Method and device for monitoring vehicle electrical parts of motorcade on same route and server

Abstract

The invention provides a method and device for monitoring vehicle electrical parts of a motorcade on the same route and a server, and relates to the technical field of big data experience systems.The method comprises the steps that electrical part parameter information sent by all new energy commercial vehicles in the motorcade on the same driving route is obtained in real time; data analysis processing is carried out on the parameter information through a preset generation type intelligent model, an electrical part analysis table corresponding to each new energy commercial vehicle is determined, and the electrical part analysis table comprises a main body fault analysis table and a part dimension analysis table; and performing difference analysis processing on the main body fault analysis table and the part dimension analysis table corresponding to each new energy commercial vehicle, determining an electrical part monitoring result, and sending the electrical part monitoring result to the new energy commercial vehicles with abnormal electrical parts in the vehicle team. According to the invention, the influence on the vehicle safety caused by the abnormity of the electrical parts of the new energy commercial vehicle can be obviously reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of big data experience systems, and in particular to a method, device and server for monitoring vehicle electrical components of a fleet on the same route. Background Art

[0002] At present, the new energy commercial vehicle industry is developing rapidly and is widely used. However, due to the characteristics of commercial vehicles with a large passenger capacity and long working hours (commercial vehicles are often the same fleet running along the same route for a long time, such as the same bus route or the same express route fleet), for new energy commercial vehicles, safety inspection of electrical components is particularly important. Relevant technologies have proposed that the diagnosis method of traditional vehicle components is to conduct separate inspections on the operating parameters of each component through regular maintenance. However, due to the increase in electrical equipment in new energy vehicles, the equipment presents a complex system of mutual interrelationships. Therefore, when any equipment fails or compatibility problems occur between equipment, other equipment may also fail to operate normally, making it difficult for inspectors to accurately find the cause of the vehicle failure, which leads to a large amount of time and manpower costs for monitoring electrical components of new energy commercial vehicles, and poor detection accuracy. Summary of the invention

[0003] In view of this, the purpose of the present invention is to provide a method, device and server for monitoring vehicle electrical components of a fleet on the same route, which can significantly reduce the impact of abnormal electrical components of new energy commercial vehicles on vehicle safety.

[0004] In a first aspect, an embodiment of the present invention provides a method for monitoring vehicle electrical components of a fleet on the same route, the method comprising: acquiring in real time electrical component parameter information sent by each new energy commercial vehicle in the fleet on the same driving route, wherein the electrical component parameter information is the parameters corresponding to each electrical component to be detected in the new energy commercial vehicle, and the number and type of electrical components to be detected corresponding to each new energy commercial vehicle in the fleet on the same driving route are the same; performing data analysis and processing on the parameter information through a preset generative intelligent model to determine an electrical component analysis table corresponding to each new energy commercial vehicle, wherein the electrical component analysis table includes: a main fault analysis table and a component dimension analysis table; performing difference analysis and processing on the main fault analysis table and the component dimension analysis table corresponding to each new energy commercial vehicle to determine the electrical component monitoring result, and sending the electrical component monitoring result to the new energy commercial vehicle with abnormal electrical components in the fleet.

[0005] In one embodiment, the parameter information is subjected to data analysis and processing by a preset generative intelligent model to determine the steps of an electrical component analysis table corresponding to each new energy commercial vehicle, including: extracting a set of main detection parameters corresponding to each monitoring type from the electrical component parameter information, and using the main detection parameter set to determine the main fault analysis table, wherein the main detection parameter set includes: system time, cumulative power consumption, cumulative power consumption, one-way power consumption, one-way power consumption, working time, downtime, temperature, component failure information, vehicle mileage and vehicle speed.

[0006] In one embodiment, the method includes: establishing a component dimension analysis table by respectively utilizing the main detection parameters contained in each electrical component in the electrical component parameter information, wherein the electrical components include: a drive motor, an air conditioner, an air pump and a steering pump of the brake system.

[0007] In one embodiment, after performing data analysis and processing on parameter information through a preset generative intelligent model to determine the electrical component analysis table corresponding to each new energy commercial vehicle, it includes: obtaining the collection time of the parameter information, and recording the collection time of the parameter information within a preset time interval to generate a data trend analysis table of the time dimension, wherein the data trend analysis table is used to indicate the impact of the data change trend on the vehicle.

