A tire monitoring and early warning method and system for new energy vehicles

Abstract

The application provides a tire monitoring and early warning method and system for a new energy vehicle, obtains a pressure data sequence of a target tire of the new energy vehicle, divides a rotation period of the target tire into multiple rotation intervals, and determines a pressure distribution feature of the target tire corresponding to each rotation interval according to the pressure data sequence; determines a pressure distribution deviation corresponding to each rotation interval based on the pressure distribution feature of each rotation interval and a reference pressure distribution feature of the corresponding rotation interval under a historical normal state; performs global health analysis on the target tire within the rotation period according to all the pressure distribution deviations and a stress damage coefficient of the target tire corresponding to each rotation interval, and obtains a global health index of the target tire of the new energy vehicle; and triggers a structural damage fault warning of the target tire of the new energy vehicle when the global health index exceeds a fault warning threshold. The technical scheme provided by the application can perform fault warning on a tire with local structural damage in the tire rotation process.

Description

Technical Field

[0001] This application relates to the field of tire monitoring and early warning technology, and more specifically, to a tire monitoring and early warning method and system for new energy vehicles. Background Technology

[0002] Tire safety directly affects driving safety. Traditional manual inspections are difficult to detect abnormal tire pressure and temperature rise in real time. To address this, tire pressure monitoring systems have emerged. These systems use sensors installed inside the tires to collect pressure and temperature data in real time and transmit it wirelessly to a receiver inside the vehicle. When an abnormality is detected, the system immediately issues a warning, prompting the driver to take timely action. This technology has become a standard feature of active vehicle safety, effectively preventing tire blowouts, reducing energy consumption, and extending tire lifespan.

[0003] In existing tire monitoring and warning systems, sensors installed inside the tires monitor tire pressure and temperature data in real time and transmit this data wirelessly to the vehicle's computer. The computer compares the received data with preset safety thresholds. If abnormally low or high tire pressure, or a rapid increase in temperature, is detected, a clear warning is immediately issued to the driver via the dashboard. However, in tire monitoring and warning systems used in new energy vehicles, traditional tire pressure monitoring relies on the absolute pressure value or average pressure changes of the tire for fault diagnosis. This approach cannot effectively identify dynamic pressure distribution anomalies caused by localized structural damage during tire rotation. These localized damages can cause changes in pressure distribution patterns within specific angular ranges during tire rotation, but the overall pressure may remain within the normal range. This can lead to missed detections when issuing warnings for tires. Therefore, how to provide fault warnings for tires with localized structural damage during tire rotation has become a challenge for the industry. Summary of the Invention

[0004] This application provides a tire monitoring and early warning method and system for new energy vehicles, which can provide early warning of tires with local structural damage during tire rotation.

[0005] In a first aspect, this application provides a tire monitoring and early warning method for new energy vehicles, comprising the following steps:

[0006] Obtain the pressure data sequence of target tires for new energy vehicles;

[0007] The rotation cycle of the target tire is divided into multiple rotation intervals, and the pressure distribution characteristics of the target tire in each rotation interval are determined based on the pressure data sequence.

[0008] The pressure distribution characteristics of each rotation interval are compared with the baseline pressure distribution characteristics of the corresponding rotation interval under historical normal conditions to generate the pressure distribution deviation corresponding to each rotation interval.

[0009] Based on all the pressure distribution deviations and the stress damage coefficient of the target tire corresponding to each rotation interval, a global health analysis of the target tire is performed within the rotation cycle, thereby obtaining the global health index of the target tire for new energy vehicles.

[0010] When the global health indicator exceeds the fault warning threshold, a structural damage fault warning for the target tire of the new energy vehicle is triggered.

[0011] In some embodiments, dividing the rotation cycle of the target tire into multiple rotation intervals specifically includes:

[0012] The parameters for dividing the rotation range are determined based on the rotation cycle of the target tire;

[0013] The rotation cycle of the target tire is divided into a preset number of rotation intervals using the division parameters.

[0014] In some embodiments, determining the pressure distribution characteristics of the target tire corresponding to each rotation interval based on the pressure data sequence specifically includes:

[0015] Extract the pressure data subsets corresponding to each rotation interval from the pressure data sequence;

[0016] Calculate the statistical characteristic parameters for each pressure data subset, including the pressure mean, pressure variance, and pressure extreme value ratio;

[0017] The statistical characteristic parameters are used as the pressure distribution characteristics of the target tire in each rotation interval.

[0018] In some embodiments, the pressure distribution characteristics of each rotation interval are compared with the baseline pressure distribution characteristics of the corresponding rotation interval under historical normal conditions to generate the pressure distribution deviation corresponding to each rotation interval, specifically including:

[0019] Obtain the baseline pressure distribution characteristics of each rotation interval under historical normal conditions;

[0020] The pressure distribution characteristics of each rotation interval within the current rotation cycle are dimensionally aligned with the corresponding baseline pressure distribution characteristics to obtain the dimensionally aligned current pressure distribution characteristics and baseline pressure distribution characteristics.

