CN114379482A - Tire maintenance prediction method and apparatus, and computer-readable storage medium - Google Patents

Abstract

The invention discloses a tire maintenance prediction method and equipment, and a computer-readable storage medium, belonging to the technical field of vehicle maintenance management. The present invention obtains the tire parameters of the vehicle under the current working condition; the tire parameters include at least one of vehicle load, vehicle speed, Z-direction acceleration, yaw moment, tire temperature and tire pressure; A trained service life prediction model, so that the service life prediction model predicts the tire life of the vehicle according to the tire parameters; when the tire life reaches a preset threshold, generate tire replacement reminder information corresponding to the vehicle , and send the tire replacement reminder information to the user terminal to remind the user to replace the tire. Prediction of life expectancy, and timely maintenance of tires according to tire life.

Description

Tire maintenance prediction method and device, computer readable storage medium

technical field

The invention relates to the technical field of vehicle maintenance management, and in particular, to a tire maintenance prediction method and device, and a computer-readable storage medium.

Background technique

Tires are annular elastic rubber products that roll on the ground and are assembled on various vehicles or machinery. Usually installed on the metal rim, it can support the body, buffer the external impact, realize the contact with the road surface and ensure the driving performance of the vehicle. In order to ensure the mileage and performance of the tires, it is necessary to regularly check and maintain the tire pressure and tire wear. At present, tires are usually replaced according to a fixed number of kilometers or a fixed time. However, under different operating conditions, the tire wear conditions are different, and the tire wear conditions under different operating conditions cannot be accurately determined, causing inconvenience to tire maintenance. , and even cause serious security problems.

The above content is only used to assist the understanding of the technical solutions of the present invention, and does not mean that the above content is the prior art.

SUMMARY OF THE INVENTION

The main purpose of the present invention is to provide a tire maintenance prediction method and equipment, and a computer-readable storage medium, aiming to solve the technical problem that the tire wear condition under different operating conditions cannot be accurately determined.

In order to achieve the above object, the present invention provides a tire maintenance prediction method, the method includes:

Obtaining tire parameters of the vehicle under the current working condition; the tire parameters include at least one of vehicle load, vehicle speed, Z-direction acceleration, yaw moment, tire temperature and tire pressure;

inputting the tire parameters into a pre-trained service life prediction model, so that the service life prediction model predicts the tire life of the vehicle according to the tire parameters;

When the tire life reaches a preset threshold, generate tire replacement reminder information corresponding to the vehicle, and send the tire replacement reminder information to a user terminal to remind the user to replace the tire.

In this embodiment, the prediction model includes a first prediction model and a second prediction model; before the step of acquiring tire parameters of the vehicle under the current operating condition, the method further includes:

Check whether the vehicle is equipped with a tire pressure monitoring system;

The step of obtaining the tire parameters of the vehicle under the current working condition includes:

When a tire pressure monitoring system is installed on the vehicle, obtain the tire temperature and tire pressure detected by the tire pressure monitoring system under the current working condition of the vehicle;

When the tire pressure monitoring system is not installed on the vehicle, obtain the vehicle load, vehicle speed, Z-direction acceleration and yaw moment of the vehicle under the current working condition;

The step of inputting the tire parameters into a pre-trained service life prediction model so that the service life prediction model predicts the tire life of the vehicle according to the tire parameters includes:

When the obtained tire pressure parameters are tire temperature and tire pressure, the tire temperature and tire pressure are input into a first prediction model; wherein, the first prediction model includes the relationship between tire temperature, tire pressure and tire life. The mapping relationship between;

After the obtained tire pressure parameters are vehicle load, vehicle speed, Z-direction acceleration and yaw moment, the tire pressure parameters are vehicle load, vehicle speed, Z-direction acceleration and yaw moment are input into the second prediction model; wherein , the second prediction model includes a mapping relationship between load samples, vehicle speed samples, Z-direction acceleration samples, yaw moment samples and tire life.

In this embodiment, before the step of acquiring the tire parameters of the vehicle under the current working condition, the method further includes:

Obtain the steering wheel angle of the vehicle, and determine the driving state of the vehicle according to the steering wheel angle of the vehicle;

When the driving state of the vehicle is a straight driving state, obtain the position information of the vehicle;

determining an offset value of the vehicle according to the location information;

When the offset value of the vehicle is located in the first offset interval, the step of detecting whether the vehicle is equipped with a tire pressure monitoring system is performed.

In this embodiment, after the step of determining the offset value of the vehicle according to the location information, the method further includes:

When the offset value of the vehicle is in the second offset interval, four-wheel alignment correction information is generated and sent to the user terminal, so as to remind the user to perform alignment correction on the tires of the vehicle.

In this embodiment, before the step of acquiring the tire parameters of the vehicle under the current working condition, the method further includes:

When a vehicle start command is detected, the maintenance record of the tires of the current vehicle is obtained;

When it is determined that the four-wheel alignment function of the vehicle is qualified according to the maintenance record of the tire, the steps of obtaining the steering wheel angle of the vehicle and determining the driving state of the vehicle according to the steering wheel angle of the vehicle are performed.

In this embodiment, the steps of the tire maintenance prediction method further include:

When it is determined that the four-wheel alignment function of the vehicle is unqualified according to the maintenance record of the tire, the four-wheel alignment correction information is sent to the user terminal, so as to remind the user to perform alignment correction on the tire of the vehicle.

