Battery short circuit early warning method, device and vehicle

Abstract

The application discloses a battery short circuit early warning method and device and a vehicle, and relates to the technical field of automobiles. A specific embodiment of the method comprises the following steps: monitoring that lithium battery charging is completed, collecting the full-charge voltage of each battery cell in a battery pack, and collecting the static voltage of each battery cell after the lithium battery is controlled to enter a static stage and remains for a preset time period; and determining the current voltage drop of each battery cell based on the full-charge voltage and the static voltage. An adaptive reference model of each battery cell is called, and the current voltage drop is compared with the voltage drop threshold of the adaptive reference model of the battery cell. The adaptive reference model of the battery cell is constructed according to the multiple historical voltage drops of the battery cell. If the current voltage drop deviates abnormally from the voltage drop threshold, it is determined that the corresponding battery cell has a micro-short-circuit abnormal risk, a short-circuit early warning for the battery cell is triggered, and a faulty battery cell in the battery pack is identified. The embodiment can realize the early warning of the micro-short circuit of the lithium battery.

Description

Technical Field

[0001] This invention relates to the field of automotive technology, and more particularly to a battery short-circuit warning method, device, and vehicle. Background Technology

[0002] Lithium-ion batteries, due to their high energy density and long cycle life, have been widely used in electric vehicles and other fields. Currently, safety monitoring of lithium-ion batteries mainly relies on battery management systems (BMS) and various laboratory testing methods. Traditional BMS primarily monitor external parameters such as voltage, current, and temperature, typically only triggering alarms when a short-circuit fault becomes severe enough to cause a sudden voltage drop or a rapid temperature rise, by which time the optimal time for safe intervention has been missed. While laboratory-level methods such as disassembly analysis and high-precision self-discharge testing can achieve micro-short-circuit detection, they cannot be performed in real-time in vehicle or online environments.

[0003] In the process of realizing this invention, the inventors discovered that the prior art has at least the following problems: the safety monitoring of lithium batteries is extremely insensitive to slowly developing micro short circuit faults, making it difficult to achieve early warning of micro short circuits in lithium batteries. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a method, apparatus, vehicle, device, and computer-readable medium for battery short circuit warning, which can realize early warning of micro-short circuits in lithium batteries.

[0005] A battery short-circuit warning method includes: Once the lithium battery charging is completed, the full-charge voltage of each cell in the battery pack is collected. After the lithium battery enters the resting stage and continues for a preset period of time, the resting voltage of each cell is collected. Based on the full-charge voltage and the resting voltage, the voltage drop of each cell in this operation is determined. The adaptive reference model of each cell is retrieved, and the voltage drop of the current cell is compared with the voltage drop threshold of the adaptive reference model of the cell. The adaptive reference model of the cell is constructed based on the cell's multiple historical voltage drops. If the voltage drop deviates abnormally from the voltage drop threshold, it is determined that the corresponding cell has a micro-short circuit risk, triggering a short circuit warning for the cell to identify faulty cells in the battery pack.

[0006] The method further includes: After a battery cell completes one charge, the voltage drop of the battery cell at this time is stored in the adaptive reference model as historical voltage drop data, and voltage drops collected outside the set time range are deleted. By utilizing the historical voltage drop in the adaptive benchmark model, the moving average and standard deviation of the historical voltage drop of the battery cell are determined again to update the voltage drop threshold of the adaptive benchmark model, thereby achieving synchronization between the adaptive benchmark model and the aging state of the battery cell.

[0007] The monitoring of the completion of lithium battery charging includes: The charging current of the lithium battery is monitored in real time. If the charging current of the cell drops below the preset charge / discharge rate, or the cell voltage reaches the preset charging cutoff voltage, the lithium battery charging is determined to be finished.

[0008] After determining that the corresponding battery cell has a micro-short circuit anomaly risk, the following is also included: The real-time surface temperature of each cell during the resting phase is monitored synchronously, and the surface temperature rise of the cell during the resting phase is calculated. If a battery cell is determined to be at risk of a micro-short circuit and its surface temperature rise exceeds a preset cell temperature rise threshold, the level of the short circuit warning will be increased. The short circuit warning includes voltage warning and temperature rise warning.

[0009] After determining that the corresponding battery cell has a micro-short circuit anomaly risk, the following is also included: Calculate the average voltage drop of all series-connected cells in the battery pack to determine the consistency threshold; If a cell is determined to be at risk of a micro-short circuit, and the voltage drop exceeds the consistency threshold, then the level of the short circuit warning will be increased.

[0010] The method further includes: For cells identified as having a micro-short circuit risk, their location code within the battery pack is obtained, and the location code and short circuit warning level are simultaneously reported to the vehicle controller via the controller local area network bus. The vehicle controller displays a visual prompt message for battery faults matching the short circuit warning level on the vehicle dashboard. At the same time, the location code and the short circuit warning level are reported to the cloud monitoring platform through the vehicle remote information processing terminal, realizing both local vehicle warning and cloud remote monitoring.

[0011] After determining that the corresponding battery cell has a micro-short circuit anomaly risk, the following is also included: The battery cell is marked as a suspected faulty cell, and the charging current of the suspected faulty cell is limited; During subsequent lithium battery charging, if the suspected faulty cell is again determined to have a micro-short circuit risk, the suspected faulty cell is confirmed to have a micro-short circuit fault, and a command to disconnect the high-voltage contactor is sent to the vehicle controller. At the same time, charging operations are prohibited for the module containing the suspected faulty cell.

[0012] The method further includes: After receiving the short circuit warning, the cloud monitoring platform analyzes the historical voltage drop of the battery cell to generate a battery cell micro short circuit fault report, and simultaneously pushes the battery cell micro short circuit fault report to the vehicle terminal and / or user terminal.

