New energy vehicle power battery pack safety monitoring system based on artificial intelligence

Abstract

The application belongs to the technical field of battery pack supervision, and is specifically a new energy automobile power battery pack safety monitoring system based on artificial intelligence, which comprises a battery pack operation monitoring module, a battery pack abnormality identification output module, a battery pack test reminding module, a battery pack test analysis module and a user terminal; the battery pack abnormality identification output module is used for identifying the abnormality of the new energy automobile power battery pack based on the operation monitoring information of the new energy automobile power battery pack, so that the battery pack management strategy can be adjusted in time to reduce or eliminate the operation threat, the user can be reminded to test the battery pack in time, and the risk of the battery pack can be accurately evaluated, the new energy automobile power battery pack can be repaired and replaced in time, the operation safety and operation performance of the new energy automobile in the future can be ensured, and the management difficulty of the new energy automobile power battery pack is significantly reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of battery pack supervision, and in particular to a new energy vehicle power battery pack safety monitoring system based on artificial intelligence. Background Art

[0002] The power battery pack is an indispensable core component of modern new energy vehicles. It is a high-voltage, large-capacity battery system formed by the precise combination of many individual battery cells. This system is responsible for not only storing electrical energy but also providing continuous power and driving capability for the vehicle by outputting electrical energy.

[0003] The Chinese invention patent publication number CN111969265A discloses a safety monitoring system and method for power battery packs used in new energy vehicles. This system detects and issues early warnings on the power battery pack's liquid cooling system temperature, leakage height, and smoke concentration, thereby improving the safety and prevention level of the power battery pack.

[0004] In actual application, the above-mentioned technical solution can only realize the identification and early warning of certain abnormal conditions. It cannot reasonably judge the urgency of testing the new energy vehicle power battery pack based on abnormality identification and provide timely reminders. It is also unable to accurately evaluate the use risk and performance of the new energy vehicle power battery pack based on various test data, making the management of the battery pack difficult.

[0005] In view of the above technical defects, a solution is now proposed. Summary of the Invention

[0006] The purpose of the present invention is to provide a new energy vehicle power battery pack safety monitoring system based on artificial intelligence, which solves the problems that the existing technology cannot combine abnormality identification to reasonably judge the urgency of testing the new energy vehicle power battery pack and provide timely reminders, and cannot accurately evaluate the use risk and performance of the new energy vehicle power battery pack based on various test data, and the operation and management of the new energy vehicle power battery pack is difficult.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] An artificial intelligence-based new energy vehicle power battery pack safety monitoring system, including a battery pack operation monitoring module, a battery pack anomaly identification and output module, a battery pack test reminder module, a battery pack test analysis module, and a user terminal;

[0009] During the operation of the new energy vehicle power battery pack, the battery pack operation monitoring module monitors the operation of the new energy vehicle power battery pack, collects the operation monitoring information of the new energy vehicle power battery pack, and sends the operation monitoring information to the battery pack abnormality identification output module;

[0010] The battery pack anomaly identification and output module identifies anomalies in the new energy vehicle power battery pack based on operational monitoring information. When an anomaly is detected in the battery pack, an early warning mechanism is triggered and a warning message is generated and sent to the user terminal. The user terminal displays the warning message, and the user adjusts the battery pack management strategy based on the warning message.

[0011] The battery pack test reminder module determines whether the new energy vehicle power battery pack needs to be tested by analyzing the module. When it is determined that the new energy vehicle power battery pack needs to be tested, it generates a test reminder signal and sends the test reminder signal to the user terminal.

[0012] When a test reminder signal is generated, several tests are performed on the new energy vehicle power battery pack, and the test data of each test is sent to the battery pack test analysis module. The battery pack test analysis module evaluates the quality status of the new energy vehicle power battery pack based on the test data, and generates a battery pack safety signal or a battery pack risk signal accordingly, and sends the battery pack safety signal or the battery pack risk signal to the user terminal.

[0013] Furthermore, the specific analysis process of the battery pack test reminder module includes:

[0014] The time of the last test on the new energy vehicle power battery pack is collected and marked as the neighboring test time, the interval between the current time and the neighboring test time is marked as the neighboring test interval value, the optimal neighboring test interval threshold is obtained through analysis, the neighboring test interval value is numerically compared with the optimal neighboring test interval threshold, and if the neighboring test interval value exceeds the optimal neighboring test interval threshold, a test reminder signal is generated.

