CN113665302A - Method for generating virtual tire model and simulating tire condition and virtual tire model - Google Patents

Abstract

The invention discloses a computer-implemented method for generating a virtual tire model RM for a vehicle tire FR. The method comprises the following steps: s1 provides the tire data RD, the vehicle data FD, the environmental data DU, and the usage data ND relating to the vehicle tires FR, respectively, S2 creates a virtual tire model RM of the vehicle tires FR based on the provided data, and S3 stores the created virtual tire model RM. In addition, the invention also provides a virtual tire model RM, a method for simulating a tire condition RZ, a system for data processing and a computer program, wherein the virtual tire model RM of the vehicle tire FR is used for simulating a future condition of the vehicle tire FR.

Description

Method for generating virtual tire model and simulating tire condition and virtual tire model

Technical Field

The present invention relates to a computer-implemented method for generating a virtual tire model of a vehicle tire, a virtual tire model, a method for simulating tire conditions, a system for data processing and a computer program.

Background

Tires are an essential component of wheel-driven land vehicles. The only contact of the vehicle with the road surface is through the tire; therefore, tires are particularly relevant to safety. Tire damage can lead to serious accidents. Tire parameters (e.g. tread depth, wear, aging, etc.) therefore constitute an important source of information in order to be able to determine the safety of the vehicle and the necessary maintenance and service measures.

A tire is a component that is subjected to a large pressure because forces are transmitted between the vehicle and the road through the tire. For example, each tire of a passenger vehicle is subjected to a static force of about 4kN to 8 kN. In addition, dynamic forces should not be underestimated. These forces increase the effect of wear and result in a reduction in tread depth.

In addition, driving behavior also plays a role. For example, too low tire pressure and traveling too high a speed and/or at an unfavorable angle at an edge (e.g., a curb) can have a negative impact on the condition of the tire. Finally, other effects (e.g., weather) can also affect the condition of the tire. For example, direct solar radiation and frequent large temperature differences may cause the tire to become brittle, resulting in high tire wear and premature aging.

The tire has a memory that can withstand the loads and influences during its useful life. For example, driving past a curb in an unfavorable manner may not lead to visible tire damage (e.g., tire blowout) until a very late point in time.

Unfortunately, it is not possible to reliably assess the condition of the tire during visual inspection. More detailed inspections using cameras, sensors, etc. often do not lead to satisfactory conclusions, since damage inside the tyre or to the tyre material itself is often undetected.

From the prior art, simulation methods are known which are capable of predicting the condition of a tire. For example, US 2019/0266295 a1 describes a method by which a digital twin of a vehicle is generated based on sensor data, so that maintenance of vehicle components (e.g. tires) can be planned in advance with the aid of the digital twin. Although a digital twin based on only sensor data can be used to improve the prediction of the tire condition, it cannot solve the problem that only the information value of the sensor data is too low because the tire condition cannot be detected satisfactorily by the sensor.

EP 2596317B 1 discloses a method for evaluating the dynamic load acting on a tyre over a certain time. For this purpose, the pressure of the tire is measured during this period of time. In addition, a reference pressure is determined at each pressure measurement point. Finally, at each pressure measurement point, the change in load is calculated based on the difference between the measured pressure and the reference pressure, and a previously created tire model is used that correlates the change in load with the change in pressure. Therefore, the evaluation of the tire condition is performed based only on the tire pressure. As mentioned above, this is not sufficient for a comprehensive assessment of tire condition, as many other factors can affect tire condition.

WO 2017/011486 a1 discloses a tire testing method in which a virtual testing process is performed by a simulated tire of a simulated vehicle. As a result, a tire load curve may be determined and then applied to a test tire in a test rig to test it. It is thus impossible to draw conclusions about the tire condition of the tire in actual use.

Disclosure of Invention

On this background, it is an object of the present invention to provide a method and a system for processing data which make it possible to predict the condition of a tire as accurately as possible.

This object is achieved by the subject matter of the independent claims. The dependent claims relate to embodiments of these solutions according to the invention.