[0013] According to a second aspect of the present invention, a battery short circuit warning device is provided, comprising: The acquisition module is used to monitor the end of lithium battery charging, acquire the full-charge voltage of each cell in the battery pack, and after controlling the lithium battery to enter the resting stage and continue for a preset period of time, acquire the resting voltage of each cell, and determine the voltage drop of each cell based on the full-charge voltage and the resting voltage. The comparison module is used to retrieve the adaptive reference model of each cell and compare the current voltage drop with the voltage drop threshold of the adaptive reference model of the cell. The adaptive reference model of the cell is constructed based on the cell's multiple historical voltage drops. The early warning module is used to determine that there is a micro short circuit risk in the corresponding cell if the current voltage drop deviates abnormally from the voltage drop threshold, and to trigger a short circuit warning for the cell in order to identify the faulty cell in the battery pack.

[0014] According to a third aspect of the present invention, a vehicle is provided, including a battery short-circuit warning device as described above.

[0015] According to a fourth aspect of the present invention, an electronic device for battery short circuit warning is provided, comprising: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors perform the methods described above.

[0016] According to a fifth aspect of the present invention, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method as described above.

[0017] One embodiment of the above invention has the following advantages or beneficial effects: monitoring the voltage drop of the cell after the lithium battery is finished charging, using the adaptive benchmark model corresponding to the cell to determine whether there is a micro short circuit risk in the cell through the voltage drop threshold, can realize early warning of micro short circuits in lithium batteries and identify faulty cells in the battery pack.

[0018] The further effects of the aforementioned unconventional alternative methods will be explained below in conjunction with specific implementation methods. Attached Figure Description

[0019] The accompanying drawings are provided to better understand the invention and are not intended to unduly limit the scope of the invention. Wherein: Figure 1 This is a schematic diagram of the main process of the battery short circuit warning method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the process for updating the adaptive baseline model according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the process for monitoring the real-time surface temperature of a battery cell during the resting stage according to an embodiment of the present invention. Figure 4 This is a schematic diagram of the process for monitoring cell consistency according to an embodiment of the present invention; Figure 5 This is a schematic diagram illustrating the process of implementing an early warning system according to an embodiment of the present invention; Figure 6 This is a flowchart illustrating real-time operation for micro-short circuit faults according to an embodiment of the present invention. Figure 7 This is a schematic diagram of the structure of a battery short circuit warning device according to an embodiment of the present invention; Figure 8 This is an exemplary system architecture diagram in which embodiments of the present invention can be applied; Figure 9 This is a schematic diagram of the structure of a computer system suitable for implementing terminal devices or servers of the present invention. Detailed Implementation

[0020] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of the present invention, including various details to aid understanding. These details should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0021] To achieve early warning of micro-short circuits in lithium batteries, the following technical solutions from the embodiments of the present invention can be adopted.

[0022] See Figure 1 , Figure 1 This is a schematic diagram of the main process of the battery short circuit warning method according to an embodiment of the present invention. Figure 1 The execution entity for each step can be the battery management system; the following explanation uses the battery management system as an example. Specifically, it includes the following steps: S101. After monitoring that the lithium battery charging is finished, collect the full-charge voltage of each cell in the battery pack, and after controlling the lithium battery to enter the resting stage and continue for a preset time period, collect the resting voltage of each cell, and determine the voltage drop of each cell based on the full-charge voltage and the resting voltage.

[0023] The battery management system collects data when it detects the end of the lithium battery charging process. For example, it monitors the charging current of the lithium battery in real time. If the charging current of the cell drops below the preset charge / discharge rate, or if the cell voltage reaches the preset charging cutoff voltage, the charging process is considered complete. For instance, if the preset charge / discharge rate is 0.05, the charging current of the cell drops to C / 20, which is a 0.05C rate current.

[0024] Upon detecting the completion of lithium battery charging, the battery management system immediately records the current time as time 1 T0 and synchronously acquires the terminal voltage of all series-connected cells in the battery pack through the voltage sampling circuit, denoted as the full-charge voltage V_full_i. The subscript i represents the cell number i=1,2,...,n, where n is the total number of series-connected cells in the battery pack. The full-charge voltage characterizes the state of charge of the cell at the end of charging.

[0025] After charging is complete, the lithium battery enters a resting state, such as when the electric vehicle is turned off and parked. The battery management system controls a timer to start timing, continuously for a preset resting period T. As an example, T is set to 30 minutes. 30 minutes is sufficient to fully demonstrate the voltage drop characteristics caused by a micro-short circuit, without affecting the daily use of the vehicle due to an excessively long waiting time.

[0026] When the timing reaches the second moment T0+T, the battery management system once again collects the terminal voltage of all cells through the voltage sampling circuit, which is recorded as the resting voltage V_rest_i.

[0027] For each cell i, the microcontroller inside the battery management system calculates the voltage drop ΔV_i for this charging cycle using the formula: ΔV_i = V_full_i - V_rest_i.

[0028] Voltage drop ΔV_i is a quantitative representation of the self-discharge rate of a battery cell after it has been left to stand at rest for a period of time in a fully charged state. For normal battery cells, due to the low self-discharge rate, ΔV_i usually remains within a small and stable range; however, for battery cells with micro-short circuit faults, the self-discharge rate will be significantly accelerated due to the presence of tiny leakage channels inside, resulting in an abnormally large increase in ΔV_i.

[0029] S102. Retrieve the adaptive reference model for each cell, and compare the current voltage drop with the voltage drop threshold of the adaptive reference model of the cell. The adaptive reference model of the cell is constructed based on the cell's multiple historical voltage drops.

[0030] After calculating the voltage drop ΔV_i for each cell in this cycle, the battery management system retrieves the pre-established and continuously updated adaptive baseline model for that cell from memory. The adaptive baseline model is based on the voltage drop of each full charge of the cell and is used to characterize the voltage drop variation of the cell during normal aging.

[0031] The historical moving average value ΔV_avg_i and standard deviation σ_i of the battery cell are obtained by using an adaptive benchmark model, and then the voltage drop threshold Th_i is determined.

