Method for modeling a surface structuring of vehicle tires optimized for use on predetermined vehicle models

Abstract

The invention relates to a method for modeling a surface structuring of vehicle tires adapted for use on predetermined vehicle models, comprising the method steps: a) selecting one or more predetermined vehicle models, b) selecting a vehicle tire base construction to be adapted with regard to the surface structuring, comprising at least one partial surface provided for the application of a surface structuring, c) modeling a surface structuring for at least one partial surface with an electronic data processing device (10) comprising a storage unit (12) on which a machine learning-based modeling module (14) is stored, wherein the electronic data processing device (10) is configured toto provide input information about the vehicle tire basic construction as input to the modeling module (14) and to model a surface structuring with the modeling module (14), wherein the training of the modeling module (14) is carried out with a set of training data which comprises a plurality of training sets for a plurality of different training vehicle tires of the corresponding vehicle tire basic construction with different surface structuring of the partial surface, and d) output of the matched surface structuring with the electronic data processing device (10).

Description

The invention relates to a method for modelling a surface structuring of vehicle tires matched to the use on predetermined vehicle models and to a method for producing a vehicle tire matched to the use on predetermined vehicle models. A vehicle tire produced by such a method is also disclosed, which is matched to the use on predetermined vehicle models.Modern vehicle tires are high-performance products which, due to their design, contribute significantly to the performance characteristics of vehicles. Accordingly, there is continuing interest in continuously improving the design and design of vehicle tires and adapting them in particular to the respective specific requirements of the application. In addition to the "inner life" of pneumatic vehicle tires, i.e. their construction from various tire components, for example the tire carcass and the belt plies, the surface design of vehicle tires is also of decisive importance.The surface of the tread comprises, with the surface profiling provided for road contact, a surface structure which can significantly influence the driving properties of the vehicle tire on different substrates, in particular their suitability for different weather conditions and substrates. In addition to the surface structuring of the tread, however, the surface configuration of the tire sidewall is also of great importance in practice. In addition to the provision of necessary and / or desired markings on the tire side wall, the side wall design must be designed in particular such that advantageous aerodynamic properties are achieved without too adversely affecting the susceptibility to soiling and / or damage to the surface structure in the side region, so that in this respect there is a conflict of goals between the desired properties in many cases.For new vehicle tire products, tire manufacturers model the surface structure for the vehicle tire, which is then converted as a negative into the vulcanization mold, from which it can be impressed on a multiplicity of vehicle tire blanks during the vulcanization.Nowadays, the step of modelling the surface structure for vehicle tires is a working step which is carried out largely experience-based, so that experienced workers, who additionally have a good feel for the surface design, can have a direct positive influence on the quality of the overall product. Although in many cases there are certain basic requirements, for example in the form of legal guidelines or in the form of requirements for the design of the surface structuring specific to the tire manufacturer, there are an incountedual number of degrees of freedom in the modelling process which can be set by experienced workers in such a way that an advantageous overall product can be obtained at the end.The fact that the performance of the designed surface designs depends very significantly on the competence of the workers used is regularly perceived as disadvantageous, in particular if correspondingly highly qualified and experienced workers are not available, for example because experienced employees are separated from the company. In addition, the dependence on the experience of the workers used inherently involves the considerable risk that unpresred preurites or human preferences in the surface design become established in the experience values of the workers, which prevent the actually optimum surface design from being obtained during the modeling of the surface structuring, for example because only a local maximum of the performance properties in the parameter space is achieved, although a fundamentally different design could lead to an even more advantageous embodiment.Accordingly, there is a fundamental interest in the field of technology in reducing the dependence on experienced workers and in automatizing the modeling of tire surfaces as far as possible and subjecting them to more objective evaluation scales.In this context, it would in principle be desirable to even further exploit the potentials of automated modelling of tire surfaces by identifying parameters which may be important for the overall performance properties of a surface-structured vehicle tire in its specific application cases, but which cannot be taken into account, or not sufficiently, in a modelling situation of workers used in the experience-based modelling of tire surfaces, which modelling situation is in any case ambiguous from