New energy bus charging monitoring method and system

Abstract

The invention relates to the technical field of charging monitoring, in particular to a new energy bus charging monitoring method and system, and the method comprises the steps: sorting vehicle operation information and vehicle charging information according to time nodes, determining the corresponding relation between the initial operation power and the initial charging data and between the non-initial operation power and the non-initial charging data, and determining the initial battery operation power corresponding to the initial charging data and the non-initial battery operation power corresponding to the non-initial charging data according to the corresponding relation, performing fatigue analysis on the initial battery operation power and the non-initial battery operation power to obtain battery fatigue information, and matching the battery fatigue information with a preset battery fatigue charging standard to obtain a battery charging scheme, and controlling the strong and weak current conversion time node when the charging pile charges the new energy bus battery according to the battery charging scheme. The application efficiency of the new energy bus battery is improved.

Description

Technical Field

[0001] The present application relates to the technical field of charging monitoring, and in particular to a charging monitoring method and system for a new energy bus. Background Art

[0002] As the world pays more attention to environmental protection and sustainable development, new energy buses, as an important part of urban public transportation, are increasingly widely used. New energy buses, especially electric buses using batteries as power sources, have shown significant advantages in reducing exhaust emissions and noise pollution.

[0003] At present, when charging new energy buses, in order to protect the battery and optimize the charging efficiency, a staged charging strategy is widely adopted, that is, a charging method of converting weak current to strong current and then to weak current. This charging method fully considers the characteristics and needs of the battery at different charging stages, aims to reduce the stress inside the battery, extend the battery life, and ensure the safety and efficiency of the charging process.

[0004] At the beginning of charging, a weak current is used for charging, which is also called the pre-charging stage. The purpose of this stage is to gradually activate the chemical reaction inside the battery, so that the battery temperature, voltage and other parameters gradually stabilize, and prepare for subsequent fast charging. Weak current charging helps to reduce the internal resistance increase and capacity attenuation problems that may occur after the battery has not been used for a long time, and at the same time avoids the damage that may be caused by the direct impact of a large current on the battery. When the battery state reaches the preset conditions (such as the voltage is stable within a certain range), the charging process will switch to the strong current stage. In this stage, the charging pile will output a large current to replenish the battery at a faster rate. Strong current charging can significantly shorten the charging time, improve the charging efficiency, and meet the needs of fast charging of new energy buses. However, strong current charging will also increase the heat generation and stress accumulation inside the battery, so it is necessary to strictly control the charging time and current size to avoid irreversible damage to the battery. As the battery power continues to increase, the charging process will switch to the weak current stage again, also known as trickle charging or maintenance charging. In this stage, the charging pile will output a small current to continue to replenish the remaining power to the battery until the battery is fully charged. Weak current charging helps balance the charge distribution inside the battery, reduce the polarization phenomenon inside the battery, and further improve the battery charging efficiency and capacity utilization. At the same time, trickle charging can also ensure that the battery maintains a stable voltage and current output after being fully charged, extending the battery life.

[0005] However, with the application of new energy buses, the performance status of the battery will change with the change of usage time, charge and discharge times, etc. If the charging pile cannot sense and respond to these changes in real time and continues to charge according to a fixed charging strategy, it may not be able to adjust the charging parameters in time to adapt to the current status of the battery, thus affecting the charging effect and battery life. Summary of the invention

[0006] In order to solve at least one of the above-mentioned technical problems, the present application provides a new energy bus charging monitoring method and system.

