A vehicle durability monitoring method and related apparatus

Abstract

The application discloses a vehicle endurance performance monitoring method and related device, and obtains the Z-direction displacement of a wheel shock absorber of a vehicle in a target period. When the vehicle passes through road surfaces with different flatness, the wheel shock absorber generates different Z-direction displacement. For example, when the vehicle passes through a horizontal road surface, the Z-direction displacement generated by the wheel shock absorber is small; and when the vehicle passes through a gravel road, the Z-direction displacement generated by the wheel shock absorber is large. Therefore, the Z-direction displacement of the wheel shock absorber is input into a pre-trained classification model, the road surface condition level of the vehicle when the wheel shock absorber generates the Z-direction displacement can be accurately predicted, the road surface condition level, the driving speed of the vehicle and the weight of the vehicle are input into an endurance performance model, and the endurance performance usage amount of the vehicle in the target period is determined. Therefore, the endurance performance usage amount of the vehicle can be accurately determined, so that the actual endurance performance condition of the individual vehicle can be reflected according to the endurance performance of the vehicle.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of automotive electronics, in particular to a vehicle endurance performance monitoring method and related device. BACKGROUND

[0002] The endurance performance of a vehicle refers to the working period of the vehicle and its assembly before reaching the limit wear value or being unable to use. For example, when the vehicle reaches or approaches the limit of endurance performance, if the vehicle continues to be driven, the vehicle will have a greater probability of fatigue endurance failure. If this failure occurs at a key position of the vehicle body structure, it may cause the vehicle to lose control or the vehicle body structure to be damaged, causing a certain degree of injury or death to the vehicle occupants; if the failure occurs at a non-key position of the vehicle body structure, it also increases the vehicle repair cost.

[0003] Although the endurance performance of a vehicle is so important, the existing endurance performance evaluation is more based on the national standards GB / T12678 and GB / T12679, which makes the experimental vehicle drive on highways, gravel roads, fish scale roads, rubbing plate roads, Belgium roads, undulating roads, swinging roads, damaged roads, square pits, standard slopes, etc. These roads can simulate the most severe working conditions in the actual use of the vehicle, and then reach the purpose of testing the endurance performance of the vehicle.

[0004] However, these measurement methods only reflect the upper limit of the endurance performance of the vehicle under laboratory conditions, and cannot reflect the actual endurance performance of the individual vehicle. SUMMARY

[0005] To solve the above problems, the present application provides a vehicle endurance performance monitoring method and related device for monitoring the endurance performance of the vehicle.

[0006] Based on this, the embodiments of the present application disclose the following technical solutions:

[0007] On the one hand, the present application provides a vehicle endurance performance monitoring method, which comprises:

[0008] Collecting the driving speed, weight and Z-direction displacement of the vehicle wheel shock absorber of the vehicle in a target period;

[0009] Inputting the Z-direction displacement of the vehicle wheel shock absorber into a classification model to predict the situation level of the road passed by the vehicle in the target period, the situation level being the flatness degree of the road passed by the vehicle when the Z-direction displacement is generated;

[0010] input the situation grade, the driving speed of the vehicle, and the weight of the vehicle into a durability performance model to determine the durability performance usage amount of the vehicle in the target period, the durability performance model being used to describe the correlation between the durability performance of the vehicle and the situation grade factor, the driving speed factor of the vehicle, and the weight factor of the vehicle.

[0011] Optionally, the inputting the Z-direction displacement of the wheel shock absorber into a classification model to predict the situation grade of the road surface passed by the vehicle in the target period comprises:

[0012] collecting a plurality of Z-direction displacements of the wheel shock absorber in the target period according to a preset collection frequency;

[0013] dividing the plurality of Z-direction displacements into at least one displacement interval according to a preset time window;

[0014] performing feature extraction on each displacement interval to obtain a Z-direction acceleration feature, and inputting the Z-direction acceleration feature into a classification model to predict the situation grade of each displacement interval;

[0015] obtaining the situation grade of the road surface passed by the vehicle in the target period according to the situation grade of each displacement interval.

[0016] Optionally, the inputting the road surface situation grade, the driving speed, and the weight into a durability performance model to obtain the durability performance usage amount of the vehicle in the target period comprises:

[0017] obtaining a road surface durability coefficient according to the situation grade;

[0018] obtaining a speed conversion coefficient according to the driving speed;

[0019] obtaining a weight conversion coefficient according to the weight;

[0020] obtaining the durability performance usage amount of the wheel shock absorber in the target period according to the product of the road surface durability coefficient, the speed conversion coefficient, and the weight conversion coefficient;

[0021] obtaining the durability performance usage amount of the vehicle in the target period according to the durability performance usage amount of the wheel shock absorber in the target period.

