Intelligent Fault Prediction System and Method

Abstract

This invention provides a vehicle fault intelligent prediction system, comprising: an in-vehicle diagnostic system, a client-side device group to be diagnosed, a diagnostic management platform, a database, and an intelligent analysis engine. The in-vehicle diagnostic engine receives and parses diagnostic task scripts from the diagnostic management platform. The vehicle host interaction module, safety module, and diagnostic module execute the diagnostic tasks. The in-vehicle diagnostic engine transmits the diagnostic results to the diagnostic management platform, which then transmits the results to the database. The database stores the diagnostic results and transmits them to the intelligent analysis engine, which analyzes the diagnostic results and infers potential vehicle fault risks. Furthermore, this invention also provides a vehicle fault intelligent prediction method.

Description

Technical Field

[0001] This invention relates to a vehicle diagnostic technology, and more particularly to a system and method for predicting vehicle faults by collecting vehicle data and using AI technology. Prior Technology

[0002] With the continuous development of automotive technology, the number of electronic control units (ECUs) and sensors installed inside vehicles is increasing, enabling real-time monitoring of vehicle operation. However, current vehicle diagnostic systems primarily rely on owners or technicians obtaining diagnostic information through on-board diagnostics II (OBD-II), failing to proactively predict potential malfunctions. This process often requires professional personnel and is typically performed only after a vehicle malfunction has occurred, thus failing to effectively prevent serious mechanical failures or driving risks.

[0003] On the other hand, for automakers, developing a vehicle fault prediction system is extremely costly and expensive, requiring separate development for different fault types. Furthermore, while known faults are relatively easy to handle, unknown and complex faults often necessitate factory recalls or business trips, which are inefficient and costly. Moreover, using isolated diagnostic data makes it difficult to collect comprehensive vehicle information, and repair experience is unlikely to be compiled into a systematic and standardized diagnostic knowledge base.

[0004] Furthermore, for car owners, when a vehicle breaks down, they can only passively wait for repairs, unable to predict the time and location of the breakdown, nor can they clearly understand the fault information. At the same time, because it's impossible to predict which part of the vehicle will break down, auto service shops cannot prepare in advance, resulting in longer repair cycles and a poor user experience. Summary of the Invention

[0005] [The problem that the invention aims to solve] As can be seen from the aforementioned prior technologies, there is currently no effective vehicle fault prediction system and method. In order to better save development costs, improve user experience, reduce vehicle use risks and warranty costs, and make up for the problems of low maintenance efficiency and poor maintenance results caused by the shortage of professional maintenance personnel after the intelligentization of automobiles, it is necessary to provide a vehicle intelligent remote diagnosis and fault prediction system and method that combines diagnosis with vehicle networking and big data. This approach is also the future trend.

[0006] [Technical means to solve the problem] A vehicle fault intelligent prediction system includes: an in-vehicle diagnostic system installed on an electronic control element within a vehicle; the in-vehicle diagnostic system includes an in-vehicle diagnostic engine, a vehicle host interaction module, a safety module, a diagnostic module, a unified diagnostic service user terminal for high-level electronic control elements, and a unified diagnostic service user terminal for low-level electronic control elements; the in-vehicle diagnostic engine is connected to the vehicle host interaction module, the safety module, and the diagnostic module; a client-side diagnostic device group installed within the vehicle; the client-side diagnostic device group includes a unified diagnostic service server for high-level electronic control elements, a unified diagnostic service server for low-level electronic control elements, a plurality of high-level electronic control elements, and a plurality of low-level electronic control elements; the unified diagnostic service server for high-level electronic control elements is connected to the high-level electronic control elements, and the unified diagnostic service server for low-level electronic control elements is connected to the low-level electronic control elements; a diagnostic management platform connected to the in-vehicle diagnostic system; and a database connected to the diagnostic management platform, the database storing a plurality of diagnostic data records. The system includes an intelligent analysis engine connected to the database and the diagnostic management platform. The safety module and the diagnostic module of the in-vehicle diagnostic system interact, perform security authentication, and read / write operations on the high-level electronic control components and low-level electronic control components via the unified diagnostic service client and the unified diagnostic service server of the high-level electronic control components and the unified diagnostic service server of the low-level electronic control components of the client-side device group to be diagnosed. The in-vehicle diagnostic engine receives at least one diagnostic task script from the diagnostic management platform and parses the script. The vehicle host interaction module, the safety module, and the diagnostic module execute the diagnostic task. The in-vehicle diagnostic engine transmits a diagnostic result to the diagnostic management platform, which then transmits the result to the database. The database stores the diagnostic result and transmits it to the intelligent analysis engine, which analyzes the result and infers the potential fault risks of the vehicle.

