Battery voltage abnormality diagnosis method

Abstract

The invention provides a battery voltage abnormity diagnosis method. The battery voltage abnormity diagnosis method comprises the following steps: acquiring voltage values and temperature values of all battery cells of a battery pack; judging whether the battery pack is in an overvoltage state or not according to the voltage value, and judging whether the battery pack is in an undervoltage state or not according to the voltage value and the temperature value; if it is judged that the battery pack is in the overvoltage state, the voltage value and the position information of the battery cell in the overvoltage state are output, and if it is judged that the battery pack is in the undervoltage state, the voltage value and the position information of the battery cell in the undervoltage state are output. According to the technical scheme, the battery voltage abnormity diagnosis method can solve the problem that the recognition accuracy of the battery voltage abnormity in the prior art is low.

Description

Technical Field

[0001] The present invention relates to the technical field of batteries, and in particular, to a method for diagnosing abnormal battery voltage. Background Art

[0002] In the context of the rapidly changing technology today, the new energy industry is booming at an unprecedented speed. As an important part of the new energy field, new energy vehicles are developing particularly rapidly. While the power battery industry is advancing by leaps and bounds, battery safety issues have become increasingly prominent and have become one of the key factors restricting the further development of new energy vehicles. At present, lithium batteries dominate the power battery field. However, due to the special nature of their constituent materials, once external conditions are met, safety accidents may be induced. Therefore, in order to reduce the risk of battery safety accidents and improve the overall safety of power batteries, we must take practical and effective measures. Voltage, as an important characteristic data of power batteries, has important practical significance for the diagnosis of its abnormalities. By monitoring the battery voltage, potential abnormal conditions can be detected in a timely manner, so that preventive measures can be taken before a failure occurs. Voltage abnormality may be a precursor to battery failure. If not controlled, it may lead to battery overheating or even fire, seriously threatening the safety of the vehicle and passengers.

[0003] However, the commonly used method for diagnosing abnormal power battery voltage is to analyze and diagnose the battery voltage data collected by the battery management system BMS. The voltage abnormality diagnosis usually only simply identifies the under-voltage or over-voltage of a single battery cell, and the recognition accuracy of battery voltage abnormality is relatively low. Summary of the Invention

[0004] The main object of the present invention is to provide a method for diagnosing abnormal battery voltage, which can solve the problem of relatively low recognition accuracy of battery voltage abnormality in the prior art.

[0005] To achieve the above object, the present invention provides a method for diagnosing abnormal battery voltage, including: obtaining the voltage values and temperature values of all battery cells in a battery pack; judging whether the battery pack is in an over-voltage state according to the voltage values, and judging whether the battery pack is in an under-voltage state by combining the voltage values and temperature values; if it is judged that the battery pack is in an over-voltage state, outputting the voltage values and the location information of the battery cells in the over-voltage state, and if it is judged that the battery pack is in an under-voltage state, outputting the voltage values and the location information of the battery cells in the under-voltage state.

[0006] With the above settings, on the one hand, through more comprehensive data collection, dual-parameter analysis, status classification, and accurate output of location information, the problem of low accuracy in identifying abnormal battery voltage in the prior art can be effectively solved, providing a more accurate and efficient method for battery health management and safe operation. On the other hand, based on the original data such as the voltage and temperature of the battery during actual operation, this application diagnoses and identifies abnormal voltage faults of the battery, realizes the accurate identification of potential voltage faults of the battery, and realizes the accurate identification of common voltage faults of the battery, which can effectively improve the battery usage efficiency and reduce the severity of battery safety accidents. In addition, starting from the voltage data of the battery operation, this application evaluates the abnormal battery voltage to ensure that the battery operates within the normal working range, guarantee the safe driving of the vehicle, discover battery risks in advance, take intervention measures in time, contain the deterioration and expansion of risks, reduce losses, and enhance the user experience. At the same time, the abnormal voltage diagnosis can assist in finding the fault point for targeted repair, thereby shortening the repair time and reducing the repair cost.

[0007] Further, the step of judging whether the battery pack is in an overvoltage state according to the voltage value includes: obtaining the maximum voltage value among all voltage values; if the maximum voltage value is not within the overvoltage range, the battery pack is not in an overvoltage state, and if the maximum voltage value is within the overvoltage range, the battery pack is in an overvoltage state.

