Cloud BMS and onboard BMS linkage DCR detection method and terminal

Abstract

The invention discloses a DCR detection method and terminal for linkage of a cloud BMS and an onboard BMS, and the method comprises the steps: monitoring a battery system in real time through the cloud BMS, judging whether the battery system meets a preset condition or not, and enabling the cloud BMS to control a PCS to output two current segments with different current magnitudes and durations to the battery system if the preset condition is met; a battery cluster control unit SBMU of the on-board BMS calculates a single-cluster DCR according to the collected two sections of current and the single-cluster voltage corresponding to the two sections of current; a cell management unit CSC of the on-board BMS calculates a cell DCR according to the collected two segments of current and the battery cell voltage corresponding to the two segments of current; summarizing the single DCR and the single cluster DCR, and uploading the summarized single DCR and the summarized single cluster DCR to a cloud BMS for analysis; according to the method, the cloud BMS and the onboard BMS are linked to detect the DCR of the battery, the accuracy of DCR calculation is improved, the single DCR and the single cluster DCR are analyzed through the cloud BMS, and the aging degree, the health degree and the abnormal collection point of the battery system can be judged.

Description

Technical Field

[0001] The present invention relates to the technical field of battery management systems, and in particular to a DCR detection method and terminal for linking a cloud BMS with an onboard BMS. Background Art

[0002] As the sales of energy storage systems increase, the number of systems in use increases dramatically. At the same time, many energy storage systems have been in operation for many years. Battery safety warning and monitoring have become an important topic in the field of energy storage. Battery DCR refers to the direct current resistance of the battery, which is an important parameter for measuring battery performance and safety. DCR mainly reflects the resistance generated internally by the battery during the discharge process. The lower this value means the lower the energy loss and the higher the efficiency of the battery during use. Generally, as the battery ages or the conditions of use change (such as temperature increase), its DCR will increase accordingly. For application areas such as electric vehicles and energy storage systems, monitoring the DCR of each unit in the battery pack can help detect potential problems in a timely manner.

[0003] In energy storage systems, unlike cars that have parking and dormant conditions, battery systems are generally always running. To measure DCR, the current must be stable for a period of time. Therefore, it is difficult to independently find the DCR calculation conditions relying solely on the onboard BMS. When calculating DCR through the cloud BMS, due to the large throughput, the frequency of data uploaded from the vehicle BMS to the cloud BMS is at least 1S. The cloud BMS cannot obtain data at a fast enough rate, which will affect the calculation of DCR. Summary of the invention The technical problem to be solved by the present invention is to provide a DCR detection method and terminal for linking a cloud BMS with an onboard BMS, thereby improving the accuracy of DCR calculation and detecting aging and abnormality of a battery system.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is: A DCR detection method for linking a cloud BMS with an onboard BMS comprises the following steps: S1. Monitor the battery system in real time through the cloud BMS and determine whether the battery system meets the preset conditions. If the preset conditions are met, the cloud BMS controls the PCS to output two currents with different current magnitudes and durations to the battery system. S2, the battery cluster control unit SBMU of the onboard BMS calculates the single cluster DCR according to the two current segments collected and the single cluster voltage corresponding to the two current segments; The cell management unit CSC of the onboard BMS calculates the cell DCR according to the two current segments collected and the battery cell voltages corresponding to the two current segments; S3. Summarize the monomer DCR and the single cluster DCR and upload them to the cloud BMS for analysis.

[0005] In order to solve the above technical problems, another technical solution adopted by the present invention is: A DCR detection terminal for linkage between a cloud BMS and an onboard BMS comprises a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: S1. Monitor the battery system in real time through the cloud BMS and determine whether the battery system meets the preset conditions. If the preset conditions are met, the cloud BMS controls the PCS to output two currents with different current magnitudes and durations to the battery system. S2, the battery cluster control unit SBMU of the onboard BMS calculates the single cluster DCR according to the two current segments collected and the single cluster voltage corresponding to the two current segments; The cell management unit CSC of the onboard BMS calculates the cell DCR according to the two current segments collected and the battery cell voltages corresponding to the two current segments; S3. Summarize the monomer DCR and the single cluster DCR and upload them to the cloud BMS for analysis.