[0021] Calculate the initial deviation between the current pressure distribution characteristics after dimension alignment and the baseline pressure distribution characteristics;

[0022] The initial deviation value is standardized and normalized to generate the pressure distribution deviation corresponding to each rotation interval.

[0023] In some embodiments, a global health analysis of the target tire is performed within the rotation cycle based on all pressure distribution deviations and the stress damage coefficient of the target tire corresponding to each rotation interval, thereby obtaining the global health indicators of the target tire for new energy vehicles, specifically including:

[0024] Determine the stress damage coefficient of the tire for each rotation range;

[0025] Using the stress damage coefficient corresponding to each rotation interval as a weighting coefficient, all pressure distribution deviations are multiplied by the stress damage coefficient of the corresponding rotation interval to obtain the weighted pressure distribution deviation of each rotation interval.

[0026] By performing a global fusion calculation on all weighted pressure distribution deviations, the global health index of the target tire of the new energy vehicle during the rotation cycle is obtained.

[0027] In some embodiments, triggering a structural damage fault warning for the target tire of a new energy vehicle when the global health indicator exceeds the fault warning threshold specifically includes:

[0028] Retrieve the structural damage fault early warning threshold that is compatible with the target tire;

[0029] If the global health index exceeds the structural damage fault warning threshold, then the structural damage fault warning triggering condition is determined to be met.

[0030] Based on the aforementioned warning triggering conditions, a structural damage fault warning operation is executed for the target tire of the new energy vehicle.

[0031] In some embodiments, a pressure data sequence of the target tire of a new energy vehicle is obtained.

[0032] Secondly, this application provides a tire monitoring and early warning system for new energy vehicles, used to execute a tire monitoring and early warning method for new energy vehicles, the system comprising:

[0033] The acquisition module is used to acquire the pressure data sequence of the target tires of new energy vehicles;

[0034] The processing module is used to divide the rotation cycle of the target tire into multiple rotation intervals and determine the pressure distribution characteristics of the target tire in each rotation interval based on the pressure data sequence.

[0035] The processing module is also used to compare the pressure distribution characteristics of each rotation interval with the benchmark pressure distribution characteristics of the corresponding rotation interval under historical normal conditions, and generate the pressure distribution deviation corresponding to each rotation interval.

[0036] The processing module is also used to perform a global health analysis of the target tire within the rotation cycle based on all pressure distribution deviations and the stress damage coefficient of the target tire corresponding to each rotation interval, thereby obtaining the global health index of the target tire for new energy vehicles.

[0037] The execution module is used to trigger a structural damage fault warning for the target tire of the new energy vehicle when the global health indicator exceeds the fault warning threshold.

[0038] Thirdly, this application provides a computer device, the computer device including a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the above-described tire monitoring and early warning method for new energy vehicles.

[0039] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described tire monitoring and early warning method for new energy vehicles.

[0040] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects:

[0041] The tire monitoring and early warning method and system for new energy vehicles provided in this application first acquires the pressure data sequence of the target tire of the new energy vehicle; secondly, the rotation cycle of the target tire is divided into multiple rotation intervals, and the pressure distribution characteristics of the target tire corresponding to each rotation interval are determined based on the pressure data sequence; further, the pressure distribution characteristics of each rotation interval are compared with the baseline pressure distribution characteristics of the corresponding rotation interval under historical normal conditions to generate the pressure distribution deviation corresponding to each rotation interval; then, based on all the pressure distribution deviations and the stress damage coefficient of the target tire corresponding to each rotation interval, a global health analysis of the target tire within the rotation cycle is performed, thereby obtaining the global health index of the target tire of the new energy vehicle; finally, when the global health index exceeds the fault early warning threshold, a structural damage fault early warning for the target tire of the new energy vehicle is triggered.

[0042] Therefore, this application can provide fault warning for tires with local structural damage during tire rotation. The first step involves acquiring the pressure data sequence of the target tire for new energy vehicles, providing a data foundation for subsequent local pressure characteristic analysis. The second step divides the rotation cycle of the target tire into multiple rotation intervals and extracts the corresponding pressure distribution characteristics from the pressure data sequence according to the rotation interval, comprehensively reflecting the structural stress state of the corresponding local location, providing a precise local assessment basis for subsequent global health analysis combined with interval stress damage coefficients. The third step generates pressure distribution deviation by comparing the consistency of the current pressure distribution characteristics with historical benchmark characteristics, achieving precise quantification of local pressure state anomalies, avoiding the ambiguity of anomaly degree caused by qualitative comparison, and providing precise local anomaly input for global health analysis. The fourth step... Global health indicators are obtained through global health analysis using the combined stress damage coefficient. This effectively identifies the structural characteristics and damage sensitivity differences in different rotational ranges of the tire, and effectively identifies abnormal dynamic pressure distribution caused by local structural damage during tire rotation. This avoids the problem of diluted abnormalities in highly sensitive ranges under equal weights, ensuring that the global indicators truly reflect the overall structural health status of the tire. The fifth step triggers an early warning based on the comparison between the global health indicators and the warning threshold, achieving effective feedback on structural damage faults. This avoids the problem of missed warnings when local damage causes changes in pressure distribution patterns within specific angle ranges during tire rotation, thus providing more comprehensive protection for driving safety. In summary, the technical solution provided in this application can provide fault warnings for tires with local structural damage during tire rotation. Attached Figure Description