[0008] In one embodiment, after the step of generating a data trend analysis table of the time dimension, it includes: performing data analysis and processing on the data trend analysis table, the main fault analysis table and the component dimension analysis table through a preset generative artificial intelligence model to determine the trend analysis results; sending the trend analysis results to a preset large language analysis model to generate usage recommendations for new energy commercial vehicles to improve unreasonable energy consumption during vehicle use.

[0009] In one embodiment, after performing difference analysis on the main fault analysis table and component dimension analysis table corresponding to each new energy commercial vehicle and determining the electrical component monitoring results, it includes: sending the electrical component monitoring results to a preset database for statistical analysis, and generating standardized abnormality evaluation indicators based on the statistical analysis results, so as to use the standardized abnormality evaluation indicators to assist in the evaluation of the next batch of vehicle electrical component monitoring.

[0010] In one embodiment, the step of using standardized abnormality evaluation indicators to assist in the evaluation of the next batch of vehicle electrical component monitoring includes: if the electrical component parameter information of any electrical component is monitored and overlaps with the standardized abnormality evaluation indicator, the electrical component is directly determined to be abnormal.

[0011] In one embodiment, after performing difference analysis on the main fault analysis table and the component dimension analysis table corresponding to each new energy commercial vehicle to determine the electrical component monitoring results, it also includes: setting key monitoring labels for electrical components of the same type as the electrical components with abnormal electrical component monitoring results in each new energy commercial vehicle, as well as new energy commercial vehicles with abnormal electrical components.

[0012] In one embodiment, after the step of setting key monitoring tags for electrical components whose monitoring results are abnormal and new energy commercial vehicles with abnormal electrical components, it includes: increasing the monitoring frequency of electrical components and new energy commercial vehicles containing key monitoring tags to achieve key investigation and processing of electrical component monitoring.

[0013] In a second aspect, an embodiment of the present invention further provides a vehicle electrical component monitoring device for a fleet on the same route, the device comprising: a data acquisition module, for acquiring in real time electrical component parameter information sent by each new energy commercial vehicle in the fleet on the same driving route, wherein the electrical component parameter information is the parameters corresponding to each electrical component to be detected in the new energy commercial vehicle, and the number and type of electrical components to be detected corresponding to each new energy commercial vehicle in the fleet on the same driving route are the same; a data statistics module, for performing data analysis and processing on the parameter information through a preset generative intelligent model, and determining an electrical component analysis table corresponding to each new energy commercial vehicle, wherein the electrical component analysis table comprises: a main fault analysis table and a component dimension analysis table; a difference analysis module, for performing difference analysis and processing on the main fault analysis table and the component dimension analysis table corresponding to each new energy commercial vehicle, determining the electrical component monitoring results, and sending the electrical component monitoring results to the new energy commercial vehicles with abnormal electrical components in the fleet.

[0014] In a third aspect, an embodiment of the present invention further provides a server, comprising a processor and a memory, wherein the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement any one of the methods provided in the first aspect.

[0015] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement any one of the methods provided in the first aspect.

[0016] The embodiments of the present invention bring the following beneficial effects: The embodiments of the present invention provide a method, device and server for monitoring electrical components of vehicles in a fleet on the same route. After acquiring the electrical component parameter information sent by each new energy commercial vehicle in the fleet on the same route in real time, the method performs data analysis and processing on the parameter information through a preset generative intelligent model to determine the electrical component analysis table corresponding to each new energy commercial vehicle. Then, a difference analysis and processing is performed on the main fault analysis table and the component dimension analysis table corresponding to each new energy commercial vehicle to determine the electrical component monitoring results, and the electrical component monitoring results are sent to the new energy commercial vehicles with abnormal electrical components in the fleet. The embodiments of the present invention can significantly improve vehicle safety by performing horizontal reliability evaluation and risk prediction on electrical parts on new energy commercial vehicles in the fleet on the same route.