[0007] Preferably, the diagnostic management platform further includes a vehicle management module, a remote diagnostic application module, a diagnostic task management module, and a user management module. The vehicle management module is used to create a list of vehicles to be diagnosed. The remote diagnostic application module is used to diagnose the client's device group to be diagnosed and report the potential fault risks of the vehicle to a user and / or an administrator. The diagnostic task management module is used to create the diagnostic task script and view multiple historical records of diagnostic results. The user management module is used to create multiple new users and grant them corresponding platform permissions.

[0008] Preferably, the intelligent analysis engine further includes an expert system and a fault code calculation module. The expert system includes a topology map of the vehicle's electronic control components. The fault code calculation module performs calculations and matching on the topology map of multiple sensors and / or electrical systems and / or electronic control components of the vehicle and derives the potential fault risks of the vehicle.

[0009] Preferably, the expert system further includes data identifiers and standardized fault codes for each of the high-level and low-level electronic control components.

[0010] Preferably, the security module and the diagnostic module communicate via a controller area network and through the unified diagnostic service client of the high-level electronic control components and the unified diagnostic service client of the low-level electronic control components with the unified diagnostic service server of the high-level electronic control components and the unified diagnostic service server of the low-level electronic control components of the client device group to be diagnosed, and perform data exchange, security authentication and read / write of the high-level electronic control components and the low-level electronic control components.

[0011] On the other hand, the present invention also provides a vehicle fault intelligent prediction method, comprising the following steps: a diagnostic management platform establishes diagnostic vehicle information and a corresponding diagnostic task script for a vehicle, wherein the vehicle includes a client-side diagnostic device group, the client-side diagnostic device group including a unified diagnostic service server for high-level electronic control components, a unified diagnostic service server for low-level electronic control components, a plurality of high-level electronic control components, and a plurality of low-level electronic control components, the unified diagnostic service server for the high-level electronic control components being connected to the high-level electronic control components, and the unified diagnostic service server for the low-level electronic control components being connected to the low-level electronic control components; an in-vehicle diagnostic engine of an in-vehicle diagnostic system receives and parses the diagnostic task script, wherein the in-vehicle diagnostic system is installed on an electronic control component in the vehicle, wherein the in-vehicle diagnostic system includes the in-vehicle diagnostic engine, a vehicle host interaction module, a safety module, a diagnostic module, and a high-level electronic control component. The vehicle diagnostic engine connects to the vehicle host interaction module, the safety module, and the diagnostic module. The vehicle host interaction module obtains the vehicle's status and information. The safety module and the diagnostic module exchange data, perform security authentication, and read / write operations on the high-level and low-level electronic control components (ENCs) via the ENCs and the client-side diagnostic device group's ENC servers. The vehicle diagnostic engine transmits a diagnostic result to the diagnostic management platform, which then transmits the result to a database. The database stores the diagnostic result and transmits it to an intelligent analysis engine, which analyzes the result and infers potential fault risks in the vehicle.

[0012] Preferably, in the intelligent vehicle fault prediction method of the present invention, the diagnostic management platform further includes a vehicle management module, a remote diagnostic application module, a diagnostic task management module, and a user management module. The vehicle management module is used to create a list of vehicles to be diagnosed. The remote diagnostic application module is used to diagnose the client device group to be diagnosed and report the potential fault risks of the vehicle to a user and / or an administrator. The diagnostic task management module is used to create the diagnostic task script and view multiple historical records of diagnostic results. The user management module is used to create multiple new users and grant corresponding platform permissions.

[0013] Preferably, in the intelligent vehicle fault prediction method of the present invention, the intelligent analysis engine further includes an expert system and a fault code calculation module. The expert system includes a vehicle electronic control component topology map, and the fault code calculation module performs calculations and matching on the topology map of a plurality of sensors and / or power systems and / or electronic control components of the vehicle and derives the potential fault risks of the vehicle.

