Automobile affair intelligent management platform based on Internet

Abstract

The invention discloses an internet-based automobile transaction intelligent management platform, which relates to the technical field of automobile transactions, and is characterized in that an automobile data acquisition module of the system can accurately monitor the running state of an automobile in real time. By means of a vehicle-mounted sensor group, such as a vibration acceleration sensor, an oil pressure sensor and a tire pressure sensor, the system can comprehensively collect running data of an automobile, including parameters such as fine vibration Ven of an engine, lubricating oil pressure Poil and tread depth Dtire, and transmits the data to an internet platform for processing and storage through an automobile networking technology. Compared with the traditional mode that vehicle maintenance depends on manual inspection and subjective judgment, the system has the advantages that the accuracy and acquisition efficiency of data are greatly improved, and the running condition of the vehicle can be monitored in real time, so that timely early warning is realized, and potential problems are prevented from developing into serious faults. According to the comprehensive data acquisition and analysis mechanism, the control force of the vehicle owner on the vehicle condition is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of automobile affairs, and in particular to an Internet-based intelligent management platform for automobile affairs. Background Art

[0002] With the development of intelligent and internet-based automobile industry, automobile management platform has gradually become an important part of realizing intelligent vehicle management and optimization. Specifically in IoT applications, Internet of Vehicles technology uses on-board sensors and communication technology to collect and analyze vehicle operation data in real time, and provide intelligent maintenance, optimization suggestions and other services to car owners. In this context, intelligent maintenance and optimization suggestion functions can help car owners predict possible vehicle failures in advance and provide personalized maintenance suggestions in a data-driven way.

[0003] In the Chinese invention application with application number CN202111612313.9, a car maintenance reservation system is disclosed. The system is equipped with a client, a server, and an enterprise side, wherein the client is used for information input and output, the server is used for information storage and calculation, and the enterprise side is used for historical data collection and analysis. At the same time, the client and the server are interconnected through a communication network, and the server and the enterprise are interconnected through the network. On the basis of the original reservation function and queuing function, a paid queuing service and a paid plus service are added, which not only mobilizes the enthusiasm of workers, but also saves customers' time and improves customer satisfaction.

[0004] In combination with the prior art, the above application still has the following deficiencies: The above vehicle maintenance and management methods usually rely on a predetermined maintenance cycle or the subjective judgment of the owner, and both methods have certain shortcomings. For example, the traditional vehicle maintenance cycle is set based on a fixed mileage or time, and does not take into account the actual operating conditions of the vehicle. This "uniform standard" maintenance method often cannot accurately reflect the personalized needs of each vehicle, and is prone to premature or late maintenance, increasing unnecessary maintenance costs and potential safety hazards. The subjective judgment of the owner is also easily limited by the experience and knowledge level, resulting in missing the best maintenance time and increasing the risk of vehicle failure. Summary of the invention

[0005] In view of the deficiencies of the prior art, the present invention provides an Internet-based intelligent management platform for automobile affairs, which solves the problems mentioned in the background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: including a vehicle data acquisition module, a maintenance cycle prediction module, an intelligent maintenance reminder module, a fuel consumption and power efficiency analysis module and an optimization feedback generation module; The vehicle data acquisition module is connected to the Internet platform through the vehicle networking technology, and then collects the vehicle operation data in real time based on the vehicle-mounted sensor group installed on the vehicle, and transmits it to the Internet platform through the vehicle networking, performs data analysis and processing, obtains the vehicle operation data set, and builds a database on the Internet platform to write the vehicle operation data set into the database; The maintenance cycle prediction module is used to extract the automobile operation data set obtained in real time from the real-time database, calculate and output the engine health coefficient Keng and the oil pressure health coefficient Koil respectively, and construct a maintenance cycle prediction formula at the same time, input the obtained engine health coefficient Keng and the oil pressure health coefficient Koil into the maintenance cycle prediction formula, and calculate and output the next maintenance time Tnext; The intelligent maintenance reminder module is used to perform a preliminary comparison and evaluation between the preset maintenance threshold W and the output next maintenance time Tnext, and automatically trigger a maintenance reminder based on the preliminary comparison and evaluation result; The fuel consumption and power efficiency analysis module constructs a fuel consumption efficiency formula, then extracts the vehicle operation data set and inputs it into the fuel consumption efficiency formula to calculate and output the actual fuel efficiency Efuel; The optimization feedback generation module is used to construct a maintenance optimization algorithm formula, and the obtained engine health coefficient Keng, oil pressure health coefficient Koil and actual fuel efficiency Efuel are input into the maintenance optimization algorithm formula in combination with the vehicle operation data set, and a comprehensive optimization score Sopt is calculated and output, and a preset optimization threshold S is compared with the obtained comprehensive optimization score Sopt for secondary evaluation and generation of optimization suggestions.