[0017] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0018] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 A schematic flow chart of a method for monitoring vehicle electrical components of a fleet on the same route provided by an embodiment of the present invention; Figure 2 A schematic diagram of a data collection method provided by an embodiment of the present invention; Figure 3 A schematic diagram of data flow provided by an embodiment of the present invention; Figure 4 A schematic diagram of the structure of a vehicle electrical component monitoring device for a fleet on the same route provided by an embodiment of the present invention; Figure 5 A schematic diagram of the structure of a server provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described in combination with the embodiments below. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] At present, the new energy commercial vehicle industry is developing rapidly and is widely used. However, due to the characteristics of commercial vehicles with a large passenger capacity and a long working time (commercial vehicles are often driven by the same fleet along the same route for a long time, such as the same bus route or the same express route fleet), for new energy commercial vehicles, the safety inspection of electrical components is particularly important. The relevant technology proposes that the diagnosis method of components of traditional vehicles is to perform separate inspections on the operating parameters of each component through regular maintenance. However, due to the increase in electrical equipment in new energy vehicles, the equipment presents a complex system that is interrelated. Therefore, when any device fails or there is a compatibility problem between the equipment, other equipment may not be able to operate normally, making it difficult for inspection personnel to accurately find the cause of the vehicle failure, which leads to a large amount of time and manpower cost consumed in the monitoring of electrical components of new energy commercial vehicles, and poor detection accuracy. Based on this, the vehicle electrical component monitoring method for the same route fleet provided by the present invention can use big data and communication technology to collect real-time information of each electrical component of the new energy commercial vehicle and perform background analysis to realize the prediction and analysis of the vehicle's failure conditions and potential risk components, provide valuable maintenance suggestions to customers, and provide reference analysis reports for development.

[0023] See also Figure 1 The flowchart of a method for monitoring vehicle electrical components of a fleet on the same route is shown, and the method mainly includes the following steps S102 to S106: Step S102, real-time acquisition of electrical component parameter information sent by each new energy commercial vehicle in the fleet on the same driving route, wherein the electrical component parameter information is the parameters corresponding to each electrical component to be detected in the new energy commercial vehicle, and the number and type of electrical components to be detected corresponding to each new energy commercial vehicle in the fleet on the same driving route are the same. In one embodiment, see Figure 2A schematic diagram of a data collection method is shown. Taking the collection of total power consumption as an example, the total power consumption is calculated based on the current detection of each component. The power consumption of each component can be calculated in combination with the total voltage of the power battery. Each component is then transmitted to the vehicle data collection controller (for example, T-BOX). The data can be sent to the instrument for the driver's reference while being transmitted to the big data background. In addition, the collection time can be recorded at the same time when the data is collected, and the vehicle data can be transmitted to the big data background in real time by using communication means such as 5G. The transmission protocol can adopt the national standard protocol for remote monitoring or a private protocol.

[0024] Step S104, through the preset generative intelligent model, the parameter information is subjected to data analysis and processing to determine the electrical component analysis table corresponding to each new energy commercial vehicle, wherein the electrical component analysis table includes: a main fault analysis table and a component dimension analysis table. Each new energy commercial vehicle in the same fleet has its corresponding main fault analysis table and component dimension analysis table, so that the main fault analysis table and component dimension analysis table of each vehicle can be used to compare the conditions of the same component of different vehicles.

[0025] In one embodiment, see Figure 3 A schematic diagram of data flow is shown, which can extract the main detection parameter sets corresponding to each monitoring type from the electrical component parameter information, and use the main detection parameter sets to determine the main fault analysis table. In addition, the main detection parameters contained in each electrical component in the electrical component parameter information are used to establish a component dimension analysis table, where the main detection parameter set includes: system time, cumulative power consumption, cumulative power consumption, one-way power consumption, one-way power consumption, working time, downtime, temperature, component failure information, vehicle mileage and vehicle speed, and the electrical components include: drive motor, air conditioning, brake system air pump and steering pump.