[0015] Furthermore, the specific process of obtaining the optimal neighbor detection interval threshold through analysis is as follows:

[0016] The time interval between the production date of the new energy vehicle power battery pack and the current date is collected and marked as the battery pack production coefficient, and the number of times the new energy vehicle power battery pack has been charged in the historical stage is collected and marked as the battery pack charge inspection value;

[0017] The power storage amount of the new energy vehicle power battery pack is collected in real time and marked as a real-time power storage value, and the real-time power storage value is compared with a preset real-time power storage threshold. If the real-time power storage value exceeds the preset real-time power storage threshold, it is determined that the new energy vehicle power battery pack is in an insufficient power storage state;

[0018] Obtain all single durations of the new energy vehicle power battery pack being in an insufficient power state in the historical period, mark the number of occurrences in which the single duration of the insufficient power state in the historical period exceeds a preset single duration threshold as an insufficient power high value, and sum up all single durations of the insufficient power state in the historical period to obtain a total insufficient power time value;

[0019] The battery pack judgment coefficient is obtained by numerically calculating the battery pack production coefficient, the battery pack charge inspection value, the insufficient power storage high holding value and the insufficient power storage total time value. Several groups of battery pack judgment coefficient ranges are set in advance, and each group of battery pack judgment coefficient ranges corresponds to a group of preset adjacent measurement interval thresholds; the battery pack judgment coefficient is compared with all battery pack judgment coefficient ranges one by one, and the preset adjacent measurement interval threshold corresponding to the battery pack judgment coefficient range containing the corresponding battery pack judgment coefficient is marked as the optimal adjacent measurement interval threshold.

[0020] Furthermore, if the neighboring test interval value does not exceed the preset neighboring test interval threshold, the time range between the current time and the neighboring test time is marked as the target time range, and all warning information generated for the new energy vehicle power battery pack within the target time range is obtained. Based on all the warning information, all abnormal conditions occurring in the new energy vehicle power battery pack within the target time range are obtained;

[0021] Classify all abnormal conditions, mark the number of times the corresponding type of abnormal condition occurs as the battery pack abnormality detection value, set a set of preset abnormality impact weight values ​​corresponding to each type of abnormal condition, and mark the product of the battery pack abnormality detection value of the corresponding type of abnormal condition and the corresponding preset abnormality impact weight value as the battery pack abnormality assessment value;

[0022] The battery pack type evaluation values ​​of all types of abnormal conditions occurring within the target time range are summed up to obtain the battery pack test emergency value, and the battery pack test emergency value is numerically compared with the preset battery pack test emergency threshold. If the battery pack test emergency value exceeds the preset battery pack test emergency threshold, a test reminder signal is generated.

[0023] Furthermore, the specific analysis process of the battery pack test analysis module is as follows:

[0024] Obtain the test data of each test, compare the test data of the corresponding test item with the corresponding preset data requirements, and if the test data of the corresponding test item does not meet the corresponding preset data requirements, mark the corresponding test item as a dangerous test item; if there is a dangerous test item in the new energy vehicle power battery pack, generate a battery pack risk signal.

[0025] Furthermore, if there are no dangerous test items in the new energy vehicle power battery pack, the deviation value between the test data of the corresponding test item and the corresponding preset data requirement is marked as the item deviation value; each test item is set in advance to correspond to a set of preset item weight values, and the product of the item deviation value of the corresponding test item and the corresponding preset item weight value is marked as the item risk value;

[0026] The project risk values ​​of all test items are summed up to obtain the battery pack analysis value, and the battery pack analysis value is numerically compared with the preset battery pack analysis threshold. If the battery pack analysis value exceeds the preset battery pack analysis threshold, a battery pack risk signal is generated; if the battery pack analysis value does not exceed the preset battery pack analysis threshold, a battery pack safety signal is generated.