[0006] The beneficial effects of the present invention are as follows: a DCR detection method and terminal for linkage between a cloud BMS and an onboard BMS of the present invention monitors the operating status of a battery system through the cloud BMS, controls the current output of a PCS, collects corresponding current and voltage according to the onboard BMS to calculate the DCR of a single cluster and a single cell, summarizes the DCR of the single cluster and the single cell and uploads it to the cloud BMS, realizes linkage between the cloud BMS and the onboard BMS to detect the DCR of the battery, finds the calculation working condition through precise current control of the cloud BMS, and calculates the DCR through data collected by the onboard BMS, thereby improving the accuracy of the DCR calculation, and by analyzing the DCR of the single cell and the single cluster through the cloud BMS, it is possible to judge the aging degree and health degree of the battery system and collect abnormal points. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 It is a flow chart of a DCR detection method for linking a cloud BMS with an onboard BMS according to an embodiment of the present invention; Figure 2 It is a flow chart of a DCR detection method for linking a cloud BMS with an onboard BMS according to an embodiment of the present invention; Figure 3 Another flowchart of a DCR detection method for linking a cloud BMS with an onboard BMS according to an embodiment of the present invention; Figure 4 A schematic diagram of the structure of an energy storage system of a three-level BMS architecture according to an embodiment of the present invention; Figure 5 A schematic diagram of the structure of an energy storage system of a two-level BMS architecture according to an embodiment of the present invention; Figure 6 This is a structural diagram of a DCR detection terminal in which a cloud BMS and an onboard BMS are linked in an embodiment of the present invention; Description of labels: 1. A DCR detection terminal that links cloud BMS and onboard BMS; 2. Processor; 3. Memory. DETAILED DESCRIPTION

[0008] In order to explain the technical content, achieved objectives and effects of the present invention in detail, the following is an explanation in combination with the implementation modes and the accompanying drawings.

[0009] Please refer to Figures 1 to 3 , a DCR detection method for linking a cloud BMS with an onboard BMS, comprising the steps of: S1. Monitor the battery system in real time through the cloud BMS and determine whether the battery system meets the preset conditions. If the preset conditions are met, the cloud BMS controls the PCS to output two currents with different current magnitudes and durations to the battery system. S2, the battery cluster control unit SBMU of the onboard BMS calculates the single cluster DCR according to the two current segments collected and the single cluster voltage corresponding to the two current segments; The cell management unit CSC of the onboard BMS calculates the cell DCR according to the two current segments collected and the battery cell voltages corresponding to the two current segments; S3. Summarize the monomer DCR and the single cluster DCR and upload them to the cloud BMS for analysis.

[0010] From the above description, it can be seen that the beneficial effects of the present invention are: monitoring the operating status of the battery system through the cloud BMS, controlling the PCS current output, collecting the corresponding current and voltage according to the onboard BMS to calculate the single cluster and single cell DCR, summarizing the single cluster and single cell DCR and uploading them to the cloud BMS, realizing the linkage between the cloud BMS and the onboard BMS to detect the battery DCR, finding the calculation condition through the precise current control of the cloud BMS, and calculating the DCR by collecting data from the onboard BMS, thereby improving the accuracy of the DCR calculation, and analyzing the single cell and single cluster DCR through the cloud BMS, it is possible to determine the aging degree and health degree of the battery system and collect abnormal points.

[0011] Furthermore, step S1 is specifically as follows: The battery system is monitored in real time by the cloud BMS. If the battery system is charged by the PCS and the SOC is within a preset range, the cloud BMS controls the PCS to output two stable charging currents with different current magnitudes and durations.

