Vehicle tire type selection method and related equipment

Abstract

The invention discloses a vehicle tire type selection method and related equipment, and the method comprises the steps: obtaining parameter setting and query conditions in response to an input instruction; the parameter setting comprises the maximum speed of the whole vehicle and front and rear wheel loads of the whole vehicle, and the query conditions comprise a rim diameter value, a section width value and an outer diameter value of a tire; extracting query information according to the query condition, and searching an initial tire specification set meeting requirements in a preset knowledge base according to the query information; the knowledge base comprises a tire rim official manual, tire pressure and load index relation information and speed and speed code corresponding information; and carrying out load index matching and speed index matching according to the initial tire specification set and the preset knowledge base, and outputting a target tire specification set. According to the embodiment of the invention, the efficiency and accuracy of vehicle tire options can be improved. The method can be widely applied to the technical field of computers.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a method and related equipment for selecting vehicle tires. Background Technology

[0002] For tire designers at automakers, developing a new tire for a completely new model or a new generation of a model / year is inefficient if they rely on manual tire specification selection. The whole process usually takes more than 4 hours, and manual selection requires a lot of work experience and is prone to errors. Summary of the Invention

[0003] The main objective of this application is to provide a method and related equipment for selecting vehicle tires, aiming to improve the efficiency and accuracy of vehicle tire selection.

[0004] To achieve the above objectives, one aspect of this application proposes a method for selecting vehicle tires, the method comprising: In response to an input command, the system obtains parameter settings and query conditions; the parameter settings include the vehicle's maximum speed and the front and rear wheel loads, and the query conditions include the tire's rim diameter, cross-sectional width, and outer diameter. Based on the query conditions, query information is extracted, and based on the query information, a set of initial tire specifications that meet the requirements is searched in a preset knowledge base; the knowledge base includes official tire and rim manuals, information on the relationship between tire pressure and load index, and information on speed and speed code correspondence; Based on the initial tire specification set and the preset knowledge base, load index matching and speed index matching are performed to output the target tire specification set.

[0005] In some embodiments, the step of obtaining parameter settings and query conditions in response to an input command includes: Responding to text and / or voice input commands, retrieve parameter settings and query criteria.

[0006] In some embodiments, extracting query information based on the query conditions includes: Extract the cross-section width query set based on the cross-section width value; Extract the outer diameter query set based on the outer diameter value.

[0007] In some embodiments, the step of searching for an initial set of tire specifications that meet the requirements in a preset knowledge base based on the query information includes: Determine whether the query information is complete; If the query information is complete, the system searches a preset knowledge base for an initial set of tire specifications that meets the requirements, based on the rim diameter, the cross-sectional width query set, and the outer diameter query set.

[0008] In some embodiments, the method further includes: The initial set of tire specifications is cleaned by removing duplicates based on the rim diameter, cross-sectional width, and outer diameter.

[0009] In some embodiments, load index matching and speed index matching are performed based on the initial tire specification set and the preset knowledge base to output a target tire specification set, including: The load-bearing capacity is determined based on the front and rear wheel loads of the vehicle, and standard tires and reinforced tires are selected from the initial tire specification set based on the load-bearing capacity and the preset knowledge base. Based on the maximum vehicle speed and the preset knowledge base, a speed symbol is determined, and the maximum vehicle speed and the speed symbol are added to the corresponding standard tire and the reinforced tire to form and output the target tire specification set.

[0010] In some embodiments, the method further includes: In response to input commands, display parameter input prompts and / or option progress information.

[0011] To achieve the above objectives, another aspect of this application provides a vehicle tire selection device, the device comprising: The acquisition module is used to acquire parameter settings and query conditions in response to input commands; the parameter settings include the vehicle's maximum speed and the front and rear wheel loads of the vehicle, and the query conditions include the tire's rim diameter, cross-sectional width, and outer diameter. The search module is used to extract query information based on the query conditions, and search for a set of initial tire specifications that meet the requirements in a preset knowledge base based on the query information; the knowledge base includes official tire and rim manuals, tire pressure and load index information, and speed and speed code correspondence information; The matching output module is used to perform load index matching and speed index matching based on the initial tire specification set and the preset knowledge base, and output the target tire specification set.