[0007] Preferably, the automobile data acquisition module includes an Internet integrated acquisition unit, a data analysis and processing unit, and a data storage unit; The Internet integrated acquisition unit connects the automobile central control system to the Internet platform through the automobile networking technology, and then collects the automobile operation data in real time through the vehicle sensor group, transmits it to the automobile central control system, and uses the data packaging tool in the automobile central control system to package the automobile operation data into an automobile operation data packet and send it to the Internet platform; The vehicle-mounted sensor group includes a vehicle-mounted control system, a vibration acceleration sensor, an oil pressure sensor, an oil temperature sensor, an engine control system ECU, a torque sensor, a tire pressure sensor, an ABS sensor, a temperature sensor, a tire tread depth sensor and a humidity sensor; The vehicle operation data includes mileage Dth, average vehicle speed Vavg, historical average fuel consumption Fan, engine fine vibration Ven, tire pressure Pti, tire temperature Tti, tread depth Dtr, lubricating oil pressure Poi, lubricating oil temperature Toi, engine torque Ten, engine speed Rpm, throttle opening Thr and ambient humidity Hen; The engine subtle vibration Ven is collected through the vehicle-mounted vibration acceleration sensor. When the car is worn or fails, the amplitude and frequency of the vibration will change slightly. The vibration acceleration sensor is used to collect vibration data of the engine at different speeds and loads.

[0008] Preferably, the data analysis and processing unit is used to set up an automobile Internet platform, receive automobile operation data packets in real time, and use an unpacking tool to unpack the automobile operation data packets, extract automobile operation data, and then perform data cleaning on the automobile operation data. After the data cleaning process, the tire pressure Pti, tire temperature Tti, tread depth Dtr, lubricating oil pressure Poi, lubricating oil temperature Toi, engine torque Ten, engine speed Rpm and throttle opening Thr in the automobile operation data are analyzed to obtain oil pressure fluctuation Poil, engine torque fluctuation Teng and tire wear status Dtir; Then, the oil pressure fluctuation Poil, engine torque fluctuation Teng and tire wear status Dtir are integrated with the mileage Dth, vehicle average speed Vavg, historical average fuel consumption Fan, engine subtle vibration Ven and ambient humidity Hen to obtain the vehicle operation data set; The oil pressure fluctuation Poil is obtained by extracting the lubricating oil pressure Poi and the lubricating oil temperature Toi from the vehicle operation data for calculation and analysis. The specific calculation formula is: , where Poi avg Indicates the average lubricating oil pressure under normal operating conditions, determined through historical data; The engine torque fluctuation Teng is obtained by extracting the engine torque Ten, the engine speed Rpm and the throttle opening Thr from the vehicle operation data, and performing calculation and analysis. The specific calculation formula is: , where Tenavg represents the average engine torque under normal operating conditions, which is determined by historical data; The tire wear state Dtir is obtained by extracting the tire pressure Pti, tire temperature Tti and tread depth Dtr from the vehicle operation data, and performing calculation and analysis. The specific calculation formula is: , where Dini represents the initial tread depth of the tire, and the specific value is initially set by the actual tread depth of the tire; The data storage unit is used to construct a time series database, and by setting a write port and a write port, the vehicle operation data set obtained after data analysis and processing is written into the time series database through the write port, and the vehicle operation data set is timestamped and stored in the order of timestamps.

[0009] Preferably, the maintenance cycle prediction module includes an engine health analysis unit, an oil pressure health analysis unit and a maintenance prediction unit; The engine health analysis unit extracts the engine torque fluctuation Teng and engine subtle vibration Ven in the vehicle operation data set in real time through the write port of the time series database for calculation, outputs the engine health coefficient Keng, and analyzes the health status of the vehicle engine; The engine health coefficient Keng is calculated by the following algorithm formula: ; Where a1 and a2 represent the adjustment parameters of engine fine vibration and motor torque fluctuation, respectively, reflecting the impact of engine status on the maintenance cycle.

[0010] Preferably, the oil pressure health analysis unit is used to extract the oil pressure fluctuation Poil in the vehicle operation data set in real time through the write port of the time series database, calculate and output the oil pressure health coefficient Koil, and analyze the state of the lubrication system of the vehicle; The oil pressure health coefficient Koil is calculated and obtained by the following algorithm formula: ; Where b1 represents the adjustment coefficient of oil pressure fluctuation.

[0011] Preferably, the maintenance prediction unit is used to construct a maintenance cycle prediction formula, and then extract the mileage Dth and the average vehicle speed Vavg in the vehicle operation data set in real time through the write port of the time series database, and combine them with the obtained engine health coefficient Keng and oil pressure health coefficient Koil to input them into the maintenance cycle prediction formula to calculate and output the next maintenance time Tnext; The next maintenance time Tnext is calculated by the following maintenance cycle prediction formula; ; Where, T current Indicates the current time, D threshold Indicates the required maintenance mileage. The specific value is set by the user based on actual conditions.

[0012] Preferably, the intelligent maintenance reminder module performs a preliminary comparative evaluation based on the maintenance threshold W initially set by the user and the next maintenance time Tnext obtained to analyze the current automobile maintenance status. The specific evaluation contents are as follows; When the next maintenance time Tnext> the maintenance threshold W, it means that the current vehicle operation status is normal and no maintenance is required; When the next maintenance time Tnext ≤ the maintenance threshold W, it indicates that the current vehicle operation status is abnormal. At this time, a maintenance reminder is sent to the vehicle central control system through the Internet platform and the vehicle network, prompting the owner to perform vehicle maintenance.