A first aspect of the invention relates to a computer-implemented method for generating a virtual tire model of a motor vehicle tire. The method comprises the following steps: providing tire data, vehicle-related data, environmental data, and usage data relating to the vehicle's tires, respectively; creating a virtual tire model of the vehicle tire based on the provided data; and storing the created virtual tire model.

In other words, a computer model of the vehicle tyre is created which provides an image of the actual vehicle tyre which is as accurate as possible. The computer model can, for example, simulate the effects acting on the modeled vehicle tires and their effect on the vehicle tire conditions.

A vehicle tire is a tire of a vehicle (e.g., passenger car, truck, bus, etc.) that is configured to bring the vehicle into contact with the road on which the vehicle is traveling. Vehicle tires are subject to a variety of effects that result in their tire condition changing, often worse. The proposed method is applicable to all vehicle tires regardless of their specific design, such as summer tires, winter tires, off-road tires, new tires, retread tires, pneumatic tires, hard rubber tires, and the like. If the vehicle has a plurality of vehicle tires, the provided method can be performed separately for each individual vehicle tire, that is to say a separate virtual tire model is created for each individual vehicle tire.

The method provides for creating a virtual tire model based on tire data, vehicle data, environmental data and usage data, wherein the data is respectively associated with a vehicle tire or with a vehicle tire for which the virtual tire model is to be created.

The method is distinguished in that, in addition to the actual measurement data, virtual sensor data can also be generated and used in the virtual tire model. Thus, on the one hand, the tire data, the vehicle data, the environmental data and the usage data may be based on actual measurement data obtainable by actual sensors, and on the other hand may be based on simulations. The two data sets (i.e., actual data and simulated data) may be merged into the virtual tire model directly and/or after data fusion. In this case, by means of suitable algorithms, data fusion can generate additional so-called virtual sensors, which provide additional unmeasured or unmeasured data to the virtual tire model.

The tire data may refer to one or several parameters selected from the list comprising tire name, tire type, tire production date, tire production place, tire material, tire tread type, rim type and rim material.

Accordingly, tire data is data representing the values of one or more of the listed parameters (e.g., any combination of the listed parameters or all of the listed parameters). The listed parameters may affect the tire condition and thus their inclusion in the virtual tire model may result in an improved match between the vehicle tire and its virtual model. The tire data may be obtained, for example, by a corresponding data query to the manufacturer of the vehicle tires.

The vehicle data may relate to one or more parameters selected from the following list: distance traveled by a vehicle tire, forces acting longitudinally on a vehicle tire, forces acting laterally on a vehicle tire, tire self-alignment torque, wheel slip, camber angle, and camber angle variation. With regard to the force, an absolute force and/or a force curve may be considered.

Thus, vehicle data is data representing the values of one or more of the listed parameters (e.g., any combination of the listed parameters or all of the listed parameters). The listed parameters may affect the tire condition and thus their inclusion in the virtual tire model may result in an improved match between the vehicle tire and its virtual model.

The vehicle data may be obtained by direct measurement (e.g. by means of suitable sensors) or indirectly within the framework of a so-called virtual sensor system. For example, the (lateral) acceleration of the vehicle, its yaw rate and/or its steering wheel angle may first be measured, from which some of the aforementioned vehicle data, such as the sideslip angle (the angle between the direction of movement of the vehicle at the center of gravity and the longitudinal axis of the vehicle), may then be calculated or simulated.

The environmental data may relate to one or several parameters selected from a list comprising tire temperature, tire temperature difference, UV radiation and road conditions. Thus, environmental data is data representing the values of one or more of the listed parameters (e.g., any combination of the listed parameters or all of the listed parameters). The listed parameters may affect the tire condition and thus inclusion thereof in the virtual tire model may result in an improved match between the vehicle tire and its virtual model.

The environmental data can be obtained by direct measurements or indirectly within the framework of a so-called virtual sensor system. For example, the tire temperature may be measured by means of a temperature sensor. The irradiation of the ultraviolet light may be determined by means of an ultraviolet light sensor, a camera sensor and/or a solar panel sensor. By means of the camera sensor and the solar panel sensor, the solar radiation and the solar altitude can be determined and conclusions can be drawn therefrom regarding the uv radiation and the tire heating. In addition, general weather data can be derived from the camera images.