[0008] With the above settings, it is possible to achieve rapid monitoring of the overvoltage state of the battery pack, avoiding the process of analyzing and comparing all cell voltage values, and greatly improving the efficiency and response speed of diagnosis. In addition, compared with the traditional method of analyzing the voltage of each cell separately, which is cumbersome and time-consuming, this application only needs to judge whether the maximum voltage value falls within the overvoltage range, simplifying the original judgment process. And once overvoltage is detected, the voltage value and location information of the cells in the overvoltage state are immediately output, enabling timely measures to be taken, such as stopping the charge and discharge operations, adjusting the battery management system strategy, etc., to avoid battery performance degradation, shortened lifespan, or more serious safety accidents caused by overvoltage, such as thermal runaway, explosion, etc.

[0009] Further, the overvoltage range includes a first overvoltage range, a second overvoltage range, and a third overvoltage range. If the maximum voltage value is within the first overvoltage range, the corresponding cell is in a first-level overvoltage state. If the maximum voltage value is within the second overvoltage range, the corresponding cell is in a second-level overvoltage state. If the maximum voltage value is within the third overvoltage range, the corresponding cell is in a third-level overvoltage state. The overvoltage degree of the first-level overvoltage state is less than that of the second-level overvoltage state, and the overvoltage degree of the second-level overvoltage state is less than that of the third-level overvoltage state.

[0010] Through the above settings, refined management of the overvoltage state of the battery cell can be achieved. This grading strategy can distinguish different degrees of overvoltage, facilitating the adoption of corresponding control measures, such as adjusting the charge and discharge strategies, limiting the charging voltage, or urgently cutting off the power supply in case of severe overvoltage, thereby effectively preventing battery performance damage and safety risks caused by overvoltage. The division of the overvoltage state from level 1 to level 3 provides a basis for the rational allocation of resources and the formulation of response strategies. For example, for the first-level overvoltage state, relatively mild measures can be taken, such as adjusting the charging current; while for the third-level overvoltage state, immediate emergency measures may be required, such as disconnecting the charging circuit.

[0011] Further, the first overvoltage range is (3700mv to 3750mv], the second overvoltage range is (3750mv to 3800mv], and the third overvoltage range is (3800mv to 4800mv).

[0012] Through the above settings, the overvoltage risk of the battery cell can be accurately evaluated. When the maximum voltage value is within the first overvoltage range, it indicates that the battery cell is in an overvoltage state but does not pose a serious threat. When the maximum voltage value is within the second overvoltage range, it indicates an increased overvoltage risk of the battery cell. When the maximum voltage value is within the third overvoltage range, it indicates a significant overvoltage risk of the battery cell, which may soon trigger battery safety problems. By setting different overvoltage ranges corresponding to different levels of overvoltage states, this strategy of adjusting the response according to the severity of overvoltage can more reasonably maintain battery safety.

[0013] Further, the steps of combining the voltage value and the temperature value to determine whether the battery pack is in an undervoltage state include: obtaining the minimum voltage value among all voltage values and the minimum temperature value among all temperature values; determining the temperature range where the minimum temperature value is located, and then judging whether the minimum voltage value is within the undervoltage range corresponding to the temperature range. If the minimum voltage value is within the undervoltage range corresponding to the temperature range, the battery pack is in an undervoltage state. If the minimum voltage value is not within the undervoltage range corresponding to the temperature range, the battery pack is not in an undervoltage state.

[0014] Through the above settings, it is possible to more accurately determine whether the battery cell is in an undervoltage state. Temperature has a significant impact on the voltage and performance of the battery. The undervoltage threshold of the battery may be different at different temperatures. Therefore, considering temperature helps to improve the accuracy of undervoltage identification and avoid misjudgment. In addition, traditional undervoltage judgment only relies on voltage values and ignores the impact of temperature on battery performance. Judging the undervoltage state by combining temperature values can effectively reduce false alarms or missed alarms caused by temperature changes and improve the reliability of battery state monitoring.

[0015] Furthermore, the temperature range includes a first temperature range, a second temperature range, and a third temperature range. Each of the first temperature range, the second temperature range, and the third temperature range corresponds to a first undervoltage range, a second undervoltage range, and a third undervoltage range. If the minimum voltage is within the first undervoltage range, the corresponding battery cell is in a first-level undervoltage state. If the minimum voltage is within the second undervoltage range, the corresponding battery cell is in a second-level undervoltage state. If the minimum voltage is within the third undervoltage range, the corresponding battery cell is in a third-level undervoltage state. And the degree of undervoltage in the first-level undervoltage state is less than that in the second-level undervoltage state, and the degree of undervoltage in the second-level undervoltage state is less than that in the third-level undervoltage state.