[0032] Th_i = ΔV_avg_i + K × σ_i. Where K is the confidence coefficient. When K is 3, the voltage drop threshold corresponds to a 99.7% confidence interval, meaning that the voltage drop of a normal battery cell has a 99.7% probability of falling below this threshold. As an example, K is set to 3 to minimize the false alarm rate while ensuring detection sensitivity.

[0033] The battery management system performs a comparison operation for each cell i to determine whether the voltage drop ΔV_i exceeds its corresponding voltage drop threshold Th_i.

[0034] S103. If the voltage drop deviates abnormally from the voltage drop threshold, it is determined that the corresponding cell has a micro short circuit risk, triggering a short circuit warning for the cell to identify the faulty cell in the battery pack.

[0035] The comparison operation is the basis for determining micro-short circuits. If the above inequality holds, it indicates that the voltage drop of cell i after this charging is significantly abnormal, and its self-discharge rate far exceeds the range allowed by its normal aging trend. It is preliminarily determined that the cell has a micro-short circuit abnormality risk.

[0036] It should be noted that abnormal deviations are not simply compared with fixed thresholds or adjacent cells, but with the historical trends of the cells themselves, which makes it possible to effectively distinguish between voltage drop increases caused by normal aging and voltage drop abrupt changes caused by micro-short circuits.

[0037] Increased voltage drop due to normal aging: This is manifested as a slow and steady rise in ΔV_avg_i, with ΔV_i fluctuating within a reasonable range around the average value without any abnormal deviation.

[0038] Sudden voltage drop caused by micro-short circuit faults: This manifests as a significant increase in ΔV_i relative to recent historical data, exceeding the fluctuation range and thus showing abnormal deviation.

[0039] If the voltage drop deviates abnormally from the voltage drop threshold, the corresponding cell is deemed to have a micro-short circuit risk, triggering a short circuit warning for that cell to identify the faulty cell within the battery pack. As an example, the short circuit warning includes three levels: Level 3: Caution; Level 2: Warning; Level 1: Critical.

[0040] In the above embodiments, the self-discharge characteristics of lithium batteries after being fully charged and left to stand are utilized. An adaptive benchmark model monitors minute voltage changes in each cell, enabling early identification and warning of micro-short-circuit faults. This achieves non-destructive online battery monitoring without increasing hardware costs, using only existing voltage and temperature sensors.

[0041] See Figure 2 , Figure 2 This is a schematic diagram of the process for updating the adaptive baseline model according to an embodiment of the present invention. Specifically, it includes: S201. After the battery cell completes one charge, the voltage drop of the battery cell at this time is stored in the adaptive reference model as historical voltage drop data, and the voltage drop with the earliest acquisition time in the adaptive reference model is deleted.

[0042] For each cell i, the adaptive baseline model maintains a voltage drop database, which stores the voltage drop data corresponding to the cell's most recent N complete charging cycles, denoted as {ΔV_i(1), ΔV_i(2), ..., ΔV_i(N)}, where ΔV_i(1) is the earliest saved data and ΔV_i(N) is the most recently saved data. This database is continuously updated as the cell is used, thus reflecting the cell's aging status in real time. As an example, N is set to 20. That is, after a cell completes one charge, the current voltage drop is stored in the adaptive baseline model as historical voltage drop data, and voltage drops collected outside the set time range are deleted. For example, the set time range includes the time period corresponding to the most recent N voltage drops.

[0043] S202. Using the historical voltage drop in the adaptive benchmark model, the moving average and standard deviation of the historical voltage drop of the battery cell are determined again to update the voltage drop threshold of the adaptive benchmark model and realize the synchronization between the adaptive benchmark model and the aging state of the battery cell.

[0044] Based on the voltage drop database, the historical moving average and standard deviation of voltage drop corresponding to the adaptive benchmark model are determined again.

[0045] Historical voltage drop moving average: represents the average self-discharge level of cell i under recent normal aging conditions: ΔV_avg_i = (1 / N) × ΣΔV_i(j), where j=1 to N.

[0046] Historical voltage drop standard deviation: indicates the degree of self-discharge fluctuation of cell i during the recent normal aging process, reflecting the dispersion of the data.

[0047] Based on the above statistical characteristic values, the adaptive benchmark model determines the voltage drop threshold to determine whether the voltage drop is abnormal.

[0048] The adaptive baseline model does not use a fixed threshold, but rather updates dynamically based on the historical data of the battery cell itself. As the battery age increases, normal aging phenomena such as increased internal resistance and capacity decay occur, and the self-discharge rate of the battery cell will naturally and slowly increase, which is reflected in the historical voltage drop data as a gradual increase in ΔV_avg_i. By continuously tracking this trend and updating the voltage drop threshold, the model effectively distinguishes between normal aging and sudden micro-short circuit faults, fundamentally solving the problem of high false alarm rates associated with fixed thresholds.

[0049] An adaptive benchmark model is established and maintained individually for each battery cell, fully considering the differences in electrochemical characteristics between individual cells due to variations in manufacturing processes, usage environments, and aging levels. Compared to models based on the overall average value of the battery pack, the adaptive benchmark model enables more accurate fault diagnosis and avoids misjudgments caused by individual cell differences.

[0050] After each charge is completed, the voltage drop is stored in the voltage drop database, while the earliest voltage drop is deleted. The size of the voltage drop database is kept constant at N times the voltage drop corresponding to the cycle, ensuring that the adaptive benchmark model always reflects the most recent state of the cell and can capture aging trends in a timely manner.

[0051] See Figure 3 , Figure 3 This is a schematic flowchart illustrating the real-time surface temperature of a battery cell during the resting phase, according to an embodiment of the present invention. Specifically, it includes the following steps: S301. Simultaneously monitor the real-time surface temperature of each cell during the resting stage and calculate the surface temperature rise of the cell during the resting stage.

[0052] To determine the risk of micro-short circuit anomalies in the battery cell, multi-source information is further introduced. By synchronously monitoring the surface temperature change of the battery cell during the resting stage, the judgment results are cross-validated, and the warning level is dynamically adjusted according to the temperature anomaly, thereby significantly improving the reliability and accuracy of the warning.