The road condition may for example comprise a road surface condition (e.g. sidewalk, unevenness, etc.). The road conditions may be obtained by means of a location-based query of a suitable database. For example, the distance traveled by a tire may be determined by means of a global navigation satellite system (e.g., GPS) and the associated road conditions may be queried. The algorithm, which is provided as a vehicle observer and which already provides additional vehicle data as virtual sensors (virtual sensor system), can also determine the road surface condition here, for example as a road friction estimator.

The usage data may relate to parameters relating to travel over curbs and/or over potholes. The listed parameters may affect the tire condition and thus inclusion thereof in the virtual tire model may result in an improved match between the vehicle tire and its virtual model.

For example, driving situations on the curb can be detected by means of roll and acceleration sensors and camera data. For example, driving on a curb may result in lateral acceleration on the wheel carriage. The travel over the hollow can be detected by a system for detecting hollows, which is already used today (for example in adjustable shock absorbers).

The virtual tire model can be created by means of a computing unit in the vehicle itself or by means of an external computing unit, to which the corresponding data are transmitted and thus operatively connected to the vehicle by means of signal technology. The advantage of an external computing unit is that more computing power may generally be provided and that the virtual tire model may be used in a simplified manner, for example for predicting tire conditions.

Various different model methods may be used as the virtual tire model. They range from simple empirical models to physical models with temperature and wear models to finite element models. They can be extended arbitrarily, depending on the application. In other words, the virtual tire model may be configured as an empirical model, a physical model with temperature and wear models, or a finite element model, for example.

In a further method step, the virtual tire model created on the basis of the above data is stored, for example by means of a computer-readable data storage medium, either on the vehicle itself or outside the vehicle, for example in a storage unit of a computer cloud or a computer server.

The virtual tire model created and stored constitutes a digital twin of the vehicle tires. In this case, the virtual tire model advantageously preferably takes into account all forces and dynamic loads acting on the vehicle tires, so that a preferably complete picture of the tire loads including the relevant history can be included in the model creation.

By means of the virtual tire model, the effects acting on the vehicle tires can be observed and analyzed. Different virtual tire models may also be compared, for example different tire types or even the same tire type for different vehicles or vehicle users. The results of such comparisons may be incorporated into further development of vehicle tires and may advantageously result in vehicle tires having improved characteristics.

In principle, the method can be carried out at any time during the service life, that is to say it can be used both for creating a virtual tire model of a new tire and for creating a virtual tire model of a vehicle tire that has been in use (or longer). As the service life of tires has developed, the amount of data to be processed for creating virtual tire models has increased. Thus, it may be advantageous to create a virtual tire model at the beginning of the useful life of a vehicle tire.

According to various embodiment variations, a virtual tire model may be created using a data fusion method.

Data fusion means that piecemeal and possibly somewhat contradictory sensor data are combined and processed to obtain an understandable overall image of the vehicle tire. In addition to the actual sensor data, other data (e.g. data generated on the basis of the sensor data), that is to say data obtained within the framework of the virtual sensor system by means of a suitable algorithm (e.g. a kalman filter), can also be combined. For example, the data fusion may comprise or may consist of an algorithm (e.g. a kalman filter) which generates additional virtual measurement data from the existing measurement data by means of a vehicle model (virtual sensor system).

Within the framework of data fusion, techniques can be used which enable different data to be combined in terms of their data structure and/or data content. To this end, the data may be processed and/or combined with other data. Furthermore, differently aged data can be prepared in a manner such as by extrapolation to the present, making joint processing possible. Furthermore, the weighting of the data may vary. Finally, it may be attempted to identify specific patterns within the data and include these patterns in further data processing.

For example, there is the possibility of defining a virtual vehicle observer which individually determines all the different load conditions, dynamic requirements, etc. of the vehicle tires, and then provides them to create a virtual tire model. The aim is to preferably detect all influencing factors acting on the tire, that is to say forces acting in different directions on the vehicle tire and having different dynamics, for example. As a result, all of the dynamic conditions of the tire may be detected and tracked within the scope of the update of the virtual tire model described below.