[0007] In the first aspect, the present application provides a new energy bus charging monitoring method, which adopts the following technical solution: Obtain vehicle operation information and vehicle charging information, wherein the vehicle operation information includes the initial operation power of the battery during the first operation of different new energy buses and the non-initial operation power of the battery during the non-first operation, and the vehicle charging information includes the initial charging data of the charging pile when charging different new energy buses for the first time and the non-initial charging data when charging for the non-first time; The vehicle operation information and the vehicle charging information are sorted according to time nodes respectively, and the corresponding relationship between the initial operation power and the non-initial operation power in the vehicle operation information and the initial charging data and the non-initial charging data in the vehicle charging information of the same new energy bus is determined; Determine, according to the corresponding relationship, the initial battery operating power corresponding to the initial charging data when each new energy bus is charged for the first time and the non-initial battery operating power corresponding to the non-initial charging data when charging is not performed for the first time; Performing fatigue analysis on the initial battery operating power and the non-initial battery operating power to obtain battery fatigue information corresponding to each new energy bus battery; Matching the battery fatigue information with a preset battery fatigue charging standard to obtain a battery charging solution for the battery fatigue information; A charging control instruction is generated according to the battery charging scheme to control the strong and weak current conversion time nodes of the charging pile when charging the battery of the new energy bus.

[0008] By adopting the above technical solutions, the data of the operation and charging of new energy buses can be fully and accurately captured. It not only covers the power performance of the battery at different stages of use, but also records the charging data of the charging pile in detail, laying a solid foundation for subsequent accurate analysis. The information sorted by time nodes enables the operating power and charging data of the same new energy bus to correspond seamlessly, providing an intuitive basis for the changes in battery performance over the use cycle. The establishment of this correspondence greatly simplifies the complexity of data analysis and improves the efficiency and accuracy of the analysis. At the same time, it can accurately identify the specific operating status of the battery of each new energy bus during the first and non-first charging. It provides key input for subsequent battery fatigue analysis, making the analysis results closer to actual use, which is of great significance for optimizing battery management strategies and extending battery life. The introduced fatigue analysis method can deeply analyze the attenuation of battery performance with the number of uses. By carefully comparing the initial and non-initial battery operating power, the system can accurately calculate the battery fatigue information, match the battery fatigue information with the preset standard, and automatically generate a personalized battery charging plan. It not only realizes the intelligent control of the charging process, but also dynamically adjusts the charging strategy according to the actual condition of the battery, effectively avoiding damage to the battery due to overcharging or over-discharging, further extending the battery life, and improving charging efficiency and safety. According to the charging control instructions finally generated, the strong and weak current conversion time nodes of the charging pile during the charging process can be accurately controlled. This precise control strategy not only optimizes the charging process and improves charging efficiency, but also reduces unnecessary energy waste and reduces operating costs, thereby improving the battery application efficiency of new energy buses.

[0009] In a possible implementation, the vehicle operation information and the vehicle charging information are sorted according to time nodes, and the correspondence between the initial operation power and the non-initial operation power in the vehicle operation information of the same new energy bus and the initial charging data and the non-initial charging data in the vehicle charging information is determined, including: Create multiple data monitoring coordinate systems, wherein the X-axes of the multiple data monitoring coordinate systems are all different time nodes, the Y-axes of the multiple data monitoring coordinate systems are different units of operating power and different units of battery charging data, and the number of the multiple data coordinate systems is consistent with the number of new energy buses to be monitored; Bind the multiple data monitoring coordinate systems to each new energy bus in a one-to-one correspondence, and map the initial operating power, the non-initial operating power, the initial charging data, and the non-initial charging data corresponding to each new energy bus to the corresponding data monitoring coordinate system according to the time node, to obtain the operating data coordinate system corresponding to each new energy bus; Determine, according to the operation data coordinate system, an initial operation waveform segment corresponding to the initial operation power, a non-initial operation waveform segment of the non-initial operation power, an initial charging waveform segment corresponding to the initial charging data, and a non-initial charging waveform segment of the non-initial charging data; A distribution correlation binding analysis is performed on the initial operation waveform segment, the non-initial operation waveform segment, the initial charging waveform segment and the non-initial charging waveform segment to determine the correspondence between the initial operation power and the non-initial operation power in the vehicle operation information and the initial charging data and the non-initial charging data in the vehicle charging information of the same new energy bus.

