impedance values ​​across a frequency range using electrochemical impedance spectroscopy. To measure the battery module, electrodes and sensors are connected to allow measurements that take into account the electrode and electrolyte conditions within the battery module.

[0044] Next, the data obtained by measuring the initial condition of the battery module serves as a baseline for comparison with subsequent measurements. To assess the initial condition of the battery module, the battery is brought to a specific state (charged) and the initial impedance data is measured while stationary. This data represents a healthy starting point for the battery module and can be considered the baseline data.

[0045] Next, regarding impedance measurements, the battery module is measured under various temperature and voltage conditions over a specific frequency range. Impedance measurements are primarily performed at various frequencies, and by measuring impedance values ​​within these frequency ranges, information regarding the electrode and electrolyte conditions within the battery, as well as the rate of ion movement, is obtained.

[0046] The module replacement decision unit analyzes previously measured impedance data to assess the health of the battery module and determines whether to replace it. The changed impedance value is related to factors such as the state of the electrodes and electrolyte within the battery, as well as the rate of ion movement. If the impedance value shows an increasing trend over time, this indicates a potential internal battery damage, which can be considered a signal for replacement. When determining whether to replace, the health of the battery module is quantified based on the impedance data. If the impedance is abnormally high or unstable during this process, the battery module can be replaced.

[0047] The control unit (140) performs intensive monitoring of battery modules that have a deviation from the reference value determined as not to be replaced through the module replacement judgment unit, and, when diagnosing a battery module classified as normal through the battery module status diagnosis unit, performs comparative analysis of the internal resistance change rate by cycle (day / month / year) and the ESS key information such as SOH (battery degradation index), SOC (battery charge rate), and temperature and humidity. Here, when a data deviation occurs, it is reclassified as abnormal and module replacement is determined again through a precise analysis of the battery module status based on EIS.

[0048] The control unit according to this embodiment enables real-time battery status diagnosis function as well as prevention of accidents to ESS facilities and human bodies through remote measurement rather than the existing direct measurement method through remote automation of internal resistance measurement.

[0049] FIG. 2 is a remote measurement concept diagram of a system for diagnosing the internal resistance of a kWh or higher lithium-ion battery according to one embodiment of the present invention.

[0050] As illustrated in Figure 2, this is a conceptual diagram of a remote measurement system for the internal resistance of a lithium-ion battery of the kWh or higher class, schematically illustrating the main components and functions for measurement. The main components are an internal resistance measurement device (including a power supply), a measurement terminal (cable), and an internal resistance remote data collection device.

[0051] Here, the internal resistance measuring device and jig are installed as many times as the number of modules that make up the ESS rack, and a single remote data collection device is configured. However, the internal resistance remote data collection device must have wireless communication capabilities and transmit data to the corresponding ESS EMS server.

[0052] FIG. 3 is an overall flowchart illustrating a method using a system for diagnosing internal resistance of a kWh or higher lithium ion battery according to one embodiment of the present invention.

[0053] As shown in Fig. 3, according to the method for measuring the internal resistance of a lithium-ion battery of the kWh class or higher and the diagnosis flow chart, first, the method for measuring the internal resistance of a lithium-ion battery of the kWh class or higher combines the main functions of the AC method and EIS, and measures the internal resistance based on the AC method to identify the basic information of the lithium-ion battery in the field and determine the resonant frequency range. Once the resonant frequency range is confirmed, it is measured again to set the reference value of the internal resistance. In other words, the first internal resistance value becomes the reference value of the internal resistance in the field, and based on this, the status diagnosis of each battery module is performed.

[0054] Here, the status diagnosis for each battery module is largely divided into two categories: normal and abnormal. For this status classification, modules with a large deviation (especially high resistance value) from the internal resistance reference value are classified as abnormal and separate precise analysis is performed through EIS.

[0055] EIS allows for precise analysis of module status to determine whether a module should be replaced. If replacement is not required, intensive monitoring is conducted on modules exhibiting deviations.

[0056] Furthermore, module diagnosis under normal conditions involves a comparative analysis of internal resistance change rates by cycle (daily / monthly / yearly) and key ESS data such as State of Health (SOH), State of Charge (SOC), and temperature and humidity. Any data deviations are classified as abnormal and, through precise analysis of the module status based on EIS, module replacement is determined.