[0012] From the above description, it can be seen that compared with the situation where the onboard BMS is difficult to find suitable calculation conditions independently, the cloud BMS can monitor the battery system status in real time and accurately control the PCS to output two stable charging currents that meet the DCR calculation requirements, providing the basic conditions for the subsequent accurate calculation of DCR, avoiding calculation errors caused by unstable current, and greatly improving the accuracy of DCR calculation.

[0013] Furthermore, the calculation of the monomer DCR and the single cluster DCR is specifically as follows: ; Among them, I1 is the charging current or discharging current of the first section, I2 is the charging current or discharging current of the second section, t1 is the charging time or discharging time of the first section, t2 is the charging time or discharging time of the second section, V1 is the voltage at the end of the first charging section or the first discharging section, and V2 is the voltage at the end of the second charging section or the second discharging section.

[0014] From the above description, it can be seen that this calculation method provides a unified calculation standard for monomer DCR and single cluster DCR, and can quickly obtain relatively accurate monomer DCR and single cluster DCR.

[0015] Furthermore, after step S2, the following steps are further included: The battery cluster control unit SBMU determines whether the battery cluster is abnormal according to the single cluster DCR and a preset single cluster DCR threshold; The cell management unit CSC determines whether a single cell battery is abnormal according to the single cell DCR and a preset single cell DCR threshold.

[0016] From the above description, it can be seen that when the SBMU detects a single-cluster DCR abnormality, it can be clearly determined that the problem lies at the battery cluster level, which may be caused by loose battery connections within the battery cluster, inconsistent battery module aging, etc.; and when the CSC detects a single-cell DCR abnormality, it can directly point to a specific single cell, which may be a problem of damaged plates inside the single cell, electrolyte leakage, etc. SBMU and CSC calculate DCR and make abnormal judgments on battery clusters and single cells respectively, which can accurately locate the level of the problem, help to quickly take targeted measures, improve maintenance efficiency, and reduce unnecessary inspections and interference with the entire battery system.

[0017] Furthermore, step S3 is specifically as follows: The single-cell DCR and the single-cluster DCR are summarized and uploaded to the cloud BMS, and the cloud BMS determines the abnormal state and change trend of the single-cell DCR and the single-cluster DCR according to the preset single-cell DCR threshold, the single-cluster DCR threshold and the historical DCR data; The historical DCR data includes historical single-cell DCR data and historical single-cluster DCR data.

[0018] From the above description, it can be seen that aggregating the single-cell DCR and single-cluster DCR to the cloud BMS can comprehensively consider the status of the battery system from both the single-cell and battery cluster levels, avoiding missing problems by focusing on a single dimension, because the failure of the battery system may be caused by the accumulation of single-cell battery problems or the overall abnormality of the battery cluster; at the same time, combined with historical DCR data (including single clusters and single cells), the cloud BMS can more accurately judge the rationality of the current DCR value. Since the performance change of the battery is a gradual process, by comparing historical data, it can identify whether it is a normal fluctuation or an abnormal change, and take corresponding optimization measures in advance.

[0019] Please refer to Figure 6 , a DCR detection terminal for linkage between a cloud BMS and an onboard BMS, comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: S1. Monitor the battery system in real time through the cloud BMS and determine whether the battery system meets the preset conditions. If the preset conditions are met, the cloud BMS controls the PCS to output two currents with different current magnitudes and durations to the battery system. S2, the battery cluster control unit SBMU of the onboard BMS calculates the single cluster DCR according to the two current segments collected and the single cluster voltage corresponding to the two current segments; The cell management unit CSC of the onboard BMS calculates the cell DCR according to the two current segments collected and the battery cell voltages corresponding to the two current segments; S3. Summarize the monomer DCR and the single cluster DCR and upload them to the cloud BMS for analysis.

[0020] From the above description, it can be seen that the beneficial effects of the present invention are: monitoring the operating status of the battery system through the cloud BMS, controlling the PCS current output, collecting the corresponding current and voltage according to the onboard BMS to calculate the single cluster and single cell DCR, summarizing the single cluster and single cell DCR and uploading them to the cloud BMS, realizing the linkage between the cloud BMS and the onboard BMS to detect the battery DCR, finding the calculation condition through the precise current control of the cloud BMS, and calculating the DCR by collecting data from the onboard BMS, thereby improving the accuracy of the DCR calculation, and analyzing the single cell and single cluster DCR through the cloud BMS, it is possible to determine the aging degree and health degree of the battery system and collect abnormal points.