[0027] Furthermore, the battery pack test and analysis module is communicatively connected to the battery pack hidden danger re-analysis module, and the battery pack test and analysis module sends the battery pack safety signal to the battery pack hidden danger re-analysis module. When the battery pack hidden danger re-analysis module receives the battery pack safety signal, it performs a secondary analysis on the safety hidden dangers of the new energy vehicle power battery pack, generates a battery pack high hidden danger signal or a battery pack low hidden danger signal through analysis, and sends the battery pack high hidden danger signal or the battery pack low hidden danger signal to the user terminal.

[0028] Furthermore, the specific analysis process of the battery pack hidden danger reanalysis module includes:

[0029] Obtain a scanned image of the new energy vehicle's power battery pack, and use image recognition technology to identify cracks, dents, and bulges on the surface of the new energy vehicle's power battery pack based on the scanned image. If any cracks, dents, or bulges are outside the corresponding allowable range, a high-risk battery pack signal is generated;

[0030] If all cracks, dents, and bulges are within the corresponding allowable range, several micro-areas will be set on the surface of the new energy vehicle power battery pack. If cracks, dents, or bulges involve a corresponding micro-area, the corresponding micro-area will be marked as a warning area;

[0031] The number of warning areas on the power battery of the new energy vehicle is obtained and marked as a warning area condition value, and the cluster area of ​​the warning area is obtained, the number of warning areas in the corresponding cluster area is marked as a warning cluster detection value, and the warning cluster detection value is compared with a preset warning cluster detection threshold. If the warning cluster detection value exceeds the preset warning cluster detection threshold, the corresponding cluster area is marked as a dangerous cluster area;

[0032] The number of dangerous cluster areas on the power battery of the new energy vehicle is obtained and marked as the dangerous cluster number value, and the warning cluster value with the largest value is marked as the warning cluster amplitude value. The scanning hidden danger value is obtained by numerically calculating the warning area condition value, the dangerous cluster number value and the warning cluster amplitude value. The scanning hidden danger value is numerically compared with the preset scanning hidden danger threshold. If the scanning hidden danger value exceeds the preset scanning hidden danger threshold, a battery pack high hidden danger signal is generated.

[0033] Furthermore, if the scanned hidden danger value does not exceed the preset scanned hidden danger threshold, the insertion depth of the connector connected to the new energy vehicle power battery pack is collected and marked as the connector penetration value, and the pressure exerted on the inserted portion of the connector in the new energy vehicle power battery pack is marked as the connector insertion pressure value;

[0034] The displacement of the current position of several parts on the new energy vehicle power battery pack compared to the corresponding initial position is collected and the average is calculated to obtain the battery pack transfer inspection value, the stable hidden danger value is obtained by numerically calculating the connector depth value, the connector insertion pressure value and the battery pack transfer inspection value, and the stable hidden danger value is numerically compared with the preset stable hidden danger threshold. If the stable hidden danger value exceeds the preset stable hidden danger threshold, a high hidden danger signal of the battery pack is generated; if the stable hidden danger value does not exceed the preset stable hidden danger threshold, a low hidden danger signal of the battery pack is generated.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] 1. In the present invention, the battery pack abnormality identification and output module identifies abnormalities in the new energy vehicle power battery pack based on the operation monitoring information of the new energy vehicle power battery pack, facilitating timely adjustment of the battery pack management strategy to reduce or eliminate operational threats. The battery pack test reminder module determines whether the new energy vehicle power battery pack needs to be tested. When a test reminder signal is generated, several tests are performed on the new energy vehicle power battery pack and the quality status of the new energy vehicle power battery pack is evaluated. This can promptly remind users to perform battery pack tests and accurately evaluate battery pack risks, thereby achieving timely maintenance and replacement of the new energy vehicle power battery pack, thereby ensuring the subsequent operational safety and performance of the new energy vehicle.

