New energy automobile power supply fault diagnosis system based on 5G communication

Abstract

The invention discloses a new energy automobile power supply fault diagnosis system based on 5G communication, relates to the technical field of fault diagnosis, and aims to solve the technical problems that a current system is relatively low in power supply data acquisition and transmission efficiency, low in timeliness and accuracy, easy to cause data leakage and has a safety risk. Comprising a data interface, a 5G communication network, a cloud server and an intelligent mobile terminal which are connected in sequence. According to the system, the high-speed and low-delay characteristics of 5G communication are fully utilized, the data interface accurately collects the power data of the new energy automobile, and the time interval of data transmission is greatly shortened through a 5G network. According to the new energy automobile power supply fault diagnosis system based on 5G communication, rapid acquisition and transmission of power supply data are realized, timeliness and accuracy of the data are ensured, a solid foundation is provided for subsequent fault diagnosis, and the whole diagnosis process is more efficient and reliable.

Description

Technical Field

[0001] The present invention relates to the technical field of fault diagnosis, and more specifically, to a new energy vehicle power supply fault diagnosis system based on 5G communication. Background Technique

[0002] With the booming development of the new energy vehicle industry, the stability and reliability of its power supply system have become key issues. Traditional fault diagnosis methods are gradually difficult to meet the requirements in terms of real-time performance, accuracy of data collection, and diagnosis efficiency. At the same time, the rise of 5G communication technology has brought new opportunities for change in the automotive field. Its characteristics such as high speed, low latency, and high reliability enable new energy vehicles to achieve more efficient data transmission and interaction. Against this background, a new energy vehicle power supply fault diagnosis system based on 5G communication has emerged, aiming to accurately and quickly collect new energy vehicle power supply data by utilizing the advantages of 5G technology.

[0003] However, although the data interface of the existing new energy vehicle power supply fault diagnosis system based on 5G communication has relatively high acquisition accuracy, in complex working conditions, such as extreme temperature, high humidity environment, or severe vehicle vibration, the stability of data may be affected, resulting in deviation or loss of the collected data. Moreover, although the 5G network has high speed and low latency, in some remote areas with weak signal coverage, data transmission may be blocked, resulting in intermittent interruption, affecting the timeliness of fault diagnosis. At the same time, the fault diagnosis algorithm of intelligent mobile terminals may have limitations. For some new and complex power supply faults, the built-in data analysis model may not be able to accurately identify and diagnose, and the algorithm needs to be continuously updated and optimized to adapt to the rapid development of new energy vehicle technology. Therefore, the security of the entire system needs to be improved. During the data transmission and storage process, it faces the risks of being hacked and data leakage, which may bring potential security hazards to users. In view of this, we propose a new energy vehicle power supply fault diagnosis system based on 5G communication. Summary of the Invention

[0004] The purpose of the present invention is to overcome the deficiencies of the prior art, adapt to the actual needs, and provide a new energy vehicle power supply fault diagnosis system based on 5G communication to solve the technical problems of low efficiency of power supply data collection and transmission, low timeliness and accuracy of the current system, and easy data leakage with security risks.

[0005] To solve the above technical problems, the present invention provides the following technical solution: A new energy vehicle power supply fault diagnosis system based on 5G communication, including a data interface, a 5G communication network, a cloud server, and an intelligent mobile terminal that are connected in sequence;

[0006] The data interface is used to collect the power supply data of new energy vehicles;

[0007] The 5G communication network and cloud server are used to connect a data interface and an intelligent mobile terminal through the 5G communication network and cloud server;

[0008] The intelligent mobile terminal is used to display power data and perform power fault prediction and diagnosis based on the power data.

[0009] Preferably, the data interface is an OBD interface;

[0010] The power data includes vehicle status data, motor current, rotor position of the motor, and instantaneous value of each-phase current of the motor;

[0011] The vehicle status data includes: vehicle speed, air-conditioning status, brake pedal signal, and gear signal;

[0012] The power data displayed by the intelligent mobile terminal includes: vehicle status data, motor current, rotor position of the motor, and instantaneous value of each-phase current of the motor;

[0013] The intelligent mobile terminal is further used to display charging history data and maintenance history records.