[0053] During the resting phase of the battery cell, from the first moment T0 to the second moment T0+T, the battery management system monitors the voltage changes and simultaneously monitors the real-time surface temperature of each battery cell during the resting phase.

[0054] Initial temperature recording: At the end of charging, T0, the battery management system collects the initial surface temperature of each cell i by using temperature sensors set on the surface of each cell, and records it as T_start_i.

[0055] Real-time temperature monitoring: During the entire resting time T, the battery management system continuously collects the real-time surface temperature of each cell at a preset sampling frequency.

[0056] Temperature rise calculation: When the resting phase ends and the second time point T0+T is reached, the battery management system records the final surface temperature T_end_i of each cell i and calculates the surface temperature rise value ΔT_i for each cell during the resting phase, ΔT_i = T_end_i - T_start_i. The surface temperature rise value ΔT_i characterizes the degree of temperature rise of the cell during the resting phase due to the thermal effects caused by internal chemical reactions and possible micro-short-circuit leakage current.

[0057] S302. If a cell is determined to be at risk of micro-short circuit, and the surface temperature rise exceeds the preset cell temperature rise threshold, the short circuit warning level will be increased. The short circuit warning includes voltage warning and temperature rise warning.

[0058] A preset temperature rise threshold Th_T is set for each cell. During the current resting phase, the average temperature rise ΔT_avg and standard deviation σ_T of all cells in the battery pack are calculated. The temperature rise threshold is: Th_T = ΔT_avg + K_T × σ_T, where K_T is the temperature confidence coefficient. As an example, K_T is set to 2 or 3.

[0059] If a battery cell is identified as having a micro-short circuit risk and its surface temperature rise exceeds a preset cell temperature rise threshold, it indicates that the cell is experiencing both voltage and temperature anomalies, significantly enhancing the reliability of micro-short circuit fault diagnosis. The short circuit warning level is raised by one level. For example, if the original warning level was Level 3 (Caution), it is upgraded to Level 2 (Warning). Simultaneously, a temperature rise warning is added to the short circuit warning, meaning the short circuit warning now includes both voltage and temperature warnings, clearly indicating the presence of a thermal anomaly risk.

[0060] exist Figure 3 In this embodiment, temperature monitoring is introduced as an auxiliary criterion to upgrade the early warning system, thereby improving the accuracy and timeliness of micro-short circuit early warning.

[0061] See Figure 4 , Figure 4 This is a schematic diagram of a process for monitoring cell consistency according to an embodiment of the present invention. Specifically, it includes the following steps: S401. Calculate the average voltage drop of all series-connected cells in the battery pack to determine the consistency threshold.

[0062] In a series-connected battery pack, because the cells have highly consistent manufacturing processes and material characteristics, and are used under the same operating conditions, normally functioning cells should maintain good consistency. Within a normal battery pack, the voltage drop ΔV_i of the cells should be distributed within a relatively concentrated range over the same resting time.

[0063] When a battery cell experiences a micro-short circuit, an abnormal leakage path appears inside, leading to a significantly accelerated self-discharge rate. This is directly reflected in the cell's voltage drop ΔV_i deviating significantly from the voltage drop distribution range of other normal cells. By introducing a consistency threshold, lateral comparisons are performed to identify abnormal cells.

[0064] Once the lithium battery charging is complete, for a battery pack consisting of n cells connected in series, calculate the average voltage drop ΔV_avg_pack of all cells during this charging process, where ΔV_avg_pack = (1 / n) × ΣΔV_i, and i = 1 to n. This average voltage drop characterizes the overall level of self-discharge of the cells in the battery pack during the current charging process.

[0065] A consistency threshold, Th_consistency, is set based on the average voltage drop of the current voltage. The consistency threshold is M times the average voltage drop of the current voltage. M is the consistency factor. Extensive experimental data has verified that when M is 1.5, it can effectively identify early micro-short circuit anomalies while preventing normal cells from being misjudged due to normal fluctuations.

[0066] S402. If a cell is determined to be at risk of a micro-short circuit, and the voltage drop exceeds the consistency threshold, then the level of the short circuit warning will be increased.

[0067] If a cell is identified as having a micro-short circuit risk, and its voltage drop exceeds the consistency threshold, it indicates that cell i's voltage drop is significantly higher than other cells, exhibiting abnormal characteristics. This situation typically signifies the presence of a micro-short circuit within the cell, thus escalating the short circuit warning level.

[0068] exist Figure 4 In the embodiments, after determining that the corresponding cell has a micro-short circuit anomaly risk, the reliability and accuracy of micro-short circuit detection are further improved by calculating the characteristics of the voltage drop of all series-connected cells in the battery pack and constructing a consistency threshold for horizontal comparison.

[0069] See Figure 5 , Figure 5 This is a schematic diagram illustrating the process of implementing an early warning system according to an embodiment of the present invention. Specifically, it includes the following steps: S501. For cells identified as having a micro-short circuit risk, obtain their location code within the battery pack and simultaneously report the location code and short circuit warning level to the vehicle controller via the controller area network bus.

[0070] The battery management system (BMS) stores a cell mapping table, which records the correspondence between the location code and logical number of each cell. After determining that cell i has a micro-short circuit risk and setting the short circuit warning level, the corresponding location code for that cell is retrieved from the cell topology mapping table. The location code provides precise guidance for quickly locating the faulty cell.

[0071] The battery management system (BMS) communicates with the vehicle controller in real time via a Controller Area Network (CAN) bus. When a short-circuit warning is triggered and the location code of a minor short-circuit anomaly is obtained, the BMS encapsulates the warning information into a CAN message according to the CAN communication protocol and sends it to the vehicle controller via the bus. The warning information includes the location code and the short-circuit warning level.

[0072] S502: The vehicle controller displays a visual prompt message for battery faults on the vehicle dashboard that matches the short circuit warning level. At the same time, the location code and short circuit warning level are reported to the cloud monitoring platform through the vehicle remote information processing terminal, realizing the warning of both local vehicle warning and cloud remote monitoring.