among a multiplicity of influence parameters.The primary object of the present invention was to eliminate or at least reduce the disadvantages of the prior art.In particular, it was the object of the present invention to specify a method for modelling a surface structuring of vehicle tires, which advantageously reduces as far as possible the dependence on the experience and competence of the workers used in modelling tire surfaces.In this respect, it was an object of the present invention that the method to be specified should enable particularly time- and cost-effective modelling of surface structures of vehicle tires.In addition, it was an object of the present invention that the surface structures that can be produced using the method to be specified should result in particularly powerful vehicle tires which can be matched particularly comprehensively to the materials and components used in the vehicle tire and are very particularly suitable for specific end use cases.In addition, it was an object of the present invention that the method to be specified should be capable of taking into account design requirements, for example legal requirements or design guidelines of the vehicle tire manufacturer.It was a desirable object of the present invention that it should be possible in the method to be specified to take account of numerous influencing parameters in the modelling of the surface structure.It was a supplementary object of the present invention to provide a method, based on the method to be specified, for producing a vehicle tire having a corresponding surface structuring.It was a secondary object of the present invention to specify a vehicle tire produced using the method to be provided, which vehicle tire has a particularly efficient surface structuring.The inventors of the present invention have now found that the above-described objects can be achieved if a method for modelling surface structuring of vehicle tires is provided if, starting from a predetermined basic vehicle tire construction and specific predetermined vehicle models, modelling of a surface structuring matched for use on the predetermined vehicle models is carried out using a machine learning-based modelling module, the training of which for the purpose of modelling vehicle tire surfaces is carried out starting from a training set which, for training vehicle tires having the corresponding basic vehicle tire construction and different surface structures, comprises performance information which was acquired when used on the predetermined vehicle models, as defined in the claims.The present invention is thus based on the finding that the modelling of tire surfaces depends on a large number of possible input parameters and is thus advantageously suitable for the use of machine learning, by means of which the underlying relationships can be used without the dependence of experience knowledge or competence of the workers used in order to model performance-optimized surface structures which can subsequently be transferred via the vulcanization mold to the vehicle tires to be produced. In this respect, the development of the inventors has led to the finding that it is particularly advantageous in the method according to the invention to design the corresponding surface structuring not in an abstract manner for a property-free tire model, but specifically for a specific vehicle tire basic construction, i.e. for example a specific construction of tire carcass, belt package and tread with a specific dimensioning.This makes it possible to take into account parameters via the training of the machine learning-based modeling module, which parameters have an influence on the design of the surface structuring, but which usually cannot be depicted in a purely experience-based method in a meaningful manner. Beyond taking into account the basic tire construction, the inventors have recognized that the corresponding method must also be used to adapt the modeling of the surface structuring to predetermined vehicle models, as a result of which a second decisive influencing factor can be mapped, which cannot be taken into account in the experience-based method, or at least not in a time- and cost-effective manner, as a result of which, however, particularly powerful surface structures can be obtained in conjunction with the specific basic vehicle tire construction.The above objects are achieved, accordingly, by the subject matter of the invention as defined in the claims. Preferred embodiments according to the invention are evident from the dependent claims and the following explanations.Such embodiments, which are referred to below as preferred, are combined in particularly preferred embodiments with features of other embodiments referred to as preferred. Combinations of two or more of the embodiments referred to below as particularly preferred are thus very particularly preferred. Also preferred are embodiments in which a feature of one embodiment designated as preferred to any extent is combined with one or more further features of other embodiments designated as preferred to any extent. Features of preferred methods for producing a vehicle tire matched to the use on predetermined vehicle models and corresponding vehicle tires result from the features of preferred methods for modeling.The invention relates in particular to a method for modelling a surface structuring of vehicle tires matched to the use on predetermined vehicle models, comprising the method steps: a) selecting one or more predetermined vehicle models, b) selecting a vehicle tire base construction to be matched with respect to the surface structuring for the use on the predetermined vehicle models, comprising at least one partial surface provided for the attachment of a surface