[0022] Optionally, if the situation grade comprises a first-class road surface, a second-class road surface, a third-class road surface, and a fourth-class road surface, the road surface durability coefficient corresponding to the first-class road surface is 1, the road surface durability coefficient corresponding to the second-class road surface is 1.1, the road surface durability coefficient corresponding to the third-class road surface is 1.5, and the road surface durability coefficient corresponding to the fourth-class road surface is 2;

[0023] The speed conversion coefficient is obtained according to the driving speed, and the speed conversion coefficient is represented as follows:

[0024] The speed conversion coefficient is obtained according to the driving speed and a vehicle speed conversion function, and the speed conversion coefficient is represented as follows:

[0025]

[0026] wherein kv represents the speed conversion coefficient, and v represents the driving speed.

[0027] The weight conversion coefficient is obtained according to the weight, and the weight conversion coefficient is represented as follows:

[0028] The weight conversion coefficient is obtained according to the weight and a vehicle weight conversion function, and the vehicle weight conversion function is represented as follows:

[0029]

[0030] wherein kw represents the weight conversion coefficient, and g represents the vehicle weight.

[0031] Optionally, the training step of the classification model comprises:

[0032] obtaining a Z-direction displacement of a wheel shock absorber and a corresponding situation level;

[0033] adjusting parameters of an initial classification model based on the Z-direction displacement and the corresponding situation level by using an objective function of the initial classification model, to obtain the classification model.

[0034] Optionally, the method further comprises:

[0035] obtaining a remaining endurance performance usage amount of the vehicle according to the endurance performance usage amount of the vehicle in the target period;

[0036] prompting the user of the remaining endurance performance usage amount of the vehicle.

[0037] In another aspect, an embodiment of the present application provides a vehicle endurance performance monitoring device, the device comprising: a collection unit, a prediction unit and a determination unit;

[0038] The collection unit is configured to collect a driving speed, a weight and a Z-direction displacement of a wheel shock absorber of a vehicle in a target period.

[0039] The prediction unit is configured to input the Z-direction displacement of the wheel shock absorber into a classification model, and predict a situation level of a road surface passed by the vehicle in the target period, the situation level being a flatness degree of a road surface passed by the vehicle when the Z-direction displacement is generated.

[0040] The determining unit is configured to input the situation level, the driving speed of the vehicle and the weight of the vehicle into a durability performance model to determine the durability performance usage of the vehicle in the target period, the durability performance model being configured to describe the correlation between the durability performance of the vehicle and the situation level factor, the driving speed factor of the vehicle and the weight factor of the vehicle.

[0041] In another aspect, the embodiments of the present application provide a vehicle durability performance monitoring device, which is connected to a CAN bus through a connector, and comprises a shell and a control chip, the control chip being fixed to the vehicle through the shell and a connecting device, and the control chip being configured to implement the method in the above aspect.

[0042] In another aspect, the embodiments of the present application provide a computer device, which comprises a processor and a memory:

[0043] The memory is configured to store program code and transmit the program code to the processor.

[0044] The processor is configured to execute the method in the above aspect according to instructions in the program code.

[0045] In another aspect, the embodiments of the present application provide a computer readable storage medium, which is configured to store a computer program, and the computer program is configured to execute the method in the above aspect.

[0046] Compared with the prior art, the above technical solutions of the embodiments of the present application have the following advantages:

[0047] The Z-direction displacement of the wheel shock absorber of the vehicle in the target period is obtained, and the wheel shock absorber will generate different Z-direction displacements when the vehicle passes through roads with different flatness, for example, the Z-direction displacement generated by the wheel shock absorber is smaller when the vehicle passes through a horizontal road, and the Z-direction displacement generated by the wheel shock absorber is larger when the vehicle passes through a gravel road. Therefore, the Z-direction displacement of the wheel shock absorber is input into a pre-trained classification model, so that the road situation level when the vehicle passes through the road can be accurately predicted when the wheel shock absorber generates the Z-direction displacement, the road situation level factor, the driving speed factor of the vehicle and the weight factor of the vehicle will all affect the durability performance of the vehicle, and the durability performance model is used to describe the correlation. Therefore, the road situation level, the driving speed of the vehicle and the weight of the vehicle are input into the durability performance model to determine the durability performance usage of the vehicle in the target period. Therefore, the road situation level is analyzed by the Z-direction displacement of the wheel shock absorber, the road situation level, the driving speed of the vehicle and the weight of the vehicle are input into the durability performance model, the durability performance usage of the vehicle can be accurately determined, and the actual durability performance of the individual vehicle can be reflected according to the durability performance of the vehicle. BRIEF DESCRIPTION OF DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced. Obviously, the accompanying drawings in the following description only represent some embodiments described in the present application, and for those skilled in the art, other drawings can also be obtained from these accompanying drawings without creative effort.