[0014] Preferably, in the intelligent vehicle fault prediction method of the present invention, the expert system further includes data identifiers and standardized fault codes for each of the higher-order electronic control components and the lower-order electronic control components.

[0015] Preferably, in the step of the vehicle host interaction module obtaining the vehicle status and information, the vehicle host interaction module confirms the current vehicle status, such as vehicle speed, gear, or battery level, to avoid the impact of such high-level and low-level electronic control components on driving safety during diagnosis.

[0016] [Invention Benefits] The intelligent vehicle fault prediction system and method of the present invention can not only perform big data analysis based on historical diagnostic data and infer the current diagnostic results based on the stored historical diagnostic data to indicate where the vehicle is at high risk of fault, but also use an intelligent analysis engine to further calculate and match the vehicle's internal systems, allowing users and / or managers to obtain the potential fault risks of the vehicle in a short time and prevent faults in advance. Simple Explanation of the Diagram

[0017] Those skilled in the art will gain a better understanding of the various aspects of the present invention, as well as its specific features and advantages, upon reading the following detailed description with reference to the accompanying drawings, which include: Figure 1 is a schematic diagram of the structure of a vehicle fault intelligent prediction system according to an embodiment of the present invention. Figure 2 is a schematic diagram of the architecture of a vehicle fault intelligent prediction system according to an embodiment of the present invention. Figure 3 is a schematic diagram of the structure of a diagnostic management platform according to another embodiment of the present invention. Figure 4 is a schematic diagram of the structure of an intelligent analysis module according to another embodiment of the present invention. Figure 5 is a flowchart of a vehicle fault intelligent prediction method according to an embodiment of the present invention. Implementation

[0018] The following description, in conjunction with the accompanying drawings and component symbols, provides a more detailed account of the embodiments of the present invention, so that those skilled in the art can implement it after studying this specification.

[0019] Figure 1 is a schematic diagram illustrating the structure of a vehicle fault intelligent prediction system according to an embodiment of the present invention; Figure 2 is a schematic diagram illustrating the architecture of a vehicle fault intelligent prediction system according to an embodiment of the present invention. Referring to Figures 1 and 2, an embodiment of the present invention provides a vehicle fault intelligent prediction system, including an in-vehicle diagnostic system 10, a client-side diagnostic device group 20, a diagnostic management platform 30, a database 40, and an intelligent analysis engine 50. The in-vehicle diagnostic system 10 is installed on an electronic control element (not shown in the figures) inside a vehicle 60. More specifically, it may be installed on a higher-level electronic control element (not shown in the figures). The in-vehicle diagnostic system 10 includes an in-vehicle diagnostic engine 101, a vehicle host interaction module 103, a safety module 105, a diagnostic module 107, a unified diagnostic service client 109 for high-level electronic control components, and a unified diagnostic service client 111 for low-level electronic control components. The in-vehicle diagnostic engine 101 is connected to the vehicle host interaction module 103, the safety module 105, and the diagnostic module 107. The in-vehicle diagnostic system 10 can connect to the vehicle host interaction module 103, the safety module 105, and the diagnostic module 107 via an intranet. The diagnostic management platform 30 can be connected to the in-vehicle diagnostic system 10 via a network. The diagnostic management platform 30 can be an application installed on a computer device or a smart mobile device.

[0020] The client-side diagnostic device group 20 is installed inside the vehicle 60. The client-side diagnostic device group 20 includes a unified diagnostic service server 201 for high-level electronic control components, a unified diagnostic service server 203 for low-level electronic control components, a plurality of high-level electronic control components 205, and a plurality of low-level electronic control components 207. The unified diagnostic service server 201 for high-level electronic control components is connected to the high-level electronic control components 205, and the unified diagnostic service server 203 for low-level electronic control components is connected to the low-level electronic control components 207. The diagnostic management platform 30 is connected to the in-vehicle diagnostic system 10. The database 40 is connected to the diagnostic management platform 30 and stores a plurality of diagnostic data entries 401. The intelligent analysis engine 50 is connected to the database 40 and the diagnostic management platform 30.