[0037] 2. In the present invention, the battery pack safety signal is sent to the battery pack hidden danger re-analysis module through the battery pack test and analysis module. When the battery pack hidden danger re-analysis module receives the battery pack safety signal, it performs a secondary analysis of the safety hazards of the new energy vehicle power battery pack. When a high-hazard signal of the battery pack is generated, the user is reminded to repair or replace the new energy battery pack, thereby further reducing the operating safety hazards of the new energy vehicle. It has a high degree of intelligence and significantly reduces the difficulty of managing the power battery pack. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings;

[0039] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0040] Figure 2 This is a system block diagram of Example 2 of the present invention. DETAILED DESCRIPTION

[0041] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0042] Example 1: Figure 1 As shown, the artificial intelligence-based new energy vehicle power battery pack safety monitoring system proposed in the present invention includes a battery pack operation monitoring module, a battery pack abnormality identification and output module, a battery pack test reminder module, a battery pack test analysis module and a user terminal;

[0043] During the operation of the new energy vehicle power battery pack, the battery pack operation monitoring module monitors the operation of the new energy vehicle power battery pack, collects the operation monitoring information of the new energy vehicle power battery pack, and sends the operation monitoring information to the battery pack abnormality identification output module; it should be noted that the battery pack operation monitoring module integrates a variety of high-precision sensors, such as voltage sensors, current sensors, temperature sensors, smoke sensors and leakage sensors, etc., which are used to collect various key parameters of the power battery pack during operation in real time, such as voltage, current, temperature, smoke concentration and coolant level.

[0044] The battery pack anomaly identification and output module identifies anomalies in the new energy vehicle power battery pack based on operational monitoring information. When an abnormality is detected in the battery pack (such as excessive temperature, abnormal current, increased smoke concentration, etc.), the early warning mechanism is triggered and a warning message is generated and sent to the user terminal. The user terminal displays the warning message, and the user adjusts the battery pack management strategy based on the warning message, such as reducing the charging power, increasing the cooling fan speed, etc., to reduce or eliminate operational threats.

[0045] It should be noted that the battery pack abnormality identification output module integrates advanced artificial intelligence algorithms, such as neural networks and machine learning, to conduct in-depth learning and analysis of operation monitoring information. By establishing a safety performance evaluation model for the power battery pack, it monitors and evaluates the working status of the battery pack in real time and identifies its abnormal conditions.

[0046] The battery pack test reminder module determines whether the new energy vehicle power battery pack needs to be tested by analyzing and determining whether the new energy vehicle power battery pack needs to be tested. When it is determined that the new energy vehicle power battery pack needs to be tested, a test reminder signal is generated and sent to the user terminal to remind the user to conduct various tests on the new energy vehicle power battery pack in a timely manner, thereby grasping the various performance and quality conditions of the new energy vehicle power battery pack in detail and ensuring its operating safety and performance. The specific analysis process of the battery pack test reminder module is as follows:

[0047] The time of the last test on the new energy vehicle power battery pack is collected and marked as the adjacent test time, and the interval between the current time and the adjacent test time is marked as the adjacent test interval value; wherein, the larger the adjacent test interval value is, the more timely it is necessary to perform various tests on the new energy vehicle power battery pack;

[0048] The time interval between the production date of the new energy vehicle power battery pack and the current date is collected and marked as the battery pack production coefficient, and the number of times the new energy vehicle power battery pack has been charged in the historical stage is collected and marked as the battery pack charge inspection value;

[0049] The power storage capacity of the new energy vehicle power battery pack is collected in real time and marked as a real-time power storage value, and the real-time power storage value is compared with a preset real-time power storage threshold. If the real-time power storage value exceeds the preset real-time power storage threshold, it indicates that the current power capacity of the new energy vehicle power battery pack is low, and it is determined that the new energy vehicle power battery pack is in an insufficient power storage state;

[0050] Obtain all single durations of the new energy vehicle power battery pack being in an insufficient power state in the historical period, mark the number of occurrences in which the single duration of the insufficient power state in the historical period exceeds a preset single duration threshold as an insufficient power high value, and sum up all single durations of the insufficient power state in the historical period to obtain a total insufficient power time value;

[0051] By formula The battery pack production coefficient Yuk, the battery pack charge inspection value Wsq, the insufficient power holding value Qhy, and the insufficient power total time value Lng are numerically calculated to obtain the battery pack judgment coefficient Psg; wherein b1, b2, b3, and b4 are preset proportional coefficients with values ​​greater than zero, and the larger the value of the battery pack judgment coefficient Psg, the more serious the performance damage of the new energy vehicle power battery pack;

[0052] Several groups of battery pack judgment coefficient ranges are set in advance, and each group of battery pack judgment coefficient ranges corresponds to a group of preset adjacent test interval thresholds. It should be noted that the larger the value of the battery pack judgment coefficient range, the smaller the value of the preset adjacent test interval threshold adapted thereto. That is, the more seriously the performance of the new energy vehicle power battery pack is damaged, the shorter the test interval needs to be to ensure its safety.