[0049] Figure 1 A flow chart of a vehicle endurance performance monitoring method provided by the present application;

[0050] Figure 2 A schematic diagram of Z-direction acceleration of a vehicle wheel shock absorber when the vehicle passes through a first-class road surface provided by the present application;

[0051] Figure 3 A schematic diagram of Z-direction acceleration of a vehicle wheel shock absorber when the vehicle passes through a second-class road surface provided by the present application;

[0052] Figure 4 A schematic diagram of Z-direction acceleration of a vehicle wheel shock absorber when the vehicle passes through a third-class road surface provided by the present application;

[0053] Figure 5 A schematic diagram of Z-direction acceleration of a vehicle wheel shock absorber when the vehicle passes through a fourth-class road surface provided by the present application;

[0054] Figure 6 A schematic diagram of a vehicle speed conversion function provided by the present application;

[0055] Figure 7 A schematic diagram of a vehicle weight conversion function provided by the present application;

[0056] Figure 8 A schematic diagram of a vehicle endurance performance monitoring device provided by the present application;

[0057] Figure 9 A schematic diagram of a housing size provided by the present application;

[0058] Figure 10 A schematic diagram of a vehicle endurance performance monitoring device provided by the present application;

[0059] Figure 11 A structural diagram of a computer device provided by the present application. DETAILED DESCRIPTION

[0060] In the following, the technical solutions in the embodiments of the present application will be described clearly and completely in conjunction with the drawings in the embodiments of the present application, so that those skilled in the art can better understand the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0061] The durability performance state of a vehicle is related to the safety of the driver and passengers of the vehicle, the repair economy of the vehicle, the price evaluation of the vehicle in the second-hand market, and the determination of the insurance premium of the vehicle. The following will be described respectively.

[0062] For the safety of the driver and passengers of the vehicle and the repair economy of the vehicle, when the vehicle reaches or approaches the durability limit, if the vehicle continues to be driven, the vehicle will have a greater probability of fatigue durability failure. If this failure occurs at a key part of the vehicle body structure, it may cause the vehicle to lose control or the vehicle body structure to be damaged, causing a certain degree of injury to the driver and passengers of the vehicle; if this failure occurs at a non-key part of the vehicle body structure, it also increases the vehicle repair cost.

[0063] For the price evaluation of the vehicle in the second-hand market, the price of the vehicle should be evaluated according to the vehicle model, brand, and use condition. In actual operation, the use condition of the vehicle is often estimated according to the driving mileage of the vehicle. From a statistical point of view, the driving mileage of the vehicle and the use condition of the vehicle are only positively correlated and cannot reflect the difference in the use condition of the individual vehicle. For example, two vehicles of the same brand and model have the same driving mileage, but one vehicle is often driven on smooth roads and the other vehicle is often driven on bumpy roads. The second vehicle has a greater load impact on the shock absorption, body welding, sheet metal parts, and other structures compared to the first vehicle. The durability performance of the second vehicle should be lower than that of the first vehicle, and the price of the second vehicle should be lower than that of the first vehicle. However, because the use condition of the vehicle is more dependent on the mileage information, and the fatigue cracks of the vehicle body are also difficult to find, accurate price evaluation of individual vehicles cannot be achieved in actual operation, which is not transparent to both the buyer and the seller in the second-hand vehicle transaction.

[0064] Although the durability of the vehicle is so important, the existing durability evaluation is more based on the national standards GB / T12678 and GB / T 12679, and the experimental vehicle is driven through the highway, the gravel road, the fish scale road, the rubbing plate road, the Belgium road, the undulating road, the swinging road, the damaged road, the square pit, the standard slope and other roads. Through these roads, the most severe working conditions in the actual use of the vehicle can be simulated, and then the purpose of testing the durability of the vehicle is achieved. However, these measurement methods only reflect the upper limit of the durability of the vehicle under laboratory conditions, and cannot reflect the actual durability of the individual vehicle.

[0065] Based on this, the embodiment of the present application provides a vehicle durability monitoring method and device, the Z direction displacement of the vehicle wheel shock absorber is obtained, and the vehicle wheel shock absorber will produce different Z direction displacement when the vehicle passes through different flatness roads. For example, when the vehicle passes through the horizontal road, the Z direction displacement produced by the vehicle wheel shock absorber is small; when the vehicle passes through the gravel road, the Z direction displacement produced by the vehicle wheel shock absorber is large. Therefore, the Z direction displacement of the vehicle wheel shock absorber is input into the pre-trained classification model, the road condition level of the vehicle passing through when the Z direction displacement of the vehicle wheel shock absorber is generated can be determined, the road condition level factor, the driving speed factor of the vehicle and the weight factor of the vehicle will all affect the durability of the vehicle, and are described by the durability model. Therefore, the road condition level, the driving speed of the vehicle and the weight of the vehicle are input into the durability model to determine the durability usage of the vehicle. Therefore, by analyzing the road condition level through the Z direction displacement of the vehicle wheel shock absorber, the road condition level, the driving speed of the vehicle and the weight of the vehicle are input into the durability model, and the durability usage of the vehicle can be accurately determined.