[0013] Preferably, the fuel consumption and power efficiency analysis module constructs a fuel consumption efficiency formula, and then extracts the engine torque fluctuation Teng, engine fine vibration Ven and historical average fuel consumption Fan in the vehicle operation data set in real time through the write port of the time series database, inputs them into the fuel consumption efficiency formula to calculate and output the actual fuel efficiency Efuel, and analyzes the fuel consumption of the vehicle; The actual fuel efficiency Efuel is calculated and outputted by the following fuel consumption efficiency formula; ; In the formula, Indicates the adjustment coefficient of the engine's subtle vibrations. Indicates the adjustment factor of engine torque fluctuation.

[0014] Preferably, the optimization feedback generation module includes an automobile optimization analysis unit and an optimization evaluation unit; The automobile optimization analysis unit is used for the Internet platform to obtain the engine health coefficient Keng, oil pressure health coefficient Koil and actual fuel efficiency Efuel through the constructed maintenance optimization algorithm formula after the vehicle owner performs vehicle maintenance, and then extract the tire wear state Dtir through the write port of the time series database, and combine it with the input maintenance optimization algorithm formula to calculate and output the comprehensive optimization score Sopt; The comprehensive optimization score Sopt is calculated and output by the following maintenance optimization algorithm formula; ; Where Ftarget represents the target fuel consumption level, which is set based on the user. It represents fuel efficiency, W1, W2, W3 and W4 represent the preset weight values ​​of engine health coefficient Keng, oil pressure health coefficient Koil, fuel efficiency and tire wear status Dtir respectively, and W1+W2+W3+W4=1, and the specific values ​​are set by the user.

[0015] Preferably, the optimization evaluation unit presets the optimization threshold S through the vehicle manufacturer, and then performs a secondary comparative evaluation with the obtained comprehensive optimization score Sopt to analyze the state of the vehicle after maintenance. The specific evaluation content is as follows; When the comprehensive optimization score Sopt>optimization threshold S, it means that the maintenance effect of the car is abnormal. At this time, the Internet platform sends a prompt "Please check the engine, fuel efficiency is abnormal, please maintain" to the central control system of the car; When the comprehensive optimization score Sopt ≤ optimization threshold S, it means that the vehicle maintenance effect is normal, and the system continues to monitor the status of the vehicle without sending any prompts.

[0016] The present invention provides an Internet-based intelligent management platform for automobile affairs, which has the following beneficial effects: (1) The vehicle data acquisition module of the system can realize real-time and accurate monitoring of the vehicle's operating status. With the help of on-board sensor groups, such as vibration acceleration sensors, oil pressure sensors, tire pressure sensors, etc., the system can comprehensively collect the vehicle's operating data, including parameters such as engine micro-vibration Ven, lubricating oil pressure Poil, tread depth Dtire, etc., and transmit the data to the Internet platform for processing and storage through vehicle networking technology. Compared with traditional vehicle maintenance that relies on manual inspection and subjective judgment, the system greatly improves the accuracy and collection efficiency of data, ensuring that the vehicle's operating status can be monitored in real time, thereby achieving timely warning and preventing potential problems from developing into serious failures. This comprehensive data collection and analysis mechanism not only improves the owner's control over the vehicle's condition, but also provides a basis for subsequent intelligent maintenance and optimization suggestions.

[0017] (2) The system makes the vehicle maintenance cycle intelligent and personalized through the maintenance cycle prediction module and the intelligent maintenance reminder module. The system extracts the engine health coefficient Keng and the oil pressure health coefficient Koil from the vehicle operation data, and constructs a maintenance cycle prediction formula based on these coefficients to dynamically calculate the next maintenance time Tnext. Then, the intelligent maintenance reminder module compares the predicted maintenance time with the preset maintenance threshold W. When the next maintenance time Tnext is less than the threshold, the system automatically generates a maintenance reminder. This personalized maintenance prediction can not only avoid the waste of resources caused by traditional fixed-cycle maintenance methods, such as premature maintenance, but also avoid the risk of vehicle failure caused by late maintenance. At the same time, the system can timely remind the owner to perform necessary maintenance based on the real-time operating status of the vehicle to ensure that the vehicle operates in the best condition, thereby greatly improving the safety and operating reliability of the vehicle.