structuring, c) modelling a surface structuring matched to the use on the predetermined vehicle models for at least one partial surface of the vehicle tire base construction with an electronic data processing device, wherein the electronic data processing device comprises a storage unit, wherein a modelling module based on machine learning is stored on the storage unit, wherein the electronic data processing device is configured to model a surface structuring matched to the use on the predetermined vehicle models, Input information about the vehicle tire base construction as input to the modelling module and to model a surface structuring of the partial surface which is matched for use on the predetermined vehicle models with the modelling module, wherein the modelling module is trained to match the surface structuring of the partial surface for use on the predetermined vehicle models from input information about a vehicle tire base construction and to model a matched surface structuring, wherein the training is carried out with a set of training data which comprises a plurality of training sets, wherein the training sets for a plurality of different training vehicle tires of the corresponding vehicle tire base construction with different surface structuring of the partial surface each comprise:i) structural information about the surface structuring of the partial surface of the training vehicle tires, andii) performance information on the performance characteristics of the training vehicle tires when used on the predetermined vehicle models, andd) outputting the matched surface structuring with the electronic data processing device.The method according to the invention serves for modelling a surface structuring of vehicle tires, i.e. for obtaining a model of a surface structuring which is provided for vehicle tires. In accordance with the expert's understanding, this is an at least largely computer-implemented method in which, in particular, method steps c) and d) are carried out by an electronic data processing device, it being expected in later practice that the input necessary for method steps a) and b) also takes place as input into an electronic data processing device. The method according to the invention aims at obtaining a surface structuring of vehicle tires which is matched to predetermined vehicle models. Relevant for most cases is a method according to the invention, wherein the vehicle tire is a pneumatic vehicle tire.In accordance with this objective, in method step a), one or more predetermined vehicle models are first selected, to which the surface structuring to be modeled is to be matched. With regard to the number of selected vehicle models, there is a conflict of goals between the training data necessary for training the artificial intelligence or the training effort and the performance of the surface structuring obtained for the respective vehicle models. In addition, a small number of vehicle models to be taken into account in practice allows a surface structuring which is particularly optimized for the specific models to be obtained, whereas a surface structuring which is optimized for a plurality of vehicle models should in practice be usually less powerful for each individual one of these vehicle models than a product specifically matched to the vehicle model. A method according to the invention is preferred, wherein exactly one predetermined vehicle model is selected. In addition or alternatively, a method according to the invention is preferred, wherein a plurality of, preferably 10 or less, particularly preferably 7 or less, particularly preferably 4 or less, predetermined vehicle models are selected.The optimization is carried out on predetermined vehicle models. Within the scope of the present invention, the term "vehicle model" is to be understood broadly as the uppermost ordering criterion for vehicles which are similar in terms of properties and / or specifications. The more similar the corresponding predetermined vehicle models are, the more efficiently an adaptation of the modeling to these specific vehicle models can be effected. The parameters include, in particular, the vehicle type, i.e. whether it is a car, for example, wherein the vehicle class can also be defined, for example because the predetermined vehicle models are sports cars or transporters in each case. A further relevant selection variable for the predetermined vehicle models is the vehicle manufacturer, the model series and the basic model. For example, four predetermined vehicle models can be selected for the method according to the invention, which are each BMW vehicles from the 3rd row, which differ with regard to the configuration as sedan, touring etc., but which originate from the same generation of the model row. A method according to the invention is preferred, wherein the predetermined vehicle models all belong to the same vehicle type, preferably cars, trucks or buses, wherein the plurality of predetermined vehicle models particularly preferably all belong to the same vehicle class, for example small cars or sport cars. In addition or as an alternative, a method according to the invention is preferred, wherein the predetermined vehicle models all originate from the same vehicle manufacturer. In addition or alternatively, a method according to the invention is preferred, wherein the predetermined vehicle models all originate from the same model series, preferably from the same generation of the model series. In addition or alternatively, a method according to the invention is preferred, wherein the predetermined vehicle models are all variants of the same basic vehicle model, and / or wherein the predetermined vehicle models all have the same chassis.In addition to the vehicle model to which the surface