[0016] Through the above settings, refined monitoring of the battery cell state can be achieved. Each temperature range has a corresponding different undervoltage range, which means that at the same voltage, the undervoltage state of the battery cell may vary due to different ambient temperatures. This hierarchical monitoring mechanism can more accurately reflect the true state of the battery cell and avoid misjudgment that may be caused by a single threshold under different temperature conditions. The clear division of temperature ranges and undervoltage ranges helps improve the accuracy of fault diagnosis. The undervoltage state is a common precursor to battery faults and safety accidents, and the hierarchical undervoltage state judgment can enhance the sensitivity and response speed to such risks, so as to take different preventive and control measures according to the undervoltage state level of the battery cell, effectively avoiding the deterioration of the battery state.

[0017] Furthermore, the first temperature range is -30°C < T min ≤ 10°C, the second temperature range is 10°C < T min ≤ 20°C, and the third temperature range is 20°C < T min ≤ 125°C.

[0018] Through the above settings, the battery characteristics under different temperature environments can be monitored, improving the temperature sensitivity of diagnosis, and thus being able to more accurately identify the undervoltage state. The undervoltage ranges set under different temperature ranges take into account the voltage characteristics of the battery under specific temperature conditions. This comprehensive judgment based on temperature and voltage reduces false alarms caused by temperature changes and improves the accuracy of diagnosis. When the system detects an undervoltage state, it can quickly locate the possible cause of the fault according to the temperature range, such as performance degradation caused by low temperature or accelerated battery aging at high temperature, thereby providing more specific and effective maintenance suggestions, shortening the fault troubleshooting time, and reducing the maintenance cost.

[0019] Furthermore, the battery voltage abnormal diagnosis method further includes: if it is determined that the battery pack is not in an undervoltage or overvoltage state, then perform the step of judging the voltage consistency abnormality of the battery pack.

[0020] The above settings ensure a comprehensive diagnosis of the health status of the battery pack. Abnormal voltage consistency is a precursor to the deterioration of the internal health of the battery pack, which may be caused by various factors such as aging differences between cells, internal short circuits, poor contact, etc. Through the voltage consistency abnormality judgment steps, these problems can be discovered at an early stage and corresponding preventive measures can be taken to avoid potential safety risks and performance degradation.

[0021] Furthermore, the step of judging the voltage consistency anomaly of the battery pack includes: screening out the voltage abnormality value from all voltage values; calculating the voltage difference between the voltage abnormality value and the voltage maximum value; judging whether the voltage difference satisfies the judgment condition, if so, outputting the voltage value and position information of the corresponding battery cell, if not, there is no voltage consistency abnormality problem.

[0022] Through the above settings, the voltage difference between the abnormal voltage value and the maximum voltage is calculated, and combined with the judgment conditions, the voltage consistency abnormality of the battery pack can be judged.

[0023] Furthermore, the judgment conditions include: the voltage difference is greater than a preset value; all voltage abnormality values ​​and the remaining voltage values ​​are sorted from large to small, and all voltage abnormality values ​​are continuously arranged at the end of the voltage value sorting sequence; and the voltage abnormality values ​​are screened out multiple times and all voltage abnormality values ​​and the remaining voltage values ​​are sorted from large to small, and all voltage abnormality values ​​are at the end of the voltage value sorting sequence for a preset number of times.

[0024] Through the above settings, false alarms caused by small voltage differences are avoided and the accuracy of judgment is improved. The voltage abnormal value is required to be arranged at the end of the voltage value sorting sequence and to continuously meet the preset number of times in multiple judgments, which increases the stability of the judgment process. Occasional voltage abnormal values ​​may be caused by measurement errors or instantaneous condition changes. Continuous abnormal value arrangement is more likely to reflect the real voltage consistency problem, thereby avoiding misjudgment.

[0025] Furthermore, the step of screening out abnormal voltage values ​​includes: using the formula: Filter abnormal voltage values, where x i is the voltage value of the battery cell, Represents the average voltage of all cells, n is the number of cells in the battery pack, if the voltage value of the cell is or Then the voltage value is an abnormal voltage value.

[0026] Through the above settings, abnormal values ​​of the cell voltage that deviate from the normal range can be accurately identified, providing an accurate data basis for subsequent fault diagnosis. The 3σ principle helps reduce the situation where voltage fluctuations caused by accidental factors are misjudged as abnormal.