[0021] Furthermore, step S1 is specifically as follows: The battery system is monitored in real time by the cloud BMS. If the battery system is charged by the PCS and the SOC is within a preset range, the cloud BMS controls the PCS to output two stable charging currents with different current magnitudes and durations.

[0022] From the above description, it can be seen that compared with the situation where the onboard BMS is difficult to find suitable calculation conditions independently, the cloud BMS can monitor the battery system status in real time and accurately control the PCS to output two stable charging currents that meet the DCR calculation requirements, providing the basic conditions for the subsequent accurate calculation of DCR, avoiding calculation errors caused by unstable current, and greatly improving the accuracy of DCR calculation.

[0023] Furthermore, the calculation of the monomer DCR and the single cluster DCR is specifically as follows: ; Among them, I1 is the charging current or discharging current of the first section, I2 is the charging current or discharging current of the second section, t1 is the charging time or discharging time of the first section, t2 is the charging time or discharging time of the second section, V1 is the voltage at the end of the first charging section or the first discharging section, and V2 is the voltage at the end of the second charging section or the second discharging section.

[0024] From the above description, it can be seen that this calculation method provides a unified calculation standard for monomer DCR and single cluster DCR, and can quickly obtain relatively accurate monomer DCR and single cluster DCR.

[0025] Furthermore, after step S2, the following steps are further included: The battery cluster control unit SBMU determines whether the battery cluster is abnormal according to the single cluster DCR and a preset single cluster DCR threshold; The cell management unit CSC determines whether a single cell battery is abnormal according to the single cell DCR and a preset single cell DCR threshold.

[0026] From the above description, it can be seen that when the SBMU detects a single-cluster DCR abnormality, it can be clearly determined that the problem lies at the battery cluster level, which may be caused by loose battery connections within the battery cluster, inconsistent battery module aging, etc.; and when the CSC detects a single-cell DCR abnormality, it can directly point to a specific single cell, which may be a problem of damaged plates inside the single cell, electrolyte leakage, etc. SBMU and CSC calculate DCR and make abnormal judgments on battery clusters and single cells respectively, which can accurately locate the level of the problem, help to quickly take targeted measures, improve maintenance efficiency, and reduce unnecessary inspections and interference with the entire battery system.

[0027] Furthermore, step S3 is specifically as follows: The single-cell DCR and the single-cluster DCR are summarized and uploaded to the cloud BMS, and the cloud BMS determines the abnormal state and change trend of the single-cell DCR and the single-cluster DCR according to the preset single-cell DCR threshold, the single-cluster DCR threshold and the historical DCR data; The historical DCR data includes historical single-cell DCR data and historical single-cluster DCR data.

[0028] From the above description, it can be seen that aggregating the single-cell DCR and single-cluster DCR to the cloud BMS can comprehensively consider the status of the battery system from both the single-cell and battery cluster levels, avoiding missing problems by focusing on a single dimension, because the failure of the battery system may be caused by the accumulation of single-cell battery problems or the overall abnormality of the battery cluster; at the same time, combined with historical DCR data (including single clusters and single cells), the cloud BMS can more accurately judge the rationality of the current DCR value. Since the performance change of the battery is a gradual process, by comparing historical data, it can identify whether it is a normal fluctuation or an abnormal change, and take corresponding optimization measures in advance.

[0029] A DCR detection method and terminal for linking a cloud BMS with an onboard BMS of the present invention are suitable for detecting the DCR of a battery in an energy storage system.

[0030] Please refer to Figure 1 and Figure 2 , Embodiment 1 of the present invention is: a DCR detection method for linkage between a cloud BMS and an onboard BMS, comprising the steps of: S1. Monitor the battery system in real time through the cloud BMS and determine whether the battery system meets the preset conditions. If the preset conditions are met, the cloud BMS controls the PCS to output two currents with different current magnitudes and durations to the battery system.