[0057] Figure 4 is a schematic flowchart illustrating a method for diagnosing internal resistance of a lithium ion battery of the kWh class or higher according to one embodiment of the present invention.

[0058] As shown in FIG. 4, a method using a system for diagnosing the internal resistance of a kWh or higher lithium-ion battery, which includes an internal resistance measurement unit, a status diagnosis unit for each battery module, a module replacement determination unit, and a control unit according to one embodiment of the present invention, is described as follows.

[0059] First, the control unit measures the AC internal resistance of the battery in the frequency domain through the internal resistance measurement unit and sets the reference value of the internal resistance (S2).

[0060] Next, the control unit evaluates the status of the battery module using the internal resistance reference value set by the internal resistance measurement unit through the status diagnosis unit for each battery module, and analyzes the deviation of the internal resistance value to identify a battery module in an abnormal state (S4).

[0061] Next, the control unit performs a precise analysis using a separate electrochemical impedance spectroscopy on the battery module classified as abnormal based on the internal resistance measurement results to determine whether to replace the battery module (S6).

[0062] The system for diagnosing the internal resistance of lithium-ion batteries of kWh or higher, according to this embodiment, efficiently diagnoses the condition of hundreds to thousands of battery modules through diagnostic technology optimized for field applications of lithium-ion battery-based ESS. It also prevents equipment and human accidents through a remote measurement system during internal resistance measurements. Furthermore, by eliminating lithium-ion battery capacity constraints and ensuring versatility, the system can be applied to a variety of ESS projects.

[0063] In addition, it has the effect of diagnosing the electrical status of lithium-ion batteries of kWh or higher for ESS by reflecting the structural characteristics of lithium-ion batteries of kWh or higher, and improving the reliability of internal resistance measurement and securing protection of the measurer through remote measurement.

Claims

1. An internal resistance measuring unit that measures the AC internal resistance of the battery in the frequency domain and sets a reference value for the internal resistance; A battery module-specific status diagnosis unit that evaluates the status of the battery module using the internal resistance reference value set in the internal resistance measurement unit and analyzes the deviation of the internal resistance value to identify an abnormal battery module. A module replacement decision unit that determines whether to replace a battery module by performing a precise analysis using electrochemical impedance spectroscopy on battery modules classified as abnormal based on the internal resistance measurement results. A system for diagnosing the internal resistance of a lithium-ion battery of kWh or higher, characterized by including a control unit that performs monitoring of normal and abnormal battery modules by utilizing internal resistance measurement results and battery module status diagnosis information.

2. In paragraph 1, A system for diagnosing the internal resistance of a lithium-ion battery of the kWh class or higher, characterized in that the control unit corrects the error rate of the instantaneous value measured through the internal resistance measurement unit and controls the battery status to be diagnosed through the status diagnosis unit for each battery module based on the internal resistance change rate at a certain period (weekly, monthly, quarterly, yearly).

3. In paragraph 1, A system for diagnosing the internal resistance of a lithium-ion battery of the kWh or higher class, characterized in that the above battery module-specific status diagnosis unit compares and analyzes the internal resistance change rate by period (day / month / year) with ESS information such as SOH (battery degradation index), SOC (battery charge rate), and temperature and humidity.

4. A method using a system for diagnosing the internal resistance of a lithium-ion battery of kWh or higher, including an internal resistance measurement unit, a status diagnosis unit for each battery module, a module replacement determination unit, and a control unit, A step in which the above control unit measures the AC internal resistance of the battery in the frequency domain through the internal resistance measuring unit and sets a reference value of the internal resistance. A step for the above control unit to evaluate the status of the battery module using the internal resistance reference value set by the internal resistance measurement unit through the status diagnosis unit for each battery module, and to analyze the deviation of the internal resistance value to identify a battery module in an abnormal state; and A method for diagnosing the internal resistance of a lithium-ion battery of a kWh or higher class, characterized in that the control unit includes a step of performing a precise analysis through a separate electrochemical impedance spectroscopy on a battery module classified as being in an abnormal state based on the internal resistance measurement results to determine whether to replace the battery module.

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