[0053] The battery pack judgment coefficient is compared with all battery pack judgment coefficient ranges one by one, and the preset neighboring test interval threshold corresponding to the battery pack judgment coefficient range containing the corresponding battery pack judgment coefficient is marked as the optimal neighboring test interval threshold; the neighboring test interval value is numerically compared with the optimal neighboring test interval threshold. If the neighboring test interval value exceeds the optimal neighboring test interval threshold, it indicates that various tests need to be performed on the new energy vehicle power battery pack in a timely manner, and a test reminder signal is generated.

[0054] Furthermore, if the neighboring test interval value does not exceed the preset neighboring test interval threshold, the time range between the current time and the neighboring test time is marked as the target time range, and all warning information generated for the new energy vehicle power battery pack within the target time range is obtained. Based on all the warning information, all abnormal conditions of the new energy vehicle power battery pack within the target time range are obtained;

[0055] All abnormal conditions are classified, and the number of occurrences of the corresponding type of abnormal condition is marked as the battery pack abnormality detection value. A set of preset abnormality impact weight values ​​is set in advance for each type of abnormal condition. It should be noted that the preset abnormality impact weight values ​​are all positive numbers, and the greater the adverse impact of the corresponding type of abnormal condition on the power battery pack, the larger the value of the preset abnormality impact weight value corresponding to it;

[0056] The product of the battery pack abnormality detection value of the corresponding type of abnormal condition and the corresponding preset abnormality impact weight value is marked as the battery pack abnormality assessment value; and the battery pack abnormality assessment values ​​of all types of abnormal conditions occurring within the target time range are summed up to obtain the battery pack test emergency value. Among them, the larger the value of the battery pack test emergency value, the more timely it is necessary to perform various tests on the new energy vehicle power battery pack;

[0057] The battery pack test emergency value is compared with the preset battery pack test emergency threshold. If the battery pack test emergency value exceeds the preset battery pack test emergency threshold, it indicates that various tests need to be performed on the new energy vehicle power battery pack in a timely manner, and a test reminder signal is generated.

[0058] When a test reminder signal is generated, several tests are performed on the new energy vehicle power battery pack (for example, a constant current discharge test is used to evaluate the actual capacity of the battery pack, as well as an internal resistance test, a voltage consistency test, and a performance test of the battery pack at different temperatures), and the test data of each test is sent to the battery pack test analysis module. The battery pack test analysis module evaluates the quality status of the new energy vehicle power battery pack based on the test data and generates a battery pack safety signal or a battery pack risk signal accordingly;

[0059] The battery pack safety signal or battery pack risk signal is sent to the user terminal. When the user terminal receives the battery pack risk signal, it issues an early warning to remind the user to inspect or replace the new energy vehicle power battery pack, thereby ensuring the subsequent operation safety and performance of the new energy vehicle. The specific analysis process of the battery pack test analysis module is as follows:

[0060] The test data of each test is obtained, and the test data of the corresponding test item is compared with the corresponding preset data requirements. If the test data of the corresponding test item does not meet the corresponding preset data requirements, the corresponding test item is marked as a dangerous test item (for example, the internal resistance data of the power battery pack is numerically compared with the preset internal resistance data threshold. If the internal resistance data exceeds the preset internal resistance data threshold, it indicates that the internal resistance of the power battery pack does not meet the requirements, and the internal resistance test item is marked as a dangerous test item); if there is a dangerous test item in the power battery pack of a new energy vehicle, a battery pack risk signal is generated.