[0043] Figure 1 This is an exemplary flowchart of a tire monitoring and early warning method for new energy vehicles, according to some embodiments of this application;

[0044] Figure 2 This is an exemplary flowchart illustrating the determination of a subset of pressure data according to some embodiments of this application;

[0045] Figure 3 This is a schematic diagram of the structure of multiple rotation intervals according to some embodiments of this application;

[0046] Figure 4 This is a schematic diagram of the structure of a computer device for implementing a tire monitoring and early warning method for new energy vehicles, according to some embodiments of this application. Detailed Implementation

[0047] To better understand the technical solution of this application, the technical solution of this application will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0048] refer to Figure 1This figure is an exemplary flowchart of a tire monitoring and early warning method for new energy vehicles according to some embodiments of this application. The figure mainly includes the following steps:

[0049] In step S101, the pressure data sequence of the target tire of the new energy vehicle is obtained.

[0050] In practice, the pressure data sequence of the target tire of the new energy vehicle is obtained through a pressure sensor. That is, the pressure sensor continuously measures the pressure value inside the target tire at a fixed sampling frequency (e.g., 1Hz to 50Hz) and arranges the pressure data sequence in chronological order.

[0051] It should be noted that the pressure data sequence in this application refers to the set of gas pressure values ​​inside the target tire arranged continuously in the order of timestamps. The pressure data sequence contains information on the dynamic changes in pressure at different times during tire operation. By acquiring the pressure data sequence, a data basis can be provided for subsequent tire structural loss failures.

[0052] In step S102, the rotation cycle of the target tire is divided into multiple rotation intervals, and the pressure distribution characteristics of the target tire corresponding to each rotation interval are determined based on the pressure data sequence.

[0053] In some embodiments, reference Figure 2 As shown, this figure is an exemplary flowchart illustrating the determination of multiple rotation intervals according to some embodiments of this application. In this embodiment, dividing the rotation cycle of the target tire into multiple rotation intervals can be achieved by the following steps:

[0054] In step S1021, the division parameters of the rotation range are determined based on the rotation cycle of the target tire;

[0055] In step S1022, the rotation cycle of the target tire is divided into a preset number of rotation intervals using the division parameters.

[0056] In practice, firstly, based on the rotation cycle of the target tire, a preset number of rotation intervals is obtained (the specific number can be set according to actual needs, for example, it can be set to 12 rotation intervals, which is not limited here). The rotation cycle is the angle of one rotation of the tire. The rotation cycle is divided by the number of rotation intervals to obtain the angular range boundary corresponding to each rotation interval, forming the division parameters of the rotation intervals. The division parameters refer to the set of angular boundary parameters used to define each rotation interval. Then, based on the starting time of the target tire's rotation, the angular range (0°-360°) corresponding to a single complete rotation cycle is evenly divided according to the angular range boundary in the division parameters, so that each divided interval corresponds to a fixed angular range, thus obtaining a preset number of rotation intervals.

[0057] It should be noted that, in this application, the rotation interval refers to multiple continuous and non-overlapping angular segments within the complete rotation cycle of the target tire. During the rotation of the target tire, the stress state at different angular positions (such as the tread contact area, the shoulder transition area, and the sidewall overhang area) exhibits significant non-uniformity. The pressure distribution characteristics are directly related to the structural integrity of the corresponding area of ​​the tire. However, traditional global pressure analysis can mask subtle structural anomalies in local areas (such as local bulges, micro-cracks, and interlayer separation). Therefore, targeted monitoring of different structural positions of the tire can be achieved through interval division. The pressure data within a single complete rotation cycle is decomposed into multiple continuous and non-overlapping local data subsets according to the angular dimension, so that each interval corresponds to a fixed physical structural position of the tire. The pressure distribution characteristics of each local area (such as the stability of the pressure peak in the contact area and the pressure fluctuation pattern of the sidewall) can be accurately extracted, avoiding feature ambiguity caused by global averaging, thereby improving the accurate identification and location of local structural damage to the target tire during tire pressure monitoring.

[0058] In some embodiments, determining the pressure distribution characteristics of the target tire corresponding to each rotation interval based on the pressure data sequence is achieved through the following steps:

[0059] Extract the pressure data subsets corresponding to each rotation interval from the pressure data sequence;

[0060] Calculate the statistical characteristic parameters for each pressure data subset, including the pressure mean, pressure variance, and pressure extreme value ratio;

[0061] The statistical characteristic parameters are used as the pressure distribution characteristics of the target tire in each rotation interval.