[0012] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the methods described above.

[0013] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods described above.

[0014] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer program product, including a computer program that, when executed by a processor, implements the methods described above.

[0015] The embodiments of this application include at least the following beneficial effects: This application provides a method, device, electronic device, storage medium, and program product for selecting vehicle tires. This solution obtains parameter settings and query conditions in response to input commands. The parameter settings include the vehicle's maximum speed and front and rear wheel loads. The query conditions include the tire's rim diameter, section width, and outer diameter. Query information is extracted based on the query conditions, and an initial set of tire specifications that meets the requirements is searched in a preset knowledge base based on the query information. The knowledge base includes official tire and rim manuals, information on the relationship between tire pressure and load index, and information on speed and speed code correspondence. Load index matching and speed index matching are performed based on the initial set of tire specifications and the preset knowledge base, and a target set of tire specifications is output. An initial set of tire specifications that meets the requirements is automatically searched from the knowledge base based on the input parameter settings and query conditions, and the initial set of tire specifications is automatically matched for load index and speed index, thereby improving the efficiency and accuracy of vehicle tire selection. Attached Figure Description

[0016] Figure 1 This is a flowchart of the vehicle tire selection method provided in the embodiments of this application; Figure 2 This is a flowchart illustrating the development process of the vehicle tire selection platform provided in this application embodiment; Figure 3 This is a framework diagram corresponding to the vehicle tire selection method provided in the embodiments of this application; Figure 4 This is a flowchart of extracting query information provided in an embodiment of this application; Figure 5 This is a flowchart illustrating the search for an initial set of tire specifications provided in an embodiment of this application; Figure 6 This is a flowchart illustrating the formation and output of a target tire specification set provided in an embodiment of this application; Figure 7 This is a framework diagram corresponding to a specific embodiment of the vehicle tire selection method provided in this application. Figure 8 This is a schematic diagram of the output interface provided in an embodiment of this application; Figure 9 This is a schematic diagram of the structure of the vehicle tire selection device provided in the embodiments of this application; Figure 10 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0018] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”

[0019] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0021] Before providing a detailed description of the embodiments of this application, some of the nouns and terms involved in the embodiments of this application will be explained first. The nouns and terms involved in the embodiments of this application are subject to the following interpretations.

[0022] Dify is an open-source Large Language Model (LLM) application development platform. It integrates the concepts of Backend as Service (Backend as Service) and LLMops, enabling developers to quickly build production-ready generative AI applications. It supports various large language models, such as Claude3 and OpenAI, and collaborates with multiple model vendors to ensure developers can choose the most suitable model based on their needs. The platform provides powerful dataset management capabilities, allowing users to upload and manage text and structured data, and simplifies prompt orchestration and application operation through visualization tools, significantly reducing the complexity of AI application development.

[0023] For tire designers at automakers, developing a new tire for a completely new car model or a model year requires first determining the tire specifications. This necessitates knowing the rim diameter of the vehicle, as the tire must be compatible with the rim, which determines the most basic parameters of the tire specifications. Other important parameters include the tire section width design value, the tire outer diameter design value (usually provided by the suspension system designer or matched based on their layout), axle load (further broken down into the load borne by each tire to select the appropriate tire load index), and the vehicle's maximum speed (used to select the tire speed rating).

[0024] The vehicle tire selection method provided in this application relates to the field of information technology. This method can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or in-vehicle terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing the vehicle tire selection method, but is not limited to the above forms.

[0025] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0026] Figure 1 This is an optional flowchart of a vehicle tire selection method provided in an embodiment of this application. Figure 1 The methods include, but are not limited to, steps S101 to S103.

[0027] Step S101: In response to the input command, obtain parameter settings and query conditions; the parameter settings include the maximum speed of the vehicle and the front and rear wheel loads of the vehicle, and the query conditions include the rim diameter, cross-sectional width and outer diameter of the tires; Step S102: Extract query information based on query conditions, and search for a set of initial tire specifications that meet the requirements in a preset knowledge base based on the query information; the knowledge base includes official tire and rim manuals, information on the relationship between tire pressure and load index, and information on speed and speed code correspondence. Step S103: Perform load index matching and speed index matching based on the initial tire specification set and the preset knowledge base, and output the target tire specification set.