In this embodiment, after the step of inputting the tire parameters into the pre-trained service life prediction model, so that the service life prediction model predicts the tire service life of the vehicle according to the tire parameters, the method further includes: :

When it is detected that the maintenance record of the tire is changed, the evaluation information of the tire corresponding to the change of the maintenance record is obtained;

The service life prediction model is updated using the tire evaluation information.

In addition, in order to achieve the above object, the present invention also provides a tire maintenance prediction device, the tire maintenance prediction device comprising: a memory, a processor, and a tire maintenance prediction stored on the memory and executable on the processor A program that, when executed by the processor, implements the steps of the tire maintenance prediction method as described above.

In addition, in order to achieve the above object, the present invention also provides a computer-readable storage medium, which stores a tire maintenance prediction program, and when the tire maintenance prediction program is executed by a processor, realizes the tire as described above. The steps of the maintenance prediction method.

The tire maintenance prediction method and device, and the technical solution of the computer-readable storage medium provided in the embodiment of the present invention obtain the tire parameters of the vehicle under the current working condition, and input the tire parameters into the corresponding service life prediction model to obtain the tire parameters. The service life prediction model is caused to predict the tire life of the vehicle based on the tire parameters. After the tire life is obtained, the tire life is compared with a preset threshold, and when the tire life reaches the preset threshold, it indicates that the tire is seriously worn at this time, and a tire replacement corresponding to the vehicle is generated. Reminder information, and send the tire replacement reminder information to the user terminal to remind the user to replace the tire. Through the above technical solutions of the present invention, the tire life can be predicted under different working conditions, the technical problem of inability to accurately determine the tire wear under different working conditions is solved, and the risk caused by improper tire maintenance is reduced.

Description of drawings

1 is a schematic flowchart of a first embodiment of a tire maintenance prediction method according to the present invention;

2 is a schematic diagram of a refinement flow of the first embodiment of the tire maintenance prediction method of the present invention;

FIG. 3 is a schematic flow chart before step S110 of the second embodiment of the tire maintenance prediction method of the present invention;

FIG. 4 is a schematic flow chart before step S110 of the third embodiment of the tire maintenance prediction method of the present invention;

5 is a schematic flowchart of a fifth embodiment of a tire maintenance prediction method according to the present invention;

FIG. 6 is a schematic structural diagram of the tire maintenance prediction equipment of the present invention.

The realization, functional features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments.

Detailed ways

For better understanding of the above technical solutions, exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure will be more thoroughly understood, and will fully convey the scope of the present disclosure to those skilled in the art.

The technical solutions of the present invention will be described below by way of examples:

First embodiment:

As shown in FIG. 1, in the first embodiment of the present invention, the tire maintenance prediction method of the present invention includes the following steps:

Step S110, obtaining tire parameters of the vehicle under the current working condition; the tire parameters include at least one of vehicle load, vehicle speed, Z-direction acceleration, yaw moment, tire temperature and tire pressure;

In this embodiment, in order to solve the problem that the tire wear conditions of the vehicle under different operating conditions cannot be accurately determined. The invention provides a tire maintenance prediction method. The method can obtain tire parameters of vehicles under different operating conditions, and input the tire parameters into a pre-trained prediction model, thereby obtaining tire life. After the tire life is obtained, the tire life is compared with a preset threshold. When the tire life reaches the preset threshold, the tire replacement reminder information of the vehicle is generated, and the user is reminded to replace the tire in time.

In this embodiment, the working conditions of different vehicles are different, and the working conditions of the vehicles can be determined according to dimensions such as load, road gradient, and road type, such as plains and mountains. Under different working conditions of the vehicle, the determined wear conditions of the tires are also different, that is, the service life of the tires is affected by the working conditions of the vehicle. Therefore, the tire maintenance prediction device can acquire tire parameters of the vehicle under the current operating conditions, and analyze the tire life of the vehicle according to the tire parameters. Wherein, the tire parameters include at least one of vehicle load, vehicle speed, Z-direction acceleration, yaw moment, tire temperature and tire pressure. Optionally, the tire parameters are parameters collected in real time during tire operation. For example, a tire pressure monitoring system may be installed on each wheel, and the tire pressure and temperature of each wheel may be monitored by the tire pressure monitoring system. The tire parameters can also be determined through detection sensors on the vehicle. For example, the vehicle load, vehicle speed, Z-direction acceleration, yaw moment, etc. can be obtained by installing sensors such as acceleration sensors or pressure sensors at preset positions of the vehicle. tire parameters.

Step S120, inputting the tire parameters into a pre-trained service life prediction model, so that the service life prediction model predicts the tire life of the vehicle according to the tire parameters;

In this embodiment, after the tire parameters are obtained, the tire parameters may be input into a pre-trained service life prediction model to obtain the tire life. Wherein, the service life prediction model is used to predict tire life, the service life prediction mode includes a first prediction model and a second prediction model, and the prediction model is obtained by training according to tire parameters under different sample working conditions. The corresponding prediction model can be selected according to the actual situation to predict the tire life. For example, a corresponding prediction model can be determined to predict tire life according to whether a tire pressure monitoring system is installed in a vehicle.