[0062] In specific implementation, pressure data corresponding to each rotation interval is extracted from the pressure data sequence, and the extracted pressure data is used as a subset of pressure data to obtain the pressure data subset corresponding to each rotation interval. The pressure data subset refers to the set of all pressure data points within the time range corresponding to the rotation interval. During tire rotation, each rotation interval corresponds to its fixed physical structural position (such as the tread contact area, the sidewall suspension area, etc.). The force mechanism, deformation degree, and pressure distribution pattern of different positions are significantly different. If the global pressure data of a single complete rotation cycle is directly used for analysis, the pressure characteristics of different positions will be superimposed and averaged, thereby masking the subtle structural anomalies in local areas (such as local bulges, micro-cracks, interlayer separation, etc.). This requires splitting the pressure data into subsets to achieve targeted analysis of each local location. Then, based on each pressure data subset, the pressure mean is obtained by taking the arithmetic mean of all data points in the subset. The sample variance of the pressure data subset is calculated as the pressure variance. The maximum and minimum pressure values ​​are selected by traversing the pressure data subsets, and the result of (maximum pressure value - minimum pressure value) / average pressure value is used as the pressure extreme value ratio. The pressure mean, pressure variance, and pressure extreme value ratio are combined into statistical characteristic parameters. These statistical characteristic parameters refer to a set of parameters that can reflect the overall level, dispersion, and extreme value characteristics of the pressure data subset. Finally, these statistical characteristic parameters are used as the pressure distribution characteristics of the target tire corresponding to each rotation interval.

[0063] It should be noted that, in this application, pressure distribution characteristics refer to a set of features reflecting the pressure characteristics of the corresponding rotation interval. Determining pressure distribution characteristics involves transforming the pressure data subsets corresponding to each rotation interval from their original data form into a quantifiable and comparable feature form. This provides a comparison object for subsequent consistency comparison with the benchmark pressure distribution characteristics of the corresponding rotation interval under historical normal conditions, ensuring the accuracy and effectiveness of pressure distribution deviation calculation. The determination of pressure distribution characteristics can also comprehensively reflect the structural stress state of the corresponding local location, providing an accurate local assessment basis for subsequent global health analysis combined with interval stress damage coefficients. Ultimately, this supports the sensitive identification and accurate judgment of local structural damage to the tire during tire pressure testing.

[0064] In step S103, the pressure distribution characteristics of each rotation interval are compared with the baseline pressure distribution characteristics of the corresponding rotation interval under historical normal conditions to generate the pressure distribution deviation corresponding to each rotation interval.

[0065] In some embodiments, the pressure distribution characteristics of each rotation interval are compared with the baseline pressure distribution characteristics of the corresponding rotation interval under historical normal conditions to generate the pressure distribution deviation corresponding to each rotation interval. This is achieved through the following steps:

[0066] Obtain the baseline pressure distribution characteristics of each rotation interval under historical normal conditions;

[0067] The pressure distribution characteristics of each rotation interval within the current rotation cycle are dimensionally aligned with the corresponding baseline pressure distribution characteristics to obtain the dimensionally aligned current pressure distribution characteristics and baseline pressure distribution characteristics.

[0068] Calculate the initial deviation between the current pressure distribution characteristics after dimension alignment and the baseline pressure distribution characteristics;

[0069] The initial deviation value is standardized and normalized to generate the pressure distribution deviation corresponding to each rotation interval.

[0070] In specific implementation, firstly, the pressure distribution characteristics of the target tire under historical normal conditions (e.g., normal tire pressure range) are extracted from the vehicle storage module to obtain the baseline pressure distribution characteristics of each rotation interval under historical normal conditions. The baseline pressure distribution characteristics refer to the standardized pressure characteristics of each rotation interval when the tire is in a normal state. Secondly, it is verified whether the number of feature dimensions and the physical meaning of each dimension of the pressure distribution characteristics of each rotation interval within the current rotation cycle are completely consistent with the corresponding baseline pressure distribution characteristics. Then, the pressure distribution characteristics and the corresponding baseline pressure distribution characteristics are rearranged according to a preset feature dimension order (e.g., a fixed order of pressure mean, pressure variance, and pressure extreme value ratio) to ensure that the same dimension corresponds to the same pressure characteristic index, resulting in the dimension-aligned current pressure distribution characteristics and the baseline pressure distribution characteristics. Force distribution characteristics and reference pressure distribution characteristics refer to two sets of standardized features that are completely matched in terms of the number of feature dimensions, dimensional order, and physical meaning. Then, the difference between the corresponding dimensional feature values ​​of the current pressure distribution characteristics and the reference pressure distribution characteristics after dimensional alignment is calculated using Euclidean distance. The square root of the sum of the squares of all differences is taken to obtain the initial deviation value reflecting the overall degree of difference between the two. The initial deviation value refers to the original quantitative value of the difference between the current feature and the reference feature. Finally, the z-score standardization algorithm is used to calculate the standard score corresponding to the initial deviation value (i.e., (initial deviation value - historical average initial deviation value) ÷ historical standard deviation value) based on the statistical results of the initial deviation values ​​of all rotation intervals under historical normal working conditions. This eliminates the problem of incomparability of pressure distribution deviations caused by differences in feature value ranges in different rotation intervals, thereby generating the pressure distribution deviations corresponding to each rotation interval.