[0010] In a possible implementation, the distribution correlation binding analysis is performed on the initial operation waveform segment, the non-initial operation waveform segment, the initial charging waveform segment, and the non-initial charging waveform segment to determine the correspondence between the initial operation power and the non-initial operation power in the vehicle operation information of the same new energy bus and the initial charging data and the non-initial charging data in the vehicle charging information, including: Determine an operating waveform segment existing before an initial time node of the initial charging waveform segment, and bind the existing operating waveform segment to the initial charging waveform segment to obtain a first corresponding relationship between the initial charging data and the initial operating power and / or the non-initial operating power; Determine a first non-initial charging waveform segment adjacent to the initial charging waveform segment, and bind a non-initial operation waveform segment between the initial charging waveform segment and the first non-initial charging waveform segment with the first non-initial charging waveform segment to obtain a second corresponding relationship between non-initial charging data corresponding to the first non-initial charging waveform segment and the non-initial operation power; Determine a second non-initial charging waveform segment adjacent to the first non-initial charging waveform segment, and bind the non-initial operation waveform segment between the first non-initial charging waveform segment and the second non-initial charging waveform segment with the second non-initial charging waveform segment to obtain a third corresponding relationship between the non-initial charging corresponding to the second non-initial charging waveform segment and the non-initial operation power; Determine a second non-initial charging waveform segment set that is not adjacent to the initial charging waveform segment, and bind a non-initial operation waveform segment between every two adjacent non-initial charging waveform segments in the second non-initial charging waveform segment set with a non-initial charging waveform segment that is positioned later in time than the adjacent non-initial charging waveform segment, to obtain a fourth corresponding relationship between non-initial charging data corresponding to each non-initial charging waveform segment in the second non-initial charging waveform segment set and non-initial operation power; The correspondence between the initial operating power and the non-initial operating power in the vehicle operating information and the initial charging data and the non-initial charging data in the vehicle charging information of the same new energy bus is determined according to the first corresponding relationship, the second corresponding relationship, the third corresponding relationship and the fourth corresponding relationship.

[0011] In a possible implementation, fatigue analysis is performed on the initial battery operating power and the non-initial battery operating power to obtain battery fatigue information corresponding to each new energy bus battery, including: Performing feature analysis on a first operation waveform segment corresponding to the initial battery operation power and a plurality of second operation waveform segments corresponding to the non-initial battery operation power to obtain first operation feature data corresponding to the first operation waveform segment and a set of second operation feature data corresponding to the plurality of second operation waveform segments; Based on a fingerprint algorithm, the first running feature data and the second running feature data are combined to generate a first running hash object, and the data format of the first running hash object is converted into a byte stream format to obtain a second running hash object; According to the fingerprint algorithm, the second operation hash object generates a reference operation data fingerprint and a fatigue monitoring operation data fingerprint set, and the fatigue monitoring operation data fingerprint set is compared with the reference operation data fingerprint one by one to obtain the operation change data of each new energy bus battery in different time periods after each charging; Identify the output current, voltage and power of each new energy bus battery according to the operation change data to obtain parameter change data of different attribute parameters; Draw a data dynamic waveform diagram of parameter change data of different attribute parameters, and perform a steady-state analysis on the corresponding new energy bus battery based on the data dynamic waveform diagram to obtain battery stability data; The battery stability data is matched with a preset battery fatigue condition evaluation standard to obtain the battery fatigue information corresponding to each new energy bus battery.

[0012] In a possible implementation, the matching the battery fatigue information with a preset battery fatigue charging standard to obtain a battery charging solution for the battery fatigue information also includes: Determining abnormal fatigue information of a battery having abnormal fatigue according to the preset battery fatigue charging standard; Determining abnormal fatigue limit data corresponding to the abnormal fatigue information of the battery in the preset battery fatigue condition assessment standard; Determine whether the battery stability data is consistent with the abnormal fatigue limit data. If consistent, generate battery maintenance information based on the new energy bus battery in the battery stability data and the consistent abnormal data, and send the battery maintenance information to the target terminal.

[0013] In a possible implementation, the determining whether the battery stability data is consistent with the abnormal fatigue limit data includes: If the battery stability data does not match the abnormal fatigue limit data, unsupervised time series data sorting is performed on the battery stability data based on the time series length in the data dynamic waveform diagram to obtain battery matrix data; Performing data periodicity analysis on the battery matrix data to generate future battery matrix data; Processing the data contained in the future battery matrix data to obtain deduction matrix data, and inputting the obtained deduction matrix data into a preset algorithm model for data calculation to obtain future battery stability data of different new energy bus batteries within a preset time in the future; Determine a future abnormal time node in the future battery stability data that meets the abnormal fatigue limit data, and generate remaining maintenance duration information according to the current time node and the future abnormal time node.