[0031] Step S1 is specifically as follows: The battery system is monitored in real time by the cloud BMS. If the battery system is charged by the PCS and the SOC is within a preset range, the cloud BMS controls the PCS to output two stable charging currents with different current magnitudes and durations.

[0032] In this embodiment, since the battery is generally discharged passively, the power demand of the load is quite random, and the discharge condition is relatively difficult to control, the charging condition is selected, and the cloud BMS sends the required current through CAN communication or other communications, so that the PCS outputs the required current, thereby controlling the stable charging current and facilitating the calculation of DCR; or according to the actual situation, the cloud BMS requires the PCS to provide a specific current, such as 0.2C first, then 0.5C, to ensure that the voltage rise is more obvious, improve the voltage differentiation, and thus improve the calculation accuracy of DCR.

[0033] In this embodiment, the SOC needs to be within a certain range. Since the DCR corresponding to different SOCs varies greatly, the preset range of SOC is 45%~55%. Generally, the SOC is selected to be 50%, that is, the platform area. The bottom and top ends will cause the battery's own voltage to change too much, which will interfere with the test. In other equivalent embodiments, it is not limited to the above SOC range.

[0034] S2, the battery cluster control unit SBMU of the onboard BMS calculates the single cluster DCR according to the two current segments collected and the single cluster voltage corresponding to the two current segments; The cell management unit CSC of the onboard BMS calculates the cell DCR according to the two current segments collected and the battery cell voltages corresponding to the two current segments.

[0035] In this embodiment, Figure 4 and Figure 5 The onboard BMS is generally divided into a two-level architecture or a three-level architecture. The two-level BMS is composed of CSC and SBMU, while the three-level BMS is composed of CSC, SBMU and MBUM. The energy storage system mainly includes power grid, load, PCS, EMS, cloud BMS, BMS, etc. The energy storage system is not limited to this embodiment, and specific functions can be implemented on different components.

[0036] Among them, PCS draws electricity from the power grid, battery or photovoltaic power, and discharges it to the load (household electricity), and can also charge the battery; BMS mainly realizes signal acquisition of the battery system, performs logical calculations through the data collected by the signals, and realizes the power on and off of the battery by controlling the relay; EMS energy storage energy management system is a specific application field of EMS, focusing on managing and optimizing the performance of energy storage systems (such as battery energy storage); Cloud BMS is a battery management system based on cloud computing technology. It combines traditional BMS functions with cloud services to achieve more efficient and intelligent battery management. It can not only monitor and manage the status of the battery in real time, but also use big data analysis, artificial intelligence and other technologies to provide more accurate services.

[0037] In this embodiment, the detection of single cluster and single monomer DCR is selected to be calculated on the bottom-level controller, that is, the DCR is calculated through the CSC and SBMU to improve the timeliness of the detection.

[0038] Specifically, the calculation method of the monomer DCR and the single cluster DCR is: ; Among them, I1 is the charging current or discharging current of the first section, I2 is the charging current or discharging current of the second section, t1 is the charging time or discharging time of the first section, t2 is the charging time or discharging time of the second section, V1 is the voltage at the end of the first charging section or the first discharging section, and V2 is the voltage at the end of the second charging section or the second discharging section.

[0039] Specifically, I1 is the discharge current or charge current, which is specified as 0.2C; I2 is the discharge current or charge current, which is specified as 1C (the current can be calibrated); t1 is the discharge time or charge time 10s, and t2 is the discharge time or charge time 1s (the duration can be calibrated); V1 is the voltage at the end of discharge or charge for 10s, and V2 is the voltage at the end of discharge or charge for 1s.

[0040] S3. Summarize the monomer DCR and the single cluster DCR and upload them to the cloud BMS for analysis.