[0021] In this system, the safety module 105 and diagnostic module 107 of the in-vehicle diagnostic system 10 interact with the unified diagnostic service client 109 for high-level electronic control components and the unified diagnostic service client 111 for low-level electronic control components via the unified diagnostic service server 201 for high-level electronic control components and the unified diagnostic service server 203 for low-level electronic control components of the client-side device group 20. This interaction allows for data exchange, security authentication, and reading / writing of the high-level and low-level electronic control components 205 and 207. Furthermore, in one embodiment of this invention, the safety module 105 and diagnostic module 107 can perform the aforementioned data exchange, security authentication, and reading / writing of electronic control components via a Controller Area Network (CAN). In other embodiments of this invention, other network connection methods can be used for operation.

[0022] On the other hand, the in-vehicle diagnostic engine 101 of the in-vehicle diagnostic system 10 receives at least one diagnostic task script (not shown in the figure) from the diagnostic management platform 30 and parses the diagnostic task script. The diagnostic task is then executed by the vehicle host interaction module 103, the safety module 105, and the diagnostic module 107. Furthermore, the in-vehicle diagnostic engine 101 transmits a diagnostic result to the diagnostic management platform 30, which then transmits the diagnostic result to the database 40. The database 40 stores the diagnostic result and transmits it to the intelligent analysis engine 50. Finally, the intelligent analysis engine 50 analyzes the diagnostic result and infers the potential fault risks of the vehicle 60. The diagnostic management platform 30 can receive the potential fault risk report generated by the intelligent analysis engine 50 and then report the potential fault risk report to the user and / or manager of the vehicle 60.

[0023] For example, if the diagnostic task script is an ECU transmission problem diagnostic script, the in-vehicle diagnostic engine 101 will parse it after receiving it, and the vehicle host interaction module 103, safety module 105, and diagnostic module 107 will execute the diagnostic task. The diagnostic task is to check whether each ECU has any faults or Diagnostic Trouble Codes (DTCs). After the check is completed, a diagnostic result will be generated. The intelligent analysis engine 50 will analyze the probability of a single ECU functional failure or a failure caused by a transmission problem in the future based on the diagnostic result. In other words, because the database 40 stores diagnostic data 401 related to fault problems, the intelligent analysis engine 50 can perform big data analysis based on the diagnostic data 401. Based on the stored past diagnostic data 401, it can predict that the current diagnostic result is that the probability of a single ECU functional failure or a failure caused by a transmission problem is high. This allows the users or managers of the vehicle 60 to know where the future failure risks of the vehicle 60 lie through the prediction results of the intelligent analysis engine 50.

[0024] In another example, if the diagnostic task script is a battery-dependent ECU troubleshooting diagnostic script, the in-vehicle diagnostic engine 101 will parse it upon receiving it, and the vehicle host interaction module 103, safety module 105, and diagnostic module 107 will execute the diagnostic task. The diagnostic task involves checking the battery-related ECUs in the vehicle 60 to confirm whether any errors or fault codes have occurred. After the check is completed, a diagnostic result will be generated. The intelligent analysis engine 50 will analyze the probability of future battery-dependent ECU-related faults based on this diagnostic result. Similarly, because the database 40 stores diagnostic data 401, the intelligent analysis engine 50 can perform big data analysis based on the diagnostic data 401 to predict whether the current diagnostic results have a probability of causing battery-dependent ECU-related faults. This allows the users or managers of the vehicle 60 to understand the future risk of battery-dependent ECU faults in the vehicle 60 through the prediction results of the intelligent analysis engine 50.

[0025] Figure 3 is a schematic diagram illustrating the structure of a diagnostic management platform according to another embodiment of the present invention. Referring to Figures 1 to 3, in another embodiment of the present invention, the diagnostic management platform 30 further includes a vehicle management module 301, a remote diagnostic application module 303, a diagnostic task management module 305, and a user management module 307. The vehicle management module 301 is used to create a list of vehicles to be diagnosed. The remote diagnostic application module 303 can be used to diagnose the client device group 20 and report the potential fault risks of the vehicle 60 to a user and / or an administrator. The diagnostic task management module 305 is used to create diagnostic task scripts and view multiple historical records of diagnostic results. The user management module 307 is used to create multiple new users and grant corresponding platform permissions. In other words, users and / or administrators can use the diagnostic management platform 30 to create diagnostic task scripts and input a list of vehicles to be tested, so as to predict the fault risks of each vehicle 60 at any time.