[0014] In a possible implementation, performing data periodicity analysis on the battery matrix data to generate future battery matrix data includes: Performing basic data distribution exploration on the battery matrix data to determine the relative periodicity of the battery stability data when changes occur, and determining the length of the time period based on the relative periodicity; Performing supervised time series data sorting on the battery matrix data based on the time period length to obtain data period regularity data; Based on the data cycle regularity data, the battery stability data change trend within a future preset time period is predicted to generate future battery matrix data.

[0015] In the second aspect, the present application provides a new energy bus charging monitoring system, which adopts the following technical solutions: A new energy bus charging monitoring system, comprising: An information acquisition module, used to acquire vehicle operation information and vehicle charging information, wherein the vehicle operation information includes the initial operation power of the battery during the first operation of different new energy buses and the non-initial operation power of the battery during the non-first operation, and the vehicle charging information includes the initial charging data of the charging pile when charging different new energy buses for the first time and the non-initial charging data when charging for the non-first time; An information sorting module, used to sort the vehicle operation information and the vehicle charging information according to time nodes, and determine the correspondence between the initial operation power and the non-initial operation power in the vehicle operation information and the initial charging data and the non-initial charging data in the vehicle charging information of the same new energy bus; A power determination module, used to determine, according to the corresponding relationship, the initial battery operating power corresponding to the initial charging data when each new energy bus is charged for the first time and the non-initial battery operating power corresponding to the non-initial charging data when charging is not performed for the first time; A fatigue analysis module, used to perform fatigue analysis on the initial battery operating power and the non-initial battery operating power to obtain battery fatigue information corresponding to each new energy bus battery; A scheme determination module, used for matching the battery fatigue information with a preset battery fatigue charging standard to obtain a battery charging scheme for the battery fatigue information; The charging control module is used to generate charging control instructions according to the battery charging scheme, and control the strong and weak current conversion time nodes of the charging pile when charging the battery of the new energy bus.

[0016] In a possible implementation, the information sorting module sorts the vehicle operation information and the vehicle charging information according to time nodes, and determines the correspondence between the initial operation power and the non-initial operation power in the vehicle operation information of the same new energy bus and the initial charging data and the non-initial charging data in the vehicle charging information, specifically for: Create multiple data monitoring coordinate systems, wherein the X-axes of the multiple data monitoring coordinate systems are all different time nodes, the Y-axes of the multiple data monitoring coordinate systems are different units of operating power and different units of battery charging data, and the number of the multiple data coordinate systems is consistent with the number of new energy buses to be monitored; Bind the multiple data monitoring coordinate systems to each new energy bus in a one-to-one correspondence, and map the initial operating power, the non-initial operating power, the initial charging data, and the non-initial charging data corresponding to each new energy bus to the corresponding data monitoring coordinate system according to the time node, to obtain the operating data coordinate system corresponding to each new energy bus; Determine, according to the operation data coordinate system, an initial operation waveform segment corresponding to the initial operation power, a non-initial operation waveform segment of the non-initial operation power, an initial charging waveform segment corresponding to the initial charging data, and a non-initial charging waveform segment of the non-initial charging data; A distribution correlation binding analysis is performed on the initial operation waveform segment, the non-initial operation waveform segment, the initial charging waveform segment and the non-initial charging waveform segment to determine the correspondence between the initial operation power and the non-initial operation power in the vehicle operation information and the initial charging data and the non-initial charging data in the vehicle charging information of the same new energy bus.