[0018] (3) The system further improves the vehicle's fuel economy and overall performance through the fuel consumption and power efficiency analysis module and the optimization feedback generation module. By constructing a fuel consumption efficiency formula and analyzing the vehicle's operating data, such as engine torque fluctuation Teng, engine fine vibration Veng, and historical average fuel consumption Fan, the system can dynamically calculate the vehicle's actual fuel efficiency Efuel. At the same time, the optimization feedback generation module inputs the vehicle's fuel efficiency, engine health factor Keng, oil pressure health factor Koil, and tire wear status Dtir into the maintenance optimization algorithm to generate a comprehensive optimization score Sopt, and compares and evaluates it with the preset optimization threshold S to provide personalized optimization suggestions. These suggestions may involve improving driving habits, optimizing vehicle components, etc. Through these optimization measures, car owners can not only improve the vehicle's fuel efficiency and reduce long-term use costs, but also improve the driving experience and reduce operational risks caused by reduced vehicle performance. At the same time, the improvement of fuel efficiency also helps reduce carbon emissions, which has positive significance for environmental protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 The present invention is a flowchart of an Internet-based intelligent management platform for automobile affairs. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0021] Example 1 See also Figure 1 The present invention provides an Internet-based intelligent management platform for automobile affairs. To achieve the above purpose, the present invention is implemented through the following technical solutions: including an automobile data acquisition module, a maintenance cycle prediction module, an intelligent maintenance reminder module, a fuel consumption and power efficiency analysis module and an optimization feedback generation module; The vehicle data acquisition module is connected to the Internet platform through the vehicle networking technology, and then collects the vehicle operation data in real time based on the vehicle-mounted sensor group installed on the vehicle, and transmits it to the Internet platform through the vehicle networking, performs data analysis and processing, obtains the vehicle operation data set, and builds a database on the Internet platform to write the vehicle operation data set into the database; The maintenance cycle prediction module is used to extract the real-time vehicle operation data set obtained in the real-time database, calculate and output the engine health coefficient Keng and the oil pressure health coefficient Koil respectively, and construct a maintenance cycle prediction formula. The obtained engine health coefficient Keng and oil pressure health coefficient Koil are input into the maintenance cycle prediction formula to calculate and output the next maintenance time Tnext; The intelligent maintenance reminder module is used to perform a preliminary comparison and evaluation between the preset maintenance threshold W and the output next maintenance time Tnext, and automatically trigger a maintenance reminder based on the preliminary comparison and evaluation results; The fuel consumption and power efficiency analysis module constructs a fuel consumption efficiency formula, then extracts the vehicle operation data set and inputs it into the fuel consumption efficiency formula to calculate and output the actual fuel efficiency Efuel; The optimization feedback generation module is used to construct the maintenance optimization algorithm formula. The obtained engine health coefficient Keng, oil pressure health coefficient Koil and actual fuel efficiency Efuel are combined with the vehicle operation data set and input into the maintenance optimization algorithm formula to calculate and output the comprehensive optimization score Sopt. The preset optimization threshold S is compared with the obtained comprehensive optimization score Sopt for secondary evaluation and generates optimization suggestions.

[0022] In this embodiment, the system uses the vehicle data acquisition module to use the vehicle sensors and vehicle networking technology to obtain core operating data including engine health, oil pressure, tire status, etc. in real time, and processes and stores them through the Internet platform to form a data foundation; the maintenance cycle prediction module dynamically calculates the engine health coefficient Keng and the oil pressure health coefficient Koil based on real-time data, and calculates the next maintenance time Tnext through the prediction formula to ensure timely maintenance; the intelligent maintenance reminder module automatically generates maintenance reminders by comparing the next maintenance time Tnext with the set maintenance threshold W, helping car owners to reasonably arrange vehicle maintenance plans; the fuel consumption and power efficiency analysis module constructs a fuel consumption efficiency formula to analyze and obtain the actual fuel efficiency Efuell, helping car owners to improve fuel economy; finally, the optimization feedback generation module comprehensively analyzes various data and generates optimization scores Sopt, providing personalized optimization suggestions to further improve vehicle performance. Compared with the traditional regular maintenance method, the system realizes personalized and precise maintenance, avoiding resource waste and safety hazards caused by premature or late maintenance. By monitoring the real-time status of the vehicle, the system not only reduces the probability of failure, but also improves the overall performance and fuel efficiency of the vehicle, thereby reducing operating costs. The system's technological advancement lies in the real-time and dynamic management of vehicles through big data and intelligent algorithms. Compared with previous maintenance methods that solely relied on time or mileage, it greatly improves the accuracy of maintenance and the driving experience of car owners.

[0023] Example 2 This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the automobile data acquisition module includes an Internet ,integrated acquisition unit, a data analysis and processing unit and a data storage unit; The Internet integrated acquisition unit connects the vehicle central control system to the Internet platform through the vehicle networking technology, and then collects the vehicle operation data in real time through the vehicle sensor group, transmits it to the vehicle central control system, and uses the data packaging tool in the vehicle central control system to package the vehicle operation data into a vehicle operation data packet and send it to the Internet platform; The vehicle sensor group includes the vehicle control system, vibration acceleration sensor, oil pressure sensor, oil temperature sensor, engine control system ECU, torque sensor, tire pressure sensor, ABS sensor, temperature sensor, tire tread depth sensor and humidity sensor; The vehicle operation data includes mileage Dth, average vehicle speed Vavg, historical average fuel consumption Fan, engine subtle vibration Ven, tire pressure Pti, tire temperature Tti, tread depth Dtr, lubricating oil pressure Poi, lubricating oil temperature Toi, engine torque Ten, engine speed Rpm, throttle opening Thr and ambient humidity Hen.