[0026] Figure 4 is a schematic diagram illustrating the structure of the intelligent analysis module according to another embodiment of the present invention. Referring to Figures 1 to 4, in another embodiment of the present invention, the intelligent analysis engine 50 further includes an expert system 501 and a fault code calculation module 503. The expert system 501 includes a topology diagram of the vehicle's electronic control components. The fault code calculation module 503 can perform calculations and matching on the topology diagrams of multiple sensors and / or electrical systems and / or electronic control components of the vehicle 60 and derive the potential fault risks of the vehicle. Therefore, the fault code calculation module 503 can cooperate with the expert system 501 to read the topology diagram of the vehicle's ECU and understand the serial connection method of all electronic control components, and determine whether the problem is a single fault in a certain ECU or a problem in all ECUs on the same route, based on the diagnostic results transmitted by the in-vehicle diagnostic engine 101.

[0027] Furthermore, the expert system 501 also provides each ECU with a Data Identifier (DID) and a Diagnostic Trouble Code (DTC), and converts raw data into a database file (DBC). Since each ECU has its own address, this address information can be used to identify which ECU is experiencing a fault. During the conversion process, the DBC can use the DID, DTC, and address to identify which ECU has a fault and its fault factors. In other words, the expert system 501 can intuitively predict future fault problems based on the information converted by the DBC.

[0028] On the other hand, the Electronic Stability Program (ESP) system in automobiles is designed to improve driving safety, especially under extreme driving conditions, by automatically adjusting the vehicle's traction and stability to prevent loss of control. However, ESP malfunctions are related to numerous sensor ECUs, the Anti-lock Braking System (ABS), the electrical system, and the ESP's own ECU. Therefore, detecting EPS malfunctions is usually quite complex and time-consuming, typically requiring vehicle technicians to use OBD-II diagnostic tools to read fault codes and perform further inspection and repair. After receiving these sensor and / or power system and / or ECU topology diagrams, the fault code calculation module 503 of the present invention will perform matching calculations and derive the possibility of potential ESP faults. It can also collect data from each ECU to clarify the cause, so that the originally complex detection can obtain results in a short time and even prevent faults in advance. The fault code calculation module 503 will match each fault factor through logical calculation. Each fault may have several corresponding causes. The fault with a higher matching ratio will be listed in the potential fault risk list. The cause of each fault will be stored in the database 40 for classification and storage.

[0029] In summary, the intelligent analysis engine 50 in the vehicle fault intelligent prediction system of the present invention can not only perform big data analysis based on diagnostic data 401 and infer the current diagnostic result based on the stored past diagnostic data 401 to indicate where the vehicle 60 has a high risk of fault, but also use the expert system 501 and the fault code calculation module 503 to further calculate and match the internal system of the vehicle 60, so that users or managers can obtain the potential fault risks of the vehicle 60 in a short time and prevent faults in advance.

[0030] Figure 5 is a flowchart illustrating a vehicle fault intelligent prediction method according to an embodiment of the present invention. Referring to Figures 1, 2, and 5, the vehicle fault intelligent prediction method according to an embodiment of the present invention includes steps S10-S50. Step S10 involves a diagnostic management platform 30 establishing diagnostic vehicle information for a vehicle 60 and a corresponding diagnostic task script for the vehicle 60. The diagnostic task script includes multiple tasks. The vehicle 60 includes a client-side diagnostic device group 20, which includes a unified diagnostic service server 201 for high-level electronic control components, a unified diagnostic service server 203 for low-level electronic control components, multiple high-level electronic control components 205, and multiple low-level electronic control components 207. The unified diagnostic service server 201 for high-level electronic control components is connected to the high-level electronic control components 205, and the unified diagnostic service server 203 for low-level electronic control components is connected to the low-level electronic control components 207. Furthermore, the diagnostic vehicle information may include the vehicle 60's license plate number, owner information, year of manufacture, historical maintenance data, etc.