[0014] Preferably, the intelligent mobile terminal is further used to perform power fault prediction and diagnosis based on the power data, including: comparing the current charging data with the historical data to determine whether the current charging data has changed: if it has changed, directly compare the current charging data with the historical data, if it has not changed, calculate the maximum matching coefficient between the current charging data and the historical data, and determine whether there is a fault in the current charging data according to the maximum matching coefficient.

[0015] Preferably, the comparison between the current charging data and the historical data includes: judging one by one the vehicle speed, air-conditioning status, brake pedal signal, and gear signal, and when any data is inconsistent, it is determined that the current charging data has changed;

[0016] The direct comparison between the current charging data and the historical data includes: respectively matching the motor current, rotor position of the motor, and instantaneous value of each-phase current of the motor in the current charging data with the corresponding motor current, rotor position of the motor, and instantaneous value of each-phase current of the motor in the historical data one by one. If all match successfully, it is determined that the current charging data is normal, otherwise, it is determined that the current charging data is abnormal.

[0017] Preferably, the maximum matching coefficient is calculated by the following method: calculate the maximum matching coefficient through the following formula:

[0018]

[0019] where λ is the maximum matching coefficient, n is the number of acquisitions, i is a certain acquired data, Ii is the current charging current, I hist is the historical charging current, θ i is the current rotor position, θ hist is the historical rotor position, α is the current matching coefficient, β is the rotor position matching coefficient, ΔI is the minimum tolerance between I i and I hist and Δθ is the minimum tolerance between θ i and θ hist between.

[0020] Preferably, the maximum matching coefficient and the fault are matched through the following functional relationship, and the functional relationship is obtained by the following method: obtaining a plurality of different types of fault data, wherein the vehicle state data, the power supply current, the rotor position of the motor, and the instantaneous value of the current of each phase of the motor in any two types of fault data are all different, and in any two types of fault data, at least one of the vehicle state data, the power supply current, the rotor position of the motor, and the instantaneous value of the current of each phase of the motor that appears is different; calculating the maximum matching coefficient for any two types of fault data obtained above according to the method of calculating the maximum matching coefficient above, and then obtaining the maximum matching coefficient of the two types of fault data; obtaining multiple groups of maximum matching coefficients of pairwise different faults; establishing multiple one-to-one correspondences between the maximum matching coefficient and the fault; establishing a matching function between the maximum matching coefficient and the fault according to the multiple one-to-one correspondences between the maximum matching coefficient and the fault established above.

[0021] Preferably, when the matching coefficient is the largest and is 1, it is determined that the current data is in the historical normal data. Otherwise, the fault that appears in the current charging data is found according to the matching function, and a fault is selected from the search results according to the matching function for output.

[0022] Preferably, when the intelligent mobile terminal is not in the standby state, real-time matching is performed according to the current charging data, the fault with the largest matching coefficient is found, and the possibility of the occurrence of the above fault is calculated, and the search result is output; when the intelligent mobile terminal is in the standby state, a preset interval time is set, and when it is not in the standby state, real-time matching is performed according to the current charging data, the fault with the largest matching coefficient is found, and the possibility of the occurrence of the above fault is calculated, and the search result is output.

[0023] Preferably, the possibility of the occurrence of the above fault is calculated by the following method: comparing the current charging data found with the charging condition data in the historical data, and then judging the current charging condition data, and then calculating the matching coefficient of the current charging condition data according to the current charging condition data, and finally obtaining the sum of the matching coefficient of the current charging data and the matching coefficient of the current charging condition data and the found matching coefficient, so as to obtain the possibility of the occurrence of the search result.

[0024] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0025] 1. The system of the present invention makes full use of the high speed and low latency characteristics of 5G communication. The data interface accurately collects the power data of new energy vehicles at an extremely high frequency, covering key information such as vehicle status data and motor current, and the collection accuracy reaches the leading level in the industry. Through the 5G network, these data can be instantly transmitted to the cloud server, greatly shortening the data transmission time interval. The present invention designs a power fault diagnosis system for new energy vehicles based on 5G communication, realizing the rapid collection and transmission of power data, ensuring the timeliness and accuracy of the data, providing a solid foundation for subsequent fault diagnosis, and making the entire diagnosis process more efficient and reliable.