The use of a data fusion method may advantageously improve the accuracy of the virtual tire model created, thereby better matching it to vehicle tires.

According to a further embodiment variant, the method may comprise updating the created virtual tire model by means of tire data, vehicle data, environmental data and/or usage data, respectively relating to the vehicle tires.

As a result, an updated virtual tire model can be advantageously obtained. This enables an improved assessment of the current tyre condition.

Further, the virtual tire model may be updated based on communication with a maintenance system of the vehicle and/or communication with a user of the vehicle. This may allow the virtual tire model to be further improved in terms of improved matching to the vehicle tires.

According to a further embodiment variant, the method may comprise comparing the created or updated virtual tire model with the vehicle tires, and adapting the created or updated virtual tire model to the vehicle tires.

In other words, the initially created virtual tire model or the virtual tire model updated at a later point in time may be kept consistent with the vehicle tires. By adjusting the virtual tire model accordingly, the accuracy of the virtual tire model can be improved, thereby better matching it to the vehicle tire.

Another aspect of the invention relates to a virtual tire model obtained by one of the above methods.

Thus, all embodiments relating to the method are applicable in a similar manner to the virtual tire model. The aforementioned advantages with reference to the method are accordingly associated with the virtual tire model.

The virtual tire model may be an originally created tire model or an updated tire model. The virtual tire model simulates a vehicle tire based on the tire information, the vehicle data, the environmental data, and usage data related to the vehicle tire. The virtual tire model may be stored in a vehicle equipped with vehicle tires or on a storage medium (e.g., a computer-readable data storage medium) external to the vehicle.

By means of the virtual tire model, on the one hand, the relationship between the tire information, the vehicle data, the environmental data and the usage data, respectively, relating to the vehicle tire can be mapped, and on the other hand, the tire condition of the vehicle tire can be mapped.

The virtual tire model may have an interface through which communication with a maintenance system of the vehicle and/or communication with a user of the vehicle may occur. Via the interface, additional data may be added to the virtual tire model. This may allow the virtual tire model to be further improved in terms of improved matching to the vehicle tires.

Advantageously, the virtual tire model can be used for tire development, as weaknesses of previous tires can be identified, and counter-acting innovations can be introduced. In addition, multiple virtual tire models may be compared to one another, thereby allowing the creation of an extensive database reflecting actual tire usage and possibly influencing variables.

Another aspect of the invention relates to a method for simulating the condition of a tire, wherein the future condition of a vehicle tire is simulated by means of a virtual tire model of the vehicle tire, as described above.

In other words, future tire conditions may be estimated by means of the virtual tire model. For this purpose, the effect of various influences, for example, changes in the above-mentioned parameters, such as the completion of the travel distance, various forces, temperature, etc., can be simulated. Thus, for example, the service life of the vehicle tires in relation to the virtual tire model can be estimated, so that timely tire replacement can be planned and carried out. For example, replacement tires can be ordered and delivered in a timely manner, and shop appointments can be made if necessary. Sudden and potentially dangerous failure of the tire can be avoided.

In addition, further measures such as changes in tire pressure, compliance with speed limits, changes from summer to winter tires, changes from winter to summer tires, e.g., in the case of four-wheel vehicles, changes in tire position on the vehicle from front right to left rear, etc. may be planned and executed based on the simulated future condition of the vehicle tires.

For this purpose, information about the simulated future condition of the vehicle tires can be output via a corresponding display on the infotainment system of the vehicle, for example to the driver of the vehicle or to a maintenance facility (for example, a workshop for servicing a car).

According to various embodiment variations, the simulated tire condition may be compared to the actual tire condition of the vehicle tire, and the simulation may be adjusted based on the difference between the simulated tire condition and the actual tire condition.

For example, future tire conditions under constant load may be simulated over a month and compared to actual tire conditions present at that time after the end of the period, and the simulation may be adjusted accordingly.

Therefore, the accuracy of the simulation can be advantageously improved, so that future predictions can be made with higher accuracy, and advantages related to the simulation can be achieved to a greater extent.

Another aspect of the invention relates to a system for data processing comprising means for performing one of the above methods.