[0028] It should be noted that the AI ​​products created using this method are not limited in form. Taking the DIFY platform as an example, they can be created as various AI products or applications such as chat assistants, intelligent agents, workflows, and dialogue streams. The vehicle tire selection method in this embodiment is applicable to various types of tires, such as radial tires, bias-ply tires, off-road tires, special tires, and T-type spare tires.

[0029] In one specific embodiment, this implementation is based on the DIFY platform, utilizing official manuals such as the *European Tire & Rim Technical Organization Standards Manual* (ETRTO) or the *China Tire & Rim Valve Standards Yearbook*, tire pressure and load index tables, and speed and speed code correspondence tables as an external knowledge base (RAG). Recall testing and tagging of the knowledge base improve retrieval accuracy. Through prompt word engineering, multiple LLM (Large Language Model) roles are set up, including natural language information extraction, intent recognition, and content judgment. The dialogue flow is then developed by combining conditional judgment, aggregator, parameter extraction, variable assignment, code execution, loops, iterations, and time-related nodes / tools within the DIFY platform. A complete dialogue flow has been developed on the DIFY platform, implemented entirely using the qwen-max large model and nearly 100 nodes and tools within DIFY.

[0030] In one specific embodiment, the development flowchart of the dialogue flow is as follows: Figure 2As shown: S1. First, install and privately deploy DIFY, deploying the LLM large language model as the "brain" of the entire dialogue flow. Based on the thinking ability of the large model, it processes the user's natural language. S2. Build a knowledge base. The knowledge base consists of professional documents. The knowledge collected and acquired by the general large model deployed in S1 is clearly described as in the professional documents. Therefore, a knowledge base needs to be built for LLM to query. This is what is often referred to as an external expert system, RAG. S3. Build a user query information input module to provide users with a user-friendly interface. Users input query conditions through parameter input and dialog box input. The parameter setting field inputs the vehicle's maximum speed and front and rear wheel loads, while the dialog box inputs values ​​such as tire rim diameter, section width, and outer diameter. The purpose of this setting is that the parameters input in the parameter setting field come from the vehicle's equipment definition file, which is easy to extract and provides an interface for subsequent direct data connection. S4. Build a user query information extraction and output module. Through the processing function of the LLM large language model, the natural language input by the user is converted into a formatted JSON string for subsequent knowledge base retrieval. S5. Place the knowledge base retrieval under the iterative node or loop node to achieve accurate retrieval under various retrieval conditions. Then clean the retrieval results and output them. S6. Based on each specification output in S5, extract the load index corresponding to each specification, and then retain the specifications that meet the wheel load requirements based on the overall wheel load. S7. Query the speed symbol. S8. Match the speed symbol to the results of S6, output it by category (standard tire, reinforced tire), and output the duration of this run.

[0031] For ease of understanding, a system framework for dialogue flow is provided. Figure 3 The following is a summary of the dialogue flow: The user interaction layer includes an information input page and a result output page. The information input page provides a dialog window; when the user enters search criteria in the dialog window and clicks the send button, the corresponding function in the AI ​​capability layer is invoked. The result output page uses a dialog-based output and displays the program's runtime, optimizing the user experience. The AI ​​capability layer utilizes the LLM capabilities provided by the DIFY platform, and its semantic understanding and reasoning capabilities include several major nodes such as knowledge base retrieval module, LLM, and parameter extraction.

[0032] The business logic layer is used to execute pre-defined business processes and work logic. Several functional modules have been developed, which are interconnected to complete the overall functionality, and finally output through the user interaction layer.

[0033] In some embodiments, in response to an input instruction, parameter settings and query conditions are obtained, including but not limited to step S201.

[0034] Step S201: In response to text and / or voice input commands, obtain parameter settings and query conditions.

[0035] Input commands can be implemented through human-computer interaction. The user interface layer includes several functions and interfaces such as parameter settings and text or voice query input. After the user inputs parameters and query text and clicks send, the dialogue flow starts running and calls the AI ​​logic flow.