[0073] After receiving the CAN message, the vehicle controller parses the location code and short-circuit warning level. Based on the different short-circuit warning levels, it displays differentiated visual prompts on the vehicle's instrument panel, providing the driver with intuitive and clear fault warnings. For example: "Battery system fault, there is a risk of micro-short circuit; please contact maintenance as soon as possible."

[0074] While reporting to the vehicle controller, the location code and short circuit warning level are also reported to the cloud monitoring platform in real time through the vehicle-mounted telematics box (T-Box), realizing the warning of both local vehicle warning and remote cloud monitoring.

[0075] exist Figure 5 In the embodiments, for battery cells with micro-short circuit anomalies, after generating corresponding warning levels, the warning information is further reported and displayed, realizing the coordinated linkage between vehicle-mounted local warning and cloud-based remote monitoring.

[0076] In one embodiment of the present invention, the powerful computing capabilities and data storage advantages of the cloud monitoring platform are utilized to analyze the reported short-circuit warnings.

[0077] The core advantage of the cloud-based monitoring platform lies in its ability to aggregate all historical data throughout the battery's entire lifecycle, analyzing macro trends and uncovering micro-level characteristics. For reported short-circuit warnings, the cloud-based monitoring platform retrieves historical voltage drop data from all past charging cycles of the battery cell for analysis, generating a micro-short-circuit fault report. This report includes fault cause analysis and handling suggestions. The micro-short-circuit fault report is then simultaneously pushed to vehicle terminals and / or user terminals, achieving multi-terminal collaborative information delivery.

[0078] See Figure 6 , Figure 6 This is a flowchart illustrating real-time operation for micro-short-circuit faults according to an embodiment of the present invention. Specifically, it includes the following steps: S601. Mark the battery cell as a suspected faulty cell and limit the charging current of the suspected faulty cell.

[0079] The battery management system (BMS) marks cell i as a suspected faulty cell in the fault management list and records the time of the first micro-short circuit anomaly and the short circuit warning level. For cell i marked as a suspected faulty cell, the BMS limits its charging current. For example, the maximum allowable charging current of the battery pack under normal conditions is 1C. After marking the cell as a suspected faulty cell, the maximum allowable charging current is limited to 0.3C.

[0080] S602. In subsequent lithium battery charging, if the suspected faulty cell is again determined to have a micro short circuit risk, the suspected faulty cell is confirmed to have a micro short circuit fault, and a command to disconnect the high voltage contactor is sent to the vehicle controller. At the same time, charging operation is prohibited for the module where the suspected faulty cell is located.

[0081] The battery management system continuously monitors potentially faulty cells during subsequent lithium battery charging. It employs... Figure 1 If the technical solution determines that the suspected faulty battery cell poses a risk of micro-short circuit anomaly again, then the suspected faulty battery cell is confirmed to have a micro-short circuit fault. A command to disconnect the high-voltage contactor is sent to the vehicle controller. For example, the battery management system sends a command to disconnect the high-voltage contactor to the vehicle controller via the CAN bus, requesting immediate disconnection of the high-voltage contactor. Simultaneously, charging operations on the module containing the suspected faulty battery cell are prohibited.

[0082] exist Figure 6 In this embodiment, while ensuring safety, overreaction due to a single anomaly is avoided, achieving a balance between detection accuracy and vehicle availability.

[0083] The following explanation uses an electric vehicle equipped with 96 series-connected battery cells as an example. The battery management system executes... Figure 1 The following details the steps involved in the process. The complete process of detection, assessment, warning, and follow-up handling is performed after the vehicle completes its 100th charging cycle.

[0084] When the battery management system detects that the charging current has dropped to C / 20 and reached the charging cutoff voltage, it determines that the charging is over. This moment is recorded as the first time point T0. The battery management system synchronously collects and records the full-charge voltage V_full_i of all 96 cells through the voltage sampling circuit.

[0085] After charging is complete, the battery enters a resting phase. The battery management system (BMS) sets the resting time to T = 30 minutes. During this period, the BMS continuously monitors the surface temperature of all cells at a sampling frequency of 1 time per minute and records the initial temperature T_start_i of each cell. After 30 minutes, at the second time point T0+T, the BMS again collects the resting voltage V_rest_i of all cells. For cell number 1, the fully charged voltage is 4.20V, and the resting voltage is 4.175V. The voltage drop ΔV_1 is calculated to be 4.20V - 4.175V = 25 mV. Simultaneously, the BMS calculates the temperature rise of cell number 1 based on the temperature monitoring data: initial temperature 25.0°C, final temperature 27.0°C, temperature rise ΔT_1 = 2.0°C.

[0086] The adaptive baseline model for each cell is retrieved, and the voltage drop of this cell is compared with the voltage drop threshold of the adaptive baseline model for that cell. The voltage drop threshold Th_1 is 14 mV. Comparing the current voltage drop with the voltage drop threshold: 25 mV > 14 mV, it is determined that cell No. 1 has a micro-short circuit anomaly risk.

[0087] The average temperature rise of all cells in the battery pack during the resting period was calculated to be 0.5°C, with a standard deviation of 0.2°C. A cell temperature rise threshold of 0.9°C was set. Cell #1 experienced a temperature rise of 2.0°C, far exceeding the cell temperature rise threshold, thus raising the short-circuit warning level.

[0088] The average voltage drop across all cells was calculated to be 9 mV, and the consistency threshold Th_consistency was set at 13.5 mV. Cell #1's voltage drop of 25 mV far exceeded the consistency threshold, thus necessitating an upgrade in the short-circuit warning level.

[0089] The battery management system (BMS) detected a micro-short circuit fault in cell #1, with the highest risk level: Level 1 Warning, severe. The BMS sends the short circuit warning to the vehicle controller via the CAN bus. The vehicle controller displays a flashing red battery fault icon in the main warning area of ​​the instrument panel, along with the text: "Battery fault, please contact maintenance immediately." The vehicle controller then reports the fault information to the cloud monitoring platform in real time via the onboard T-Box.