[0026] In another embodiment, the specific data analysis process takes fault power consumption and data trends as an example. If there is a real-time fault, it will be directly analyzed and displayed; the efficiency of the components can be compared and analyzed based on the power consumption of each component to provide a basis for the efficiency evaluation of the components. In addition, based on the horizontal comparison of the power consumption of the components, predictive inspections or attention can be carried out on components with large differences (the range of differences can be determined as needed); when analyzing data trends, time is used as a dimension to analyze and set the impact of data change trends on the vehicle, such as the time when the air conditioner is turned on, the proportion of time that the braking and steering systems work, the working temperature of components, etc., so as to make predictions and suggestions on driving behavior and the reliability of vehicle components.

[0027] Step S106, perform difference analysis processing on the main fault analysis table and component dimension analysis table corresponding to each new energy commercial vehicle, determine the electrical component monitoring results, and send the electrical component monitoring results to the new energy commercial vehicles with abnormal electrical components in the fleet. In other words, big data analysis can be performed on vehicle data from the multi-vehicle horizontal dimension or the single-vehicle time dimension. After statistical analysis using mathematical analysis methods such as difference analysis and variance analysis, difference components or vehicles are mined, and such components or vehicles are analyzed or maintained in key areas. After that, data analysis and statistics are performed on the current fault conditions as an evaluation indicator of component reliability. Finally, based on the relevant data used by some customers, vehicle usage suggestions can be provided to customers (such as air conditioning usage time when parking, braking system working time, etc.), thereby improving unreasonable energy consumption during vehicle use.

[0028] In a real-time manner, after determining the monitoring results of electrical components, the embodiment of the present invention further provides an implementation method for performing auxiliary evaluation and key monitoring based on the monitoring results of electrical components, as shown in (1) to (2) below: (1) The electrical component monitoring results are sent to a preset database for statistical analysis, and standardized abnormality evaluation indicators are generated based on the statistical analysis results. The standardized abnormality evaluation indicators are used to assist in the evaluation of the next batch of vehicle electrical component monitoring. If the electrical component parameter information of any electrical component is monitored and overlaps with the standardized abnormality evaluation indicators, the electrical component is directly determined to be abnormal.

[0029] (2) For each new energy commercial vehicle, set key monitoring tags for electrical components of the same type as those with abnormal electrical component monitoring results, as well as for new energy commercial vehicles with abnormal electrical components. By increasing the monitoring frequency of electrical components and new energy commercial vehicles with key monitoring tags, the monitoring of electrical components can be focused on investigation and treatment.

[0030] The above-mentioned vehicle electrical component monitoring method for the same-route fleet provided by the embodiment of the present invention can collect real-time parameters of the vehicle (such as: failure status of each component, power consumption, temperature, proportion of working time, etc.), perform big data analysis in the background, and refer to other vehicles under the same operating conditions to perform parameter analysis on batches of vehicles, provide basic vehicle operating conditions, potential risk components and current fault conditions, etc., not only provide current fault problem points, but also provide predictive evaluation of potential problems existing in the current vehicle based on the big data analysis results.

[0031] In addition, the embodiment of the present invention also provides an implementation method for generating vehicle electrical component usage recommendations, see (A) to (C) below for details: (A) Obtaining the collection time of parameter information, and generating a data trend analysis table of the time dimension by recording the collection time of the parameter information within a preset time interval, wherein the data trend analysis table is used to indicate the impact of the data change trend on the vehicle.

[0032] (B) Through the preset generative artificial intelligence model, data analysis and processing are performed on the data trend analysis table, the main fault analysis table and the component dimension analysis table to determine the trend analysis results. In other words, the analysis performed through the main fault analysis table and the component dimension analysis table is a comparison between different electronic components of each vehicle to determine abnormal components; the analysis performed through the data trend analysis table combined with the main fault analysis table and the component dimension analysis table is based on the trend of the curve to make predictions and suggestions on the reliability of components, thereby changing the traditional real-time alarm method of automobile faults into a predictive and forward-looking method, which is of great significance to improving customer service satisfaction and technical improvements.

[0033] (C) Send the trend analysis results to the preset large language analysis model to generate usage recommendations for new energy commercial vehicles to improve unreasonable energy consumption during vehicle use. The large language analysis model can use large-scale data sets to train the model so that it can understand and generate natural language text, thereby learning and simulating the complex laws of human language through a layered neural network structure, and achieving text generation capabilities close to human levels.