[0036] In some embodiments, see Figure 4 Extract query information based on the query conditions, including but not limited to steps S301 to S302.

[0037] Step S301: Extract the cross-section width query set based on the cross-section width value; Step S302: Extract the outer diameter query set based on the outer diameter value.

[0038] The process involves extracting a cross-section width lookup range based on the cross-section width value, and then extracting a cross-section width lookup set based on that range. Similarly, it involves extracting an outer diameter lookup range based on the outer diameter value, and then extracting an outer diameter lookup set based on that range. For example, if the cross-section width value is 235 and the outer diameter value is 690, the cross-section width lookup range is extracted as 225-245, and the outer diameter lookup range is extracted as 670-710. Multiple cross-section width lookup values ​​are then extracted from the cross-section width lookup range to form a cross-section width lookup set, and multiple outer diameter lookup values ​​are extracted from the outer diameter lookup range to form a cross-section width lookup set.

[0039] In some embodiments, see Figure 5 Based on the query information, search the preset knowledge base for an initial set of tire specifications that meet the requirements, including but not limited to steps S401 to S402.

[0040] Step S401: Determine if the query information is complete; Step S402: If the query information is complete, search the preset knowledge base for an initial set of tire specifications that meet the requirements based on the rim diameter, cross-section width query set, and outer diameter query set.

[0041] If the query information includes the tire's rim diameter, section width set, and outer diameter set, the query information is complete; otherwise, the query information is incomplete. If the query information is incomplete, the process ends. If the query information is complete, the system searches a preset knowledge base for an initial set of tire specifications that meets the requirements, based on the rim diameter, section width, and outer diameter query sets. The search process is determined based on the actual application; for example, two factors may be selected for searching first, and then filtered based on the last factor, such as filtering first based on the rim diameter + section width query set, and then filtering based on the outer diameter query set.

[0042] In some embodiments, the method for selecting vehicle tires further includes step S501.

[0043] Step S501: Perform deduplication cleaning on the initial tire specification set based on the rim diameter, cross-sectional width, and outer diameter.

[0044] Specifically, the initial tire specification set was cleaned by removing duplicates based on three aspects: rim diameter, cross-sectional width, and outer diameter, in order to reduce the amount of computational data and improve the accuracy of the results.

[0045] In some embodiments, see Figure 6 Based on the initial tire specification set and the preset knowledge base, load index matching and speed index matching are performed to output the target tire specification set, including but not limited to steps S601 to S602.

[0046] Step S601: Determine the load-bearing capacity based on the front and rear wheel loads of the vehicle, and select standard tires and reinforced tires from the initial tire specification set based on the load-bearing capacity and a preset knowledge base; Step S602: Determine the speed symbol based on the maximum vehicle speed and the preset knowledge base, add the maximum vehicle speed and speed symbol to the corresponding standard tire and reinforced tire, and form and output the target tire specification set.

[0047] First, extract the maximum value from the input front axle load and rear axle load. Then, divide the maximum axle load by 2 to obtain the wheel load corresponding to each wheel. Since a vehicle typically has four identical tires, the maximum load capacity must be met. The tire load index is obtained by consulting the tire pressure-load index mapping table based on the axle load. Standard and reinforced tires are then selected from the initial tire specification set based on the load index. The speed symbol is then looked up in the speed-speed symbol matching table and added to the corresponding standard and reinforced tires, forming and outputting the target tire specification set.

[0048] In some embodiments, the method for selecting vehicle tires further includes step S701.

[0049] Step S701: In response to the input command, display parameter input prompts and / or option progress information.

[0050] Input parameter prompts include, but are not limited to, precautions for input parameters. Process information includes, but is not limited to, which stage of the process is currently running and the estimated computation time.

[0051] The following is a detailed introduction and explanation of the solution of the present invention, using specific examples of vehicle tire selection as examples: See Figure 7At the user interface layer, there are several functions and interfaces, including parameter settings, text or voice input, and query result output. The user inputs parameters and query text and clicks send, at which point the dialogue flow begins, invoking the AI ​​logic flow.

[0052] The AI ​​capability layer includes knowledge base retrieval capabilities, voice acquisition and processing capabilities, and natural language processing capabilities.