[0071] It should be noted that, in this application, pressure distribution deviation refers to a value that measures the degree of difference between the current pressure distribution characteristics and the baseline pressure distribution characteristics. The determination of pressure distribution deviation lies in transforming the difference between the current pressure distribution characteristics and the baseline pressure distribution characteristics into a comparable quantitative indicator. Dimension alignment ensures the accuracy of the difference comparison (avoiding miscalculations caused by dimension mismatch). The feature distance metric achieves precise quantification of the degree of difference. Standardization and normalization processes eliminate the influence of different ranges of feature values, giving each range of pressure distribution deviation a unified evaluation benchmark. This provides a core calculation unit for subsequent weighted analysis combining stress damage coefficients of each range, and provides reliable input data for the calculation of global health indicators. Ultimately, it achieves the connection from local anomaly quantification to global health assessment, solving the technical problem that traditional qualitative comparison cannot accurately quantify the degree of anomaly, and providing a key basis for the accurate triggering of fault warnings.

[0072] In step S104, a global health analysis of the target tire is performed within the rotation cycle based on all pressure distribution deviations and the stress damage coefficient of the target tire corresponding to each rotation interval, thereby obtaining the global health index of the target tire for new energy vehicles.

[0073] In some embodiments, the global health analysis of the target tire within the rotation cycle is performed based on all pressure distribution deviations and the stress damage coefficient of the target tire corresponding to each rotation interval, thereby obtaining the global health index of the target tire for new energy vehicles. This is achieved through the following steps:

[0074] Determine the stress damage coefficient of the tire for each rotation range;

[0075] Using the stress damage coefficient corresponding to each rotation interval as a weighting coefficient, all pressure distribution deviations are multiplied by the stress damage coefficient of the corresponding rotation interval to obtain the weighted pressure distribution deviation of each rotation interval.

[0076] By performing a global fusion calculation on all weighted pressure distribution deviations, the global health index of the target tire of the new energy vehicle during the rotation cycle is obtained.

[0077] In specific implementation, firstly, the stress damage coefficient of the tire corresponding to each rotation interval is determined; secondly, the stress damage coefficient corresponding to each rotation interval is used as a weighting coefficient, and all pressure distribution deviations are multiplied by the stress damage coefficient of the corresponding rotation interval to obtain the weighted pressure distribution deviation of each rotation interval. The weighted pressure distribution deviation refers to the pressure distribution deviation value that reflects the interval damage risk weight; finally, all weighted pressure distribution deviations are summed, and when using the sigmoid function mapping method, the summation result of the weighted pressure distribution deviations is used as the input of the sigmoid function. The calculation is performed using the formula 1÷(1+e^(-k×(summation result-μ))) (where k is a coefficient for adjusting the mapping sensitivity, which can be set according to actual needs, and μ is the average value of the historical summation results, calibrated based on historical tire data), and the calculation result is used as the global health indicator of the target tire of the new energy vehicle within the rotation cycle.

[0078] It should be noted that the global health index in this application refers to a numerical value that characterizes the overall structural health status of the target tire. In the fault warning of the tire pressure monitoring system, the core role of determining the global health index is to break through the limitation of traditional tire pressure monitoring that only focuses on abnormal tire pressure values. It integrates fragmented information such as abnormal local pressure distribution and structural stress deviation in each rotation interval into a unified quantitative index that characterizes the overall structural health status of the tire. This provides the system with an intuitive and comparable health assessment benchmark. The global health index can accurately reflect the current overall structural integrity of the tire (e.g., when the tire pressure is normal but there are structural damages such as local bulges or interlayer separation, an abnormal increase in the index triggers a warning). It can also capture the damage evolution law through dynamic trend analysis of the index over multiple rotation cycles (e.g., a continuous increase in the index indicates that the damage is spreading). By comparing this index with the preset fault warning threshold in real time, it is possible to quickly determine whether the tire is in a normal, sub-healthy, or critical fault state, and accurately trigger graded warnings. This improves the coverage and accuracy of the tire pressure monitoring system's warnings for all types of tire faults (abnormal tire pressure + structural damage), providing all-dimensional protection for driving safety.

[0079] In some embodiments, the stress damage coefficient of the tire corresponding to each rotation range is determined by the following steps:

[0080] Obtain the operating parameters and structural mechanical parameters of the target tire;

[0081] The stress distribution coefficient for each rotation interval is calculated based on the operating parameters and the structural mechanical parameters.

[0082] The stress damage coefficient for each rotation range is identified based on historical tire damage data and the stress distribution coefficient for each rotation range.