[0090] After arriving at the site, the maintenance personnel used a mobile terminal to view the micro-short circuit fault report pushed by the cloud monitoring platform and directly located cell number 1. They quickly inspected and replaced the module containing cell number 1.

[0091] See Figure 7 , Figure 7 This is a schematic diagram of the main structure of a battery short-circuit warning device according to an embodiment of the present invention. The battery short-circuit warning device can implement a battery short-circuit warning method. The battery short-circuit warning device specifically includes: The acquisition module 701 is used to monitor the end of lithium battery charging, acquire the full-charge voltage of each cell in the battery pack, and after controlling the lithium battery to enter the resting stage and continue for a preset time period, acquire the resting voltage of each cell, and determine the voltage drop of each cell based on the full-charge voltage and the resting voltage. The comparison module 702 is used to retrieve the adaptive reference model of each cell and compare the current voltage drop with the voltage drop threshold of the adaptive reference model of the cell. The adaptive reference model of the cell is constructed based on the cell's multiple historical voltage drops. The early warning module 703 is used to determine that there is a micro short circuit risk in the corresponding cell if the current voltage drop deviates abnormally from the voltage drop threshold, and to trigger a short circuit warning for the cell in order to identify the faulty cell in the battery pack.

[0092] In one embodiment of the present invention, the comparison module 702 is used to store the voltage drop of the battery cell as historical voltage drop data in the adaptive reference model after the battery cell completes one charge, and delete the voltage drop collected outside the set time range. By utilizing the historical voltage drop in the adaptive benchmark model, the moving average and standard deviation of the historical voltage drop of the battery cell are determined again to update the voltage drop threshold of the adaptive benchmark model, thereby achieving synchronization between the adaptive benchmark model and the aging state of the battery cell.

[0093] In one embodiment of the present invention, the acquisition module 701 is used to monitor the charging current of the lithium battery in real time. If the charging current of the battery cell is detected to drop below the preset charge-discharge rate, or the battery cell voltage is detected to reach the preset charging cut-off voltage, then the lithium battery charging is determined to be finished.

[0094] In one embodiment of the present invention, the acquisition module 701 is used to synchronously monitor the real-time surface temperature of each cell during the resting stage and calculate the surface temperature rise value of the cell during the resting stage. The early warning module 703 is used to raise the level of the short circuit warning if the surface temperature rise of a battery cell that is determined to be at risk of micro short circuit exceeds a preset battery cell temperature rise threshold. The short circuit warning includes voltage warning and temperature rise warning.

[0095] In one embodiment of the present invention, the early warning module 703 is used to calculate the average voltage drop of all series-connected cells in the battery pack to determine a consistency threshold. If a cell is determined to be at risk of a micro-short circuit, and the voltage drop exceeds the consistency threshold, then the level of the short circuit warning will be increased.

[0096] In one embodiment of the present invention, the early warning module 703 is used to obtain the location code of the battery cell that is determined to have a micro short circuit abnormality risk in the battery pack, and to synchronously report the location code and short circuit warning level to the vehicle controller through the controller local area network bus. The vehicle controller displays a visual prompt message for battery faults matching the short circuit warning level on the vehicle dashboard. At the same time, the location code and the short circuit warning level are reported to the cloud monitoring platform through the vehicle remote information processing terminal, realizing both local vehicle warning and cloud remote monitoring.

[0097] In one embodiment of the present invention, the early warning module 703 is used to mark the battery cell as a suspected faulty battery cell and limit the charging current of the suspected faulty battery cell; During subsequent lithium battery charging, if the suspected faulty cell is again determined to have a micro-short circuit risk, the suspected faulty cell is confirmed to have a micro-short circuit fault, and a command to disconnect the high-voltage contactor is sent to the vehicle controller. At the same time, charging operations are prohibited for the module containing the suspected faulty cell.

[0098] In one embodiment of the present invention, the early warning module 703 is used to control the cloud monitoring platform to receive the short circuit warning, analyze the historical voltage drop of the battery cell to generate a battery cell micro short circuit fault report, and simultaneously push the battery cell micro short circuit fault report to the vehicle terminal and / or user terminal.

[0099] The battery short-circuit warning device in this embodiment of the invention can be applied to vehicles.

[0100] Figure 8 An exemplary system architecture 800 is shown, in which the battery short-circuit warning method or device of embodiments of the present invention can be applied.

[0101] like Figure 8 As shown, the vehicle system architecture 800 may include various systems, such as a driving control system 801, a power system 802, a sensor system 803, a control system 804, a lane change assist system 805, one or more peripheral devices 806, a power supply 807, a computer system 808, and a user interface 809. The battery short-circuit warning method provided in this embodiment can be implemented through interaction with the aforementioned systems, or by controlling the systems through external devices, or by a robot driving the vehicle operating the systems. Optionally, the vehicle system architecture 800 may include more or fewer systems, and each system may include multiple components. Furthermore, each system and component of the vehicle system architecture 800 can be interconnected via wired or wireless means.

[0102] The vehicle system architecture 800 includes a driving control system 801, which can be in a fully or partially automated driving mode. For example, the driving control system 801 can automatically control the vehicle's movement based on control signals or control commands without interaction with a human, external devices, or a robot driving the vehicle.

[0103] The powertrain 802 may include components that provide power to the vehicle. For example, the powertrain 802 may include an engine, an energy source, a transmission, wheels, tires, etc. The engine may be an internal combustion engine, an electric motor, an air-compressed engine, or other combinations of engines, such as a hybrid engine consisting of a gasoline engine and an electric motor, or a hybrid engine consisting of an internal combustion engine and an air-compressed engine. The engine converts the energy source into mechanical energy to supply the transmission. Examples of energy sources may include gasoline, diesel, other petroleum-based fuels, propane, other compressed gas-based fuels, ethanol, solar panels, batteries, and other electrical sources. The energy source may also provide energy to other systems in the vehicle. Furthermore, the transmission may include a gearbox, a differential, a drive shaft, and a clutch, etc.