structuring is to be matched, the selected vehicle tire base construction is also predefined. In accordance with the skilled understanding, the vehicle tire base construction denotes the structural design of the vehicle tire, including its dimensions, without considering the surface structuring. The basic vehicle tire construction thus denotes the basic structural design of the vehicle tire which is to be provided with an adapted modeled surface structuring. A method according to the invention is preferred, wherein the selected vehicle tire base construction is defined by tire components installed in the interior of the vehicle tire, in particular their structure and / or material composition, and their arrangement in the interior of the vehicle tire, preferably by all of the installed tire components and their arrangement. In addition or alternatively, a method according to the invention is preferred, wherein the selected vehicle tire base construction is defined by the structure and / or material composition and / or arrangement of one or more, preferably of two or more, particularly preferably three or more, in particular preferably of all, of the following tire components:I) the tire carcass,II) one or more belt plies arranged radially outside the tire carcass,III) one or more winding bandages arranged radially outside the belt plies, preferably not for truck tires,IV) of a radially outer tread,V) the side wall elements, andVI) of the bead cores.In the design of a new vehicle tire, the vehicle tire base construction can in principle have an unstructured surface, since the information about the surface structuring is not required as the parameter of the overall vehicle tire, which parameter is to be modeled anyway, as an input. Advantageously, however, it is also possible with the method according to the invention to subsequently optimize the already existing surface structuring for existing tire models, in which case information about the already existing surface structuring can also be taken into account within the scope of the basic tire construction, wherein it is also possible to preset a certain maximum change of the existing surface structuring by specific specifications for the modelling module. This makes it possible, for example, to generate a sub-row specifically optimized for use with specific vehicle models for a generic row of vehicle tires. A method according to the invention is preferred, wherein the selected vehicle tire base construction has on at least one partial surface an initial surface structure that is not matched to the use on the predetermined vehicle models.According to the above definition, the vehicle tire base construction comprises at least one partial surface on which the surface structuring to be modeled and matched to the predetermined vehicle models is to be applied in the later product. The partial surfaces can be in particular the tread surface and the sidewall surfaces or parts thereof. A method according to the invention is preferred, wherein the vehicle tire base construction comprises two or more, preferably three or more, partial surfaces provided for applying a surface structuring. In addition or alternatively, a method according to the invention is preferred, wherein the partial surface provided for applying a surface structuring is selected from the group consisting of the tread surface and the tire sidewall surfaces.In the case of surface structuring of the tread surface, the modeled surface structuring is a tread profile which will regularly comprise a multiplicity of profile grooves and corresponding profile blocks. A method according to the invention is preferred, wherein the partial surface provided for applying a surface structuring is the tread surface, wherein the surface structuring is a tread profiling. In addition or alternatively, a method according to the invention is preferred, wherein the tread profiling in the tread comprises a multiplicity of profile blocks separated from one another by profile grooves.As the most important alternative to the tread surface, the surface structuring of the tire sidewall surface is of particular importance. A method according to the invention is preferred, wherein the partial surface provided for applying a surface structuring is one or both of the tire sidewall surfaces, wherein the surface structuring is a sidewall structuring. In addition or alternatively, a method according to the invention is preferred, wherein the side wall structuring comprises a multiplicity of elevations and depressions on the side wall surface.In accordance with the skilled person's understanding, it is possible to carry out the method according to the invention in parallel or sequentially for a plurality of partial surfaces, in order to model a vehicle tire base construction for all partial surfaces, for example.In method step c), the surface structuring of the partial surface under consideration, which is matched for use on the predetermined vehicle models, is modeled, which can be carried out both by fundamental redesigning of a surface structuring and by modifying a predefined initial surface structuring in accordance with the above disclosures. A method according to the invention is preferred, wherein the modelling of the surface structuring matched for the use on the predetermined vehicle models comprises the adaptation of an initial surface structuring not matched to the use on the predetermined vehicle models.In method step c), a surface structuring is modeled. According to the skilled person, a modeled surface texture is a plurality of surface texture parameters, which in many cases can be read out in their entirety by typical processing software such that, for example, a three-dimensional computer model of the modeled