Specifically, in the test and development stage of the whole vehicle, the whole vehicle is controlled to run under different sample conditions, and the tire sample parameters of the whole vehicle under different sample conditions are collected in real time, so as to train the corresponding prediction through the tire sample parameters Model. in,

First, the training process for the first prediction model corresponding to the tire pressure monitoring system installed:

The tire temperature and tire pressure under different sample conditions can be obtained by installing a tire pressure monitoring system on each wheel of the vehicle. The service life corresponding to the tire temperature and the tire pressure is determined, and the first prediction model is trained by using the mapping relationship between the tire temperature, the tire pressure and the service life. Wherein, the service life corresponding to the tire temperature and the tire pressure is determined, and the process of training the first prediction model by using the mapping relationship between the tire temperature, the tire pressure and the service life is as follows: The sample working condition is alpine road, driving 10km under the working condition with a load of 1 ton, and recording the tire pressure and tire temperature of the whole vehicle during the operation of the first sample working condition based on the preset time interval, and recording in the same The tire pattern condition at the preset time interval, and then the tire life is determined according to the tire pattern condition. A mapping relationship between the tire pressure, the tire temperature and the tire life is established, and a first prediction model is iteratively trained based on the mapping relationship. Wherein, the tire temperature and the tire pressure have corresponding weighting coefficients, and the mapping relationship between tire temperature and tire life, tire pressure and tire life can be determined respectively. When training the first prediction model, it is necessary to calculate the tire temperature and the tire pressure are respectively multiplied by the corresponding weighting coefficients and then accumulated, so as to obtain the service life of the tire with the tire pressure monitoring system installed.

In one embodiment, the tire pressure and tire temperature of the entire vehicle after the operation of the first sample operating condition can also be directly obtained, and the tire life can be determined according to the tire pattern, and the tire pressure, the tire temperature and all the tire pressure can be established. The mapping relationship of the tire life is obtained, and the first prediction model is iteratively trained based on the mapping relationship.

In one embodiment, the whole vehicle can also be controlled to run for 20 km under the second sample operating condition of a plain road and a load of 1.5 tons, and the tire life can be determined according to the tire pattern. Through the above method, the tire life of the whole vehicle under the second sample operating condition can be obtained, and the mapping relationship between the tire life under the second sample operating condition and the tire pressure and tire temperature at the end of the second sample operating condition can be established, and based on The mapping relationship iteratively trains the first training model. The tire life is obtained by accumulating the tire life under the first sample working condition and the tire life under the second sample working condition.

Second, the training process for the second prediction model without the tire pressure monitoring system installed:

The tire parameters such as vehicle load, vehicle speed, Z-direction acceleration, and yaw moment can be obtained by installing sensors such as acceleration sensors or pressure sensors at the preset positions of the vehicle. Determine the service life corresponding to the vehicle load, vehicle speed, Z-direction acceleration, and yaw moment, and use the mapping relationship between the vehicle load, vehicle speed, Z-direction acceleration, yaw moment and the corresponding service life to train the second prediction model. Among them, the vehicle load, vehicle speed, Z-direction acceleration, and yaw moment have corresponding weighting coefficients, which can respectively determine vehicle load and tire life, vehicle speed and tire life, Z-direction acceleration and tire life, yaw moment and tire life. The mapping relationship between the two, when training the second prediction model, it is necessary to multiply the vehicle load, vehicle speed, Z-direction acceleration, and yaw moment by the corresponding weighting coefficients and then accumulate them, so as to obtain the first corresponding to the tire pressure monitoring system. Two prediction models.

Step S130, when the tire life reaches a preset threshold, generate tire replacement reminder information corresponding to the vehicle, and send the tire replacement reminder information to a user terminal to remind the user to replace the tire.

In this embodiment, after the tire life is obtained through the prediction model, the tire life is compared with a preset threshold. The preset thresholds corresponding to different models of vehicles are different. The preset threshold is the life span of a pre-calibrated vehicle, and the preset threshold can be determined according to the tire wear condition of the vehicle of this model after running a preset mileage. When the tire life reaches the preset threshold value, it means that the tire wear is serious and the tire needs to be replaced in time.

Specifically, when the tire maintenance prediction device detects that the tire life reaches a preset threshold, a tire replacement reminder signal corresponding to the vehicle is generated. The tire replacement reminder signal may include information such as the model of the vehicle, the manufacturer of the vehicle, and the failure of the vehicle. The tire replacement reminder signal can be sent to the user terminal through the tire maintenance prediction device to remind the user to replace the tire in time. The user terminal may be an intelligent terminal such as a mobile phone or a computer of a user to which the vehicle belongs. The tire replacement reminder signal is sent to the user's smart terminal to remind tire replacement. The user terminal may also be a smart terminal belonging to a seller, and a DMS (sales system) is installed on the smart terminal of the seller. The user terminal may also be an intelligent terminal belonging to a manufacturer, and ES (production system) is installed on the intelligent terminal of the manufacturer. The tire replacement reminder signal is sent to the smart terminals of the manufacturer and the seller to update the tire maintenance record.