[0024] The engine's subtle vibration Ven is collected through the vehicle's vibration acceleration sensor. When the car is worn or fails, the amplitude and frequency of the vibration will change slightly. The vibration acceleration sensor collects the vibration data of the engine at different speeds and loads. The data analysis and processing unit is used to set up the automobile Internet platform, receive the automobile operation data packet in real time, and use the unpacking tool to unpack the automobile operation data packet, extract the automobile operation data, and then perform data cleaning on the automobile operation data. After the data cleaning process, the tire pressure Pti, tire temperature Tti, tread depth Dtr, lubricating oil pressure Poi, lubricating oil temperature Toi, engine torque Ten, engine speed Rpm and throttle opening Thr in the automobile operation data are analyzed to obtain the oil pressure fluctuation Poil, engine torque fluctuation Teng and tire wear status Dtir; Then, the oil pressure fluctuation Poil, engine torque fluctuation Teng and tire wear status Dtir are integrated with the mileage Dth, vehicle average speed Vavg, historical average fuel consumption Fan, engine subtle vibration Ven and ambient humidity Hen to obtain the vehicle operation data set; The oil pressure fluctuation Poil is obtained by extracting the lubricating oil pressure Poi and lubricating oil temperature Toi from the vehicle operation data for calculation and analysis. The specific calculation formula is: , where Poi avgIndicates the average lubricating oil pressure under normal operating conditions, determined through historical data; The engine torque fluctuation Teng is obtained by extracting the engine torque Ten, engine speed Rpm and throttle opening Thr from the vehicle operation data and performing calculation and analysis. The specific calculation formula is: , where Tenavg represents the average engine torque under normal operating conditions, which is determined by historical data; The tire wear state Dtir is obtained by extracting the tire pressure Pti, tire temperature Tti and tread depth Dtr from the vehicle operation data and performing calculation and analysis. The specific calculation formula is: , where Dini represents the initial tread depth of the tire, and the specific value is initially set by the actual tread depth of the tire; The data storage unit is used to build a time series database, and by setting a write port and a write port, the vehicle operation data set obtained after data analysis and processing is written into the time series database through the write port, and the vehicle operation data set is timestamped and stored in the order of timestamps.

[0025] In this embodiment, the Internet integrated acquisition unit collects various types of operating data of the car in real time through the vehicle-mounted sensor group, and transmits the data packet to the Internet platform through data encapsulation technology to ensure stable and efficient data transmission. Then, the data analysis and processing unit uses unpacking and data cleaning tools to process the collected data and analyze important indicators such as oil pressure fluctuation Poil, engine torque fluctuation Teng and tire wear status Dtir. These key indicators provide a basis for subsequent intelligent maintenance and optimization. Finally, the data storage unit constructs a time series database, stores the processed data in an orderly manner and adds a timestamp to ensure the traceability of historical data and the accuracy of analysis. The system realizes real-time and automated data collection and analysis, greatly reduces the need for manual inspection, and improves the accuracy and timeliness of detection. Through in-depth analysis of automobile operation data, the system can detect potential problems in vehicle operation in a timely manner and provide early warnings, avoiding vehicle failures caused by untimely maintenance or missing data. This improvement not only improves the safety and reliability of the vehicle, but also optimizes the vehicle's maintenance plan and cost control, effectively improving the owner's driving experience and vehicle management efficiency.

[0026] Example 3 This embodiment is explained in Example 2. Please refer to Figure 1 ,Specifically: the maintenance cycle prediction module includes an engine health analysis unit, an oil pressure health analysis unit and a ,maintenance prediction unit; The engine health analysis unit extracts the engine torque fluctuation Teng and engine subtle vibration Ven from the vehicle operation data set in real time through the write port of the time series database, calculates the engine health coefficient Keng, and analyzes the health status of the vehicle engine; The engine health factor Keng is calculated by the following algorithm formula; ; Where a1 and a2 represent the adjustment parameters of engine fine vibration and motor torque fluctuation, respectively, reflecting the impact of engine status on the maintenance cycle.

[0027] The oil pressure health analysis unit is used to extract the oil pressure fluctuation Poil in the vehicle operation data set in real time through the write port of the time series database, calculate and output the oil pressure health coefficient Koil, and analyze the status of the vehicle's lubrication system; The oil pressure health coefficient Koil is calculated by the following algorithm formula; ; Where b1 represents the adjustment coefficient of oil pressure fluctuation.

[0028] The maintenance prediction unit is used to construct a maintenance cycle prediction formula, and then extract the mileage Dth and vehicle average speed Vavg in the vehicle operation data set in real time through the write port of the time series database, and combine them with the obtained engine health coefficient Keng and oil pressure health coefficient Koil to input into the maintenance cycle prediction formula to calculate and output the next maintenance time Tnext; The next maintenance time Tnext is calculated using the following maintenance cycle prediction formula: ; Where, T current Indicates the current time, D threshold Indicates the required maintenance mileage. The specific value is set by the user based on actual conditions.

[0029] In this embodiment, the system realizes real-time monitoring of key vehicle systems and accurate maintenance cycle prediction through the coordinated work of the engine health analysis unit, the oil pressure health analysis unit and the maintenance prediction unit. The engine health analysis unit dynamically calculates the engine health coefficient Keng by analyzing the engine torque fluctuation Teng and the engine subtle vibration Veng data, and effectively evaluates the working status of the engine. The oil pressure health analysis unit calculates the oil pressure health coefficient Koil by extracting and analyzing the oil pressure fluctuation Poil, and accurately monitors the status of the lubrication system. The maintenance prediction unit combines the engine health coefficient Keng and the oil pressure health coefficient Koil with the mileage Dth and the average vehicle speed Vavg to calculate the next maintenance time Tnext, ensuring the personalization and timeliness of vehicle maintenance. The module dynamically calculates the maintenance cycle through real-time data, significantly improving the accuracy of the maintenance plan. Users no longer rely on preset time or mileage for maintenance, but make intelligent predictions based on the actual vehicle operating status, avoiding unnecessary costs and risks caused by premature or late maintenance. By warning of potential health problems of the vehicle in advance, the system effectively reduces the possibility of sudden vehicle failures, extends the service life of the vehicle, and improves the safety and operating efficiency of the vehicle.