[0027] Applying the technical solution of the present invention to obtain the voltage values and temperature values of all the battery cells in the battery pack ensures that the diagnostic method can be analyzed based on a complete data set, avoiding diagnostic deviations caused by incomplete data. Different from the diagnostic method that solely relies on voltage values, this application combines voltage values and temperature values to judge the undervoltage state, improving the comprehensiveness and accuracy of the diagnosis. Especially under complex working conditions, it can more accurately identify the undervoltage situation. This application not only judges the overvoltage state or undervoltage state, but also can further output the specific voltage values and location information of the battery cells in the abnormal state, facilitating quick response and handling. In summary, this application can effectively solve the problem of low accuracy in identifying abnormal battery voltages in the prior art through more comprehensive data collection, dual-parameter analysis, state classification, and accurate output of location information. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The accompanying drawings forming a part of this invention are used to provide a further understanding of the invention. The illustrative embodiments and descriptions thereof of the invention are used to explain the invention and do not constitute an improper limitation of the invention. In the drawings:

[0029] Figure 1 The flowchart of the battery voltage abnormal diagnosis method according to the embodiment of the present invention is shown. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0030] It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the drawings and in combination with the embodiments.

[0031] As Figure 1 shown, the present invention provides a battery voltage abnormal diagnosis method, which includes: obtaining the voltage values and temperature values of all the battery cells in the battery pack; judging whether the battery pack is in an overvoltage state according to the voltage values, and judging whether the battery pack is in an undervoltage state by combining the voltage values and temperature values; if it is judged that the battery pack is in an overvoltage state, outputting the voltage values and the location information of the battery cells in the overvoltage state, and if it is judged that the battery pack is in an undervoltage state, outputting the voltage values and the location information of the battery cells in the undervoltage state.

[0032] In this embodiment, the voltage values and temperature values of all the battery cells in the battery pack are obtained, which ensures that the diagnostic method can be analyzed based on a complete data set and avoids diagnostic deviations caused by incomplete data. Different from the diagnostic method that simply relies on voltage values, this application combines voltage values and temperature values to determine the undervoltage state. Temperature has a significant impact on battery performance. Especially under extreme temperature conditions, the voltage change of the battery may be very different from that under normal temperature. By considering both voltage and temperature simultaneously, the comprehensiveness and accuracy of the diagnosis are improved. Especially under complex working conditions, the undervoltage situation can be identified more accurately. This application not only determines the overvoltage state or undervoltage state, but also can further output the specific voltage values and position information of the battery cells in the abnormal state, which is convenient for quick response and processing. To sum up, this application can effectively solve the problem of low accuracy in identifying abnormal battery voltages in the prior art through more comprehensive data collection, dual-parameter analysis, state classification, and accurate output of position information, and provides a more accurate and efficient method for battery health management and safe operation.

[0033] Battery voltage abnormal faults mainly include battery undervoltage, battery overvoltage, and voltage consistency abnormality. Based on the original data such as the voltage and temperature of the actual operation of the battery, this application diagnoses and identifies the battery voltage abnormal faults, realizes the accurate identification of potential voltage faults of the battery, realizes the accurate identification of common voltage faults of the battery, can effectively improve the use efficiency of the battery, and reduce the severity of battery safety accidents. In addition, starting from the voltage data of the battery operation, this application evaluates the battery voltage abnormality to ensure that the battery operates within the normal working range, ensures the safe driving of the vehicle, discovers battery risks in advance, takes intervention measures in time, curbs the deterioration and expansion of the risks, reduces losses, and improves the user experience. At the same time, voltage abnormality diagnosis can assist in finding the fault point for targeted maintenance, thereby shortening the maintenance time and reducing the maintenance cost.

[0034] In one embodiment of the present invention, the steps of determining whether the battery pack is in an overvoltage state according to the voltage value include: obtaining the maximum voltage value among all the voltage values; if the maximum voltage value is not within the overvoltage range, the battery pack is not in an overvoltage state, and if the maximum voltage value is within the overvoltage range, the battery pack is in an overvoltage state.

[0035] In this embodiment, the maximum voltage value among all the voltage values is obtained. If the maximum voltage value is not within the overvoltage range, the battery cells with smaller remaining voltage values must not be in the overvoltage range, and the battery pack is not in the overvoltage state. If the maximum voltage value is within the overvoltage range, it means that the battery pack is in the overvoltage state. Through the above settings, the rapid detection of the overvoltage state of the battery pack can be realized, avoiding the process of analyzing and comparing the voltage values of all battery cells, and greatly improving the efficiency and response speed of the diagnosis.

[0036] In addition, compared with the traditional method of analyzing the voltage of each battery cell individually, which is cumbersome and time-consuming, the present application only needs to determine whether the maximum voltage falls within the overvoltage range, simplifying the original judgment process. Moreover, once overvoltage is detected, the voltage value and location information of the battery cell in the overvoltage state are immediately output, enabling timely measures to be taken, such as stopping the charge and discharge operations, adjusting the battery management system strategy, etc., to avoid a decline in battery performance, shortening of lifespan, or more serious safety accidents caused by overvoltage, such as thermal runaway, explosion, etc.