[0031] Step S20 is as follows: An in-vehicle diagnostic engine 101 of an in-vehicle diagnostic system 10 receives and parses the diagnostic task script. The in-vehicle diagnostic system 10 is installed on an electronic control element in the vehicle 60, such as a high-level electronic control element. The in-vehicle diagnostic system 10 includes an in-vehicle diagnostic engine 101, a vehicle host interaction module 103, a safety module 105, a diagnostic module 107, a unified diagnostic service user terminal 109 for high-level electronic control elements, and a unified diagnostic service user terminal 111 for low-level electronic control elements. The in-vehicle diagnostic engine 101 is connected to the vehicle host interaction module 103, the safety module 105, and the diagnostic module 107.

[0032] Step S30 is: the vehicle host interaction module 103 obtains the vehicle status and information of the vehicle 60; in this step, the vehicle host interaction module 103 will confirm the current vehicle status of the vehicle 60, such as vehicle speed, gear or battery level, to avoid the high-level electronic control component 205 and the low-level electronic control component 207 affecting driving safety during diagnosis.

[0033] Step S40 is as follows: The security module 105 and the diagnostic module 107 use the unified diagnostic service client 109 for high-level electronic control components and the unified diagnostic service client 111 for low-level electronic control components to perform data exchange, security authentication, and read / write operations on the high-level electronic control components 205 and the low-level electronic control components 207 of the client device group 20 to be diagnosed, through the unified diagnostic service client 109 for high-level electronic control components and the unified diagnostic service client 111 for low-level electronic control components.

[0034] Step S50 is as follows: The in-vehicle diagnostic engine 101 transmits a diagnostic result to the diagnostic management platform 30. The diagnostic management platform 30 then transmits the diagnostic result to the database 40. The database 40 stores the diagnostic result and transmits it to an intelligent analysis engine 50. The intelligent analysis engine 50 analyzes the diagnostic result and infers the potential fault risks of the vehicle 60. The diagnostic management platform 30 can receive the potential fault risk report generated by the intelligent analysis engine 50 and then report the potential fault risk report to the user and / or manager of the vehicle 60. The intelligent analysis engine 50 can perform big data analysis based on the diagnostic data 401 stored in the database 40 to predict what related fault problems the current diagnostic results might cause in the vehicle 60. This allows the user or manager of the vehicle 60 to understand the level of risk of future faults in the vehicle 60 through the prediction results of the intelligent analysis engine 50.

[0035] Referring again to Figures 1 to 3, in the intelligent vehicle fault prediction method of the present invention, the diagnostic management platform 30 further includes a vehicle management module 301, a remote diagnostic application module 303, a diagnostic task management module 305, and a user management module 307. The vehicle management module 301 is used to create a list of vehicles to be diagnosed. The remote diagnostic application module 303 can be used to diagnose the client device group 20 and report the potential fault risks of the vehicle 60 to a user and / or an administrator. The diagnostic task management module 305 is used to create diagnostic task scripts and view multiple historical records of diagnostic results. The user management module 307 is used to create multiple new users and grant corresponding platform permissions. In other words, users and / or administrators can use the diagnostic management platform 30 to create diagnostic task scripts and input the list of vehicles to be tested, so as to predict the fault risks of each vehicle 60 at any time.

[0036] Referring again to Figures 1 to 4, in the intelligent vehicle fault prediction method of the present invention, the intelligent analysis engine 50 further includes an expert system 501 and a fault code calculation module 503. The expert system 501 includes a topology diagram of the vehicle's electronic control components. The fault code calculation module 503 can perform calculations and matching on the topology diagrams of multiple sensors and / or electrical systems and / or electronic control components of the vehicle 60, and derive the potential fault risks of the vehicle. Therefore, the fault code calculation module 503 can cooperate with the expert system 501 to read the topology diagram of the vehicle's ECUs and understand the connection method of all electronic control components, and determine, based on the diagnostic results transmitted by the in-vehicle diagnostic engine 101, whether the problem is a single fault in a particular ECU or a problem in all ECUs along the same route.

[0037] Furthermore, the expert system 501 includes the ECU's Data Identifier (DID) and Diagnostic Trouble Code (DTC), and can convert raw data into a database file (DBC). Since each ECU has its own address, this address can be used to identify which ECU is experiencing a fault. During the conversion process, the DBC can use the DID, DTC, and address to identify which ECU has a fault and its fault factors. In other words, the expert system 501 can intuitively predict future fault problems based on the information converted by the DBC.