Optionally, maintenance records of DMS (sales system) and ES (production system) are updated synchronously after tire repair. At the same time, the tire maintenance prediction device obtains the evaluation information of used tires. Wherein, the used tire is the evaluation information of the tire corresponding to the change of the maintenance record. The evaluation information of the used tire includes evaluation information such as the tire pattern of the used tire, the historical mileage of the used tire, and the tire pressure of the used tire. After the evaluation information of the used tire is obtained, the service life prediction model is updated by using the evaluation information of the used tire, so that the prediction result of the tire life is more accurate. Wherein, the process of using the evaluation information of the used tire to update the service life prediction model includes: using the evaluation information of the used tire to update the tire service life prediction model corresponding to the vehicle model to which the used tire belongs. Specifically, the evaluation information of the used tire may be used to update the weighting coefficient corresponding to each tire parameter in the service life prediction model. For example, the actual service life of the used tire is determined according to the tire pressure of the used tire, and the preset tire pressure corresponding to the actual service life of the used tire is obtained by looking up a table. The update of the service life prediction model is completed by adjusting the weighting coefficient corresponding to the preset tire pressure so that the product of the preset tire pressure and the weighting coefficient is equal to the actual service life.

In the technical solution of this embodiment, the tire parameters of the vehicle under the current working conditions are obtained, the tire parameters are input into the corresponding prediction model, and the tire life is obtained through the preset model. After the tire life is obtained, the tire life is compared with a preset threshold, and when the tire life reaches the preset threshold, it indicates that the tire is seriously worn at this time, and a tire replacement corresponding to the vehicle is generated. Reminder information, and send the tire replacement reminder information to the user terminal to remind the user to replace the tire. Through the above technical solutions of the present invention, the tire life can be predicted under different working conditions, the technical problem of inability to accurately determine the tire wear under different working conditions is solved, and the risk caused by improper tire maintenance is reduced.

Second embodiment:

As shown in FIG. 2 , in the second embodiment of the present invention, step S220 in the second embodiment is located before step S110 in the first embodiment, and steps S111 to S112 are the refinement steps of step S110 in the first embodiment. Steps S121 to S122 are refinement steps of step S120 of the first embodiment. Include the following steps:

Step S110, obtaining tire parameters of the vehicle under the current working condition; the tire parameters include at least one of vehicle load, vehicle speed, Z-direction acceleration, yaw moment, tire temperature and tire pressure;

Step S220, detecting whether the vehicle is equipped with a tire pressure monitoring system;

If so, step S111 is executed to obtain the tire temperature and tire pressure detected by the tire pressure monitoring system of the vehicle under the current operating condition;

If not, step S112 is executed to obtain the vehicle load, vehicle speed, Z-direction acceleration and yaw moment of the vehicle under the current working condition;

Step S121, when the obtained tire pressure parameters are tire temperature and tire pressure, input the tire temperature and tire pressure into a first prediction model; wherein the first prediction model includes tire temperature, tire pressure and The mapping relationship between tire life;

Step S122, after the obtained tire pressure parameters are vehicle load, vehicle speed, Z-direction acceleration and yaw moment, the tire pressure parameters are vehicle load, vehicle speed, Z-direction acceleration and yaw moment are input into the second prediction. model; wherein, the second prediction model includes a load sample, a vehicle speed sample, a Z-direction acceleration sample, a yaw moment sample and a mapping relationship between tire life.

Step S130, when the tire life reaches a preset threshold, generate tire replacement reminder information corresponding to the vehicle, and send the tire replacement reminder information to a user terminal to remind the user to replace the tire.

In this embodiment, a corresponding prediction model can be determined according to whether the vehicle is installed with a tire pressure monitoring system, so as to obtain the tire life. The tire pressure monitoring system can be divided into two types: one is an indirect tire pressure monitoring system, which judges whether the tire is abnormal by the difference in the rotation speed of the tire; the other is a direct tire pressure monitoring system. Four tire pressure monitoring sensors are installed to automatically monitor tire pressure and temperature in real time when the car is stationary or driving, and timely alarm tire high pressure, low pressure, and high temperature to avoid traffic accidents caused by tire failures and ensure driving safety. .

In this embodiment, the prediction model of the present invention includes a first prediction model and a second prediction model. Specifically, when it is detected that the vehicle is installed with a tire pressure monitoring system, the prediction model is determined to be the first prediction model. Wherein, the first prediction model includes a mapping relationship between tire temperature, tire pressure and tire life, and the tire temperature and tire pressure are detected according to different sample operating conditions of the whole vehicle during the test. For the training process of the first prediction model, reference may be made to the first embodiment, which will not be repeated here. Obtain each tire temperature and tire pressure detected by the tire pressure monitoring system of the vehicle under the current operating condition. The tire temperature and the tire pressure are input into a first prediction model to obtain tire life.

In this embodiment, a corresponding prediction model can be determined according to whether the vehicle is installed with a tire pressure monitoring system, so as to obtain the tire life. Specifically, when it is detected that the vehicle is not equipped with a tire pressure monitoring system, the prediction model is determined to be the second prediction model. Wherein, the vehicle load, vehicle speed, Z-direction acceleration and the yaw moment are obtained by detecting the whole vehicle under different sample operating conditions during the test. The second prediction model includes a load sample, a vehicle speed sample, a Z-direction acceleration sample, a yaw moment sample and a mapping relationship between tire life, and each of the tire parameters has a corresponding weighting coefficient. For the training process of the second prediction model, reference may be made to the first embodiment, which will not be repeated here. Obtain the vehicle load, vehicle speed, Z-direction acceleration and yaw moment of the vehicle under the current operating conditions. The vehicle load, the vehicle speed, the Z-direction acceleration and the yaw moment are input into the second prediction model, according to the vehicle load, the vehicle speed, the Z-direction acceleration, the yaw moment and the corresponding The weighting factor of , obtains the tire life.