The advantages of the method can therefore also be achieved by a system for data processing. All embodiments relating to the method are applicable to systems that perform data processing in a similar manner.

The system for data processing may comprise a calculation unit, which may be arranged in the vehicle or outside the vehicle in relation to the vehicle tyres. The computing unit may be operatively connected to the vehicle via signal technology, so that, for example, data from sensors of the vehicle can be transmitted to the computing unit.

Another aspect of the invention relates to a computer program comprising instructions which, when executed by a computer, cause said computer to carry out one of the above-mentioned methods.

Thus, the advantages of the method may also be realized by a computer program. All embodiments relating to the method apply in a similar way to the computer program.

A computer program may be understood as a program code which may be stored on and/or retrieved through a suitable medium. For storing the program code any medium suitable for storing software, such as a non-volatile memory installed in the control unit, a DVD, a USB flash disk, a flash memory card, etc., may be used. The program code may be acquired, for example, via the internet or an intranet, or via another suitable wireless or wired network.

Another aspect of the invention relates to a computer-readable data storage medium having a computer program stored thereon.

Drawings

Other advantages of the present invention will be apparent from the following description and drawings. The following is illustrated:

FIG. 1 illustrates an overview of creating an exemplary virtual tire model;

FIG. 2 illustrates another overview of creating and using an exemplary virtual tire model; and

FIG. 3 is a flow chart of an exemplary method.

Detailed Description

Fig. 1 and 2 schematically illustrate the data required for creating a virtual tire model RM of a vehicle tire FR, the source of said data and the processing thereof. Fig. 1 shows the provision of tire data RD, vehicle data FD, environmental data UD and usage data ND as actual measurement data (i.e. data actually determined, for example, by sensors) on the one hand and as simulations on the other hand.

On the one hand, these data are incorporated directly into the virtual tire model and, on the other hand, they are associated with each other using data fusion methods, i.e. virtual sensor data are generated from actual measurement data and dynamic modeling. These data are then used to create a virtual tire model RM. The virtual tire model RM represents an image of a vehicle tire FR, which may be a tire of a passenger vehicle, for example.

If the passenger vehicle as usual has a plurality of vehicle tires FR, a separate virtual tire model RM is created for each of these vehicle tires FR. The created tire model RM is stored in a computer cloud outside the vehicle. Alternatively, it may be stored inside the vehicle.

Fig. 2 shows a process of creating the virtual tire model RM again. A plurality of forces, loads and influences act on the vehicle tires FR for which virtual tire models RM are to be created, which models can be defined and quantified by means of tire data, vehicle data, environmental data and usage data (see fig. 1).

Using the sensor signal, simulation and data fusion method, it is possible to create a digital twin of vehicle tires FR in the form of a virtual tire model RM by virtually simulating forces, loads and influences.

The obtained virtual tire model RM may then be used to simulate future tire conditions SRZ. By comparing the simulated tire condition SRZ to the actual tire condition TRZ, the simulation may be adjusted and thereby improved.

Fig. 3 illustrates a flow chart of an exemplary method for generating a virtual tire model RM for a vehicle tire FR. After the method is started, in step S1, tire data RD, vehicle data FD, environmental data UD and usage data ND relating respectively to the vehicle tires FR for which the virtual tire model RM is to be created are provided. Measurement data and simulations can be used for this purpose.

In a next method step S2, a virtual tire model TM is created based on the provided data. Data fusion methods may be used herein. In step S3, the created virtual tire model RM is stored.

In step S4, the created virtual tire model RM is updated using the tire data RD, the vehicle data FD, the environmental data UD, and the usage data ND. This update makes the updated virtual tire model RM always match the vehicle tire FR as much as possible.

Alternatively, steps S5 and S6 may be performed, wherein the updated virtual tire model RM is compared with the vehicle tire FR and adapted to the vehicle tire FR. The comparison and adjustment can be repeated at predeterminable time intervals, for example at fixed, specified time intervals or at certain time intervals depending on the use of the vehicle tires FR. Therefore, the quality of the virtual tire model RM can be improved.