[0034] In summary, the present invention can evaluate the reliability of electrical components of commercial vehicles and provide a feasible and effective solution based on the evaluation. It can also predict the functions of risky components, thereby providing an effective solution for further improving the service methods of vehicle manufacturers and improving customer satisfaction, and to a certain extent reducing the impact of component problems on vehicle safety and customer operations.

[0035] Regarding the vehicle electrical component monitoring method for a fleet on the same route provided in the above-mentioned embodiment, an embodiment of the present invention provides a vehicle electrical component monitoring device for a fleet on the same route, see Figure 4 The structure diagram of a vehicle electrical component monitoring device for a fleet on the same route is shown, and the device includes the following parts: The data acquisition module 402 acquires in real time the electrical component parameter information sent by each new energy commercial vehicle in the fleet on the same driving route, wherein the electrical component parameter information is the parameters corresponding to each electrical component to be detected in the new energy commercial vehicle, and the number and type of electrical components to be detected corresponding to each new energy commercial vehicle in the fleet on the same driving route are the same; The data statistics module 404 performs data analysis and processing on the parameter information through a preset generative intelligent model to determine the electrical component analysis table corresponding to each new energy commercial vehicle, wherein the electrical component analysis table includes: a main body fault analysis table and a component dimension analysis table; The difference analysis module 406 performs difference analysis on the main fault analysis table and the component dimension analysis table corresponding to each new energy commercial vehicle, determines the electrical component monitoring results, and sends the electrical component monitoring results to the new energy commercial vehicles with abnormal electrical components in the fleet.

[0036] The vehicle electrical component monitoring device for the above-mentioned same-route fleet provided in the embodiment of the present application can significantly reduce the impact of abnormalities in electrical components of new energy commercial vehicles on vehicle safety.

[0037] In one embodiment, when performing data analysis and processing on parameter information through a preset generative intelligent model to determine the electrical component analysis table corresponding to each new energy commercial vehicle, the above-mentioned data statistics module 404 is also used to: extract the main detection parameter sets corresponding to each monitoring type from the electrical component parameter information, and use the main detection parameter set to determine the main fault analysis table, wherein the main detection parameter set includes: system time, cumulative power consumption, cumulative power consumption, one-way power consumption, one-way power consumption, working time, downtime, temperature, component failure information, vehicle mileage and vehicle speed.

[0038] In one embodiment, the data statistics module 404 is also used to establish a component dimension analysis table using the main detection parameters contained in each electrical component in the electrical component parameter information, wherein the electrical components include: drive motor, air conditioner, brake system air pump and steering pump.

[0039] In one embodiment, after performing data analysis and processing on parameter information through a preset generative intelligent model to determine the electrical component analysis table corresponding to each new energy commercial vehicle, the above-mentioned data statistics module 404 is also used to: obtain the collection time of the parameter information, and generate a data trend analysis table of the time dimension by recording the collection time of the parameter information within a preset time interval, wherein the data trend analysis table is used to indicate the impact of the data change trend on the vehicle.

[0040] In one embodiment, after the step of generating a data trend analysis table of the time dimension, the data statistics module 404 is also used to: perform data analysis and processing on the data trend analysis table, the main fault analysis table and the component dimension analysis table through a preset generative artificial intelligence model to determine the trend analysis results; send the trend analysis results to a preset large language analysis model to generate usage recommendations for new energy commercial vehicles to improve unreasonable energy consumption during vehicle use.

[0041] In one embodiment, after performing difference analysis on the main fault analysis table and component dimension analysis table corresponding to each new energy commercial vehicle to determine the electrical component monitoring results, the above-mentioned difference analysis module 406 is also used to: send the electrical component monitoring results to a preset database for statistical analysis, and generate standardized abnormality evaluation indicators based on the statistical analysis results, so as to use the standardized abnormality evaluation indicators to assist in the evaluation of the next batch of vehicle electrical component monitoring.

[0042] In one embodiment, when performing the step of using standardized abnormality evaluation indicators to assist in the evaluation of the next batch of vehicle electrical component monitoring, the difference analysis module 406 is also used to: if the electrical component parameter information of any electrical component is monitored and overlaps with the standardized abnormality evaluation indicator, the electrical component is directly determined to be abnormal.