[0066] The following will be combined Figure 1 A vehicle durability monitoring method provided by the embodiment of the present application is introduced. Referring to Figure 1 The figure is a flow chart of a vehicle durability monitoring method provided by the present application, which can include the following steps 101-103.

[0067] S101: Collecting the driving speed, weight and Z direction displacement of the vehicle wheel shock absorber of the vehicle in the target period.

[0068] It is found through analysis that the vehicle is continuously subjected to road impact load caused by uneven road surface when driving, and is also subjected to the action of steering lateral force, driving force and braking force. These forces generally change with time and show a periodic cycle state. At the same time, for the vehicle, the engine of the traditional fuel vehicle and the driving motor of the new energy vehicle are also a vibration source.

[0069] Therefore, the vehicle is in a relatively complex stress environment during driving, and basically each component of the vehicle will be affected by stress and strain changing over time. After a certain period of time, some components will produce durability problems, appear fatigue damage, and be destroyed, thereby affecting the service life of the vehicle. That is, the durability of the vehicle is closely related to the load borne by the vehicle.

[0070] The factors affecting the load include the weight of the vehicle, the roughness of the road, the driving speed of the vehicle, the driving time length, the acceleration and deceleration, and the like.

[0071] It is found through analysis that the heavier the vehicle, the faster the vehicle drives, the more uneven the driving road, and the more frequent the acceleration and deceleration, the greater the impact load borne by each component of the vehicle, and the more obvious the durability degradation of the vehicle and the faster the service life decreases. Therefore, the driving speed of the vehicle, the weight of the vehicle, and the Z-direction displacement of the wheel shock absorber in a target period, such as the time period from the start time to the end time of the current driving of the vehicle, can be obtained.

[0072] As a possible implementation manner, the vehicle durability monitoring method provided by the embodiment of the application can be integrated in a vehicle domain controller, continuously obtains the driving state information of the vehicle through a vehicle networking background data, or is applied to a separate controller and designed in an automobile electrical architecture, and the controller is integrated on a chassis control CAN bus (CH CAN), and the driving state information of the vehicle is obtained from the CH CAN. The driving state information of the vehicle includes the Z-direction displacement of each wheel shock absorber of the vehicle, the driving speed of the vehicle, the weight of the vehicle, and the like.

[0073] The Z-direction displacement is established as a center of the wheel shock absorber of the vehicle at rest, and the displacement in the Z-axis direction when the wheel shock absorber moves is the Z-direction displacement.

[0074] S102: input the Z-direction displacement of the wheel shock absorber into the classification model, and predict the situation level of the road passed by the vehicle in the target period.

[0075] The situation level is the flatness degree of the road passed by the vehicle when the Z-direction displacement is generated. The application does not specifically limit the flatness degree of the road, and the following is described by taking four levels as an example.

[0076] This classification mode mainly considers the impact load when the vehicle runs, and the road load excitation of the same level is similar. With the increase of the road level, the Z-direction displacement of the wheel shock absorber is larger and larger, as shown in Figures 2-5A Z-direction acceleration curve of a shock absorber of a vehicle passing through different levels of road surfaces. The first level of road surface is a horizontal road surface, an urban road surface, etc., and the impact load caused by the vehicle driving on this type of road surface is the smallest, as shown in Figure 2 The second level of road surface is a general impact road surface, such as a gravel road, etc., as shown in Figure 3 The third level of road surface is a resonance road surface, as shown in Figure 4 The fourth level of road surface is a square pit road, etc., as shown in Figure 5

[0077] As a possible implementation, the Z-direction displacement of the wheel shock absorber in the target period can be collected at a preset collection frequency, the Z-direction displacement is divided into at least one displacement interval according to a preset time window, feature extraction is performed for each displacement interval to obtain Z-direction acceleration features, the Z-direction acceleration features are input into a classification model to predict the condition level of each displacement interval, and the condition level of the road surface passed by the vehicle in the target period is obtained according to the condition level of each displacement interval.

[0078] For example, the preset collection frequency is 1 kHz, the Z-direction displacement of the vehicle shock absorber is collected in the target period, the preset time window w is 8, i.e. the target period is divided into multiple displacement intervals according to 8 ms, and there is at least one displacement interval. Taking one displacement interval as an example, the Z-direction displacement of the vehicle shock absorber in 8 ms is obtained, and feature extraction is performed, such as maximum acceleration value, minimum acceleration value, acceleration mean value, and total acceleration value change. Z-direction acceleration features such as XGboost, Random Forest, neural network model, etc. are used for classification to obtain the condition level of the road surface passed by the vehicle in the displacement interval. Thus, the condition level of the road surface passed by the vehicle in the target period can be obtained.