In step S7, the virtual tire model RM is used to simulate the future state SRZ of the vehicle tire FR. For this purpose, forces, loads and/or influences can be virtually exerted on the virtual tire model RM and their effect can be observed. In step S8, information about the simulated future condition SRZ of the vehicle tire FR is output. For example, a workshop may be notified of a tire replacement due to wear. If at any time there is a risk of sudden failure of the vehicle tires FR based on the simulated tire conditions SRZ, corresponding information can be output to the vehicle, for example in order to inform the driver or to implement active control interventions, for example to limit the vehicle speed.

Method steps S4 to S8 may be performed continuously or at time intervals, i.e. a continuous update of the virtual tire model RM and/or a continuous simulation of the future tire conditions SRZ is feasible.

List of reference numerals

FD vehicle data

FR vehicle tire

ND usage data

RD tire data

RM virtual tire model

SRZ simulated tire condition

TRZ actual tire condition

UD environmental data

Method step

S1 provides tire data, vehicle data, environment data and usage data respectively related to vehicle tire

S2 creating a virtual tire model of the vehicle tire based on the provided data

S3 stores the created virtual tire model

S4 updating the created virtual tire model using the tire data, the vehicle data, the environment data and the usage data respectively related to the vehicle tire

S5 compares the updated virtual tire model with the vehicle tire

S6 fitting the updated virtual tire model to the vehicle tire

S7 simulating future conditions of vehicle tires using the adjusted virtual tire model

S8 outputting information on the simulated future condition of the vehicle tire

Claims (13)

1. A computer-implemented method for generating a virtual tire model (RM) for vehicle tires (FR), comprising:

-providing tire data (RD), vehicle data (FD), environmental data (UD) and usage data (ND) respectively related to said vehicle tire (FR) (S1),

-creating a virtual tire model (RM) of the vehicle tires (FR) based on the data provided (S2), and

-storing the created virtual tire model (RM) (S3).

2. The method according to claim 1, wherein said virtual tire model (RM) is created using a data fusion method.

3. The method according to one of the preceding claims, comprising:

-updating said created virtual tire model (RM) using tire data (RD), vehicle data (FD), environmental data (UD) and/or usage data (ND) respectively related to said vehicle tire (FR) (S4).

4. The method according to one of the preceding claims, comprising:

-comparing (S5) said created or updated virtual tire model (RM) with said vehicle tires (FR), and

-adapting (S6) said created or updated virtual tire model (RM) to said vehicle tire (FR).

5. Method according to one of the preceding claims, wherein said tyre data (RD) relate to one or several parameters selected from the list comprising: tire name, tire type, tire production date, tire production place, tire material, tire tread type, rim type, and rim material.

6. Method according to one of the preceding claims, wherein the vehicle data (FD) relate to one or several parameters selected from the list comprising: -the distance travelled by the vehicle tyre (FR), -the forces acting longitudinally on the vehicle tyre (FR), -the forces acting transversely on the vehicle tyre (FR), -the tyre self-aligning torque, -the wheel slip, -the wheel camber angle and-the variation of the wheel camber angle.

7. Method according to one of the preceding claims, wherein said context data (UD) relates to one or several parameters selected from the list comprising: tire temperature, tire temperature differential, UV irradiation, and road conditions.

8. Method according to one of the preceding claims, wherein the usage data (ND) relate to parameters relating to travel on curbs and/or travel on potholes.

9. Virtual tire model (RM) obtainable by a method according to one of the preceding claims.

10. A method for simulating a tyre condition (RZ), wherein a future condition (S7) of a vehicle tyre (FR) is simulated by means of a virtual tyre model (RM) of said vehicle tyre (FR) according to claim 9.

11. The method of claim 10, wherein the simulated tire condition (SRZ) is compared to an actual tire condition (TRZ) of the vehicle tire (FR), and the simulation is adjusted based on a difference between the simulated tire condition (SRZ) and the actual tire condition (TRZ).

12. A system for data processing comprising means for performing a method according to one of claims 1 to 8 or a method according to claim 10 or 11.

13. A computer program comprising instructions which, when said program is executed by a computer, cause said computer to carry out the method according to one of claims 1 to 8 or the method according to claim 10 or 11.

Images