[0083] In specific implementation, firstly, the operating parameters of the target tire (including load, vehicle speed, and road adhesion coefficient) are acquired through onboard sensors, and structural mechanical parameters (including the elastic modulus of the tire carcass material, sidewall stiffness, and tread thickness) are retrieved from the tire design technical documents. The real-time operating parameters refer to the set of dynamic parameters reflecting the tire's driving state, while the structural mechanical parameters refer to the set of inherent parameters characterizing the tire's material properties and structural strength. Secondly, based on the operating parameters and structural mechanical parameters, a simplified mechanical model of the tire is established using the well-known finite element analysis method of elasticity, with the real-time operating parameters used as load input. Structural mechanical parameters are used as boundary conditions of the model. By solving the static equilibrium equations, the stress magnitude and distribution law of each rotation interval under the current working condition are calculated, and the stress distribution coefficient of each rotation interval is obtained. That is, based on the working condition parameters and structural mechanical parameters, the well-known finite element analysis method of elasticity is used to first establish a simplified mechanical model of the target tire (retaining the core force-bearing structure of the tread, shoulder, sidewall, and carcass cord layer, ignoring the fine structure of the tread grooves and non-critical auxiliary components of the valve stem to balance calculation accuracy and efficiency). The geometric dimensions of the simplified mechanical model are determined by the tire structural parameters (such as tread width, sidewall height, carcass height, etc.). Thickness is determined, and material properties are assigned values ​​using structural mechanical parameters (such as the elastic modulus, Poisson's ratio, and sidewall stiffness of the tire material). The simplified mechanical model is then discretized using a mesh, with hexahedral solid elements used to divide the overall tire structure. This ensures that each rotational interval contains at least 5-8 continuous elements, and the boundaries of each rotational interval are used as auxiliary reference lines for mesh generation, ensuring precise correspondence between the element division and the angular interval boundaries. Next, the operating parameters are converted into loads and constraints for the finite element model. The load is converted into a vertically distributed load applied to the contact area between the tire tread and the ground, and the vehicle speed is combined with road surface conditions. The coefficients are converted into rolling resistance and lateral force, and the tire hub mounting position is set as a fixed constraint boundary to simulate the actual installation state. The static equilibrium equation is solved by the finite element analysis tool to obtain the stress field distribution data of the overall tire structure. All discrete elements corresponding to each rotation interval are traversed, and the equivalent stress value of each discrete element is extracted. The arithmetic mean of the equivalent stress of all discrete elements in the rotation interval is calculated, and then the average equivalent stress of the overall tire structure is calculated to obtain the stress distribution coefficient of each rotation interval. The stress distribution coefficient refers to the parameter characterizing the stress per unit area in each rotation interval.Finally, historical damage data of tires of the same model as the target tire is obtained from the tire historical damage database (the tire historical damage database is obtained in advance through laboratory bench accelerated life tests, finite element simulation analysis combined with material fatigue characteristics, or statistical analysis from large-scale fleet operation and maintenance data, which will not be elaborated here). Based on the tire historical damage data, the set of historical stress distribution coefficients for each rotation interval under the damage occurrence condition is calculated using the same calculation method as the "stress distribution coefficient of the current rotation interval". For each rotation interval, the minimum value of the historical stress distribution coefficient at the time of damage occurrence is counted as the corresponding rotation interval stress critical threshold. The ratio of the stress distribution coefficient of the current rotation interval to the damage critical threshold of the rotation interval is used as the initial stress damage coefficient (a ratio > 1 indicates that the current stress has exceeded the damage critical threshold, and the damage risk has increased significantly; a ratio ≤ 1 indicates that the current stress has not reached the damage critical value, and the damage risk is low). The minimum-maximum normalization method is used to map the initial stress damage coefficients of all rotation intervals to the [0,1] interval. The normalized value is the stress damage coefficient of each rotation interval.

[0084] It should be noted that the stress damage coefficient in this application refers to a coefficient that characterizes the weight of the damage influence of stress changes in each rotational zone on structural damage. The determination of the stress damage coefficient is based on the inherent differences in the physical structure (such as tread, shoulder, and sidewall) and stress mechanism of each rotational zone of the tire. This leads to significant differences in the response sensitivity of different zones to structural damage and the degree of damage influence of stress-induced damage. If a uniform weight is used to weight the pressure distribution deviation of each zone, the essential difference in damage risk between the slight deviation of the high-sensitivity zone (such as the shoulder, where stress is concentrated and cracks are prone to occur) and the significant deviation of the low-sensitivity zone (such as the non-stress core area of ​​the sidewall) will be ignored, thus leading to a distortion of the overall health assessment. Therefore, quantifying the "correlation between stress distribution characteristics and damage occurrence" of each rotational zone into a clear coefficient index can accurately characterize the sensitivity of different zones to damage. This provides a scientific weight basis that fits the actual damage risk for the subsequent weighted calculation of pressure distribution deviation, allowing the small characteristic deviations of the high-sensitivity zone to be given more full attention, and the normal fluctuations of the low-sensitivity zone to not excessively interfere with the overall assessment results.