[0017] In another possible implementation, the information sorting module performs distribution association binding analysis on the initial operation waveform segment, the non-initial operation waveform segment, the initial charging waveform segment, and the non-initial charging waveform segment to determine the correspondence between the initial operation power and the non-initial operation power in the vehicle operation information of the same new energy bus and the initial charging data and the non-initial charging data in the vehicle charging information, specifically for: Determine an operating waveform segment existing before an initial time node of the initial charging waveform segment, and bind the existing operating waveform segment to the initial charging waveform segment to obtain a first corresponding relationship between the initial charging data and the initial operating power and / or the non-initial operating power; Determine a first non-initial charging waveform segment adjacent to the initial charging waveform segment, and bind a non-initial operation waveform segment between the initial charging waveform segment and the first non-initial charging waveform segment with the first non-initial charging waveform segment to obtain a second corresponding relationship between non-initial charging data corresponding to the first non-initial charging waveform segment and the non-initial operation power; Determine a second non-initial charging waveform segment adjacent to the first non-initial charging waveform segment, and bind the non-initial operation waveform segment between the first non-initial charging waveform segment and the second non-initial charging waveform segment with the second non-initial charging waveform segment to obtain a third corresponding relationship between the non-initial charging corresponding to the second non-initial charging waveform segment and the non-initial operation power; Determine a second non-initial charging waveform segment set that is not adjacent to the initial charging waveform segment, and bind a non-initial operation waveform segment between every two adjacent non-initial charging waveform segments in the second non-initial charging waveform segment set with a non-initial charging waveform segment that is positioned later in time than the adjacent non-initial charging waveform segment, to obtain a fourth corresponding relationship between non-initial charging data corresponding to each non-initial charging waveform segment in the second non-initial charging waveform segment set and non-initial operation power; The correspondence between the initial operating power and the non-initial operating power in the vehicle operating information and the initial charging data and the non-initial charging data in the vehicle charging information of the same new energy bus is determined according to the first corresponding relationship, the second corresponding relationship, the third corresponding relationship and the fourth corresponding relationship.

[0018] In another possible implementation, when the fatigue analysis module performs fatigue analysis on the initial battery operating power and the non-initial battery operating power to obtain the battery fatigue information corresponding to each new energy bus battery, it is specifically used to: Performing feature analysis on a first operation waveform segment corresponding to the initial battery operation power and a plurality of second operation waveform segments corresponding to the non-initial battery operation power to obtain first operation feature data corresponding to the first operation waveform segment and a set of second operation feature data corresponding to the plurality of second operation waveform segments; Based on a fingerprint algorithm, the first running feature data and the second running feature data are combined to generate a first running hash object, and the data format of the first running hash object is converted into a byte stream format to obtain a second running hash object; According to the fingerprint algorithm, the second operation hash object generates a reference operation data fingerprint and a fatigue monitoring operation data fingerprint set, and the fatigue monitoring operation data fingerprint set is compared with the reference operation data fingerprint one by one to obtain the operation change data of each new energy bus battery in different time periods after each charging; Identify the output current, voltage and power of each new energy bus battery according to the operation change data to obtain parameter change data of different attribute parameters; Draw a data dynamic waveform diagram of parameter change data of different attribute parameters, and perform a steady-state analysis on the corresponding new energy bus battery based on the data dynamic waveform diagram to obtain battery stability data; The battery stability data is matched with a preset battery fatigue condition evaluation standard to obtain the battery fatigue information corresponding to each new energy bus battery.

[0019] In another possible implementation, the system further includes: a first determination module, a second determination module, and a maintenance generation module, wherein: The first determination module is used to determine abnormal fatigue information of a battery with abnormal fatigue according to the preset battery fatigue charging standard; The second determination module is used to determine the abnormal fatigue limit data corresponding to the abnormal fatigue information of the battery in the preset battery fatigue condition assessment standard; The maintenance generation module is used to determine whether the battery stability data is consistent with the abnormal fatigue limit data. If it is consistent, the battery maintenance information is generated based on the new energy bus battery in the battery stability data and the consistent abnormal data, and the battery maintenance information is sent to the target terminal.