[0026] 2. The data interface of the present invention, as the front end of data collection, is responsible for collecting various power data and quickly uploading them to the cloud server through the 5G communication network for storage and preliminary analysis and processing. The cloud server uses its powerful computing power to integrate and classify the data, and the intelligent mobile terminal obtains the data from the cloud server. It can not only intuitively display the power data, but also predict and diagnose power faults by virtue of the advanced algorithms built in. The present invention constructs a complete fault diagnosis process through the sequential connection of the data interface, 5G communication network, cloud server and intelligent mobile terminal. The entire process is closely connected, and each link cooperates with each other, completing the process from data collection to fault diagnosis in one go, forming an efficient and accurate fault diagnosis closed loop.

[0027] 3. The intelligent mobile terminal of the present invention has a simple and intuitive user interface, which can clearly display power data such as vehicle status data and motor current, allowing users to understand the working status of the vehicle power at any time. At the same time, the built-in intelligent diagnosis module adopts advanced data analysis technology to compare the current charging data with historical data in multiple dimensions. Whether through direct comparison or calculating the maximum matching coefficient, it can quickly determine whether the current charging data is normal. Once an abnormality is found, it immediately searches for faults according to the matching function and accurately calculates the possibility of the fault occurring. The present invention uses the intelligent mobile terminal to display power data and perform real-time prediction and diagnosis of power faults based on the data, providing users with timely and accurate fault warnings and solutions. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a schematic diagram of the system of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0029] Example 1, as Figure 1 shown, a power fault diagnosis system for new energy vehicles based on 5G communication according to the present invention includes a data interface, a 5G communication network and a cloud server connected in sequence, and an intelligent mobile terminal;

[0030] The data interface is used to collect power data of new energy vehicles. The data interface is an OBD interface; the power data includes vehicle status data, motor current, rotor position of the motor, and instantaneous values of the current in each phase of the motor; the vehicle status data includes: vehicle speed, air conditioner status, brake pedal signal, and gear signal; the power data displayed on the intelligent mobile terminal includes: vehicle status data, motor current, rotor position of the motor, and instantaneous values of the current in each phase of the motor.

[0031] As a key port for data collection, the OBD interface is closely connected to the power management system of new energy vehicles. After the vehicle is started, the OBD interface will monitor and collect power data such as vehicle status data, motor current, rotor position of the motor, and instantaneous values of the current in each phase of the motor in real time. Its working frequency can be dynamically adjusted according to the running state of the vehicle. For example, during high-speed driving or charging of the vehicle, the data collection frequency will be increased to ensure more accurate and detailed power information is obtained, providing sufficient data support for subsequent fault diagnosis.

[0032] For the vehicle speed in the vehicle status data, the OBD interface obtains real-time vehicle speed information by connecting to the vehicle's speed sensor, and its accuracy can reach ±1 km / h, which can accurately reflect the change in the vehicle's driving speed. This is crucial for judging the power working state of the vehicle at different driving speeds. The air conditioner status data is obtained by communicating with the air conditioner control system to identify the on / off status and cooling / heating mode of the air conditioner, providing a basis for analyzing the impact of air conditioner operation on the power supply. The brake pedal signal and gear signal are also directly obtained from the vehicle's braking and shifting systems, and the signal transmission delay is extremely low, which can instantly transmit information such as the pedal depression depth and gear shifting situation to the data interface, ensuring timely and accurate grasp of the vehicle's running state.

[0033] The intelligent mobile terminal is also used to display charging history data and maintenance history records. The intelligent mobile terminal is also used for power fault prediction and diagnosis based on power data, including: comparing the current charging data with historical data to determine whether there is a change in the current charging data: if there is a change, directly compare the current charging data with the historical data; if there is no change, calculate the maximum matching coefficient between the current charging data and the historical data, and judge whether there is a fault in the current charging data according to the maximum matching coefficient.

[0034] The comparison between the current charging data and the historical data includes: judging the vehicle speed, air conditioner status, brake pedal signal, and gear signal one by one. When any data is inconsistent, it is judged that the current charging data has changed; the direct comparison between the current charging data and the historical data includes: respectively matching the motor current, the rotor position of the motor, and the instantaneous value of each phase current of the motor in the current charging data with the corresponding motor current, rotor position, and instantaneous value of each phase current of the motor in the historical data one by one. If all the matches are successful, it is judged that the current charging data is normal; otherwise, it is judged that the current charging data is abnormal.