[0061] Furthermore, if there are no dangerous test items in the new energy vehicle power battery pack, the deviation value between the test data of the corresponding test item and the corresponding preset data requirement is marked as the item deviation value; each test item is set in advance to correspond to a set of preset item weight values, wherein the values ​​of the preset item weight values ​​are all positive numbers, and the more important the corresponding test item is, the larger the value of the preset item weight value corresponding to it is; the product of the item deviation value of the corresponding test item and the corresponding preset item weight value is marked as the item risk value;

[0062] The battery pack analysis value is calculated by summing up the project risk values ​​of all test items. The larger the battery pack analysis value, the greater the risk of using the new energy vehicle power battery pack;

[0063] The battery pack analysis value is numerically compared with the preset battery pack analysis threshold. If the battery pack analysis value exceeds the preset battery pack analysis threshold, it indicates that the use risk of the new energy vehicle power battery pack is relatively high, and a battery pack risk signal is generated; if the battery pack analysis value does not exceed the preset battery pack analysis threshold, it indicates that the use risk of the new energy vehicle power battery pack is relatively low, and a battery pack safety signal is generated.

[0064] Example 2: Figure 2 As shown, the difference between this embodiment and the first embodiment is that the battery pack test and analysis module is communicatively connected to the battery pack hidden danger re-analysis module. The battery pack test and analysis module sends the battery pack safety signal to the battery pack hidden danger re-analysis module. When the battery pack hidden danger re-analysis module receives the battery pack safety signal, it performs a secondary analysis on the safety hidden danger of the new energy vehicle power battery pack and generates a battery pack high hidden danger signal or a battery pack low hidden danger signal through the analysis.

[0065] The high-risk signal or low-risk signal of the battery pack is sent to the user terminal. When the user terminal receives the high-risk signal of the battery pack, it issues an early warning to remind the user to repair or replace the new energy battery pack, further reducing the operating safety risks of new energy vehicles. The high degree of intelligence significantly reduces the difficulty of managing power battery packs. The specific analysis process of the battery pack hidden danger re-analysis module is as follows:

[0066] Obtaining an external scan image of the new energy vehicle power battery pack, using image recognition technology and based on the external scan image to identify cracks, dents, and bulges on the surface of the new energy vehicle power battery pack; if there are cracks, dents, or bulges that are not within the corresponding allowable range (for example, comparing the extended length, width, and depth of the crack with preset extended length thresholds, width thresholds, and depth thresholds, respectively; if the extended length, width, or depth of the crack exceeds the corresponding preset thresholds, it indicates that the safety hazard posed by the corresponding crack is relatively large, that is, the corresponding crack is not within the allowable range), then generating a high-hazard signal for the battery pack;

[0067] If all cracks, dents, and bulges are within the corresponding allowable range, several micro-areas will be set on the surface of the new energy vehicle power battery pack. If cracks, dents, or bulges involve a corresponding micro-area, the corresponding micro-area will be marked as a warning area;

[0068] The number of warning areas on the power battery of the new energy vehicle is obtained and marked as a warning area condition value, and the cluster area of ​​the warning areas (i.e., an area formed by connecting and clustering several warning areas) is obtained, and the number of warning areas in the corresponding cluster area is marked as a warning cluster detection value. The warning cluster detection value is numerically compared with a preset warning cluster detection threshold. If the warning cluster detection value exceeds the preset warning cluster detection threshold, it indicates that the safety hazard brought by the corresponding cluster area is relatively large, and the corresponding cluster area is marked as a dangerous cluster area;

[0069] Obtain the number of dangerous concentration areas on the power battery of the new energy vehicle and mark them as dangerous concentration number value, and mark the largest warning concentration detection value as warning concentration amplitude value;

[0070] The warning area condition value SY, the dangerous concentration value SN, and the warning concentration amplitude value SF are numerically calculated using the formula XL = qs2*SN + (qs1*SY + qs3*SF) / 2 to obtain the scanning hidden danger value XL. Here, qs1, qs2, and qs3 are preset proportional coefficients, and qs2>qs3>qs1>0. Furthermore, the larger the value of the scanning hidden danger value XL, the more abnormal the appearance of the new energy vehicle power battery pack, and the greater the potential safety hazard.

[0071] The scanning hidden danger value XL is numerically compared with the preset scanning hidden danger threshold. If the scanning hidden danger value XL exceeds the preset scanning hidden danger threshold, it indicates that the appearance of the new energy vehicle power battery pack is abnormal and the potential safety hazard it brings is large, and a high hidden danger signal for the battery pack is generated.