[0041] Step S3 is specifically as follows: The single-cell DCR and the single-cluster DCR are summarized and uploaded to the cloud BMS, and the cloud BMS determines the abnormal state and change trend of the single-cell DCR and the single-cluster DCR according to the preset single-cell DCR threshold, the single-cluster DCR threshold and the historical DCR data; The historical DCR data includes historical single-cell DCR data and historical single-cluster DCR data.

[0042] In this embodiment, the cloud BMS can save the single cluster DCR and monomer DCR data for several weeks or even years. By analyzing the DCR change curve over time, the future DCR change trend can be predicted and corresponding measures can be taken in advance, such as adjusting the charging and discharging strategy and optimizing the balancing control.

[0043] Please refer to Figure 3 , Embodiment 2 of the present invention is: a DCR detection method for linkage between a cloud BMS and an onboard BMS, which is different from Embodiment 1 in that after step S2, it further includes: The battery cluster control unit SBMU determines whether the battery cluster is abnormal according to the single cluster DCR and a preset single cluster DCR threshold; The cell management unit CSC determines whether a single cell battery is abnormal according to the single cell DCR and a preset single cell DCR threshold.

[0044] In this embodiment, before summarizing the single cell DCR and single cluster DCR, the calculated single cell DCR and single cluster DCR values ​​can be compared with the single cell DCR and single cluster DCR thresholds by the single cell management unit CSC and the battery cluster control unit SBMU to determine whether there is a cell abnormality or a battery cluster abnormality based on the difference.

[0045] Among them, the single cell DCR is more suitable for judging the abnormality of the battery cell; the single cluster DCR includes the single cell and the copper busbar, and it is difficult to check if a single cell is abnormal, while the abnormal value of the copper busbar changes greatly and is easier to detect. Assuming that the built-in resistance of a single battery cell is about 4 milliohms, there are 100 cells in a single cluster, and one of them changes to 10 milliohms, the change in the whole cluster is not very large, and it cannot be judged that there is a problem with the battery cell.

[0046] Please refer to Figure 6 , Embodiment 3 of the present invention is: a DCR detection terminal 1 for linkage between a cloud BMS and an onboard BMS, comprising a processor 2, a memory 3, and a computer program stored in the memory 3 and executable on the processor 2, wherein the processor 2 implements the steps of a DCR detection method for linkage between a cloud BMS and an onboard BMS in Embodiment 1 or 2 when executing the computer program.

[0047] In summary, the present invention provides a DCR detection method and terminal for linkage between cloud BMS and onboard BMS, which monitors the operating status of the battery system through cloud BMS, controls the current output of PCS, collects corresponding current and voltage according to onboard BMS to calculate the DCR of single cluster and single cell, summarizes the DCR of single cluster and single cell and uploads it to cloud BMS, realizes linkage between cloud BMS and onboard BMS to detect the DCR of battery, finds the calculation condition through precise current control of cloud BMS, and calculates DCR by collecting data from onboard BMS, thereby improving the accuracy of DCR calculation, and analyzes the DCR of single cell and single cluster through cloud BMS, so as to judge the aging degree, health degree and abnormal collection points of the battery system.

[0048] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's specification and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A DCR detection method for linkage between cloud BMS and onboard BMS, characterized in that: Includes steps: S1. Monitor the battery system in real time through the cloud BMS and determine whether the battery system meets the preset conditions. If the preset conditions are met, the cloud BMS controls the PCS to output two currents with different current magnitudes and durations to the battery system. S2, the battery cluster control unit SBMU of the onboard BMS calculates the single cluster DCR according to the two current segments collected and the single cluster voltage corresponding to the two current segments; The cell management unit CSC of the onboard BMS calculates the cell DCR according to the two current segments collected and the battery cell voltages corresponding to the two current segments; S3. Summarize the monomer DCR and the single cluster DCR and upload them to the cloud BMS for analysis.

2. A DCR detection method for linkage between cloud BMS and onboard BMS according to claim 1, characterized in that: Step S1 is specifically as follows: The battery system is monitored in real time by the cloud BMS. If the battery system is charged by the PCS and the SOC is within a preset range, the cloud BMS controls the PCS to output two stable charging currents with different current magnitudes and durations.