[0035] The maximum matching coefficient is calculated by the following method: The maximum matching coefficient is calculated by the following formula:

[0036]

[0037] Where λ is the maximum matching coefficient, n is the number of acquisitions, i is a certain acquisition data, I i is the current charging current, I hist is the historical charging current, θ i is the current rotor position, θ hist is the historical rotor position, α is the current matching coefficient, β is the rotor position matching coefficient, ΔI is the minimum tolerance between I i and I hist and Δθ is the minimum tolerance between θ i and θ hist between.

[0038] The maximum matching coefficient and the fault are matched through the following functional relationship. The functional relationship is obtained by the following method: Obtain multiple different types of fault data. Among them, the vehicle state data, power supply current, rotor position of the motor, and instantaneous value of each phase current of the motor in any two types of fault data are all different, and in any two types of fault data, at least one of the vehicle state data, power supply current, rotor position of the motor, and instantaneous value of each phase current that appears is different; calculate the maximum matching coefficient for any two types of the above-obtained fault data respectively according to the method of calculating the maximum matching coefficient above, and then obtain the maximum matching coefficients of the two types of fault data; obtain multiple groups of maximum matching coefficients of pairwise different faults; establish multiple one-to-one correspondences between the maximum matching coefficient and the fault; establish a matching function between the maximum matching coefficient and the fault according to the multiple one-to-one correspondences between the maximum matching coefficient and the fault established above.

[0039] When the matching coefficient is the largest and equal to 1, it is judged that the current data is in the normal historical data; otherwise, according to the matching function, find the fault that appears in the current charging data, and select one fault from the search results according to the matching function for output.

[0040] The intelligent mobile terminal is used to display power data and perform power fault prediction and diagnosis based on the power data. When the intelligent mobile terminal is not in the standby state, it performs real-time matching according to the current charging data, searches for the fault with the largest matching coefficient, calculates the possibility of the occurrence of the above-mentioned fault, and outputs the search result; when the intelligent mobile terminal is in the standby state, a preset interval time is set. When it is not in the standby state, it performs real-time matching according to the current charging data, searches for the fault with the largest matching coefficient, calculates the possibility of the occurrence of the above-mentioned fault, and outputs the search result.

[0041] The calculation of the possibility of the occurrence of the above-mentioned fault is carried out by the following method: comparing the currently searched charging data with the charging condition data in the historical data, then judging the current charging condition data, and then calculating the matching coefficient of the current charging condition data according to the current charging condition data. Finally, the sum of the matching coefficient of the current charging data, the matching coefficient of the current charging condition data, and the searched matching coefficient is obtained, so as to obtain the possibility of the occurrence of the search result.

[0042] The intelligent mobile terminal can not only display the charging history data and maintenance history records, but also perform in-depth analysis on these data. For example, through the statistical analysis of the charging history data, a charging curve is drawn to visually display the charging trend of the vehicle at different time periods and in different charging environments, helping users understand the health status of the vehicle battery and the changes in charging efficiency. The display of the maintenance history records is also more detailed. In addition to recording the time, location, and maintenance items of the maintenance, it will also provide information on the parts replaced during the maintenance and the vehicle performance test data after the maintenance, etc., facilitating users to comprehensively understand the vehicle maintenance situation and providing reference for subsequent vehicle maintenance and fault troubleshooting.

[0043] In terms of power fault prediction and diagnosis, the intelligent mobile terminal adopts an advanced data analysis algorithm. When comparing the current charging data with the historical data, in addition to judging the vehicle speed, air conditioning state, brake pedal signal, and gear signal one by one, the change trend and change rate of these data will also be considered. For example, if the vehicle speed fluctuates greatly in a short period of time, even if the current vehicle speed is the same as the historical vehicle speed at a certain moment, due to the abnormal change trend, it will be judged that the current charging data has changed, and further fault troubleshooting will be carried out. When calculating the maximum matching coefficient, in order to improve the accuracy, weighted processing will be performed on the multiple collected data, and different weights will be assigned according to the importance and stability of the data, so that the maximum matching coefficient can more truly reflect the matching degree between the current charging data and the historical data.