surface texture, or a set of control information for a tool for manufacturing a vulcanization mold can be obtained in the light of these surface textures. A method according to the invention is preferred, wherein the modelling of the surface structuring matched for use on the predetermined vehicle models comprises defining one or more, preferably two or more, particularly preferably three or more, very particularly preferably all, surface structure parameters which are selected from the group consisting of the number of surface elevations, the shape of the surface elevations, the arrangement of the surface elevations, the surface configuration of the surface elevations, the number of surface depressions, the shape of the surface depressions and the arrangement of the surface depressions. In addition or alternatively, a method according to the invention is preferred, wherein the modeling of a tread profiling comprises the definition of one or more profile parameters which are selected from the group consisting of the shape of the profile blocks, the number of profile blocks, the arrangement of the profile blocks, the surface configuration of the profile blocks, the shape of the profile grooves, the number of profile grooves and the arrangement of the profile grooves. In addition or alternatively, a method according to the invention is preferred, wherein the modelling of the surface structuring matched for use on the predetermined vehicle models is carried out for two or more partial surfaces, preferably for all partial surfaces provided for the application of a surface structuring.The modeling of the surface structuring itself, which is matched for use on the predetermined vehicle models, is carried out using machine learning, wherein the corresponding module, which is provided on the storage unit of the electronic data processing device, is referred to as a "modeling module" for the purpose of clear identification. The general concept of machine learning, which is also referred to as "artificial intelligence", is fundamentally known to the person skilled in the art. Suitable software solutions, which can be converted into a modeling module by suitable training, are available on the market from numerous suppliers and can be trained by the person skilled in the art in the light of the present disclosure to function as a modeling module in the method according to the invention. A method according to the invention is preferred, wherein the training of the modelling module is carried out by means of monitored learning. In addition or alternatively, a method according to the invention is preferred, wherein the modeling module is based on a machine learning algorithm which is selected from the group consisting of algorithms of monitored learning, preferably selected from the group consisting of artificial neural networks, and / or wherein the modeling module is obtained by applying a machine learning algorithm to the set of training data, wherein the algorithm is selected from the group consisting of algorithms of monitored learning, preferably selected from the group consisting of artificial neural networks.The ability to model a surface structuring of the partial surface matched to the vehicle tire base construction and the predetermined vehicle model is gained by the modeling module by a corresponding training with a set of training data. The training data thereby comprise a plurality of training sets which have been collected for vehicle tires which are referred to as "training vehicle tires" for the purpose of clearer identification and which correspond with respect to their basic construction to the basic vehicle tire construction. A corresponding set of training data can be obtained relatively easily for the person skilled in the art in view of the invention, for example via own vehicle fleets of the tire manufacturers, in cooperation with specific vehicle manufacturers and / or fleet operators. Thanks to the data acquisition capabilities that have increased greatly over the past decades, there is comprehensive performance information available for combinations of specific vehicle tires with specific vehicle models in many of these locations, which performance information can be used for training. In addition to recourse to already existing databases of performance parameters, corresponding sets of training data can also be obtained by tests which can be carried out in the field or at the test stand, it being possible for different training vehicle tires to be drawn onto the vehicle models in question and examined with regard to the performance properties of interest in each case.Even if the training data can comprise further information, it is essential that this information comprises information about the respective surface structuring of the relevant partial surface and performance information about the performance properties of the correspondingly structured training vehicle tires when used on the predetermined vehicle model. A method according to the invention is preferred, wherein the structural information comprises geometric information about the configuration of the surface structuring of the partial surface of the vehicle tires or correlates therewith, preferably comprises it. In addition or alternatively, a method according to the invention is preferred, wherein the performance information comprises information on one or more performance properties selected from the group consisting of wear behavior, braking performance, rolling resistance on a wet roadway, rolling resistance on snow and ice, fuel consumption and noise development.The modeling module can advantageously be configured such that it weights the relevance of the performance properties during the modeling of the matched surface structuring