[0079] The classification model is pre-trained, and as a possible implementation, the training steps of the classification model are described below. The Z-direction displacement of the wheel shock absorber and the corresponding condition level are obtained, the objective function of the initial classification model is used to adjust the parameters of the initial classification model based on the Z-direction displacement and the corresponding condition level, and the classification model is obtained.

[0080] For example, a road test can be performed by driving an experimental vehicle to collect the Z-direction displacement of the wheel shock absorber and the video of the contact between the wheel and the ground. The Z-direction displacement of the shock absorber and the condition level of the road surface are labeled by video comparison, and the Z-direction displacement of the wheel shock absorber and the corresponding condition level are obtained as training data. As a possible implementation, 80% of the training data can be used as a training set, and 20% of the training data can be used as a test set. The training set is input into the classification model for training, and the test set is used for verification. The classification accuracy is used as the evaluation standard to optimize the parameters of the classification model.​

[0081] For example, the Z-direction acceleration is acquired every 1 kHz, 16 groups of Z-direction acceleration and their corresponding situation levels (labels) are acquired, each 8 ms is divided into a displacement interval, 9 displacement intervals are obtained, the Z-direction acceleration features (maximum acceleration and average acceleration) are extracted for each displacement interval, the Z-direction acceleration features are input into the classification model, and the situation level (classification result) of each displacement interval is predicted, as shown in Table 1.

[0082] Table 1 Road test shock absorber z-direction acceleration signal labeling and classification result

[0083]

[0084] As a possible implementation manner, if the classification model is an XGBoost model, the Z-direction displacement and the corresponding situation level are input into the XGBoost model, and the objective function is composed of a loss function and a regularization term, as follows:

[0085]

[0086] wherein, is the cumulative model output, is the label, characterizes the complexity of the tree.

[0087] S103: input the situation level, the driving speed of the vehicle, and the weight of the vehicle into the durability performance model to determine the durability performance usage of the vehicle in the target period.

[0088] The durability performance model is used to describe the correlation between the durability performance of the vehicle and the situation level factor, the driving speed factor of the vehicle, and the weight factor of the vehicle. The following will be described respectively.

[0089] The situation level factor can be represented as a road surface durability coefficient Kr, wherein r represents the situation level. As described above, the more uneven the road surface, the greater the impact load the vehicle receives when driving, and the greater the impact on the durability performance of the vehicle, so Kr is also greater. As a possible implementation manner, corresponding to the four situation levels shown in Table 1, the road surface durability coefficient K1 of the first-class road surface can be 1, the road surface durability coefficient K2 of the second-class road surface can be 1.1, the road surface durability coefficient K3 of the third-class road surface can be 1.5, and the road surface durability coefficient K4 of the fourth-class road surface can be 2. Figures 2-5

[0090] The driving speed factor of the vehicle can be represented as a speed conversion coefficient Kv, wherein the speed conversion coefficient Kv is positively correlated with the durability performance usage of the vehicle. As a possible implementation manner, the driving speed of the vehicle can be converted into the speed conversion coefficient Kv through a speed conversion function, and the speed conversion function is as follows​Figure 6 As shown in the formula (1), the durability performance usage of the vehicle in the target period can be represented as follows:

[0091]

[0092] wherein, kv represents the speed conversion coefficient, and v represents the driving speed. For example, when the vehicle speed v is 25km / h, Kv=1.

[0093] The weight factor of the vehicle can be represented as a weight conversion coefficient Kw, wherein the weight conversion coefficient Kw is positively correlated with the durability performance usage of the vehicle. As a possible implementation manner, the weight of the vehicle can be converted into the weight conversion coefficient Kw through a vehicle weight conversion function, such as Figure 7 As shown in the formula (2), the durability performance usage of the vehicle in the target period can be represented as follows:

[0094]

[0095] wherein, Kw represents the weight conversion coefficient, and g represents the vehicle weight. For example, when the vehicle weight g is 1.5t, Kw=1.5.

[0096] As a possible implementation manner, the case level, the driving speed of the vehicle, and the weight of the vehicle are input into the durability performance model to determine the durability performance usage of the vehicle in the target period As shown in the formula (3), the durability performance usage of the vehicle in the target period can be represented as follows:

[0097]

[0098] The formula indicates that, when the vehicle is driving, the speed conversion coefficient Kv, the weight conversion coefficient Kw, and the road durability coefficient are multiplied and then accumulated in the time dimension and the multiple wheel shock absorber losses are accumulated, i.e., the durability performance usage of the vehicle in the target period It should be noted that the vehicle has multiple wheel shock absorbers, such as four, and the durability performance usage of the vehicle in the target period is obtained by accumulating each wheel shock absorber.