[0037] In one embodiment of the present invention, the overvoltage range includes a first overvoltage range, a second overvoltage range, and a third overvoltage range. If the maximum voltage is within the first overvoltage range, the corresponding battery cell is in a first-level overvoltage state. If the maximum voltage is within the second overvoltage range, the corresponding battery cell is in a second-level overvoltage state. If the maximum voltage is within the third overvoltage range, the corresponding battery cell is in a third-level overvoltage state. The overvoltage degree of the first-level overvoltage state is less than that of the second-level overvoltage state, and the overvoltage degree of the second-level overvoltage state is less than that of the third-level overvoltage state.

[0038] In this embodiment, by setting three different overvoltage ranges, refined management of the overvoltage state of the battery cells can be achieved. This grading strategy can distinguish different degrees of overvoltage, facilitating the adoption of corresponding control measures, such as adjusting the charge and discharge strategy, limiting the charging voltage, or emergently cutting off the power supply in case of severe overvoltage, thereby effectively preventing battery performance damage and safety risks caused by overvoltage. The division of the overvoltage state from the first level to the third level provides a basis for the reasonable allocation of resources and the formulation of response strategies. For example, for the first-level overvoltage state, relatively mild measures can be taken, such as adjusting the charging current; while for the third-level overvoltage state, immediate emergency measures may be required, such as disconnecting the charging circuit.

[0039] In one embodiment of the present invention, the first overvoltage range is (3700mv to 3750mv], the second overvoltage range is (3750mv to 3800mv], and the third overvoltage range is (3800mv to 4800mv).

[0040] In this embodiment, by setting specific voltage intervals, the overvoltage risk of the battery cells can be accurately evaluated. When the maximum voltage is within the first overvoltage range, it indicates that the battery cell is in an overvoltage state but does not pose a serious threat. When the maximum voltage is within the second overvoltage range, it indicates that the overvoltage risk of the battery cell increases. When the maximum voltage is within the third overvoltage range, it indicates that the battery cell has a significant overvoltage risk and may soon cause battery safety problems. By setting different overvoltage ranges corresponding to different levels of overvoltage states, this strategy of adjusting the response according to the severity of overvoltage can more reasonably maintain battery safety.

[0041] In one embodiment of the present invention, the steps of determining whether the battery pack is in an undervoltage state by combining the voltage value and the temperature value include: obtaining the minimum voltage value among all the voltage values, and obtaining the minimum temperature value among all the temperature values; determining the temperature range where the minimum temperature value is located, and then determining whether the minimum voltage value is within the undervoltage range corresponding to the temperature range. If the minimum voltage value is within the undervoltage range corresponding to the temperature range, the battery pack is in an undervoltage state. If the minimum voltage value is not within the undervoltage range corresponding to the temperature range, the battery pack is not in an undervoltage state.

[0042] In this embodiment, obtaining the minimum voltage value among all the voltage values and the minimum temperature value among all the temperature values, then determining the temperature range where the minimum temperature value is located, and then determining whether the minimum voltage value is within the undervoltage range corresponding to the temperature range can more accurately determine whether the battery cell is in an undervoltage state. Temperature has a significant impact on the voltage and performance of the battery. The undervoltage threshold of the battery may be different at different temperatures. Therefore, considering temperature helps to improve the accuracy of undervoltage identification and avoid misjudgment. In addition, traditional undervoltage judgment only relies on the voltage value and ignores the influence of temperature on the battery performance. Judging the undervoltage state by combining the temperature value can effectively reduce false alarms or missed alarms caused by temperature changes and improve the reliability of battery state monitoring.

[0043] In one embodiment of the present invention, the temperature range includes a first temperature range, a second temperature range, and a third temperature range. The first temperature range, the second temperature range, and the third temperature range all correspond to a first undervoltage range, a second undervoltage range, and a third undervoltage range. If the minimum voltage value is within the first undervoltage range, the corresponding battery cell is in a first-level undervoltage state. If the minimum voltage value is within the second undervoltage range, the corresponding battery cell is in a second-level undervoltage state. If the minimum voltage value is within the third undervoltage range, the corresponding battery cell is in a third-level undervoltage state. And the undervoltage degree of the first-level undervoltage state is less than that of the second-level undervoltage state, and the undervoltage degree of the second-level undervoltage state is less than that of the third-level undervoltage state.