[0104] The sensor system 803 may include sensors for sensing the vehicle's surrounding environment (such as sensors for detecting the presence of obstacles) and pressure sensors for sensing the presence of passengers in the seats. Examples include a positioning system (which may be a Global Positioning System (GPS), BeiDou Navigation Satellite System, or other positioning systems), radar, a laser rangefinder, an inertial measurement unit (IMU), and cameras. The positioning system can be used to determine the vehicle's geographical location. The IMU is used to sense changes in the vehicle's position and orientation based on inertial acceleration. In one embodiment, the IMU may be a combination of an accelerometer and a gyroscope. The radar can use radio signals to sense objects in the vehicle's surrounding environment. In some embodiments, in addition to sensing objects, the radar can also be used to sense the speed and / or direction of travel of objects.

[0105] To detect environmental information and objects outside the vehicle, cameras can be configured at appropriate locations on the vehicle's exterior. For example, to acquire environmental images of the vehicle's sides, a camera can be mounted on the side mirror. The camera can be a still or video camera.

[0106] The control system 804 may include software systems for implementing vehicle driving control, such as systems for analyzing the vehicle's surrounding environment, pretensioning seat belts, route planning, obstacle avoidance, and image analysis. The control system 804 may also include hardware systems such as an accelerator, steering wheel system, seat belt system, airbag system, and peripheral devices (such as projection equipment and displays). Furthermore, the control system 804 may add or replace components other than those shown and described. Alternatively, some of the components shown above may be reduced.

[0107] In addition, the control system 804 can also interact with external sensors, other autonomous driving devices, other computer systems, or users via peripheral devices 806. Peripheral devices 806 may include wireless communication systems, on-board computers, microphones and / or speakers, cameras, and projectors, etc.

[0108] In some embodiments, peripheral device 806 provides a means for user interaction with the control system 804 via a user interface. For example, an onboard computer may provide information to a user of the vehicle. The user interface may also operate the onboard computer to receive user input. The onboard computer may be operated via a touchscreen. In other cases, peripheral device may provide a means for communicating with other devices located within the vehicle. For example, a microphone may receive audio (e.g., voice commands or other audio input) from a user of the control system. Similarly, a speaker may output audio to a user of the control system.

[0109] Wireless communication systems can communicate wirelessly with one or more devices, either directly or via a communication network. For example, wireless communication systems can use networks such as cellular networks, WiFi, and wireless local area networks (WLANs), or they can use infrared links, Bluetooth, or ZigBee to communicate directly with devices. Other wireless protocols include those used in various autonomous driving communication systems.

[0110] The power source 807 can provide power to various components of the vehicle. The power source 807 can be a rechargeable lithium-ion battery or a lead-acid battery.

[0111] The implementation of some or all of the functions of the battery short-circuit warning method is controlled by a computer system 808. The computer system 808 may include at least one processor that executes instructions stored in a non-transitory computer-readable medium such as memory. The computer system 808 provides the execution code for the battery short-circuit warning method to the aforementioned control system.

[0112] The processor can be any conventional processor, such as a commercially available central processing unit (CPU). Alternatively, the processor can be a special-purpose device such as an application-specific integrated circuit (ASIC) or other hardware-based processor. Those skilled in the art will understand that the processor, computer, or memory can actually include multiple processors, computers, or memories that may or may not be stored in the same physical housing. For example, memory can be a hard disk drive or other storage media located in a housing different from that of a computer. Therefore, references to processors or computers will be understood to include references to a collection of processors or computers or memories that may or may not operate in parallel. Unlike using a single processor to perform the steps described herein, some components, such as steering and deceleration components, may each have their own processor that performs only determinations related to the component's specific function.

[0113] User interface 809 is used to provide information to or receive information from users of the vehicle. Optionally, user interface 809 may include one or more input / output devices within a set of peripheral devices 806, such as wireless communication systems, on-board computers, microphones, and speakers.

[0114] It should be understood that the components described above are merely an example. In actual applications, components in the various modules or systems mentioned above may be added or removed as needed. Figure 8 This should not be construed as a limitation on the embodiments of this application.

[0115] The following is for reference. Figure 9 It shows a schematic diagram of the structure of a computer system 900 suitable for implementing a terminal device of the present invention. Figure 9 The terminal device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0116] like Figure 9 As shown, the computer system 900 includes a central processing unit (CPU) 901, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 902 or programs loaded from storage section 908 into random access memory (RAM) 903. The RAM 903 also stores various programs and data required for the operation of the system 900. The CPU 901, ROM 902, and RAM 903 are interconnected via a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0117] The following components are connected to I / O interface 905: an input section 906 including a keyboard, mouse, etc.; an output section 907 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 908 including a hard disk, etc.; and a communication section 909 including a network interface card such as a LAN card, modem, etc. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to I / O interface 905 as needed. A removable medium 911, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 910 as needed so that computer programs read from it can be installed into storage section 908 as needed.

[0118] In particular, according to the embodiments disclosed in this invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 909, and / or installed from removable medium 911. When the computer program is executed by central processing unit (CPU) 901, it performs the functions defined above in the system of this invention.

[0119] It should be noted that the computer-readable medium shown in this invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0120] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0121] The modules described in the embodiments of the present invention can be implemented in software or hardware. The described modules can also be housed in a processor; for example, a processor can be described as including a data acquisition module, a comparison module, and a warning module. The names of these modules do not necessarily limit the module itself. For example, the data acquisition module can also be described as "used to monitor the end of lithium battery charging, acquire the full-charge voltage of each cell in the battery pack, and after controlling the lithium battery to enter a resting phase and continuing for a preset time period, acquire the resting voltage of each cell, and determine the voltage drop of each cell based on the full-charge voltage and the resting voltage."