[0043] In one embodiment, after performing difference analysis processing on the main fault analysis table and the component dimension analysis table corresponding to each new energy commercial vehicle to determine the electrical component monitoring results, the above-mentioned difference analysis module 406 is also used to set key monitoring labels for electrical components of the same type as the electrical components with abnormal electrical component monitoring results in each new energy commercial vehicle, as well as new energy commercial vehicles with abnormal electrical components.

[0044] In one embodiment, after performing the step of setting key monitoring labels for electrical components with abnormal monitoring results and new energy commercial vehicles with abnormal electrical components, the above-mentioned difference analysis module 406 is also used to: achieve key investigation and processing of electrical component monitoring by increasing the monitoring frequency of electrical components and new energy commercial vehicles containing key monitoring labels.

[0045] The device provided in the embodiment of the present invention has the same implementation principle and technical effects as those of the aforementioned method embodiment. For the sake of brief description, for matters not mentioned in the device embodiment, reference may be made to the corresponding contents in the aforementioned method embodiment.

[0046] An embodiment of the present invention provides a server. Specifically, the server includes a processor and a storage device. The storage device stores a computer program, and when the computer program is executed by the processor, it executes the method described in any one of the above-mentioned embodiments.

[0047] Figure 5 A structural diagram of a server provided in an embodiment of the present invention, the server 100 includes: a processor 50, a memory 51, a bus 52 and a communication interface 53, wherein the processor 50, the communication interface 53 and the memory 51 are connected via the bus 52; the processor 50 is used to execute an executable module stored in the memory 51, such as a computer program.

[0048] The memory 51 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk memory. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 53 (which may be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. may be used.

[0049] The bus 52 may be an ISA bus, a PCI bus, or an EISA bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0050] Among them, the memory 51 is used to store programs, and the processor 50 executes the program after receiving the execution instruction. The method executed by the device for flow process definition disclosed in any embodiment of the above-mentioned embodiment of the present invention can be applied to the processor 50 or implemented by the processor 50.

[0051] The processor 50 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 50. The above processor 50 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present invention can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in the embodiments of the present invention can be directly embodied as a hardware decoding processor to be executed, or can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 51, and the processor 50 reads the information in the memory 51 and completes the steps of the above method in combination with its hardware.

[0052] The computer program product of the readable storage medium provided in the embodiment of the present invention includes a computer-readable storage medium storing program code, and the instructions included in the program code can be used to execute the methods described in the previous method embodiments. The specific implementation can be referred to the previous method embodiments, which will not be repeated here.

[0053] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0054] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for monitoring electrical components of vehicles in a fleet on the same route, characterized in that: The method comprises: Real-time acquisition of electrical component parameter information sent by each new energy commercial vehicle in the fleet on the same driving route, wherein the electrical component parameter information is the parameters corresponding to each electrical component to be detected in the new energy commercial vehicle, and the number and type of the electrical components to be detected corresponding to each new energy commercial vehicle in the fleet on the same driving route are the same; By using a preset generative intelligent model, the parameter information is subjected to data analysis and processing to determine an electrical component analysis table corresponding to each new energy commercial vehicle, wherein the electrical component analysis table includes: a main body fault analysis table and a component dimension analysis table; A difference analysis process is performed on the main fault analysis table and the component dimension analysis table corresponding to each new energy commercial vehicle to determine the electrical component monitoring results, and the electrical component monitoring results are sent to the new energy commercial vehicles in the fleet that have abnormal electrical components.

2. The method for monitoring vehicle electrical components of a fleet on the same route according to claim 1, characterized in that: The step of performing data analysis and processing on the parameter information by using a preset generative intelligent model to determine an electrical component analysis table corresponding to each new energy commercial vehicle includes: From the electrical component parameter information, the main detection parameter sets corresponding to each monitoring type are extracted respectively, and the main fault analysis table is determined using the main detection parameter sets, wherein the main detection parameter sets include: system time, cumulative power consumption, cumulative power consumption, one-way power consumption, one-way power consumption, working time, downtime, temperature, component failure information, vehicle mileage and vehicle speed.