In the technical solution of this embodiment, by detecting whether the vehicle is equipped with a tire pressure monitoring system, and by detecting whether the vehicle is equipped with a tire pressure monitoring system, when the vehicle is equipped with a tire pressure monitoring system, the tire temperature of the vehicle under the current working condition is obtained. and tire pressure and input the first prediction model, so as to obtain the tire life, by obtaining the vehicle load, vehicle speed, Z-direction acceleration and yaw moment of the vehicle under the current working condition when it is detected that the vehicle is not installed with the tire pressure monitoring system And input the second prediction model, so as to obtain the tire life, and realize the prediction of tire life.

Third embodiment:

As shown in FIG. 3 , in the third embodiment of the present invention, before step S110 based on the second embodiment, the following steps are further included:

Step S310, obtaining the steering wheel angle of the vehicle, and determining the driving state of the vehicle according to the steering wheel angle of the vehicle;

Step S320, when the driving state of the vehicle is a straight driving state, obtain the position information of the vehicle;

Step S330, determining the offset value of the vehicle according to the position information;

Step S340, judging whether the offset value of the vehicle is located in the first offset interval;

If yes, execute the step S220: detecting whether the vehicle is equipped with a tire pressure monitoring system;

If no, go to step S350: when the offset value of the vehicle is located in the second offset interval, generate four-wheel alignment correction information and send the four-wheel alignment correction information to the user terminal to remind the user of the vehicle The tires are positioned for correction.

In this embodiment, the steering wheel angle of the vehicle is acquired after the vehicle runs for a period of time, or after the vehicle runs for a certain mileage. Wherein, the steering wheel angle can be determined by a steering wheel angle sensor. The steering wheel angle sensor is an integral part of the vehicle stability control system. It is mainly installed in the steering column below the steering wheel and is generally connected to the PCM through the CAN bus. It can be divided into an analog steering wheel angle sensor and a digital steering wheel angle sensor.

In this embodiment, after acquiring the steering wheel angle of the vehicle, the driving state of the vehicle is determined according to the steering wheel angle of the vehicle. The driving state of the vehicle includes a straight driving state and a non-straight driving state, wherein the degree of fluctuation of the steering wheel angle of the vehicle in the straight driving state is smaller than the fluctuation degree of the steering wheel angle in the non-straight driving state. The driving state of the vehicle may be determined according to the degree of fluctuation of the steering wheel angle. When the running state of the vehicle is a straight running state, the position information of the vehicle is acquired. Wherein, the location information of the vehicle can be acquired according to the GPS sensor on the vehicle. The position information is compared with the position information of the vehicle in a pre-calibrated straight driving state, so as to determine the offset value of the vehicle. When the offset value of the vehicle is located in the first offset interval, it means that the vehicle is running relatively stable at this time. Return to the execution to detect whether the vehicle is equipped with a tire pressure monitoring system, so as to further predict the tire life.

Optionally, when the offset value of the vehicle is located in the second offset interval, it means that the vehicle is running unstable at this time, and the tire wear may be serious. At this time, four-wheel alignment correction information is generated, and the four-wheel alignment correction information is sent to the user terminal, so as to remind the user to perform alignment correction on the tires of the vehicle. After the user performs positioning and correction on the tires of the vehicle, return to execute to obtain the tire parameters of the vehicle under the current working condition, where the tire parameters include vehicle load, vehicle speed, Z-direction acceleration, yaw moment, tire temperature and tire pressure At least one of: inputting the tire parameters into a prediction model to obtain the tire life, wherein the prediction model is obtained by training the tire parameter samples under different sample working conditions; when the tire life reaches a preset threshold, the tire life is generated. The tire replacement reminder information corresponding to the vehicle is sent, and the tire replacement reminder information is sent to the user terminal to remind the user to replace the tire.

In the technical solution of this embodiment, the driving state of the vehicle is determined by acquiring the steering wheel angle of the vehicle after the vehicle has been driven for a period of time, and when the driving state is a straight-line driving state, the position information of the vehicle is acquired, and further according to the position The information determines the offset value of the vehicle, and performs corresponding actions according to the offset interval in which the offset value is located, so as to realize the notification of the user to replace the tire through the user terminal, and to realize the management and monitoring of the tire.

Fourth embodiment:

As shown in FIG. 4 , in the fourth embodiment of the present invention, before step S110 of the third embodiment, the tire maintenance prediction method of the present invention includes the following steps:

Step S410, obtaining the maintenance record of the tires of the current vehicle when the vehicle start instruction is detected;

Step S420, determining whether the four-wheel alignment function of the vehicle is qualified according to the maintenance record of the tire;

If yes, execute the step S310, obtain the steering wheel angle of the vehicle, and determine the driving state of the vehicle according to the steering wheel angle of the vehicle;

If not, step S430 is performed, and the four-wheel alignment correction information is sent to the user terminal, so as to remind the user to perform alignment correction on the tires of the vehicle.