[0030] Example 4 This embodiment is explained in Example 3, please refer to Figure 1 ,Specifically: the intelligent maintenance reminder module performs a preliminary comparative evaluation based on the user’s initial ,set maintenance threshold W, and the next maintenance time Tnext obtained, and analyzes the current ,car maintenance situation. The specific evaluation contents are as follows; When the next maintenance time Tnext> the maintenance threshold W, it means that the current vehicle operation status is normal and no maintenance is required; When the next maintenance time Tnext ≤ the maintenance threshold W, it indicates that the current vehicle operation status is abnormal. At this time, a maintenance reminder is sent to the vehicle central control system through the Internet platform and the vehicle network, prompting the owner to perform vehicle maintenance.

[0031] In this embodiment, the system realizes automatic judgment and real-time reminder of vehicle maintenance needs through the design of intelligent maintenance reminder module. Users can set the maintenance threshold W according to actual needs. When the next maintenance time Tnext calculated by the system is greater than the maintenance threshold W, it means that the vehicle is in normal operation and no maintenance is required; when the next maintenance time Tnext is less than or equal to the maintenance threshold W, the system determines that there may be a problem with the vehicle and sends a maintenance reminder to the central control system of the vehicle through the Internet platform and the vehicle network. This automated evaluation mechanism greatly improves the accuracy and timeliness of maintenance and avoids the owner's misjudgment of the timing of vehicle maintenance.

[0032] Example 5 This embodiment is explained in Example 4. Please refer to Figure 1 Specifically: the fuel consumption and power efficiency analysis module constructs a fuel consumption efficiency formula, and then extracts the engine torque fluctuation Teng, engine subtle vibration Ven and historical average fuel consumption Fan in the vehicle operation data set in real time through the write port of the time series database, and inputs them into the fuel consumption efficiency formula to calculate and output the actual fuel efficiency Efuel, so as to analyze the fuel consumption of the vehicle; The actual fuel efficiency Efuel is calculated and output by the following fuel consumption efficiency formula; ; In the formula, Indicates the adjustment coefficient of the engine's subtle vibrations. Indicates the adjustment factor of engine torque fluctuation.

[0033] In this embodiment, the system can accurately evaluate the fuel consumption of the vehicle based on real-time data through the fuel consumption and power efficiency analysis module. The module constructs a fuel consumption efficiency formula and extracts engine torque fluctuation Teng, engine fine vibration Veng and historical average fuel consumption Fav from the time series database in real time to dynamically calculate the actual fuel efficiency Efuel. This fuel efficiency analysis based on the actual vehicle operating status can help car owners understand the current vehicle's fuel consumption performance, find the difference between expected fuel consumption, and provide a basis for optimizing fuel economy. This module provides a more in-depth fuel efficiency evaluation by analyzing key engine data, no longer relying solely on a simple comparison of mileage and fuel volume. By monitoring the vehicle's fuel efficiency in real time, car owners can promptly identify potential power system problems or bad driving habits, and then make corresponding adjustments, optimize driving methods or arrange maintenance. This intelligent fuel analysis method not only improves fuel economy and reduces vehicle operating costs, but also reduces carbon emissions, conforms to environmental protection trends, and greatly improves the intelligence and environmental benefits of vehicle management.

[0034] Example 6 This embodiment is explained in Example 5. Please refer to Figure 1 ,Specifically: the optimization feedback generation module includes an automobile optimization analysis unit and an optimization evaluation unit; The automobile optimization analysis unit is used to calculate and output the comprehensive optimization score Sopt by combining the engine health coefficient Keng, oil pressure health coefficient Koil and actual fuel efficiency Efuel obtained by the Internet platform through the constructed maintenance optimization algorithm formula, and then extracting the tire wear status Dtir through the write port of the time series database, and inputting the maintenance optimization algorithm formula. The comprehensive optimization score Sopt is calculated and output by the following maintenance optimization algorithm formula; ; Where Ftarget represents the target fuel consumption level, which is set based on the user. It represents fuel efficiency, W1, W2, W3 and W4 represent the preset weight values ​​of engine health coefficient Keng, oil pressure health coefficient Koil, fuel efficiency and tire wear status Dtir respectively, and W1+W2+W3+W4=1, and the specific values ​​are set by the user.

[0035] The optimization evaluation unit presets the optimization threshold S through the vehicle manufacturer, and then performs a secondary comparative evaluation with the obtained comprehensive optimization score Sopt to analyze the vehicle status after maintenance. The specific evaluation contents are as follows; When the comprehensive optimization score Sopt>optimization threshold S, it means that the maintenance effect of the car is abnormal. At this time, the Internet platform sends a prompt "Please check the engine, fuel efficiency is abnormal, please maintain" to the central control system of the car; When the comprehensive optimization score Sopt ≤ optimization threshold S, it means that the vehicle maintenance effect is normal, and the system continues to monitor the status of the vehicle without sending any prompts.