in a predetermined ratio or a ratio that can be adjusted for the modeling task, wherein it is also possible, for example, to substantially completely mask out individual performance properties, because, for example, the noise generation for racing tires is a factor that is to be ignored. A method according to the invention is preferred, wherein the modeling in step c) is carried out to improve one or more, preferably more, optionally mutually weighted predefined performance properties of the vehicle tire, wherein the modeling module is trained to adapt the surface structuring of the partial surface for use on the predefined vehicle models from input information about the vehicle tire basic construction and to model a matched surface structuring by means of which the one or more predefined performance properties are improved.The above-described set of training data is, as contemplated by the inventors, the amount needed for basic functionality. At the same time, it is advantageous, according to the inventors' judgment, to design the set of training data as broadly as possible by recording further training sets. In this respect, the inventors propose that such training sets can also be included in the set of training data in which the structural information and the performance information are present for vehicle tires which have been included on the predetermined vehicle models, but for such training vehicle tires which differ from the vehicle tires to be optimized with regard to the basic vehicle tire construction. As a result, not only is a modelling module obtained in an advantageous manner, which can be more easily switched to different vehicle tyre base structures, but it is also found in practice that specific modelling rules for the configuration of the surface structuring only show a comparatively low variance as a function of the vehicle tyre base structure, with the result that the modelling module based on machine learning can also provide better results overall for the desired vehicle tyres. A method according to the invention is preferred, wherein the set of training data comprises additional further training sets, which each comprise, for a plurality of different training vehicle tires, a vehicle tire basic construction different from the vehicle tire basic construction to be matched and having a different surface structuring of the partial surface:i.b) structural information about the surface structuring of the partial surface of the training vehicle tires, andii.b) performance information about the performance characteristics of the training vehicle tires when used on the predetermined vehicle models, wherein all training sets comprise identification information about the respective vehicle tire base construction, wherein the modelling module is trained to use training data exclusively assigned to the vehicle tire base construction to be adapted for the adaptation of the surface structuring of the partial surface of the vehicle tire base construction or to weight it to a predetermined extent during the modelling.Analogous to deviations in the basic vehicle tire construction, the training set can also comprise supplementary training sets, the performance information of which has been acquired on other vehicle models in order to put the data on which the training is based on a broader basis. A method according to the invention is preferred, wherein the set of training data comprises additional supplementary training sets, which comprise a) for a plurality of different training vehicle tires of the basic vehicle tire construction to be adapted, and / or b) for a plurality of training vehicle tires of a basic vehicle tire construction different from the basic vehicle tire construction to be adapted, with different surface structuring of the partial surface:i.b) structural information about the surface structuring of the partial surface of the training vehicle tires,ii.b) performance information on the performance characteristics of the training vehicle tires, which are not the predetermined vehicle model or models, wherein all training sets comprise identification information about the respective vehicle models, wherein the modeling module is trained to use only training data assigned to the predetermined vehicle models for the matching of the surface structuring of the partial surface of the vehicle tire base construction or to weight it to a predetermined extent higher during the modeling.In addition to the training data, the training modelling module can also utilize modelling specifications which the modelling module has to take into account in the manner of boundary parameters. A method according to the invention is preferred, wherein the training of the modelling module takes place such that the modelling module takes into account one or more modelling specifications, wherein the one or more modelling specifications comprise one or more specifications for modelling the surface structuring of the part surface, wherein the specifications are preferably selected from the group consisting of legal specifications, specifications which are obligatory for the vehicle tyre basic construction and manufacturer-specific design specifications. In addition or alternatively, a method according to the invention is preferred, wherein the modeling module is trained to model only surface structures of the partial surface that meet one or more modeling specifications, wherein the one or more modeling specifications comprise one or more specifications for modeling the surface structure of the partial surface, wherein the specifications are preferably selected from the group consisting of legal specifications, specifications that are obligatory for the vehicle tire base construction, and manufacturer-specific