[0044] In this embodiment, by associating the temperature range with the undervoltage state level, refined monitoring of the battery cell state can be achieved. Each temperature range has a corresponding different undervoltage range, which means that at the same voltage, the undervoltage state of the battery cell may vary due to different ambient temperatures. This hierarchical monitoring mechanism can more accurately reflect the true state of the battery cell and avoid misjudgment that may be caused by a single threshold under different temperature conditions. The clear division of the temperature range and the undervoltage range helps to improve the accuracy of fault diagnosis. The undervoltage state is a common precursor to battery failures and safety accidents, and the hierarchical undervoltage state judgment can enhance the sensitivity and response speed to such risks, so as to take different preventive and control measures according to the undervoltage state level of the battery cell and effectively avoid the deterioration of the battery state.

[0045] In one embodiment of the present invention, the first temperature range is -30°C < T min ≤ 10°C, the second temperature range is 10°C < T min ≤ 20°C, and the third temperature range is 20°C < T min ≤ 125°C.

[0046] In this embodiment, by subdividing the temperature range, it is possible to monitor the battery characteristics under different temperature environments, improving the temperature sensitivity of the diagnosis, and thus being able to more accurately identify the undervoltage state. The undervoltage ranges set for different temperature ranges take into account the voltage characteristics of the battery under specific temperature conditions. This comprehensive judgment based on temperature and voltage reduces false alarms caused by temperature changes and improves the accuracy of the diagnosis. When the system detects an undervoltage state, it can quickly locate the possible cause of the fault according to the temperature range, such as performance degradation caused by low temperature or accelerated battery aging at high temperature, thereby providing more specific and effective maintenance suggestions, shortening the troubleshooting time, and reducing the maintenance cost.

[0047] In one embodiment of the present invention, the first undervoltage range corresponding to the first temperature range is V min ≤ 2.2V, the second undervoltage range corresponding to the first temperature range is V min ≤ 2.0V, the third undervoltage range corresponding to the first temperature range is V min ≤ 1.8V, the first undervoltage range corresponding to the second temperature range is V min ≤ 2.4V, the second undervoltage range corresponding to the second temperature range is V min ≤ 2.3V, the third undervoltage range corresponding to the second temperature range is V min ≤ 2.1V, the first undervoltage range corresponding to the third temperature range is V min ≤ 2.6V, the second undervoltage range corresponding to the third temperature range is V min ≤ 2.5V, the third undervoltage range corresponding to the third temperature range is V min ≤ 2.3V.

[0048] It should be noted that the undervoltage ranges and overvoltage ranges of the above first temperature range, second temperature range, and third temperature range are applicable to the diagnosis of 110Ah lithium iron phosphate batteries.

[0049] In one embodiment of the present invention, the battery voltage abnormal diagnosis method further includes: if it is determined that the battery pack is not in an undervoltage or overvoltage state, then perform the step of judging the voltage consistency abnormality of the battery pack.

[0050] In this embodiment, after confirming that the battery pack has no undervoltage or overvoltage faults, continuing to check for voltage consistency anomalies can ensure a comprehensive diagnosis of the health status of the battery pack. Voltage consistency anomalies are a precursor to the deterioration of the internal health of the battery pack, which may be caused by various factors such as aging differences between cells, internal short circuits, poor contact, etc. Through the voltage consistency anomaly judgment step, these problems can be discovered at an early stage, and corresponding preventive measures can be taken to avoid potential safety risks and performance degradation.

[0051] In one embodiment of the present invention, the step of judging the voltage consistency anomaly of the battery pack includes: screening out the voltage abnormality value from all voltage values; calculating the voltage difference between the voltage abnormality value and the voltage maximum value; judging whether the voltage difference satisfies the judgment condition, if the judgment condition is met, outputting the voltage value and position information of the corresponding battery cell, if not, there is no voltage consistency abnormality problem.

[0052] In this embodiment, the voltage difference between the abnormal voltage value and the maximum voltage is calculated, and combined with the judgment conditions, it is possible to judge whether the voltage consistency of the battery pack is abnormal.

[0053] In one embodiment of the present invention, the judgment conditions include: the voltage difference is greater than a preset value; all voltage abnormality values ​​and the remaining voltage values ​​are sorted from large to small, and all voltage abnormality values ​​are continuously arranged at the end of the voltage value sorting sequence; and the voltage abnormality values ​​are screened out multiple times and all voltage abnormality values ​​and the remaining voltage values ​​are sorted from large to small, and all voltage abnormality values ​​are at the end of the voltage value sorting sequence for a preset number of times.

[0054] In this embodiment, the setting of the above judgment conditions avoids false alarms caused by slight voltage differences and improves the accuracy of judgment. It is required that the voltage abnormal value is arranged at the end of the voltage value sorting sequence and continuously meets the preset number of times in multiple judgments, which increases the stability of the judgment process. Occasional voltage abnormal values ​​may be caused by measurement errors or instantaneous condition changes. Continuous abnormal value arrangement is more likely to reflect the real voltage consistency problem, thereby avoiding misjudgment.