[0099] The following further illustrates with specific data of a certain vehicle in a certain trip. The driving parameters of the vehicle and each wheel shock absorber in this trip are converted by the above model, and the results are shown in Table 2:

[0100] Table 2

[0101]

[0102] As a possible implementation manner, the durability performance remaining amount of the vehicle is obtained by the historical durability performance remaining amount of the vehicle and the durability performance usage in the target period, and is output, stored, and used. For example, it is displayed on the vehicle-mounted large screen, and the durability performance remaining amount is input to downstream tasks, such as maintenance, vehicle condition reminding, and second-hand vehicle price evaluation.

[0103] For example, according to the historical durability performance remaining amount, the durability performance remaining amount of the vehicle can be calculated, which can be expressed as follows:

[0104]

[0105] wherein, represents the durability performance remaining amount of the vehicle, represents the historical durability performance remaining amount, i.e. the durability performance remaining amount of the total durability performance of the vehicle before the target period.

[0106] Continuing with the above example, in general, according to experience and durability test data, the total durability performance of the vehicle is converted to , and the historical durability performance remaining amount converted from the driving record of the vehicle before the target period (before this trip) is .

[0107] It is known that the vehicle weight of the vehicle is 1.4t, the total driving time of this trip is 92.42min, and the vehicle speed does not exceed 120km / h. Substituting the data into the durability performance model, , we get:

[0108]

[0109] The durability performance remaining ratio before this trip is , the durability performance remaining amount of the vehicle after this trip is , the durability performance usage ratio of this trip is , and the durability performance remaining ratio after this trip is , and the coefficient can be used for display on the central control screen.

[0110] As can be seen from the above technical solution, the Z-direction displacement of the vehicle wheel shock absorber in the target period is obtained. When the vehicle passes through roads of different flatness, the wheel shock absorber will produce different Z-direction displacement. For example, when the vehicle passes through a horizontal road, the Z-direction displacement produced by the wheel shock absorber is small; when the vehicle passes through a gravel road, the Z-direction displacement produced by the wheel shock absorber is large. Therefore, inputting the Z-direction displacement of the wheel shock absorber into the pre-trained classification model can accurately predict the road condition level of the vehicle when the wheel shock absorber produces Z-direction displacement. The road condition level factor, the driving speed factor of the vehicle and the weight factor of the vehicle all affect the durability performance of the vehicle, and are described by the durability performance model. Therefore, the road condition level, the driving speed of the vehicle and the weight of the vehicle are inputted into the durability performance model to determine the durability performance usage amount of the vehicle in the target period. Therefore, by analyzing the road condition level through the Z-direction displacement of the wheel shock absorber and inputting the road condition level, the driving speed of the vehicle and the weight of the vehicle into the durability performance model, the durability performance usage amount of the vehicle can be accurately determined, so as to reflect the actual durability performance of the individual vehicle according to the durability performance of the vehicle.

[0111] The embodiment of the present application provides a vehicle endurance performance monitoring method, and further provides a vehicle endurance performance monitoring device. Figure 8 As shown in the figure, the device comprises a shell 801 and a control chip 802, and the control chip 802 is fixed on the vehicle through the shell 801, and the device is connected to the CAN bus through a connector, which is not shown in the figure.

[0112] The embodiment of the present application does not specifically limit the size of the device, as shown in the figure. Figure 9 The figure is a schematic diagram of the size of the shell provided by the embodiment of the present application. The unit of the data in the figure is millimeter. The control chip can be built in the shell, and the control chip is used for executing the vehicle endurance performance monitoring method in any one of the preceding embodiments.

[0113] The embodiment of the present application provides a vehicle endurance performance monitoring method, and further provides a vehicle endurance performance monitoring device, as shown in the figure. Figure 10 The device comprises a collection unit 1001, a prediction unit 1002 and a determination unit 1003.

[0114] The collection unit 1001 is configured to collect a driving speed, a weight and a Z-direction displacement of a wheel shock absorber of a vehicle in a target period.

[0115] The prediction unit 1002 is configured to input the Z-direction displacement of the wheel shock absorber into a classification model, and predict a situation level of a road surface passed by the vehicle in the target period, wherein the situation level is a flatness degree corresponding to the road surface passed by the vehicle when the Z-direction displacement is generated.

[0116] The determination unit 1003 is configured to input the situation level, the driving speed of the vehicle and the weight of the vehicle into a endurance performance model, and determine an endurance performance usage amount of the vehicle in the target period, wherein the endurance performance model is used for describing an association relationship among the endurance performance of the vehicle, a situation level factor, a driving speed factor of the vehicle and a weight factor of the vehicle.

[0117] As a possible implementation manner, the prediction unit 1002 is configured to:

[0118] Collect a plurality of Z-direction displacements of the wheel shock absorber in the target period according to a preset collection frequency;

[0119] Divide the plurality of Z-direction displacements into at least one displacement interval according to a preset time window;

[0120] Extract a feature for each displacement interval to obtain a Z-direction acceleration feature, input the Z-direction acceleration feature into the classification model, and predict a situation level of each displacement interval.