[0020] In another possible implementation, when determining whether the battery stability data is consistent with the abnormal fatigue limit data, the maintenance generation module is specifically configured to: If the battery stability data does not match the abnormal fatigue limit data, unsupervised time series data sorting is performed on the battery stability data based on the time series length in the data dynamic waveform diagram to obtain battery matrix data; Performing data periodicity analysis on the battery matrix data to generate future battery matrix data; Processing the data contained in the future battery matrix data to obtain deduction matrix data, and inputting the obtained deduction matrix data into a preset algorithm model for data calculation to obtain future battery stability data of different new energy bus batteries within a preset time in the future; Determine a future abnormal time node in the future battery stability data that meets the abnormal fatigue limit data, and generate remaining maintenance duration information according to the current time node and the future abnormal time node.

[0021] In another possible implementation, when the maintenance generation module performs data periodicity regularity analysis on the battery matrix data to generate future battery matrix data, it is specifically used to: Performing basic data distribution exploration on the battery matrix data to determine the relative periodicity of the battery stability data when changes occur, and determining the length of the time period based on the relative periodicity; Performing supervised time series data sorting on the battery matrix data based on the time period length to obtain data period regularity data; Based on the data cycle regularity data, the battery stability data change trend within a future preset time period is predicted to generate future battery matrix data.

[0022] In a third aspect, the present application provides an electronic device, which adopts the following technical solution: at least one processor; Memory; At least one application, wherein at least one application is stored in a memory and configured to be executed by at least one processor, and at least one application is configured to: execute a new energy bus charging monitoring method as described in any one of the first aspects.

[0023] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium stores a computer program, which, when executed in a computer, causes the computer to execute any of the new energy bus charging monitoring methods of the first aspect.

[0024] In summary, the present application includes at least one of the following beneficial technical effects: When charging new energy buses, the data of the operation and charging dimensions of new energy buses are captured comprehensively and accurately. It not only covers the power performance of the battery at different stages of use, but also records the charging data of the charging pile in detail, laying a solid foundation for subsequent accurate analysis. The information organized by time nodes enables seamless correspondence between the operating power and charging data of the same new energy bus, providing an intuitive basis for the changes in battery performance over the use cycle. The establishment of this correspondence greatly simplifies the complexity of data analysis and improves the efficiency and accuracy of the analysis. At the same time, it can accurately identify the specific operating status of the battery of each new energy bus during the first and non-first charging. It provides key input for subsequent battery fatigue analysis, making the analysis results closer to actual use, which is of great significance for optimizing battery management strategies and extending battery life. The introduced fatigue analysis method can deeply analyze the attenuation of battery performance with the number of uses. By carefully comparing the initial and non-initial battery operating power, the system can accurately calculate the battery fatigue information, match the battery fatigue information with the preset standard, and automatically generate a personalized battery charging plan. It not only realizes the intelligent control of the charging process, but also dynamically adjusts the charging strategy according to the actual condition of the battery, effectively avoiding damage to the battery due to overcharging or over-discharging, further extending the battery life, and improving charging efficiency and safety. According to the charging control instructions finally generated, the strong and weak current conversion time nodes of the charging pile during the charging process can be accurately controlled. This precise control strategy not only optimizes the charging process and improves charging efficiency, but also reduces unnecessary energy waste and reduces operating costs, thereby improving the battery application efficiency of new energy buses. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A schematic flow chart of a new energy bus charging monitoring method provided in an embodiment of the present application.

[0026] Figure 2 A schematic diagram of the structure of a new energy bus charging monitoring system provided in an embodiment of the present application.

[0027] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The following is combined with Figure 1-3 This application is described in further detail.

[0029] This specific embodiment is merely an explanation of the present application and is not a limitation of the present application. After reading this specification, a person skilled in the art may make non-creative modifications to the present embodiment as needed, but such modifications are protected by the patent law as long as they are within the scope of the present application.

[0030] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0031] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0032] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0033] The embodiment of the present application provides a method for monitoring charging of a new energy bus, which is executed by an electronic device, wherein the electronic device can be an independent physical electronic device, or an electronic device cluster or distributed system composed of multiple physical electronic devices, or a cloud electronic device that provides cloud computing services. The embodiment of the present application is not limited here, such as Figure 1 As shown, the method includes: Step S10: Acquire vehicle operation information and vehicle charging information.