design specifications.The surface structuring coordinated by the modeling module is output in method step d). Even if it would in principle be conceivable to output the coordinated surface structuring only to a user, for example via a display, it is preferred for substantially all embodiments to provide directly a digitally usable output, which is output directly to a suitable design software, for example for the purpose of fine adaptation, or directly as output to a production machine, which can convert the modeled surface structuring directly into production steps. A method according to the invention is preferred, wherein the coordinated surface structuring is output to a construction software, preferably in the form of three-dimensional structure information. In addition or alternatively, a method according to the invention is preferred, wherein the coordinated surface structuring is output to a production machine, preferably a production machine for producing vulcanization molds, preferably in the form of control information for forming a surface structure corresponding to the negative of the coordinated surface structuring.The invention also relates to a method for producing a vehicle tire matched to the use on predetermined vehicle models, comprising the method steps of the method according to the invention for obtaining a surface structuring of vehicle tires matched to the use on predetermined vehicle models, and the steps:x) producing or providing a vulcanization mold, wherein the vulcanization mold has a surface structure in a region of the wall intended for forming the partial surface, which surface structure corresponds to the negative of the coordinated surface structure, andy) vulcanizing a green vehicle tire in the vulcanization mold to obtain a vehicle tire to form the adjusted surface pattern on the partial surface.As explained above, the modeled surface structuring of the partial surface that is matched to the predetermined vehicle models can be used to configure the corresponding partial surface in the production of vehicle tires according to the model. This can be effected in a particularly time- and cost-effective manner by shaping a vulcanization mold, wherein the negative of the desired surface structuring is introduced into the corresponding complementary regions of the vulcanization mold, so that the desired surface structuring can be impressed into the surface of the vehicle tire by the vulcanization mold during the vulcanization of a vehicle tire blank.Also disclosed within the scope of the present invention is a vehicle tire manufactured or producible with the method according to the invention for manufacturing a vehicle tire adapted for use on predetermined vehicle models.The invention and preferred embodiments of the invention are explained and described in more detail below with reference to the attached figures. The following are shown: FIG. 1 shows a schematic illustration of the method steps of the method according to the invention in a preferred embodiment, and FIG. 2 shows a schematic illustration of an electronic data processing device optimized for carrying out the method according to the invention.FIG. 1 schematically visualizes the steps of the method according to the invention for modeling a surface structuring of vehicle tires matched to the use of predetermined vehicle models. In the first method step 100, one or more predetermined vehicle models are first selected, for example the BMW G 20 and BMW G 21 of the seventh generation of BMW 3er as sedan and touring.In the second method step 200, a series tire from the manufacturer Continental, for example, which is suitable for use on 3 BMW with regard to its construction and its dimensions, is provided as the vehicle tire base construction in the configuration as a summer tire. The partial surface to be optimized can be selected, for example, as the tire sidewall that is located on the outside after attachment to the vehicle, in order to optimize it with regard to the structural elements present on the sidewall.The modeling itself takes place in the third method step 300 with the machine learning-based modeling module 14, which is provided on the storage unit 12 of an electronic data processing device 10, as schematically visualized in FIG. 2.The modeling module 14 can be based, for example, on an artificial neural network, which was trained by means of monitored learning to carry out the modeling of the surface structuring. The set of training data used for this purpose comprises a multiplicity of training sets which, for a wide range of training vehicle tires of different tire base construction, each comprise information on how the respective surface structuring of the training vehicle tires is designed and which performance properties of the specifically designed training vehicle tires have in each case resulted when used on different vehicle models. For the purpose of optimizing the modeling module 14 and limiting the training effort, the training set is selected such that more than 50%, preferably more than 70%, particularly preferably more than 90%, of the training sets contained in the set of training data correspond to the tire base construction to be optimized and have additionally been recorded on the predetermined vehicle models, i.e. the BMW models designated above.The modeling by the modeling module 14 is carried out on the basis of the initial surface structure that is not matched to the use on the predetermined vehicle models, but the design specifications of continental are taken into account as boundary conditions in order to maintain the necessary intersection with the company's own design philosophy.Among other parameters, the performance information in the training sets includes, in particular, the fuel consumption and the noise generation of the vehicle, wherein the corresponding performance properties are particularly heavily weighted in the exemplary optimization of the tire sidewall.List of reference characters10 Electronic data processing device 12 Storage unit 14 Modeling module 100 Method step a) 200 Method step b) 300 Method step c) 400 Method step d)