[0085] In step S105, when the global health indicator exceeds the fault warning threshold, a structural damage fault warning for the target tire of the new energy vehicle is triggered.

[0086] In some embodiments, when the global health indicator exceeds the fault warning threshold, triggering a structural damage fault warning for the target tire of the new energy vehicle is achieved through the following steps:

[0087] Retrieve the structural damage fault early warning threshold that is compatible with the target tire;

[0088] If the global health index exceeds the structural damage fault warning threshold, then the structural damage fault warning triggering condition is determined to be met.

[0089] Based on the aforementioned warning triggering conditions, a structural damage fault warning operation is executed for the target tire of the new energy vehicle.

[0090] In specific implementation, firstly, the structural damage fault warning threshold adapted to the target tire is retrieved through the vehicle's storage module. This structural damage fault warning threshold is pre-calibrated and stored according to tire structural safety design standards and industry fault warning specifications, or set according to actual needs, which will not be elaborated here. The structural damage fault warning threshold refers to the critical value that quantifies whether the risk of tire structural damage needs to trigger a warning. Secondly, if the global health index exceeds the structural damage fault warning threshold, it is determined that the structural damage fault warning triggering condition is met. The warning triggering condition refers to the numerical judgment standard that needs to be met to trigger the tire structural damage fault warning. Finally, the warning execution module of the tire pressure monitoring system executes the structural damage fault warning operation for the target tire of the new energy vehicle according to the warning triggering condition. Specifically, this includes displaying a fault warning icon on the vehicle's central control display screen and playing a voice alarm prompt through the vehicle's audio system (some models can simultaneously trigger a mobile APP push alarm).

[0091] It should be noted that the structural damage fault warning operation in this application refers to a series of visual and audible information transmission operations by which the tire pressure monitoring system provides feedback to the user on the risk of tire structural damage.

[0092] In another aspect, in some embodiments, this application provides a tire monitoring and early warning system for new energy vehicles, with reference to... Figure 3 The figure is a schematic diagram of the structure of a tire monitoring and early warning system for new energy vehicles according to some embodiments of this application. The tire monitoring and early warning system for new energy vehicles includes: an acquisition module 201, a processing module 202, and an execution module 203, which are described below:

[0093] The acquisition module 201 in this application is mainly used to acquire the pressure data sequence of the target tire of the new energy vehicle;

[0094] Processing module 202, in this application, is mainly used to divide the rotation cycle of the target tire into multiple rotation intervals, and determine the pressure distribution characteristics of the target tire corresponding to each rotation interval based on the pressure data sequence.

[0095] The processing module 202 is also used to compare the pressure distribution characteristics of each rotation interval with the benchmark pressure distribution characteristics of the corresponding rotation interval under historical normal conditions, and generate the pressure distribution deviation corresponding to each rotation interval.

[0096] In addition, the processing module 202 is also used to perform a global health analysis of the target tire within the rotation cycle based on all pressure distribution deviations and the stress damage coefficient of the target tire corresponding to each rotation interval, thereby obtaining the global health index of the target tire of the new energy vehicle.

[0097] The execution module 203 in this application is mainly used to trigger a structural damage fault warning for the target tire of the new energy vehicle when the global health index exceeds the fault warning threshold.

[0098] In addition, this application also provides a computer device, the computer device including a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the above-described tire monitoring and early warning method for new energy vehicles.

[0099] In some embodiments, reference Figure 4 The figure is a schematic diagram of the structure of a computer device implementing a tire monitoring and early warning method for new energy vehicles, according to some embodiments of this application. The tire monitoring and early warning method for new energy vehicles in the above embodiments can be implemented through... Figure 4 The computer device shown is used to implement this, and the computer device includes at least one processor 301, a communication bus 302, a memory 303, and at least one communication interface 304.

[0100] The processor 301 can be a general-purpose central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more devices used to control the execution of the tire monitoring and early warning method for new energy vehicles described in this application.

[0101] The communication bus 302 can be used to transmit information between the aforementioned components.

[0102] The memory 303 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disks or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory 303 may exist independently and be connected to the processor 301 via the communication bus 302. The memory 303 may also be integrated with the processor 301.

[0103] The memory 303 stores program code for executing the solution of this application, and its execution is controlled by the processor 301. The processor 301 executes the program code stored in the memory 303. The program code may include one or more software modules. In the above embodiments, the determination of the tire monitoring and early warning method for new energy vehicles can be implemented by the processor 301 and one or more software modules in the program code in the memory 303.

[0104] Communication interface 304 uses any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0105] In a specific implementation, as one example, a computer device may include multiple processors, each of which may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. Here, a processor may refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).

[0106] The aforementioned computer device can be a general-purpose computer device or a special-purpose computer device. In specific implementations, the computer device can be a desktop computer, a portable computer, a network server, a handheld digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. This application does not limit the type of computer device.