In this embodiment, the four-wheel alignment is based on the four-wheel parameters of the vehicle, and is adjusted to ensure good driving performance and certain reliability of the vehicle. Therefore, at the moment when the vehicle is started, the maintenance record of the tires of the current vehicle is obtained. Among them, the maintenance records of vehicles are stored in MES (production system) and DMS (sales system). The maintenance record of the vehicle can be inquired through the MES (production system) and the DMS (sales system), so as to determine whether the four-wheel alignment function of the vehicle is qualified according to the maintenance record. Optionally, before querying the maintenance record of the vehicle, the user to which the vehicle belongs needs to have access rights to the MES (production system) and the DMS (sales system). After the authority verification of the user to which the vehicle belongs is successful, the maintenance record of the vehicle is inquired through the MES (production system) and the DMS (sales system). Wherein, each time the vehicle is repaired, a maintenance record will be generated, and the maintenance record may be recorded in the MES (production system) and the DMS (sales system). The content recorded in the maintenance record may include: maintenance items, repair time, repair methods and repair results. For example, the maintenance item may be an item such as unstable tire pressure. The repair method may be through four-wheel alignment; the repair result may be resolved or unresolved. When the maintenance result of the tire pressure instability recorded in the MES (production system) and the DMS (sales system) is unresolved, it means that the four-wheel alignment function is unqualified. Otherwise, the four-wheel alignment function is qualified.

When it is determined that the four-wheel alignment function of the vehicle is qualified according to the maintenance record of the tire, after the vehicle has been running for a period of time, the steering wheel angle of the vehicle is obtained and the driving state of the vehicle is determined according to the steering wheel angle, so that the vehicle is running during the driving process. Further determine whether wheel alignment correction is required.

Optionally, when it is determined that the four-wheel alignment function of the vehicle is unqualified according to the maintenance record of the tire, the four-wheel alignment correction information is sent to the user terminal to remind the user to locate the tire of the vehicle. Correction.

In the technical solution of this embodiment, the present invention obtains the maintenance record of the tires of the current vehicle when the vehicle is started, determines whether the four-wheel alignment function of the vehicle is qualified according to the maintenance record, and determines whether the four-wheel alignment function of the vehicle is qualified or not. When qualified, the corresponding operation is performed, so as to notify the user to replace the tire through the user terminal, and realize the management and monitoring of the tire.

Referring to FIG. 5 , FIG. 5 is a schematic flowchart of a fifth embodiment of the tire maintenance prediction method of the present invention. This implementation introduces a vehicle tire maintenance prediction method from start-up during travel. specific:

First, step S410 is performed. Wherein, in step S410, when a vehicle start instruction is detected, a maintenance record of the tires of the current vehicle is acquired.

Next, execute step S420; if yes, execute step S310-step S330, if not, execute step S430. Wherein, in step S420, it is determined whether the four-wheel alignment function of the vehicle is qualified according to the maintenance record of the tire. Step S310, obtaining the steering wheel angle of the vehicle, and determining the driving state of the vehicle according to the steering wheel angle of the vehicle; Step S320, obtaining the position information of the vehicle when the driving state of the vehicle is a straight driving state; Step S330, An offset value of the vehicle is determined according to the position information. It is judged whether the offset value of the vehicle is located in the first offset interval. Step S430, sending the four-wheel alignment correction information to the user terminal to remind the user to perform alignment correction on the tires of the vehicle.

Next, after the step S330, it is determined whether the offset value of the vehicle is located in the first offset interval, and if so, the step S220 is performed, and if not, the step S350 is performed. Wherein, in step S220, it is detected whether a tire pressure monitoring system is installed on the vehicle. Step S350, generating four-wheel alignment correction information and sending the four-wheel alignment correction information to a user terminal to remind the user to perform alignment correction on the tires of the vehicle.

Finally, after the step S220, if yes, execute step S111, step S121 and step S130; if not, execute step S112, step S122 and step S130. Wherein, in step S111, the tire temperature and tire pressure detected by the tire pressure monitoring system of the vehicle under the current working condition are obtained; in step S121, when the obtained tire pressure parameters are the tire temperature and tire pressure, all The tire temperature and tire pressure are input into the first prediction model; wherein, the first prediction model includes the mapping relationship between tire temperature, tire pressure and tire life; step S112, obtain the vehicle load of the vehicle under the current working condition, Vehicle speed, Z-direction acceleration and yaw moment; Step S122, after the obtained tire pressure parameters are vehicle load, vehicle speed, Z-direction acceleration and yaw moment, the tire pressure parameters are vehicle load, vehicle speed, Z-direction The acceleration and yaw moment are input into the second prediction model; wherein, the second prediction model includes a mapping relationship between load samples, vehicle speed samples, Z-direction acceleration samples, yaw moment samples and tire life. Step S130, when the tire life reaches a preset threshold, generate tire replacement reminder information corresponding to the vehicle, and send the tire replacement reminder information to a user terminal to remind the user to replace the tire.

The embodiment of the present invention provides an embodiment of the tire maintenance prediction method. It should be noted that although the logic sequence is shown in the flowchart, in some cases, the shown or described steps.

Based on the same inventive concept, an embodiment of the present invention also provides a tire maintenance prediction device. As shown in FIG. 6 , as shown in FIG. 6 , FIG. 6 is a schematic structural diagram of a hardware operating environment involved in the solution of an embodiment of the present invention.

It should be noted that FIG. 6 can be a schematic structural diagram of the hardware operating environment of the tire maintenance prediction equipment.

As shown in FIG. 6 , the tire maintenance prediction apparatus may include: a processor 1001 , such as a CPU, a memory 1005 , a user interface 1003 , a network interface 1004 , and a communication bus 1002 . Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. Optionally, the network interface 1004 may include a standard wired interface and a wireless interface (eg, a WI-FI interface). The memory 1005 may be high-speed RAM memory, or may be non-volatile memory, such as disk memory. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001 .