[0122] In another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiments; or it may exist independently and not assembled into the device. The computer-readable medium carries one or more programs, which, when executed by the device, cause the device to include: Once the lithium battery charging is completed, the full-charge voltage of each cell in the battery pack is collected. After the lithium battery enters the resting stage and continues for a preset period of time, the resting voltage of each cell is collected. Based on the full-charge voltage and the resting voltage, the voltage drop of each cell in this operation is determined. The adaptive reference model of each cell is retrieved, and the voltage drop of the current cell is compared with the voltage drop threshold of the adaptive reference model of the cell. The adaptive reference model of the cell is constructed based on the cell's multiple historical voltage drops. If the voltage drop deviates abnormally from the voltage drop threshold, it is determined that the corresponding cell has a micro-short circuit risk, triggering a short circuit warning for the cell to identify faulty cells in the battery pack.

[0123] According to the technical solution of the present invention, the voltage drop of the cell after the lithium battery charging is completed is monitored, and the cell is judged by the voltage drop threshold through the adaptive benchmark model corresponding to the cell to determine whether there is a micro short circuit risk in the cell. This can realize the early warning of micro short circuit in lithium battery and identify faulty cells in the battery pack.

[0124] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention. It should be noted that the acquisition, storage, and application of user personal information involved in the technical solutions of this disclosure comply with relevant laws and regulations and do not violate public order and good morals.

Claims

1. A battery short-circuit early warning method, characterized in that, include: Once the lithium battery charging is completed, the full-charge voltage of each cell in the battery pack is collected. After the lithium battery enters the resting stage and continues for a preset period of time, the resting voltage of each cell is collected. Based on the full-charge voltage and the resting voltage, the voltage drop of each cell in this operation is determined. The adaptive reference model of each cell is retrieved, and the voltage drop of the current cell is compared with the voltage drop threshold of the adaptive reference model of the cell. The adaptive reference model of the cell is constructed based on the cell's multiple historical voltage drops. If the voltage drop deviates abnormally from the voltage drop threshold, it is determined that the corresponding cell has a micro-short circuit risk, triggering a short circuit warning for the cell to identify faulty cells in the battery pack.

2. The battery short-circuit early warning method according to claim 1, characterized in that, The method further includes: After a battery cell completes one charge, the voltage drop of the battery cell at this time is stored in the adaptive reference model as historical voltage drop data, and voltage drops collected outside the set time range are deleted. By utilizing the historical voltage drop in the adaptive benchmark model, the moving average and standard deviation of the historical voltage drop of the battery cell are determined again to update the voltage drop threshold of the adaptive benchmark model, thereby achieving synchronization between the adaptive benchmark model and the aging state of the battery cell.

3. The battery short-circuit early warning method according to claim 1, characterized in that, The monitoring of the completion of lithium battery charging includes: The charging current of the lithium battery is monitored in real time. If the charging current of the cell drops below the preset charge / discharge rate, or the cell voltage reaches the preset charging cutoff voltage, the lithium battery charging is determined to be finished.

4. The battery short-circuit early warning method according to claim 1, characterized in that, After determining that the corresponding battery cell has a micro-short circuit anomaly risk, the following is also included: The real-time surface temperature of each cell during the resting phase is monitored synchronously, and the surface temperature rise of the cell during the resting phase is calculated. If a battery cell is determined to be at risk of a micro-short circuit and its surface temperature rise exceeds a preset cell temperature rise threshold, the level of the short circuit warning will be increased. The short circuit warning includes voltage warning and temperature rise warning.

5. The battery short-circuit early warning method according to claim 1 or 4, characterized in that, After determining that the corresponding battery cell has a micro-short circuit anomaly risk, the following is also included: Calculate the average voltage drop of all series-connected cells in the battery pack to determine the consistency threshold; If a cell is determined to be at risk of a micro-short circuit, and the voltage drop exceeds the consistency threshold, then the level of the short circuit warning will be increased.

6. The battery short-circuit early warning method according to claim 1, characterized in that, The method further includes: For cells identified as having a micro-short circuit risk, their location code within the battery pack is obtained, and the location code and short circuit warning level are simultaneously reported to the vehicle controller via the controller local area network bus. The vehicle controller displays a visual prompt message for battery faults matching the short circuit warning level on the vehicle dashboard. At the same time, the location code and the short circuit warning level are reported to the cloud monitoring platform through the vehicle remote information processing terminal, realizing both local vehicle warning and cloud remote monitoring.

7. The battery short-circuit early warning method according to claim 1, characterized in that, After determining that the corresponding battery cell has a micro-short circuit anomaly risk, the following is also included: The battery cell is marked as a suspected faulty cell, and the charging current of the suspected faulty cell is limited; During subsequent lithium battery charging, if the suspected faulty cell is again determined to have a micro-short circuit risk, the suspected faulty cell is confirmed to have a micro-short circuit fault, and a command to disconnect the high-voltage contactor is sent to the vehicle controller. At the same time, charging operations are prohibited for the module containing the suspected faulty cell.

8. The battery short-circuit early warning method according to claim 1, characterized in that, The method further includes: After receiving the short circuit warning, the cloud monitoring platform analyzes the historical voltage drop of the battery cell to generate a battery cell micro short circuit fault report, and simultaneously pushes the battery cell micro short circuit fault report to the vehicle terminal and / or user terminal.

9. A device for battery short-circuit warning, characterized in that, include: The acquisition module is used to monitor the end of lithium battery charging, acquire the full-charge voltage of each cell in the battery pack, and after controlling the lithium battery to enter the resting stage and continue for a preset period of time, acquire the resting voltage of each cell, and determine the voltage drop of each cell based on the full-charge voltage and the resting voltage. The comparison module is used to retrieve the adaptive reference model of each cell and compare the current voltage drop with the voltage drop threshold of the adaptive reference model of the cell. The adaptive reference model of the cell is constructed based on the cell's multiple historical voltage drops. The early warning module is used to determine that there is a micro short circuit risk in the corresponding cell if the current voltage drop deviates abnormally from the voltage drop threshold, and to trigger a short circuit warning for the cell in order to identify the faulty cell in the battery pack.

10. A vehicle, characterized in that, Includes the battery short circuit warning device as described in claim 9.

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