[0107] In addition, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described tire monitoring and early warning method for new energy vehicles.

[0108] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0109] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A tire monitoring and early warning method for new energy vehicles, characterized in that, Includes the following steps: Obtain the pressure data sequence of target tires for new energy vehicles; The rotation cycle of the target tire is divided into multiple rotation intervals, and the pressure distribution characteristics of the target tire in each rotation interval are determined based on the pressure data sequence. The pressure distribution characteristics of each rotation interval are compared with the baseline pressure distribution characteristics of the corresponding rotation interval under historical normal conditions to generate the pressure distribution deviation corresponding to each rotation interval. Obtain the operating parameters and structural mechanical parameters of the target tire; calculate the stress distribution coefficient for each rotation range based on the operating parameters and the structural mechanical parameters; The stress damage coefficient of each rotation interval is identified based on historical tire damage data and stress distribution coefficients of each rotation interval. The stress damage coefficient corresponding to each rotation interval is used as a weighting coefficient, and all pressure distribution deviations are multiplied by the stress damage coefficient of the corresponding rotation interval to obtain the weighted pressure distribution deviation of each rotation interval. All weighted pressure distribution deviations are globally fused to obtain the global health index of the target tire of the new energy vehicle within the rotation cycle. The stress distribution coefficient is a parameter that characterizes the stress magnitude per unit area in each rotation interval, and the stress damage coefficient is a coefficient that characterizes the weight of the damage influence of stress changes in each rotation interval on structural damage. When the global health indicator exceeds the fault warning threshold, a structural damage fault warning for the target tire of the new energy vehicle is triggered.

2. The method as described in claim 1, characterized in that, The rotation cycle of the target tire is divided into multiple rotation intervals, specifically including: The parameters for dividing the rotation range are determined based on the rotation cycle of the target tire; The rotation cycle of the target tire is divided into a preset number of rotation intervals using the division parameters.

3. The method as described in claim 1, characterized in that, Determining the pressure distribution characteristics of the target tire corresponding to each rotation interval based on the pressure data sequence specifically includes: Extract the pressure data subsets corresponding to each rotation interval from the pressure data sequence; Calculate the statistical characteristic parameters for each pressure data subset, including the pressure mean, pressure variance, and pressure extreme value ratio; The statistical characteristic parameters are used as the pressure distribution characteristics of the target tire in each rotation interval.

4. The method as described in claim 1, characterized in that, The pressure distribution characteristics of each rotation interval are compared with the baseline pressure distribution characteristics of the corresponding rotation interval under historical normal conditions to generate the pressure distribution deviation for each rotation interval. Specifically, this includes: Obtain the baseline pressure distribution characteristics of each rotation interval under historical normal conditions; The pressure distribution characteristics of each rotation interval within the current rotation cycle are dimensionally aligned with the corresponding baseline pressure distribution characteristics to obtain the dimensionally aligned current pressure distribution characteristics and baseline pressure distribution characteristics. Calculate the initial deviation between the current pressure distribution characteristics after dimension alignment and the baseline pressure distribution characteristics; The initial deviation value is standardized and normalized to generate the pressure distribution deviation corresponding to each rotation interval.

5. The method as described in claim 1, characterized in that, When the global health indicator exceeds the fault warning threshold, triggering a structural damage fault warning for the target tire of the new energy vehicle specifically includes: Retrieve the structural damage fault early warning threshold that is compatible with the target tire; If the global health index exceeds the structural damage fault warning threshold, then the structural damage fault warning triggering condition is determined to be met. Based on the aforementioned warning triggering conditions, a structural damage fault warning operation is executed for the target tire of the new energy vehicle.

6. A tire monitoring and early warning system for new energy vehicles, used to execute the tire monitoring and early warning method for new energy vehicles as described in any one of claims 1 to 5, characterized in that, The system includes: The acquisition module is used to acquire the pressure data sequence of the target tires of new energy vehicles; The processing module is used to divide the rotation cycle of the target tire into multiple rotation intervals and determine the pressure distribution characteristics of the target tire in each rotation interval based on the pressure data sequence. The processing module is also used to compare the pressure distribution characteristics of each rotation interval with the benchmark pressure distribution characteristics of the corresponding rotation interval under historical normal conditions, and generate the pressure distribution deviation corresponding to each rotation interval. The processing module is also used to perform a global health analysis of the target tire within the rotation cycle based on all pressure distribution deviations and the stress damage coefficient of the target tire corresponding to each rotation interval, thereby obtaining the global health index of the target tire for new energy vehicles. The execution module is used to trigger a structural damage fault warning for the target tire of the new energy vehicle when the global health indicator exceeds the fault warning threshold.

7. A computer device, characterized in that, The computer device includes a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the tire monitoring and early warning method for new energy vehicles as described in any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the tire monitoring and early warning method for new energy vehicles as described in any one of claims 1 to 5.

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