[0038] As can be seen from the above description, this invention provides a vehicle fault intelligent prediction system and method. The advantages and effects of this invention are as follows: 1. Increased convenience: Vehicle owners can check vehicle status anytime, anywhere through the diagnostic management platform without needing to visit a service center. 2. Reduced repair time: Technicians can identify potential vehicle fault risks before diagnosing problems, shortening troubleshooting time. 3. Reduced repair costs: Predictive maintenance helps vehicle owners perform maintenance before problems become serious, thereby reducing repair costs. 4. Enhanced safety: Early fault detection helps improve vehicle safety and reduce accident risks. 5. Data analysis: By collecting and analyzing operational data, in-depth insights into driving behavior and vehicle performance can be obtained, helping to optimize usage. 6. Universality of expert systems: Expert systems are based on the experience rules of vehicle manufacturers' technicians. Since the basic principles of vehicle fault analysis have a main framework, the implementation of this invention's vehicle fault intelligent prediction system is not limited to the same vehicle type.

[0039] 10: In-vehicle diagnostic system 20: Client-side devices to be diagnosed 30: Diagnostic Management Platform 40: Database 50: Intelligent Analysis Engine 60: Vehicles 101: In-vehicle engine diagnostics 103: Vehicle Host Interaction Module 105: Security Module 107: Diagnostic Module 109: Unified Diagnostic Service for High-End Electronic Control Components (User End) 111: Unified Diagnostic Service for Low-Level Electronic Control Components (User End) 201: Unified Diagnostic Service Server for High-End Electronic Control Components 203: Unified Diagnostic Service Server for Low-Level Electronic Control Components 205: High-end electronic control components 207: Low-order electronic control components 301: Vehicle Management Module 303: Remote Diagnostic Application Module 305: Diagnostic Task Management Module 307: User Management Module 401: Diagnostic Data 501: Expert Systems 503: Fault Code Calculation Module S10-S50: Steps

Claims

1. A vehicle fault intelligent prediction system, comprising: An in-vehicle diagnostic system, installed on an electronic control element within a vehicle, includes an in-vehicle diagnostic engine, a vehicle host interaction module, a safety module, a diagnostic module, a unified diagnostic service client for high-level electronic control elements, and a unified diagnostic service client for low-level electronic control elements. The in-vehicle diagnostic engine is connected to the vehicle host interaction module, the safety module, and the diagnostic module. A client-side diagnostic device group, installed within the vehicle, includes a unified diagnostic service server for high-level electronic control elements, a unified diagnostic service server for low-level electronic control elements, a plurality of high-level electronic control elements, and a plurality of low-level electronic control elements. The unified diagnostic service server for the high-level electronic control elements is connected to the high-level electronic control elements, and the unified diagnostic service server for the low-level electronic control elements is connected to the low-level electronic control elements. A diagnostic management platform is connected to the in-vehicle diagnostic system. A database connected to the diagnostic management platform stores multiple diagnostic records; and an intelligent analysis engine connected to both the database and the diagnostic management platform. The safety module and the diagnostic module of the in-vehicle diagnostic system interact, perform security authentication, and read / write operations on the high-level electronic control components and low-level electronic control components via the unified diagnostic service client and the unified diagnostic service server of the high-level electronic control components and low-level electronic control components of the client-side device group to be diagnosed. The in-vehicle diagnostic engine of the in-vehicle diagnostic system receives and parses at least one diagnostic task script from the diagnostic management platform, and the diagnostic task is executed by the vehicle host interaction module, the safety module, and the diagnostic module. The in-vehicle diagnostic engine transmits a diagnostic result to the diagnostic management platform, which then transmits the diagnostic result to the database. The database stores the diagnostic result and transmits it to the intelligent analysis engine, which analyzes the diagnostic result and infers the potential risks of vehicle malfunctions.

2. The vehicle fault intelligent prediction system as described in claim 1, wherein, The diagnostic management platform further includes a vehicle management module, a remote diagnostic application module, a diagnostic task management module, and a user management module. The vehicle management module is used to create a list of vehicles to be diagnosed. The remote diagnostic application module is used to diagnose the client's equipment group to be diagnosed and report the potential risks of the vehicle's failure to a user and / or an administrator. The diagnostic task management module is used to create the diagnostic task script and view multiple historical records of diagnostic results. The user management module is used to create multiple new users and grant them corresponding platform permissions.