[0053] The business logic layer includes several modules: user query information extraction and output module, knowledge base retrieval and result output module, load index selection and matching module, speed index selection module, and selection result output module. First is the user query information extraction and output module. Since the user inputs query conditions in natural language, the "parameter extractor" node is needed. Leveraging the large model capabilities of LLM, the input information is processed using natural language. For ease of development and understanding, this "parameter extractor" node is named "query information extraction." Through condition judgment, it determines whether the query information is complete. If complete, it proceeds to the next workflow; otherwise, the process ends. Complete query information enters the rim diameter judgment node. This dialog flow has six branches from 17 inches to 22 inches. Each branch performs workflows for generating cross-section width and outer diameter, ultimately merging the six branches through an aggregator. Next, the initial query condition generation process begins: rim diameter + cross-section width retrieval parameter generation. Since the user query conditions are not singular but within a certain range, the query parameters are a series of combinations of rim diameter + cross-section width, saved as a list. The knowledge base retrieval and result output module iterates through the list of query parameters for rim diameter and cross-section width. Each set of query parameters in the list undergoes a knowledge base retrieval, yielding multiple results each time, inevitably leading to some overlap. Three loops—"cross-section width cleaning," "outer diameter cleaning," and "rim diameter cleaning"—are then used to remove parameters outside the user's query range. The initial results are output in list format. The load index selection and matching module first extracts the maximum value from the input front and rear axle loads, then divides the maximum axle load by 2 to obtain the wheel load corresponding to each wheel. This is because, generally, all four tires on a vehicle are identical, requiring the maximum load capacity to be met. The load index is then retrieved using a load index retrieval method to find the corresponding load index. Since there are two tire types—standard and reinforced—the tire load index matching process needs to differentiate between them. Their load capacities differ under the same load index. Therefore, a loop is used to evaluate each specification entering the loop, categorizing the results into three types: standard tires meeting the load requirements, reinforced tires meeting the load requirements, and tires not meeting the load requirements. Once matching is complete, the second round of filtering results can be output. The speed index selection module extracts the user-input speed and retrieves the corresponding speed symbol from the knowledge base. The speed selection result output function assigns the speed symbol to each specification in the second round of filtering results. The selection result output module includes standard tire specification output and reinforced tire specification output. A time recording tool is pre-called; therefore, the workflow time will be output when the results are displayed. See also... Figure 8 , Figure 8 This represents the output result graph.

[0054] Please see Figure 9 This application also provides a vehicle tire selection device that can implement the above-described method. The device includes: The acquisition module is used to retrieve parameter settings and query conditions in response to input commands. The parameter settings include the vehicle's maximum speed and the front and rear wheel loads of the vehicle. The query conditions include the tire's rim diameter, cross-sectional width, and outer diameter. The search module is used to extract query information based on query conditions and search the preset knowledge base for an initial set of tire specifications that meet the requirements. The knowledge base includes official tire and rim manuals, tire pressure and load index information, and speed and speed code correspondence information. The matching output module is used to perform load index matching and speed index matching based on the initial tire specification set and the preset knowledge base, and output the target tire specification set.

[0055] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0056] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0057] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0058] Please see Figure 10 , Figure 10 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 1001 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 1002 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 1002 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1002 and is called and executed by the processor 1001 using the methods described in the embodiments of this application. Input / output interface 1003 is used to implement information input and output; The communication interface 1004 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 1005 transmits information between various components of the device (e.g., processor 1001, memory 1002, input / output interface 1003, and communication interface 1004); The processor 1001, memory 1002, input / output interface 1003 and communication interface 1004 are connected to each other within the device via bus 1005.