[0072] Furthermore, if the scan potential danger value XL does not exceed the preset scan potential danger threshold, the insertion depth of the connector connected to the new energy vehicle power battery pack is collected and marked as the connector penetration value, and the pressure exerted on the inserted portion of the connector in the new energy vehicle power battery pack is marked as the connector insertion pressure value (i.e., the pressure data exerted on the portion of the connector inserted into the battery pack socket); wherein, the smaller the value of the connector penetration value and the smaller the value of the connector insertion pressure value, the greater the risk of the connector loosening and falling off, and the greater the potential safety hazard;

[0073] and collecting the displacement of the current positions of several parts of the new energy vehicle power battery pack compared to the corresponding initial positions and calculating the average thereof to obtain a battery pack displacement inspection value; wherein, a larger value of the battery pack displacement inspection value indicates a more serious displacement of the new energy vehicle power battery pack and a greater potential safety hazard;

[0074] By formula The connector penetration value MS, the connector insertion pressure value MY, and the battery pack inspection value ML are numerically calculated to obtain a stable hidden danger value MF. Here, ey1, ey2, and ey3 are preset proportional coefficients with values ​​greater than zero. A larger value of the stable hidden danger value MF indicates a greater potential safety hazard of the new energy vehicle power battery pack.

[0075] The stable hidden danger value MF is numerically compared with the preset stable hidden danger threshold. If the stable hidden danger value MF exceeds the preset stable hidden danger threshold, it indicates that the potential safety hidden danger of the new energy vehicle power battery pack is large, and a high hidden danger signal for the battery pack is generated; if the stable hidden danger value MF does not exceed the preset stable hidden danger threshold, it indicates that the potential safety hidden danger of the new energy vehicle power battery pack is small, and a low hidden danger signal for the battery pack is generated.

[0076] The working principle of the present invention is as follows: when in use, the operation of the new energy vehicle power battery pack is monitored by the battery pack operation monitoring module, and the battery pack abnormality identification output module identifies abnormalities of the new energy vehicle power battery pack based on the operation monitoring information of the new energy vehicle power battery pack. When an abnormality is detected in the battery pack, an early warning information is sent to the user terminal. The user adjusts the battery pack management strategy based on the early warning information to reduce or eliminate the operation threat, and determines whether the new energy vehicle power battery pack needs to be tested through the battery pack test reminder module. When it is determined that the new energy power battery pack needs to be tested, a test reminder signal is generated. When the test reminder signal is generated, several tests are performed on the new energy vehicle power battery pack. The battery pack test analysis module evaluates the quality status of the new energy vehicle power battery pack based on various test data and generates a battery pack safety signal or a battery pack risk signal. It can promptly remind the user to perform battery pack testing and accurately evaluate the risk of the battery pack, and realize timely maintenance and replacement of the new energy vehicle power battery pack, thereby ensuring the subsequent operation safety and operation performance of the new energy vehicle, and significantly reducing the difficulty of managing the power battery pack.