3. The method for monitoring vehicle electrical components of a fleet on the same route according to claim 2, characterized in that: The method comprises: The component dimension analysis table is established by respectively utilizing the main detection parameters included in each electrical component in the electrical component parameter information, wherein the electrical components include: a drive motor, an air conditioner, an air pump and a steering pump of a brake system.

4. The method for monitoring vehicle electrical components of a fleet on the same route according to claim 1, characterized in that: After the step of performing data analysis and processing on the parameter information by using the preset generative intelligent model to determine the electrical component analysis table corresponding to each new energy commercial vehicle, the method includes: The collection time of the parameter information is obtained, and a data trend analysis table of the time dimension is generated by recording the collection time of the parameter information within a preset time interval, wherein the data trend analysis table is used to indicate the impact of the data change trend on the vehicle.

5. The method for monitoring vehicle electrical components of a fleet on the same route according to claim 4, characterized in that: After the step of generating the data trend analysis table of the time dimension, the following steps are included: By using a preset generative artificial intelligence model, data analysis and processing are performed on the data trend analysis table, the main body failure analysis table, and the component dimension analysis table to determine a trend analysis result; The trend analysis results are sent to a preset large language analysis model to generate usage suggestions for new energy commercial vehicles to improve unreasonable energy consumption during vehicle use.

6. The method for monitoring vehicle electrical components of a fleet on the same route according to claim 1, characterized in that: After performing difference analysis on the main fault analysis table and the component dimension analysis table corresponding to each new energy commercial vehicle to determine the monitoring result of the electrical components, the method includes: The electrical component monitoring results are sent to a preset database for statistical analysis, and standardized abnormality evaluation indicators are generated based on the statistical analysis results, so as to use the standardized abnormality evaluation indicators to assist in the evaluation of the next batch of vehicle electrical component monitoring.

7. The method for monitoring vehicle electrical components of a fleet on the same route according to claim 6, characterized in that: The step of using the standardized abnormality evaluation index to assist in the evaluation of the next batch of vehicle electrical components monitoring includes: If the electrical component parameter information of any electrical component is monitored and overlaps with the standardized abnormality evaluation index, the electrical component is directly determined to be abnormal.

8. The method for monitoring vehicle electrical components of a fleet on the same route according to claim 1, characterized in that: After performing difference analysis on the main fault analysis table and the component dimension analysis table corresponding to each new energy commercial vehicle to determine the monitoring results of the electrical components, the method further includes: For each new energy commercial vehicle, a key monitoring label is set for electrical components of the same type as the electrical components with abnormal monitoring results, and for new energy commercial vehicles with abnormal electrical components.

9. The method for monitoring vehicle electrical components of a fleet on the same route according to claim 8, characterized in that: After the step of setting a key monitoring label for the electrical components with abnormal monitoring results and the new energy commercial vehicles with abnormal electrical components, the method includes: By increasing the monitoring frequency of the electrical components and the new energy commercial vehicles containing key monitoring tags, key inspection and processing of electrical components monitoring can be achieved.

10. A vehicle electrical component monitoring device for a fleet of vehicles on the same route, characterized in that: The device comprises: A data acquisition module is used to acquire in real time the electrical component parameter information sent by each new energy commercial vehicle in a fleet of vehicles on the same driving route, wherein the electrical component parameter information is the parameters corresponding to each electrical component to be detected in the new energy commercial vehicle, and the number and type of the electrical components to be detected corresponding to each new energy commercial vehicle in the fleet of vehicles on the same driving route are the same; The data statistics module performs data analysis and processing on the parameter information through a preset generative intelligent model to determine an electrical component analysis table corresponding to each new energy commercial vehicle, wherein the electrical component analysis table includes: a main body fault analysis table and a component dimension analysis table; The difference analysis module performs difference analysis on the main fault analysis table and the component dimension analysis table corresponding to each new energy commercial vehicle, determines the electrical component monitoring results, and sends the electrical component monitoring results to the new energy commercial vehicles with abnormal electrical components in the fleet.

11. A server, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the method according to any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement the method according to any one of claims 1 to 9.

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