[0059] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0060] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0061] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0062] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0063] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0064] This application provides a method, apparatus, electronic device, storage medium, and program product for selecting vehicle tires. This solution, in response to input commands, obtains parameter settings and query conditions. Parameter settings include the vehicle's maximum speed and front and rear wheel loads. Query conditions include the tire's rim diameter, section width, and outer diameter. Query information is extracted based on the query conditions, and a set of initial tire specifications that meets the requirements is searched in a preset knowledge base. The knowledge base includes official tire and rim manuals, information on the relationship between tire pressure and load index, and information on speed and speed code correspondence. Load index matching and speed index matching are performed based on the initial tire specification set and the preset knowledge base, outputting a target tire specification set. The system automatically searches the knowledge base for a set of initial tire specifications that meets the requirements based on the input parameter settings and query conditions, and automatically matches the initial tire specification set with load index and speed index, thereby improving the efficiency and accuracy of vehicle tire selection. In addition, this embodiment has the following advantages: updability, as the standard manual is updated regularly, the knowledge base of this embodiment can also be updated with the manual; easy promotion and knowledge transfer, as the original master-apprentice method requires a certain amount of time to teach the method of tire specification selection, and newcomers cannot quickly get started to take on projects, while this dialogue flow can be quickly transferred among engineers through sharing links and QR codes, and can be used directly.

[0065] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0066] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0067] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0068] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0069] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0070] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0071] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0072] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0073] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0074] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0075] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method of selecting a vehicle tire, characterized in that, The method comprises the following steps: In response to an input instruction, a parameter setting and a query condition are acquired; the parameter setting comprises a maximum vehicle speed and front and rear wheel loads of a whole vehicle, and the query condition comprises a rim diameter value, a section width value and an outer diameter value of a tire; According to the query condition, query information is extracted, and according to the query information, an initial tire specification set meeting requirements is searched in a preset knowledge base; the knowledge base comprises an official manual of a tire rim, information about a tire pressure and a load index, and information about a speed and a speed code correspondence; According to the initial tire specification set and the preset knowledge base, load index matching and speed index matching are performed, and a target tire specification set is output.

2. The method of claim 1, wherein, The response to the input instruction to acquire the parameter setting and the query condition comprises: In response to a text and / or voice input instruction, the parameter setting and the query condition are acquired.

3. The method of claim 1, wherein, The extraction of the query information according to the query condition comprises: According to the section width value, a section width query set is extracted; According to the outer diameter value, an outer diameter query set is extracted.

4. The method of claim 3, wherein, The searching of the initial tire specification set meeting requirements in the preset knowledge base according to the query information comprises: It is judged whether the query information is complete; If the query information is complete, the initial tire specification set meeting requirements is searched in the preset knowledge base according to the rim diameter, the section width query set and the outer diameter query set.

5. The method of claim 4, wherein, The method further comprises: According to the rim diameter, the section width and the outer diameter, the initial tire specification set is cleaned by removing duplicates.

6. The method of claim 1, wherein, According to the initial tire specification set and the preset knowledge base, load index matching and speed index matching are performed, and a target tire specification set is output, which comprises: According to the front and rear wheel loads of the whole vehicle, a bearing load is determined, and according to the bearing load and the preset knowledge base, a standard tire and a reinforced tire are selected from the initial tire specification set; According to the maximum vehicle speed and the preset knowledge base, a speed symbol is determined, and the maximum vehicle speed and the speed symbol are added to the corresponding standard tire and the reinforced tire to form and output a target tire specification set.

7. The method according to any one of claims 1 to 6, characterized in that, The method further comprises: In response to an input instruction, parameter input prompt information and / or option process information are displayed.

8. A selection device for vehicle tyres, characterized in that it comprises: The device comprises: An acquisition module is configured to acquire a parameter setting and a query condition in response to an input instruction; the parameter setting comprises a maximum vehicle speed and front and rear wheel loads of a whole vehicle, and the query condition comprises a rim diameter value, a section width value and an outer diameter value of a tire; A search module is configured to extract query information according to the query condition, and search an initial tire specification set meeting requirements in a preset knowledge base according to the query information; the knowledge base comprises an official manual of a tire rim, information about a tire pressure and a load index, and information about a speed and a speed code correspondence; A matching and output module is configured to perform load index matching and speed index matching according to the initial tire specification set and the preset knowledge base, and output a target tire specification set.

9. An electronic device, comprising: It comprises: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor is caused to implement the method recited in any one of claims 1-7.

10. A computer program product comprising a computer program, characterized in that, The computer program, which is executed by a processor, implements the method recited in any one of claims 1 to 7.

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