[0055] It should be noted that in the prior art, the commonly used diagnostic method for abnormal power battery voltage is to analyze and diagnose the collected battery voltage data based on the battery management system BMS. Due to the shortcomings of BMS in complex computing capabilities, the voltage abnormality diagnosis usually only performs simple identification of undervoltage or overvoltage of a single battery cell, and the identification accuracy is low. However, this application uses abnormal value identification and rule judgment based on the characteristics of battery voltage data to identify and diagnose battery voltage abnormalities. This application mines and analyzes the characteristics of the battery voltage data based on the battery terminal data, and diagnoses and identifies the battery cells with abnormal voltage in the battery pack.

[0056] In one embodiment, the value of the preset number of times is greater than or equal to eight times.

[0057] In one embodiment of the present invention, the step of screening out voltage abnormal values includes: using the formula: to screen the voltage abnormal values, where x i is the voltage value of the battery cell, represents the average value of the voltages of all the battery cells, n is the number of battery cells in the battery pack, and if the voltage value of the battery cell is within or then the voltage value is the voltage abnormal value.

[0058] In this embodiment, through the above steps, the abnormal values deviating from the normal range in the battery cell voltage can be accurately identified, providing an accurate data basis for subsequent fault diagnosis. The 3σ principle helps to reduce the situation where voltage fluctuations caused by accidental factors are misjudged as abnormal.

[0059] In one embodiment of the present invention, the step of obtaining the voltage values and temperature values of all the battery cells in the battery pack includes: performing data cleaning processing on the invalid values and abnormal values in the obtained voltage values and temperature values. The invalid values and abnormal values mainly clean the error values and invalid values in the acquisition, transmission, and decoding processes to eliminate misjudgments caused by abnormal values and invalid values.

[0060] In one embodiment of the present invention, after the step of screening out voltage abnormal values from all the voltage values, it includes: determining the positions of the abnormal values according to the voltage abnormal values, and recording and storing the voltage abnormal values and the positions of the abnormal values.

[0061] In one embodiment of the present invention, the value of the preset value in the judgment condition is the voltage difference corresponding to a 15% difference in the state of charge (SOC) between the battery cells. Specifically, according to the average temperature of the battery pack to be measured, the relationship between the open-circuit voltage (OCV) and SOC at the corresponding temperature can be found in the OCV-SOC table. In the non-plateau period (i.e., the two intervals of SOC from 0% to 30% and from 30% to 85%), find the voltage difference corresponding to a 15% difference in SOC.

[0062] It should be noted that the plateau period during the charge and discharge process of the battery refers to the interval where the SOC changes greatly but the voltage changes little. The voltage consistency judgment criteria inside and outside the plateau period may be different. Therefore, choosing the non-plateau period for voltage consistency abnormal judgment can more accurately reflect the influence of SOC differences on the voltage. The found voltage difference is used as the preset value in the judgment condition. The acquisition of the OCV-SOC table can adopt the means of the existing technology and will not be elaborated here. Since the lithium iron phosphate battery has a charge and discharge plateau period, that is, there is an interval where the battery SOC changes greatly and the voltage changes little, therefore, when the battery voltage abnormal diagnosis method of the present application is applied to lithium iron phosphate battery cells, it can only be used in the non-plateau period.

[0063] From the above description, it can be seen that the above embodiments of the present invention achieve the following technical effects: obtaining the voltage values and temperature values of all the battery cells in the battery pack, which ensures that the diagnostic method can be analyzed based on a complete data set, avoiding diagnostic deviations caused by incomplete data. Different from the diagnostic method that solely relies on voltage values, this application combines voltage values and temperature values to judge the undervoltage state, improving the comprehensiveness and accuracy of the diagnosis. Especially under complex working conditions, it can more accurately identify the undervoltage situation. This application not only judges the overvoltage state or undervoltage state, but also can further output the specific voltage values and position information of the battery cells in the abnormal state, facilitating rapid response and processing. In summary, this application can effectively solve the problem of low accuracy in identifying abnormal battery voltages in the prior art through more comprehensive data collection, dual-parameter analysis, state classification, and accurate output of position information.

[0064] Obviously, the above-described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0065] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0066] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for diagnosing abnormal battery voltage, characterized in that, Including: Obtain the voltage values and temperature values of all the battery cells in the battery pack; Judge whether the battery pack is in an overvoltage state according to the voltage values, and judge whether the battery pack is in an undervoltage state by combining the voltage values and the temperature values; If it is judged that the battery pack is in the overvoltage state, output the voltage value and the location information of the battery cell in the overvoltage state. If it is judged that the battery pack is in the undervoltage state, output the voltage value and the location information of the battery cell in the undervoltage state.