[0077] The above formulas are all dimensionless and calculated by taking their numerical values. The formula is a formula for the latest real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made based on the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can well understand and use the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. The artificial intelligence-based new energy vehicle power battery pack safety monitoring system is characterized by: It includes a battery pack operation monitoring module, a battery pack abnormality identification and output module, a battery pack test reminder module, a battery pack test analysis module and a user terminal; During the operation of the new energy vehicle power battery pack, the battery pack operation monitoring module monitors the operation of the new energy vehicle power battery pack, collects the operation monitoring information of the new energy vehicle power battery pack, and sends the operation monitoring information to the battery pack abnormality identification output module; The battery pack anomaly identification and output module identifies anomalies in the new energy vehicle power battery pack based on operation monitoring information. When an anomaly is detected in the battery pack, an early warning message is sent to the user terminal, and the user adjusts the battery pack management strategy based on the early warning information. The battery pack test reminder module determines whether the new energy vehicle power battery pack needs to be tested by analysis, and generates a test reminder signal when it determines that the new energy vehicle power battery pack needs to be tested; The specific analysis process of the battery pack test reminder module includes: The time of the last test on the new energy vehicle power battery pack is collected and marked as the adjacent test time, the interval between the current time and the adjacent test time is marked as the adjacent test interval value, and the optimal adjacent test interval threshold is obtained through analysis. If the adjacent test interval value exceeds the optimal adjacent test interval threshold, a test reminder signal is generated; The specific process of obtaining the optimal neighbor detection interval threshold through analysis is as follows: The battery pack judgment coefficient is obtained by numerically calculating the battery pack production coefficient, the battery pack charge inspection value, the insufficient power storage high holding value and the insufficient power storage total time value, and the battery pack judgment coefficient is compared with all battery pack judgment coefficient ranges one by one, and the preset adjacent measurement interval threshold corresponding to the battery pack judgment coefficient range containing the corresponding battery pack judgment coefficient is marked as the optimal adjacent measurement interval threshold; If the neighbor test interval value does not exceed the preset neighbor test interval threshold, the time range between the current time and the neighbor test time is marked as the target time range, and all abnormal conditions of the new energy vehicle power battery pack within the target time range are obtained based on all warning information; The battery pack abnormality assessment values ​​of all types of abnormal conditions occurring within the target time range are summed up to obtain a battery pack test emergency value. If the battery pack test emergency value exceeds a preset battery pack test emergency threshold, a test reminder signal is generated; When generating a test reminder signal, several tests are performed on the new energy vehicle power battery pack. The battery pack test analysis module evaluates the quality status of the new energy vehicle power battery pack based on the test data, and generates a battery pack safety signal or a battery pack risk signal accordingly.

2. The artificial intelligence-based new energy vehicle power battery pack safety monitoring system according to claim 1 is characterized in that: The specific analysis process of the battery pack test analysis module is as follows: The test data of each test is obtained. If the test data of the corresponding test item does not meet the corresponding preset data requirements, the corresponding test item will be marked as a dangerous test item; if there is a dangerous test item in the new energy vehicle power battery pack, a battery pack risk signal will be generated.

3. The artificial intelligence-based new energy vehicle power battery pack safety monitoring system according to claim 2 is characterized in that: If there are no dangerous test items in the new energy vehicle power battery pack, the risk values ​​of all test items are summed up to obtain the battery pack analysis value. If the battery pack analysis value exceeds the preset battery pack analysis threshold, a battery pack risk signal is generated. If the battery pack analysis value does not exceed the preset battery pack analysis threshold, a battery pack safety signal is generated.

4. The artificial intelligence-based new energy vehicle power battery pack safety monitoring system according to claim 2 is characterized in that: The battery pack test and analysis module is communicatively connected to the battery pack hidden danger re-analysis module. The battery pack test and analysis module sends the battery pack safety signal to the battery pack hidden danger re-analysis module. When the battery pack hidden danger re-analysis module receives the battery pack safety signal, it performs a secondary analysis of the safety hidden dangers of the new energy vehicle power battery pack and sends the battery pack high hidden danger signal or the battery pack low hidden danger signal to the user terminal.

5. The artificial intelligence-based new energy vehicle power battery pack safety monitoring system according to claim 4 is characterized in that: The specific analysis process of the battery pack hidden danger reanalysis module includes: Obtain a scanned image of the new energy vehicle's power battery pack, and use image recognition technology to identify cracks, dents, and bulges on the surface of the new energy vehicle's power battery pack based on the scanned image. If any cracks, dents, or bulges are outside the corresponding allowable range, a high-risk battery pack signal is generated; If all cracks, dents and bulges are within the corresponding allowable range, the scanning hidden danger value is obtained by numerically calculating the warning area condition value, the dangerous condition value and the warning amplitude value. If the scanning hidden danger value exceeds the preset scanning hidden danger threshold, a high hidden danger signal of the battery pack is generated.

6. The artificial intelligence-based new energy vehicle power battery pack safety monitoring system according to claim 5 is characterized in that: If the scanned hidden danger value does not exceed the preset scanned hidden danger threshold, the stable hidden danger value is obtained by numerically calculating the connector depth value, the connector insertion pressure value and the battery pack inspection value. If the stable hidden danger value exceeds the preset stable hidden danger threshold, a battery pack high hidden danger signal is generated; if the stable hidden danger value does not exceed the preset stable hidden danger threshold, a battery pack low hidden danger signal is generated.

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