[0034] Among them, the vehicle operation information includes the initial operating power of the battery during the first operation of different new energy buses and the non-initial operating power of the battery during non-first operation; the vehicle charging information includes the initial charging data of the charging pile when charging different new energy buses for the first time and the non-initial charging data when not charging for the first time.

[0035] For the embodiment of the present application, the vehicle operation information refers to various data records about the new energy bus during operation, which are used to indicate the performance of the vehicle under different conditions. Specifically, the initial operating power of the battery during the first operation indicates the output power of the battery in the initial stage when the new energy bus is first put into use, which is an important indicator for evaluating the initial performance of the battery. The non-initial operating power of the battery during the non-first operation refers to the power change of the battery at different use stages in the subsequent operation, reflecting the attenuation of the battery performance with the number of uses. The vehicle charging information refers to the relevant data records when the charging pile provides charging services for the new energy bus, which is used to reflect various parameters in the charging process. Among them, the initial charging data of the charging pile when charging different new energy buses for the first time indicates the key data such as the charging starting conditions, charging power, and charging amount recorded by the charging pile when each new energy bus is charged for the first time. The non-initial charging data during the non-first charging refers to the charging data recorded by the charging pile during the subsequent charging process that is different from the first charging. These data can reflect the changes in the charging efficiency and charging characteristics of the battery under different charging cycles.

[0036] In the embodiment of the present application, the vehicle-mounted sensor will monitor and record the battery power data of the vehicle in real time during operation, including the initial operating power during the first operation and the subsequent non-initial operating power. At the same time, when the vehicle is charging, the charging pile control system will record the detailed data of each charge, including the initial charging data of the first charge and the subsequent non-initial charging data. These data will then be transmitted to the background data center for unified storage and analysis.

[0037] Step S11, sorting the vehicle operation information and the vehicle charging information according to the time nodes, and determining the correspondence between the initial operation power and the non-initial operation power in the vehicle operation information and the initial charging data and the non-initial charging data in the vehicle charging information of the same new energy bus.

[0038] Specifically, multiple data monitoring coordinate systems are created, the X-axes of the multiple data monitoring coordinate systems are different time nodes, the Y-axes of the multiple data monitoring coordinate systems are different units of operating power and different units of battery charging data, the number of the multiple data coordinate systems is consistent with the number of new energy buses to be monitored, the multiple data monitoring coordinate systems are bound to each new energy bus in a one-to-one correspondence, and the initial operating power, non-initial operating power, initial charging data and non-initial charging data corresponding to each new energy bus are mapped to the corresponding data monitoring coordinate system according to the time node, so as to obtain the operating data coordinate system corresponding to each new energy bus, and the initial operating waveform segment corresponding to the initial operating power, the non-initial operating waveform segment of the non-initial operating power, the initial charging waveform segment corresponding to the initial charging data and the non-initial charging waveform segment of the non-initial charging data are determined according to the operating data coordinate system, and the initial operating waveform segment, the non-initial operating waveform segment, the initial charging waveform segment and the non-initial charging waveform segment are subjected to distribution correlation binding analysis, so as to determine the corresponding relationship between the initial operating power and the non-initial operating power in the vehicle operating information and the initial charging data and the non-initial charging data in the vehicle charging information of the same new energy bus.