[0121] According to the situation level of each displacement interval, a situation level of a road surface passed by the vehicle in the target period is obtained.

[0122] As a possible implementation manner, the determination unit 1003 is configured to:

[0123] According to the situation level, a road surface endurance coefficient is obtained;

[0124] According to the driving speed, a speed conversion coefficient is obtained;

[0125] According to the weight, a weight conversion coefficient is obtained;

[0126] According to a product of the road surface endurance coefficient, the speed conversion coefficient and the weight conversion coefficient, a durability performance usage amount of the wheel shock absorber in the target period is obtained;

[0127] According to the durability performance usage amount of the shock absorber in the target period, a durability performance usage amount of the vehicle in the target period is obtained.

[0128] As a possible implementation manner, if the situation level includes a first-class road surface, a second-class road surface, a third-class road surface and a fourth-class road surface, the road surface endurance coefficient corresponding to the first-class road surface is 1, the road surface endurance coefficient corresponding to the second-class road surface is 1.1, the road surface endurance coefficient corresponding to the third-class road surface is 1.5, and the road surface endurance coefficient corresponding to the fourth-class road surface is 2;

[0129] The determination unit 1003 is configured to:

[0130] According to the driving speed and a vehicle speed conversion function, a speed conversion coefficient is obtained, and the speed conversion coefficient is represented as follows:

[0131]

[0132] Wherein, kv represents the speed conversion coefficient, and v represents the driving speed.

[0133] The determination unit 1003 is configured to:

[0134] According to the weight and a vehicle weight conversion function, a weight conversion coefficient is obtained, and the vehicle weight conversion function is represented as follows:

[0135]

[0136] Wherein, kw represents the weight conversion coefficient, and g represents the vehicle weight.

[0137] As a possible implementation manner, the training step of the classification model includes:

[0138] Obtaining Z-direction displacement of a wheel shock absorber of a vehicle and a corresponding road condition level;

[0139] Based on the Z-direction displacement and the corresponding road condition level, adjusting parameters of an initial classification model by using an objective function of the initial classification model to obtain the classification model.

[0140] As a possible implementation, the apparatus further comprises a training unit configured to:

[0141] Obtaining a remaining durability performance usage amount of the vehicle according to the durability performance usage amount of the vehicle in the target period;

[0142] Prompting the user with the remaining durability performance usage amount of the vehicle.

[0143] Obtaining Z-direction displacement of a wheel shock absorber of a vehicle in a target period. The wheel shock absorber generates different Z-direction displacement when the vehicle passes through roads with different flatness. For example, when the vehicle passes through a horizontal road, the Z-direction displacement generated by the wheel shock absorber is small; when the vehicle passes through a gravel road, the Z-direction displacement generated by the wheel shock absorber is large. Thus, the Z-direction displacement of the wheel shock absorber is input into a pre-trained classification model, which can accurately predict the road condition level when the wheel shock absorber generates Z-direction displacement. The road condition level factor, the driving speed factor of the vehicle, and the weight factor of the vehicle all affect the durability performance of the vehicle and are described by a durability performance model. Therefore, the road condition level, the driving speed of the vehicle, and the weight of the vehicle are input into the durability performance model to determine the durability performance usage amount of the vehicle in the target period. Thus, by analyzing the road condition level through the Z-direction displacement of the wheel shock absorber, and inputting the road condition level, the driving speed of the vehicle, and the weight of the vehicle into the durability performance model, the durability performance usage amount of the vehicle can be accurately determined, so as to reflect the actual durability performance of the individual vehicle according to the durability performance of the vehicle.

[0144] The embodiments of the present application also provide a computer device, referring to Figure 11 The figure shows a structure diagram of a computer device provided by the embodiments of the present application, as shown in Figure 11 The device comprises a processor 1120 and a memory 1110:

[0145] The memory 1110 is configured to store program code and transmit the program code to the processor;

[0146] The processor 1120 is configured to execute any one of the vehicle durability performance monitoring methods provided by the above embodiments according to instructions in the program code.

[0147] The embodiment of the application provides a computer readable storage medium for storing a computer program, the computer program is used for executing any vehicle endurance performance monitoring method provided by the above embodiment.

[0148] Each of the embodiments in the specification is described in a progressive manner, and the same and similar parts of each of the embodiments can be referred to each other. Each of the embodiments focuses on the difference from other embodiments. In particular, for the device embodiments, since they are basically similar to the method embodiments, they are described more simply, and the relevant parts can be referred to the part of the method embodiments. The device embodiments described above are only schematic, and the units and modules described as separate components can or can not be physically separated. In addition, part or all of the units and modules can be selected according to actual needs to achieve the purpose of the embodiment. Those skilled in the art can understand and implement without creative labor.

[0149] The above is only a specific embodiment of the application, and it should be pointed out that, for those skilled in the art, without departing from the principle of the application, a number of improvements and refinements can be made, which should be regarded as the protection scope of the application.