2. The battery voltage abnormal diagnosis method according to claim 1, wherein The step of judging whether the battery pack is in an overvoltage state according to the voltage values includes: Obtain the maximum voltage value among all the voltage values; If the maximum voltage value is not within the overvoltage range, the battery pack is not in an overvoltage state. If the maximum voltage value is within the overvoltage range, the battery pack is in the overvoltage state.

3. The battery voltage abnormal diagnosis method according to claim 2, characterized in that, The overvoltage range includes a first overvoltage range, a second overvoltage range, and a third overvoltage range. If the maximum voltage value is within the first overvoltage range, the corresponding battery cell is in a first-level overvoltage state. If the maximum voltage value is within the second overvoltage range, the corresponding battery cell is in a second-level overvoltage state. If the maximum voltage value is within the third overvoltage range, the corresponding battery cell is in a third-level overvoltage state. The overvoltage degree of the first-level overvoltage state is less than that of the second-level overvoltage state, and the overvoltage degree of the second-level overvoltage state is less than that of the third-level overvoltage state.

4. The battery voltage abnormal diagnosis method according to claim 3, characterized in that The first overvoltage range is (3700mv to 3750mv], the second overvoltage range is (3750mv to 3800mv], and the third overvoltage range is (3800mv to 4800mv).

5. The battery voltage abnormality diagnosis method according to any one of claims 1 to 4, characterized in that, The step of judging whether the battery pack is in an undervoltage state by combining the voltage values and the temperature values includes: Obtain the minimum voltage value among all the voltage values and the minimum temperature value among all the temperature values; Determine the temperature range where the minimum temperature value is located, and then judge whether the minimum voltage value is within the undervoltage range corresponding to the temperature range. If the minimum voltage value is within the undervoltage range corresponding to the temperature range, the battery pack is in the undervoltage state. If the minimum voltage value is not within the undervoltage range corresponding to the temperature range, the battery pack is not in the undervoltage state.

6. The battery voltage abnormal diagnosis method according to claim 5, characterized in that, The temperature range includes a first temperature range, a second temperature range, and a third temperature range. The first temperature range, the second temperature range, and the third temperature range all correspond to a first undervoltage range, a second undervoltage range, and a third undervoltage range. If the minimum voltage value is within the first undervoltage range, the corresponding battery cell is in a first-level undervoltage state. If the minimum voltage value is within the second undervoltage range, the corresponding battery cell is in a second-level undervoltage state. If the minimum voltage value is within the third undervoltage range, the corresponding battery cell is in a third-level undervoltage state. And the undervoltage degree of the first-level undervoltage state is less than that of the second-level undervoltage state, and the undervoltage degree of the second-level undervoltage state is less than that of the third-level undervoltage state.

7. The battery voltage abnormal diagnosis method according to claim 6, wherein The first temperature range is -30°C < T min ≤ 10°C, the second temperature range is 10°C < T min ≤ 20°C, and the third temperature range is 20°C < T min ≤ 125°C.

8. The battery voltage abnormal diagnosis method according to any one of claims 1 to 4, characterized in that The battery voltage abnormal diagnosis method further includes: if it is determined that the battery pack is not in the undervoltage or overvoltage state, then perform the step of judging the abnormal voltage consistency of the battery pack.

9. The battery voltage abnormal diagnosis method according to claim 8, wherein, The step of judging the abnormal voltage consistency of the battery pack includes: Screen out the abnormal voltage values from all the voltage values; Calculate the voltage difference between the abnormal voltage value and the maximum voltage value; Judge whether the voltage difference meets the judgment condition. If the judgment condition is met, output the voltage value and position information of the corresponding battery cell. If not, there is no problem with abnormal voltage consistency.

10. The battery voltage abnormal diagnosis method according to claim 9, wherein, The judgment condition includes: the voltage difference is greater than a preset value; sort all the abnormal voltage values and the remaining voltage values from largest to smallest, and all the abnormal voltage values are continuously arranged at the end of the voltage value sorting sequence; and screen out the abnormal voltage values multiple times and sort all the abnormal voltage values and the remaining voltage values from largest to smallest, and all the abnormal voltage values are continuously arranged at the end of the voltage value sorting sequence for a preset number of times.

11. The battery voltage abnormal diagnosis method according to claim 10, wherein, The steps to screen out voltage abnormal values include: using the formula: to screen the voltage abnormal values, where x i is the voltage value of the battery cell, represents the average value of the voltages of all the battery cells, n is the number of battery cells in the battery pack, if the voltage value of the battery cell is within or then the voltage value is the voltage abnormal value.

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