[0036] In this embodiment, the system can perform in-depth evaluation and optimization analysis on the operating status of the vehicle after maintenance by optimizing the automobile optimization analysis unit and optimization evaluation unit in the feedback generation module. The automobile optimization analysis unit inputs key data such as engine health factor Keng, oil pressure health factor Koil, actual fuel efficiency Efuel and tire wear status Dtir into the optimization algorithm through the maintenance optimization algorithm to generate a comprehensive optimization score Sopt, which fully reflects the overall health status of the vehicle. The optimization evaluation unit compares and analyzes the comprehensive score with the preset optimization threshold S to determine whether the maintenance has achieved the expected effect. If the comprehensive optimization score Sopt is higher than the optimization threshold S, the system will remind the owner to perform further inspection and maintenance; if the comprehensive optimization score Sopt is lower than or equal to the optimization threshold S, it means that the maintenance has reached the ideal state, and the system continues to monitor the vehicle status without issuing a warning. This module provides more accurate and comprehensive feedback by comprehensively analyzing multiple key performance indicators. By evaluating the status of the vehicle after maintenance in real time, the owner can not only confirm the maintenance effect, but also find potential problems in time and make adjustments. This intelligent feedback mechanism avoids the risk of incomplete maintenance, ensures that the vehicle can maintain the best operating state after maintenance, and extends the service life of the vehicle. At the same time, the comprehensive optimization score helps car owners optimize fuel consumption and performance, reduce long-term use costs, and improve the overall efficiency of the vehicle.

[0037] While the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that many changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the invention.

Claims

1. An Internet-based intelligent management platform for automobile affairs, characterized by: It includes automobile data collection module, maintenance cycle prediction module, intelligent maintenance reminder module, fuel consumption and power efficiency analysis module and optimization feedback generation module; The vehicle data acquisition module is connected to the Internet platform through the vehicle networking technology, and then collects the vehicle operation data in real time based on the vehicle-mounted sensor group installed on the vehicle, and transmits it to the Internet platform through the vehicle networking technology, performs data analysis and processing, obtains the vehicle operation data set, and builds a database on the Internet platform to write the vehicle operation data set into the database; The maintenance cycle prediction module is used to extract the automobile operation data set obtained in real time from the real-time database, calculate and output the engine health coefficient Keng and the oil pressure health coefficient Koil respectively, and construct a maintenance cycle prediction formula at the same time, input the obtained engine health coefficient Keng and the oil pressure health coefficient Koil into the maintenance cycle prediction formula, and calculate and output the next maintenance time Tnext; The intelligent maintenance reminder module is used to perform a preliminary comparison and evaluation between the preset maintenance threshold W and the output next maintenance time Tnext, and automatically trigger a maintenance reminder based on the preliminary comparison and evaluation result; The fuel consumption and power efficiency analysis module constructs a fuel consumption efficiency formula, then extracts the vehicle operation data set and inputs it into the fuel consumption efficiency formula to calculate and output the actual fuel efficiency Efuel; The optimization feedback generation module is used to construct a maintenance optimization algorithm formula, and the obtained engine health coefficient Keng, oil pressure health coefficient Koil and actual fuel efficiency Efuel are input into the maintenance optimization algorithm formula in combination with the vehicle operation data set, and a comprehensive optimization score Sopt is calculated and output, and a preset optimization threshold S is compared with the obtained comprehensive optimization score Sopt for secondary evaluation and generation of optimization suggestions.

2. The Internet-based automobile affairs intelligent management platform according to claim 1 is characterized by: The automobile data acquisition module includes an Internet integrated acquisition unit, a data analysis and processing unit, and a data storage unit; The Internet integrated acquisition unit connects the automobile central control system to the Internet platform through the automobile networking technology, and then collects the automobile operation data in real time through the vehicle sensor group, transmits it to the automobile central control system, and uses the data packaging tool in the automobile central control system to package the automobile operation data into an automobile operation data packet and send it to the Internet platform; The vehicle-mounted sensor group includes a vehicle-mounted control system, a vibration acceleration sensor, an oil pressure sensor, an oil temperature sensor, an engine control system ECU, a torque sensor, a tire pressure sensor, an ABS sensor, a temperature sensor, a tire tread depth sensor and a humidity sensor; The vehicle operation data includes mileage Dth, vehicle average speed Vavg, historical average fuel consumption Fan, engine fine vibration Ven, tire pressure Pti, tire temperature Tti, tread depth Dtr, lubricating oil pressure Poi, lubricating oil temperature Toi, engine torque Ten, engine speed Rpm, throttle opening Thr and ambient humidity Hen.

3. The Internet-based automobile affairs intelligent management platform according to claim 2 is characterized by: The data analysis and processing unit is used to set up an automobile Internet platform, receive automobile operation data packets in real time, and use an unpacking tool to unpack the automobile operation data packets, extract automobile operation data, and then perform data cleaning on the automobile operation data. After the data cleaning process, the tire pressure Pti, tire temperature Tti, tread depth Dtr, lubricating oil pressure Poi, lubricating oil temperature Toi, engine torque Ten, engine speed Rpm and throttle opening Thr in the automobile operation data are analyzed to obtain oil pressure fluctuation Poil, engine torque fluctuation Teng and tire wear status Dtir; Then, the oil pressure fluctuation Poil, engine torque fluctuation Teng and tire wear status Dtir are integrated with the mileage Dth, vehicle average speed Vavg, historical average fuel consumption Fan, engine subtle vibration Ven and ambient humidity Hen to obtain the vehicle operation data set; The data storage unit is used to construct a time series database, and by setting a write port and a write port, the vehicle operation data set obtained after data analysis and processing is written into the time series database through the write port, and the vehicle operation data set is timestamped and stored in the order of timestamps.