Claims

1. A vehicle durability monitoring method characterized by, The method comprises: collecting the driving speed, weight and Z-direction displacement of the vehicle in a target period; collecting multiple Z-direction displacements of the wheel shock absorber in the target period according to a preset collection frequency; dividing the multiple Z-direction displacements into at least one displacement interval according to a preset time window; extracting features for each displacement interval to obtain Z-direction acceleration features, inputting the Z-direction acceleration features into a classification model to predict the condition level of each displacement interval, wherein the Z-direction acceleration features include one or more of maximum acceleration, minimum acceleration, average acceleration and total acceleration value change; obtaining the condition level of the road surface passed by the vehicle in the target period according to the condition level of each displacement interval, wherein the condition level is the flatness of the road surface passed by the vehicle when the Z-direction displacement is generated; inputting the condition level, driving speed and weight of the vehicle into a durability performance model to determine the durability performance usage of the vehicle in the target period, wherein the durability performance model is used to describe the correlation between the durability performance of the vehicle and the condition level factor, the driving speed factor and the weight factor of the vehicle.

2. The method of claim 1, wherein, The inputting the condition level, driving speed and weight of the vehicle into a durability performance model to determine the durability performance usage of the vehicle in the target period comprises: obtaining a road surface durability coefficient according to the condition level; obtaining a speed conversion coefficient according to the driving speed; obtaining a weight conversion coefficient according to the weight; obtaining the durability performance usage of the wheel shock absorber in the target period according to the product of the road surface durability coefficient, the speed conversion coefficient and the weight conversion coefficient; obtaining the durability performance usage of the vehicle in the target period according to the durability performance usage of the wheel shock absorber in the target period.

3. The method of claim 2, wherein, If the condition level includes first-class road surface, second-class road surface, third-class road surface and fourth-class road surface, the road surface durability coefficient corresponding to the first-class road surface is 1, the road surface durability coefficient corresponding to the second-class road surface is 1.1, the road surface durability coefficient corresponding to the third-class road surface is 1.5, and the road surface durability coefficient corresponding to the fourth-class road surface is 2; The obtaining a speed conversion coefficient according to the driving speed comprises: obtaining a speed conversion coefficient according to the driving speed and a speed conversion function, wherein the speed conversion coefficient is represented as follows: ； wherein kv represents the speed conversion coefficient and v represents the driving speed; The obtaining a weight conversion coefficient according to the weight comprises: obtaining a weight conversion coefficient according to the weight and a weight conversion function, wherein the weight conversion function is represented as follows: ； wherein kw represents the weight conversion coefficient and g represents the vehicle weight.

4. The method of claim 1, wherein, The training step of the classification model comprises: obtaining the Z-direction displacement of the wheel shock absorber and the corresponding condition level; adjusting the parameters of an initial classification model based on the Z-direction displacement and the corresponding condition level by using the objective function of the initial classification model to obtain the classification model.

5. The method according to any one of claims 1 to 4, characterized in that, The method further comprises: obtaining the remaining durability performance usage of the vehicle according to the durability performance usage of the vehicle in the target period; The remaining durability performance usage of the vehicle is prompted to a user.

6. A vehicle durability monitoring apparatus characterized by comprising: The device comprises a collection unit, a prediction unit and a determination unit; The collection unit is configured to collect driving speed, weight and Z-direction displacement of a wheel shock absorber of a vehicle in a target period; The prediction unit is configured to collect a plurality of Z-direction displacements of the wheel shock absorber in the target period according to a preset collection frequency; The plurality of Z-direction displacements are divided into at least one displacement interval according to a preset time window; For each displacement interval, a feature is extracted to obtain a Z-direction acceleration feature, the Z-direction acceleration feature is input into a classification model, and a condition level of each displacement interval is predicted, the Z-direction acceleration feature comprises one or more of maximum acceleration, minimum acceleration, acceleration mean value and total acceleration value change amount; According to the condition level of each displacement interval, a condition level of a road surface passed by the vehicle in the target period is obtained, the condition level is a flatness degree corresponding to a road surface passed by the vehicle when the Z-direction displacement is generated; The determination unit is configured to input the condition level, driving speed and weight of the vehicle into a durability performance model to determine durability performance usage of the vehicle in the target period, and the durability performance model is used to describe the correlation between durability performance of the vehicle and condition level factors, driving speed factors and weight factors of the vehicle.

7. A vehicle durability monitoring apparatus characterized by comprising: The device is connected to a CAN bus through a connector, and is composed of a shell and a control chip, the control chip is fixed on a vehicle through the shell and a connecting device, and the control chip is used to execute the method of any one of claims 1-5.

8. A computer device, comprising: The computer device comprises a processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is used to execute the method of any one of claims 1-5 according to instructions in the program code.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium is used to store program code, and the program code is used to execute the method of any one of claims 1-5.

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