As shown in FIG. 6 , the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module and a tire maintenance prediction program. Among them, the operating system is a program for managing and controlling the hardware and software resources of the tire maintenance prediction equipment, the operation of the tire maintenance prediction program and other software or programs.

In the tire maintenance prediction device shown in FIG. 6 , the user interface 1003 is mainly used to connect the terminal and perform data communication with the terminal; the network interface 1004 is mainly used for the background server to perform data communication with the background server; the processor 1001 can be used to call The tire maintenance prediction program stored in the memory 1005 .

In this embodiment, the tire maintenance prediction device includes: a memory 1005, a processor 1001, and a tire maintenance prediction program stored on the memory and executable on the processor, wherein:

When the processor 1001 calls the tire maintenance prediction program stored in the memory 1005, the following operations are performed:

Obtaining tire parameters of the vehicle under the current working condition; the tire parameters include at least one of vehicle load, vehicle speed, Z-direction acceleration, yaw moment, tire temperature and tire pressure;

inputting the tire parameters into a pre-trained service life prediction model, so that the service life prediction model predicts the tire life of the vehicle according to the tire parameters;

When the tire life reaches a preset threshold, generate tire replacement reminder information corresponding to the vehicle, and send the tire replacement reminder information to a user terminal to remind the user to replace the tire.

When the processor 1001 calls the tire maintenance prediction program stored in the memory 1005, the following operations are performed:

Check whether the vehicle is equipped with a tire pressure monitoring system;

The step of obtaining the tire parameters of the vehicle under the current working condition includes:

When a tire pressure monitoring system is installed on the vehicle, obtain the tire temperature and tire pressure detected by the tire pressure monitoring system under the current working condition of the vehicle;

When the tire pressure monitoring system is not installed on the vehicle, obtain the vehicle load, vehicle speed, Z-direction acceleration and yaw moment of the vehicle under the current working condition;

The step of inputting the tire parameters into the pre-trained service life prediction model, so that the service life prediction model predicts the tire service life of the vehicle according to the tire parameters, includes:

When the obtained tire pressure parameters are tire temperature and tire pressure, the tire temperature and tire pressure are input into a first prediction model; wherein, the first prediction model includes the relationship between tire temperature, tire pressure and tire life. The mapping relationship between;

After the obtained tire pressure parameters are vehicle load, vehicle speed, Z-direction acceleration and yaw moment, the tire pressure parameters are vehicle load, vehicle speed, Z-direction acceleration and yaw moment are input into the second prediction model; wherein , the second prediction model includes a mapping relationship between load samples, vehicle speed samples, Z-direction acceleration samples, yaw moment samples and tire life.

When the processor 1001 calls the tire maintenance prediction program stored in the memory 1005, the following operations are performed:

Obtain the steering wheel angle of the vehicle, and determine the driving state of the vehicle according to the steering wheel angle of the vehicle;

When the driving state of the vehicle is a straight driving state, obtain the position information of the vehicle;

determining an offset value of the vehicle according to the location information;

When the offset value of the vehicle is located in the first offset interval, the step of detecting whether the vehicle is equipped with a tire pressure monitoring system is performed.

When the processor 1001 calls the tire maintenance prediction program stored in the memory 1005, the following operations are performed:

When the offset value of the vehicle is in the second offset interval, four-wheel alignment correction information is generated and sent to the user terminal, so as to remind the user to perform alignment correction on the tires of the vehicle.

When the processor 1001 calls the tire maintenance prediction program stored in the memory 1005, the following operations are performed:

When a vehicle start command is detected, the maintenance record of the tires of the current vehicle is obtained;

When it is determined that the four-wheel alignment function of the vehicle is qualified according to the maintenance record of the tire, after the vehicle has been driven for a period of time, the steering wheel angle of the vehicle is obtained, and the steering wheel angle of the vehicle is determined according to the steering wheel angle of the vehicle. Steps in the driving state.

When the processor 1001 calls the tire maintenance prediction program stored in the memory 1005, the following operations are performed:

When it is determined that the four-wheel alignment function of the vehicle is unqualified according to the maintenance record of the tire, the four-wheel alignment correction information is sent to the user terminal, so as to remind the user to perform alignment correction on the tire of the vehicle.

When the processor 1001 calls the tire maintenance prediction program stored in the memory 1005, the following operations are performed:

When it is detected that the maintenance record of the tire is changed, the evaluation information of the tire corresponding to the change of the maintenance record is obtained;

The service life prediction model is updated using the tire evaluation information.

Those skilled in the art can understand that the structure of the tire maintenance prediction device shown in FIG. 6 does not constitute a limitation to the tire maintenance prediction device, and may include more or less components than the one shown, or combine some components, or different component layout. It is not repeated here.

Based on the same inventive concept, an embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores a tire maintenance prediction program, and the tire maintenance prediction program is executed by a processor to implement the above-mentioned The various steps of tire maintenance prediction can achieve the same technical effect. In order to avoid repetition, they will not be repeated here.

Since the computer-readable storage medium provided by the embodiment of the present invention is the computer-readable storage medium used for implementing the method of the embodiment of the present invention, based on the method introduced by the embodiment of the present invention, those skilled in the art can understand that the computer can The specific structure and deformation of the read storage medium will not be repeated here. All computer-readable storage media used in the methods of the embodiments of the present invention belong to the scope of protection of the present invention.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable computer-readable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein .

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block in the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing device to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing device produce Means for implementing the functions specified in a flow or flow of a flowchart and/or a block or blocks of a block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory result in an article of manufacture comprising instruction means, the instructions The apparatus implements the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.

These computer program instructions can also be loaded on a computer or other programmable data processing device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process such that The instructions provide steps for implementing the functions specified in the flow or blocks of the flowcharts and/or the block or blocks of the block diagrams.

It should be noted that, in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not preclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In a unit claim enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, and third, etc. do not denote any order. These words can be interpreted as names.

Although the preferred embodiments of the present invention have been described, additional changes and modifications to these embodiments may occur to those skilled in the art once the basic inventive concepts are known. Therefore, the appended claims are intended to be construed to include the preferred embodiment and all changes and modifications that fall within the scope of the present invention.

It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit and scope of the invention. Thus, provided that these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims (9)

1. A tire maintenance prediction method is characterized in that, the tire maintenance prediction method comprises: Obtaining tire parameters of the vehicle under the current working condition; the tire parameters include at least one of vehicle load, vehicle speed, Z-direction acceleration, yaw moment, tire temperature and tire pressure; inputting the tire parameters into a pre-trained service life prediction model, so that the service life prediction model predicts the tire life of the vehicle according to the tire parameters; When the tire life reaches a preset threshold, generate tire replacement reminder information corresponding to the vehicle, and send the tire replacement reminder information to a user terminal to remind the user to replace the tire. 2. The tire maintenance prediction method according to claim 1, wherein the service life prediction model comprises a first prediction model and a second prediction model; , the method also includes: Check whether the vehicle is equipped with a tire pressure monitoring system; The step of obtaining the tire parameters of the vehicle under the current working condition includes: When a tire pressure monitoring system is installed on the vehicle, obtain the tire temperature and tire pressure detected by the tire pressure monitoring system under the current working condition of the vehicle; When the tire pressure monitoring system is not installed on the vehicle, obtain the vehicle load, vehicle speed, Z-direction acceleration and yaw moment of the vehicle under the current working condition; The step of inputting the tire parameters into the pre-trained service life prediction model, so that the service life prediction model predicts the tire service life of the vehicle according to the tire parameters, includes: When the obtained tire pressure parameters are tire temperature and tire pressure, input the tire temperature and tire pressure into a first prediction model; wherein, the first prediction model includes the relationship between tire temperature, tire pressure and tire life. The mapping relationship between; After the obtained tire pressure parameters are vehicle load, vehicle speed, Z-direction acceleration and yaw moment, the tire pressure parameters are vehicle load, vehicle speed, Z-direction acceleration and yaw moment are input into the second prediction model; wherein , the second prediction model includes a mapping relationship between load samples, vehicle speed samples, Z-direction acceleration samples, yaw moment samples and tire life. 3. The tire maintenance prediction method according to claim 2, wherein before the step of acquiring tire parameters of the vehicle under the current working condition, the method further comprises: Obtain the steering wheel angle of the vehicle, and determine the driving state of the vehicle according to the steering wheel angle of the vehicle; When the driving state of the vehicle is a straight driving state, obtain the position information of the vehicle; determining an offset value of the vehicle according to the location information; When the offset value of the vehicle is located in the first offset interval, the step of detecting whether the vehicle is equipped with a tire pressure monitoring system is performed. 4. The tire maintenance prediction method according to claim 3, wherein after the step of determining the offset value of the vehicle according to the position information, the method further comprises: When the offset value of the vehicle is in the second offset interval, four-wheel alignment correction information is generated and sent to the user terminal, so as to remind the user to perform alignment correction on the tires of the vehicle. 5 . The tire maintenance prediction method according to claim 3 , wherein, before the step of acquiring tire parameters of the vehicle under current operating conditions, the method further comprises: 6 . When a vehicle start command is detected, the maintenance record of the tires of the current vehicle is obtained; When it is determined that the four-wheel alignment function of the vehicle is qualified according to the maintenance record of the tire, the steps of obtaining the steering wheel angle of the vehicle and determining the driving state of the vehicle according to the steering wheel angle of the vehicle are performed. 6. The tire maintenance prediction method according to claim 5, wherein the steps of the tire maintenance prediction method further comprise: When it is determined that the four-wheel alignment function of the vehicle is unqualified according to the maintenance record of the tire, the four-wheel alignment correction information is sent to the user terminal, so as to remind the user to perform alignment correction on the tire of the vehicle. 7. The tire maintenance prediction method according to claim 1, wherein the tire parameters are input into a pre-trained service life prediction model, so that the service life prediction model predicts according to the tire parameters After the step of tire life of the vehicle, it also includes: When it is detected that the maintenance record of the tire is changed, the evaluation information of the tire corresponding to the change of the maintenance record is obtained; The service life prediction model is updated using the tire evaluation information. 8. A tire maintenance prediction device, characterized in that the tire maintenance prediction device comprises: a memory, a processor, and a tire maintenance prediction program stored on the memory and executable on the processor, the tire The maintenance prediction program, when executed by the processor, implements the steps of the tire maintenance prediction method according to any one of claims 1-7. 9. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a tire maintenance prediction program, and when the tire maintenance prediction program is executed by a processor, the implementation of any one of claims 1-7 is realized. The steps of the tire maintenance prediction method described above.

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