3. A DCR detection method for linkage between cloud BMS and onboard BMS according to claim 1, characterized in that: The calculation of the monomer DCR and the single cluster DCR is specifically as follows: ; Among them, I1 is the charging current or discharging current of the first section, I2 is the charging current or discharging current of the second section, t1 is the charging time or discharging time of the first section, t2 is the charging time or discharging time of the second section, V1 is the voltage at the end of the first charging section or the first discharging section, and V2 is the voltage at the end of the second charging section or the second discharging section.

4. A DCR detection method for linkage between cloud BMS and onboard BMS according to claim 1, characterized in that: After step S2, the method further includes: The battery cluster control unit SBMU determines whether the battery cluster is abnormal according to the single cluster DCR and a preset single cluster DCR threshold; The cell management unit CSC determines whether a single cell battery is abnormal according to the single cell DCR and a preset single cell DCR threshold.

5. The DCR detection method for linkage between cloud BMS and onboard BMS according to claim 1 is characterized in that: Step S3 is specifically as follows: The single-cell DCR and the single-cluster DCR are summarized and uploaded to the cloud BMS, and the cloud BMS determines the abnormal state and change trend of the single-cell DCR and the single-cluster DCR according to the preset single-cell DCR threshold, the single-cluster DCR threshold and the historical DCR data; The historical DCR data includes historical single-cell DCR data and historical single-cluster DCR data.

6. A DCR detection terminal for linkage between a cloud BMS and an onboard BMS, comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the following steps are implemented: S1. Monitor the battery system in real time through the cloud BMS and determine whether the battery system meets the preset conditions. If the preset conditions are met, the cloud BMS controls the PCS to output two currents with different current magnitudes and durations to the battery system. S2, the battery cluster control unit SBMU of the onboard BMS calculates the single cluster DCR according to the two current segments collected and the single cluster voltage corresponding to the two current segments; The cell management unit CSC of the onboard BMS calculates the cell DCR according to the two current segments collected and the battery cell voltages corresponding to the two current segments; S3. Summarize the monomer DCR and the single cluster DCR and upload them to the cloud BMS for analysis.

7. A DCR detection terminal for linkage between cloud BMS and onboard BMS according to claim 6, characterized in that: Step S1 is specifically as follows: The battery system is monitored in real time by the cloud BMS. If the battery system is charged by the PCS and the SOC is within a preset range, the cloud BMS controls the PCS to output two stable charging currents with different current magnitudes and durations.

8. A DCR detection terminal for linkage between cloud BMS and onboard BMS according to claim 6, characterized in that: The calculation of the monomer DCR and the single cluster DCR is specifically as follows: ; Among them, I1 is the charging current or discharging current of the first section, I2 is the charging current or discharging current of the second section, t1 is the charging time or discharging time of the first section, t2 is the charging time or discharging time of the second section, V1 is the voltage at the end of the first charging section or the first discharging section, and V2 is the voltage at the end of the second charging section or the second discharging section.

9. A DCR detection terminal for linkage between cloud BMS and onboard BMS according to claim 6, characterized in that: After step S2, the method further includes: The battery cluster control unit SBMU determines whether the battery cluster is abnormal according to the single cluster DCR and a preset single cluster DCR threshold; The cell management unit CSC determines whether a single cell battery is abnormal according to the single cell DCR and a preset single cell DCR threshold.

10. A DCR detection terminal for linkage between cloud BMS and onboard BMS according to claim 6, characterized in that: Step S3 is specifically as follows: The single-cell DCR and the single-cluster DCR are summarized and uploaded to the cloud BMS, and the cloud BMS determines the abnormal state and change trend of the single-cell DCR and the single-cluster DCR according to the preset single-cell DCR threshold, the single-cluster DCR threshold and the historical DCR data; The historical DCR data includes historical single-cell DCR data and historical single-cluster DCR data.

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