3. The vehicle fault intelligent prediction system as described in claim 1, wherein, The intelligent analysis engine further includes an expert system and a fault code calculation module. The expert system includes a topology map of the vehicle's electronic control components. The fault code calculation module performs calculations and matching on the topology map of multiple sensors and / or electrical systems and / or electronic control components of the vehicle and derives the potential fault risks of the vehicle.

4. The vehicle fault intelligent prediction system as described in claim 3, wherein, The expert system further includes data identifiers and standardized fault codes for each of the high-level and low-level electronic control components.

5. The vehicle fault intelligent prediction system as described in claim 1, wherein, The security module and the diagnostic module communicate via a controller area network and through the unified diagnostic service client of the high-level electronic control components and the unified diagnostic service client of the low-level electronic control components with the unified diagnostic service server of the high-level electronic control components and the unified diagnostic service server of the low-level electronic control components of the client device group to be diagnosed, and perform data exchange, security authentication and read / write of the high-level electronic control components and the low-level electronic control components.

6. A vehicle fault intelligent prediction method, comprising the following steps: A diagnostic management platform establishes diagnostic vehicle information for a vehicle and a corresponding diagnostic task script for that vehicle, wherein, The vehicle includes a client-side diagnostic device group, which includes a unified diagnostic service server for high-level electronic control components, a unified diagnostic service server for low-level electronic control components, a plurality of high-level electronic control components, and a plurality of low-level electronic control components. The unified diagnostic service server for the high-level electronic control components is connected to the high-level electronic control components, and the unified diagnostic service server for the low-level electronic control components is connected to the low-level electronic control components. An in-vehicle diagnostic engine of an in-vehicle diagnostic system receives and parses the diagnostic task script. The in-vehicle diagnostic system is installed on an electronic control component within the vehicle. The in-vehicle diagnostic system includes the in-vehicle diagnostic engine, a vehicle host interaction module, a safety module, a diagnostic module, a unified diagnostic service client for high-level electronic control components, and a unified diagnostic service client for low-level electronic control components. The in-vehicle diagnostic engine is connected to the vehicle host interaction module, the safety module, and the diagnostic module. The vehicle host interaction module obtains the vehicle's status and information. The safety module and the diagnostic module exchange data, perform security authentication, and read / write operations on the high-level electronic control components and the low-level electronic control components through the unified diagnostic service client and the unified diagnostic service server of the high-level electronic control components and the unified diagnostic service server of the low-level electronic control components of the client device group to be diagnosed. The in-vehicle diagnostic engine transmits a diagnostic result to the diagnostic management platform, which then transmits the diagnostic result to a database. The database stores the diagnostic result and transmits it to an intelligent analysis engine, which analyzes the diagnostic result and infers the potential fault risks of the vehicle.

7. The intelligent vehicle fault prediction method as described in claim 6, wherein, The diagnostic management platform further includes a vehicle management module, a remote diagnostic application module, a diagnostic task management module, and a user management module. The vehicle management module is used to create a list of vehicles to be diagnosed. The remote diagnostic application module is used to diagnose the client's equipment group to be diagnosed and report the potential risks of the vehicle's failure to a user and / or an administrator. The diagnostic task management module is used to create the diagnostic task script and view multiple historical records of diagnostic results. The user management module is used to create multiple new users and grant them corresponding platform permissions.

8. The intelligent vehicle fault prediction method as described in claim 6, wherein, The intelligent analysis engine further includes an expert system and a fault code calculation module. The expert system includes a topology map of the vehicle's electronic control components. The fault code calculation module performs calculations and matching on the topology map of multiple sensors and / or electrical systems and / or electronic control components of the vehicle and derives the potential fault risks of the vehicle.

9. The intelligent vehicle fault prediction method as described in claim 8, wherein, The expert system further includes data identifiers and standardized fault codes for each of the high-level and low-level electronic control components.

10. In the intelligent vehicle fault prediction method as described in claim 6, during the step of the vehicle host interaction module obtaining the vehicle status and information, the vehicle host interaction module confirms the current vehicle status to avoid the high-level electronic control components and the low-level electronic control components affecting driving safety during diagnosis.

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