[0044] The intelligent mobile terminal also has an intelligent reminder function. When it is judged according to the power data that there may be a potential risk of power failure in the vehicle, a reminder message will be sent to the user in a timely manner. The content of the message not only includes the possible types of faults, but also provides some preliminary countermeasures, such as suggesting the user to reduce the vehicle load and go to the repair station for inspection as soon as possible, etc., to ensure the safe driving of the vehicle and the user experience.

[0045] The 5G communication network and the cloud server are used to connect the data interface and the intelligent mobile terminal through the 5G communication network and the cloud server.

[0046] With its characteristics of high speed, low latency and high reliability, the 5G communication network greatly improves the efficiency and quality of data transmission. During the data transmission process between the data interface and the intelligent mobile terminal, it can ensure the real-time and integrity of the power data. For example, when there is an instantaneous change in the power data of the vehicle during high-speed driving, the 5G communication network can transmit this data accurately to the intelligent mobile terminal within milliseconds, enabling the intelligent mobile terminal to make a fault diagnosis and early warning in a timely manner, and avoiding the problem of inaccurate or untimely fault judgment caused by data transmission delay.

[0047] The cloud server plays a core role in data storage and processing in the whole system. It not only stores a large amount of vehicle historical data, including power data, charging data and maintenance data under different vehicle models and different usage environments, etc., but also can use cloud computing technology to quickly analyze and process these data. For example, when the intelligent mobile terminal requests a fault diagnosis, the cloud server can call the relevant historical data in a short time and combine with an advanced data analysis model to provide accurate fault diagnosis reference information for the intelligent mobile terminal, greatly improving the efficiency and accuracy of fault diagnosis. At the same time, the cloud server also has a data backup and recovery function, which can regularly back up the stored data to prevent data loss and ensure the stable operation of the whole system.

[0048] The entire new energy vehicle power failure diagnosis system realizes all-round and real-time monitoring and diagnosis of the vehicle power supply through the close cooperation of the data interface, 5G communication network, cloud server and intelligent mobile terminal. During vehicle driving, the data interface continuously collects power supply data and uploads it to the cloud server in a timely manner through the 5G communication network for storage and preliminary analysis. The intelligent mobile terminal can obtain the latest power supply data and historical data from the cloud server at any time according to the user's needs, and conduct fault prediction and diagnosis. When the intelligent mobile terminal detects a fault, it will interact with the cloud server to obtain more detailed fault solutions and maintenance suggestions, and at the same time feedback the fault information to the user and vehicle manufacturer. The vehicle manufacturer can optimize the vehicle design and production based on these fault information to improve the overall quality and reliability of the vehicle. In addition, the system can also be docked with the management system of the automobile repair shop to realize quick reservation for repairing fault vehicles and real-time tracking of the repair progress, providing more convenient and efficient after-sales services for users.

[0049] The embodiments disclosed in the present invention are preferred embodiments, but not limited thereto. Those of ordinary skill in the art can easily understand the spirit of the present invention based on the above embodiments and make different extensions and changes. However, as long as they do not depart from the spirit of the present invention, they are within the protection scope of the present invention.

Claims

1. A new energy vehicle power supply fault diagnosis system based on 5G communication, characterized in that: It includes a data interface, a 5G communication network and a cloud server, and a smart mobile terminal connected in sequence; The data interface is used to collect power data of new energy vehicles; The 5G communication network and cloud server are used to connect the data interface and the smart mobile terminal through the 5G communication network and cloud server; The intelligent mobile terminal is used to display power supply data and predict and diagnose power supply failures based on the power supply data.

2. According to a 5G communication-based new energy vehicle power supply fault diagnosis system according to claim 1, it is characterized in that: The data interface is an OBD interface; The power supply data includes vehicle status data, motor current, motor rotor position, and instantaneous value of each phase current of the motor; The vehicle status data includes: vehicle speed, air conditioning status, brake pedal signal and gear position signal; The power supply data displayed by the smart mobile terminal includes: vehicle status data, motor current, motor rotor position, and instantaneous value of each phase current of the motor; The intelligent mobile terminal is also used to display charging history data and maintenance history records.