4. The Internet-based automobile affairs intelligent management platform according to claim 3 is characterized by: The maintenance cycle prediction module includes an engine health analysis unit, an oil pressure health analysis unit and a maintenance prediction unit; The engine health analysis unit extracts the engine torque fluctuation Teng and engine subtle vibration Ven in the vehicle operation data set in real time through the write port of the time series database for calculation, outputs the engine health coefficient Keng, and analyzes the health status of the vehicle engine; The engine health coefficient Keng is calculated by the following algorithm formula: ； Where a1 and a2 represent the adjustment parameters of engine fine vibration and motor torque fluctuation, respectively, reflecting the impact of engine status on the maintenance cycle.

5. The Internet-based automobile affairs intelligent management platform according to claim 4 is characterized by: The oil pressure health analysis unit is used to extract the oil pressure fluctuation Poil in the vehicle operation data set in real time through the write port of the time series database, calculate and output the oil pressure health coefficient Koil, and analyze the state of the lubrication system of the vehicle; The oil pressure health coefficient Koil is calculated and obtained by the following algorithm formula: ； Where b1 represents the adjustment coefficient of oil pressure fluctuation.

6. The Internet-based automobile affairs intelligent management platform according to claim 4 is characterized by: The maintenance prediction unit is used to construct a maintenance cycle prediction formula, and then extract the mileage Dth and the average vehicle speed Vavg in the vehicle operation data set in real time through the write port of the time series database, and combine them with the obtained engine health coefficient Keng and oil pressure health coefficient Koil to input them into the maintenance cycle prediction formula to calculate and output the next maintenance time Tnext; The next maintenance time Tnext is calculated by the following maintenance cycle prediction formula; ； Where, T current Indicates the current time, D threshold Indicates the required maintenance mileage. The specific value is set by the user based on actual conditions.

7. The Internet-based automobile affairs intelligent management platform according to claim 4 is characterized by: The intelligent maintenance reminder module performs a preliminary comparative evaluation based on the user's initial maintenance threshold W and the next maintenance time Tnext, and analyzes the current vehicle maintenance status. The specific evaluation contents are as follows: When the next maintenance time Tnext> the maintenance threshold W, it means that the current vehicle operation status is normal and no maintenance is required; When the next maintenance time Tnext ≤ the maintenance threshold W, it indicates that the current vehicle operation status is abnormal. At this time, a maintenance reminder is sent to the vehicle central control system through the Internet platform and the vehicle network, prompting the owner to perform vehicle maintenance.

8. The Internet-based automobile affairs intelligent management platform according to claim 1 is characterized by: The fuel consumption and power efficiency analysis module constructs a fuel consumption efficiency formula, and then extracts the engine torque fluctuation Teng, engine subtle vibration Ven and historical average fuel consumption Fan in the vehicle operation data set in real time through the write port of the time series database, inputs them into the fuel consumption efficiency formula to calculate and output the actual fuel efficiency Efuel, and analyzes the fuel consumption of the vehicle; The actual fuel efficiency Efuel is calculated and outputted by the following fuel consumption efficiency formula; ； In the formula, Indicates the adjustment coefficient of the engine's subtle vibrations. Indicates the adjustment factor of engine torque fluctuation.

9. The Internet-based automobile affairs intelligent management platform according to claim 1 is characterized by: The optimization feedback generation module includes an automobile optimization analysis unit and an optimization evaluation unit; The automobile optimization analysis unit is used for the Internet platform to obtain the engine health coefficient Keng, oil pressure health coefficient Koil and actual fuel efficiency Efuel through the constructed maintenance optimization algorithm formula after the vehicle owner performs vehicle maintenance, and then extract the tire wear state Dtir through the write port of the time series database, and combine it with the input maintenance optimization algorithm formula to calculate and output the comprehensive optimization score Sopt; The comprehensive optimization score Sopt is calculated and output by the following maintenance optimization algorithm formula; ； Where Ftarget represents the target fuel consumption level, which is set based on the user. It represents fuel efficiency, W1, W2, W3 and W4 represent the preset weight values ​​of engine health coefficient Keng, oil pressure health coefficient Koil, fuel efficiency and tire wear status Dtir respectively, and W1+W2+W3+W4=1, and the specific values ​​are set by the user.

10. The Internet-based automobile affairs intelligent management platform according to claim 9, characterized in that: The optimization evaluation unit presets the optimization threshold S through the vehicle manufacturer, and then performs a secondary comparative evaluation with the obtained comprehensive optimization score Sopt to analyze the state of the vehicle after maintenance. The specific evaluation content is as follows; When the comprehensive optimization score Sopt>optimization threshold S, it means that the maintenance effect of the car is abnormal. At this time, the Internet platform sends a prompt "Please check the engine, fuel efficiency is abnormal, please maintain" to the central control system of the car; When the comprehensive optimization score Sopt ≤ optimization threshold S, it means that the vehicle maintenance effect is normal, and the system continues to monitor the status of the vehicle without sending any prompts.

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