Claims

Method for modelling a surface structuring of vehicle tyres matched to the use on predetermined vehicle models, comprising the method steps: a) selecting one or more predetermined vehicle models, b) selecting a basic vehicle tyre construction to be matched with respect to the surface structuring for the use on the predetermined vehicle models, comprising at least one partial surface provided for applying a surface structuring, c) modelling a surface structuring matched to the use on the predetermined vehicle models for at least one partial surface of the basic vehicle tyre construction with an electronic data processing device (10), wherein the electronic data processing device (10) comprises a storage unit (12), wherein a modelling module (14) based on machine learning is stored on the storage unit (12), wherein the electronic data processing device (10) is configured to, Input information about the vehicle tire base construction as input to the modelling module (14) and to model a surface structuring of the partial surface matched for use on the predetermined vehicle models with the modelling module (14), wherein the modelling module (14) is trained to match the surface structuring of the partial surface for use on the predetermined vehicle models from input information about a vehicle tire base construction and to model a matched surface structuring, wherein the training is carried out with a set of training data which comprises a plurality of training sets, wherein the training sets for a plurality of different training vehicle tires of the corresponding vehicle tire base construction with different surface structuring of the partial surface each comprise: i) structural information about the surface structuring of the partial surface of the training vehicle tires, and ii) performance information on the performance characteristics of the training vehicle tires when used on the predetermined vehicle models, and d) outputting the matched surface texture with the electronic data processing device (10).The method of claim 1, wherein the predetermined vehicle models are all of the same vehicle type.Method according to either of Claims 1 and 2, wherein the selected vehicle tyre basic construction is defined by tyre components installed in the interior of the vehicle tyre.The method according to any one of claims 1 to 3, wherein the partial surface provided for applying a surface structuring is selected from the group consisting of the tread surface and the tire sidewall surfaces.The method of any of claims 1 to 4, wherein modeling the surface texture matched for deployment on the predetermined vehicle models comprises adjusting an initial surface texture not matched for deployment on the predetermined vehicle models.The method of any of claims 1 to 5, wherein modeling the surface texture tuned for use on the predetermined vehicle models comprises determining one or more surface texture parameters selected from the group consisting of the number of surface protrusions, the shape of the surface protrusions, the arrangement of the surface protrusions, the surface configuration of the surface protrusions, the number of surface recesses, the shape of the surface recesses, and the arrangement of the surface recesses.Method according to one of Claims 1 to 6, wherein the structural information comprises geometric information about the configuration of the surface structuring of the partial surface of the vehicle tires or correlates with said surface structuring, and / or wherein the performance information comprises information about one or more performance characteristics selected from the group consisting of wear behavior, braking performance, rolling resistance on a wet roadway, rolling resistance on snow and ice, fuel consumption and noise development.Method according to one of Claims 1 to 7, wherein the modelling in step c) is carried out in order to improve one or more optionally mutually weighted predefined performance properties of the vehicle tyre, wherein the modelling module is trained to tune the surface structuring of the partial surface for use on the predefined vehicle models from input information about the vehicle tyre basic construction and to model a tuned surface structuring by means of which the one or more predefined performance properties are improved.The method according to any one of claims 1 to 8, wherein the modeling module is trained to model only surface structures of the partial surface that meet one or more modeling specifications, wherein the one or more modeling specifications comprise one or more specifications for modeling the surface structure of the partial surfaceMethod for producing a vehicle tyre matched to the use on predetermined vehicle models, comprising the method steps of the method for obtaining a surface structuring of vehicle tyres matched to the use on predetermined vehicle models according to one of Claims 1 to 9, and the steps: x) producing or providing a vulcanization mould, wherein the vulcanization mould has a surface structure in a region of the wall intended for forming the partial surface, which surface structure corresponds to the negative of the matched surface structuring, and y) vulcanizing a vehicle tyre blank in the vulcanization mould to obtain a vehicle tyre, forming the matched surface structuring on the partial surface.

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