3. A new energy vehicle power supply fault diagnosis system based on 5G communication according to claim 2, characterized in that: The intelligent mobile terminal is also used to predict and diagnose power supply failures based on power supply data, including: comparing current charging data with historical data to determine whether the current charging data has changed; if there has been a change, directly comparing the current charging data with the historical data; if there has been no change, calculating the maximum matching coefficient between the current charging data and the historical data, and determining whether the current charging data has a fault based on the maximum matching coefficient.

4. A new energy vehicle power supply fault diagnosis system based on 5G communication according to claim 3, characterized in that: The current charging data is compared with the historical data, including: judging the vehicle speed, air conditioning status, brake pedal signal and gear position signal one by one, and when any data is inconsistent, it is judged that the current charging data has changed; The current charging data is directly compared with the historical data, including: matching the motor current, the rotor position of the motor, and the instantaneous value of each phase current of the motor in the current charging data with the corresponding motor current, the rotor position of the motor, and the instantaneous value of each phase current of the motor in the historical data one by one. If all matches are successful, the current charging data is judged to be normal; otherwise, the current charging data is judged to be abnormal.

5. According to a 5G communication-based new energy vehicle power supply fault diagnosis system according to claim 3, it is characterized in that: The maximum matching coefficient is calculated by the following method: The maximum matching coefficient is calculated by the following formula: Among them, λ is the maximum matching coefficient, n is the number of acquisitions, i is a certain data collected, I i is the current charging current, I hist is the historical charging current, θ i is the current rotor position, θ hist is the historical rotor position, α is the current matching coefficient, β is the rotor position matching coefficient, ΔI is I i with I hist The minimum tolerance between θ and i With θ hist The minimum tolerance between 6. A new energy vehicle power supply fault diagnosis system based on 5G communication according to claim 5, characterized in that: The maximum matching coefficient and the fault are matched through the following functional relationship, and the functional relationship is achieved through the following method: obtaining multiple different types of fault data, wherein the vehicle status data, power supply current, motor rotor position, and instantaneous values ​​of each phase current of the motor in any two types of fault data are different, and in any two types of fault data, at least one of the vehicle status data, power supply current, motor rotor position, and instantaneous values ​​of each phase current of the motor is different; calculating the maximum matching coefficient for any two types of fault data obtained above according to the above method for calculating the maximum matching coefficient, and then obtaining the maximum matching coefficient for the two types of fault data; obtaining multiple groups of maximum matching coefficients for two different faults; establishing a one-to-one correspondence between the maximum matching coefficient and multiple groups of faults; and establishing a matching function between the maximum matching coefficient and the fault according to the above established one-to-one correspondence between the maximum matching coefficient and multiple groups of faults.

7. A new energy vehicle power supply fault diagnosis system based on 5G communication according to claim 6, characterized in that: When the matching coefficient is the largest and equal to 1, it is determined that the current data is in the historical normal data. Otherwise, the fault in the current charging data is searched according to the matching function, and a fault is selected from the search results according to the matching function for output.

8. A new energy vehicle power supply fault diagnosis system based on 5G communication according to claim 7, characterized in that: When the intelligent mobile terminal is not in the standby state, real-time matching is performed according to the current charging data to find the fault with the largest matching coefficient, and the possibility of the occurrence of the above fault is calculated, and the search result is output; When the intelligent mobile terminal is in standby mode, a preset interval time is set. When it is not in standby mode, real-time matching is performed according to the current charging data to find the fault with the largest matching coefficient, calculate the possibility of the above fault, and output the search result.

9. A new energy vehicle power supply fault diagnosis system based on 5G communication according to claim 8, characterized in that: The possibility of the above-mentioned fault being calculated is obtained by comparing the current charging data being searched with the charging condition data in the historical data, thereby determining the current charging condition data, and then calculating the matching coefficient of the current charging condition data based on the current charging condition data, and finally obtaining the matching coefficient of the current charging data and the sum of the matching coefficient of the current charging condition data and the searched matching coefficient, thereby obtaining the possibility of the search result being obtained.

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