[0039] Specifically, the operating waveform segment existing before the initial time node of the initial charging waveform segment is determined, and the existing operating waveform segment is bound to the initial charging waveform segment to obtain a first corresponding relationship between the initial charging data and the initial operating power and / or the non-initial operating power, a first non-initial charging waveform segment adjacent to the initial charging waveform segment is determined, and the non-initial operating waveform segment between the initial charging waveform segment and the first non-initial charging waveform segment is bound to the first non-initial charging waveform segment to obtain a second corresponding relationship between the non-initial charging data corresponding to the first non-initial charging waveform segment and the non-initial operating power, a second non-initial charging waveform segment adjacent to the first non-initial charging waveform segment is determined, and the non-initial operating waveform segment between the first non-initial charging waveform segment and the second non-initial charging waveform segment is bound to the second non-initial charging waveform segment to obtain a first corresponding relationship between the non-initial charging data corresponding to the first non-initial charging waveform segment and the non-initial operating power. A third correspondence between the non-initial charging and the non-initial operating power corresponding to the second non-initial charging waveform segment is determined, a second non-initial charging waveform segment set that is not adjacent to the initial charging waveform segment is determined, and the non-initial operating waveform segment between every two adjacent non-initial charging waveform segments in the second non-initial charging waveform segment set is bound with the non-initial charging waveform segment that is time-postponed with the adjacent non-initial charging waveform segment, to obtain a fourth correspondence between the non-initial charging data corresponding to each non-initial charging waveform segment in the second non-initial charging waveform segment set and the non-initial operating power, and the correspondence between the initial operating power and the non-initial operating power in the vehicle operating information of the same new energy bus and the initial charging data and the non-initial charging data in the vehicle charging information is determined according to the first correspondence, the second correspondence, the third correspondence and the fourth correspondence.

[0040] Step S12: Determine the initial battery operating power corresponding to the initial charging data when each new energy bus is charged for the first time and the non-initial battery operating power corresponding to the non-initial charging data when charging is not the first time according to the corresponding relationship.

[0041] Step S13: Perform fatigue analysis on the initial battery operating power and the non-initial battery operating power to obtain battery fatigue information corresponding to each new energy bus battery.

[0042] Specifically, feature analysis is performed on the first operating waveform segment corresponding to the initial battery operating power and the multiple second operating waveform segments corresponding to the non-initial battery operating power to obtain first operating feature data corresponding to the first operating waveform segment and a second operating feature data set corresponding to the multiple second operating waveform segments. Then, based on the fingerprint algorithm, the first operating feature data and the second operating feature data set are used to generate a first operating hash object, and the data format of the first operating hash object is converted into a byte stream format to obtain a second operating hash object. Then, according to the fingerprint algorithm, the second operating hash object is used to generate a control operating data fingerprint and a fatigue monitoring operating data fingerprint set, and the fatigue monitoring operating data fingerprint set is compared one by one with the control operating data fingerprint to obtain the operating change data of each new energy bus battery in different time periods after each charging. Then, the output current, voltage and power of each new energy bus battery are identified according to the operating change data to obtain parameter change data of different attribute parameters, and then a data dynamic waveform diagram of the parameter change data of different attribute parameters is drawn, and a steady-state analysis is performed on the corresponding new energy bus battery based on the data dynamic waveform diagram to obtain battery stability data, and then the battery stability data is matched with a preset battery fatigue condition evaluation standard to obtain battery fatigue information corresponding to each new energy bus battery.

[0043] In the embodiments of the present application, steady-state analysis refers to the process of evaluating and analyzing the performance of the battery in a stable output state. Since the battery cannot immediately reach a stable output state during the initial operation stage, it is necessary to determine the corresponding output data of the battery in a stable output state, i.e., the battery stability data, based on the data dynamic waveform diagram.

[0044] For the embodiment of the present application, the preset battery fatigue condition assessment standard of the new energy bus battery includes the following aspects: Battery capacity decay: Battery capacity is one of the main indicators for evaluating battery health and fatigue. Generally, a battery capacity that is maintained at more than 80% of the initial capacity is considered to be in a relatively healthy state. As the battery is used for a longer period of time, the battery capacity will gradually decay, and the degree of decay directly reflects the battery's fatigue condition.

[0045] Battery internal resistance changes: Battery internal resistance will increase as the battery ages, and the increase in internal resistance will lead to a decrease in operating power and cycle times. Therefore, battery internal resistance is also an important parameter for evaluating battery fatigue. For different types of batteries, the specific threshold of internal resistance increase may be different, but generally speaking, a significant increase in internal resistance means that the battery health has significantly decreased.

[0046] Cyclic charge and discharge performance: As the number of cycles increases, the battery's charge and discharge performance will gradually decrease. By testing parameters such as charge and discharge rate, discharge time, and discharge voltage curve, the battery's cyclic charge and discharge performance can be evaluated, thereby reflecting the battery's fatigue condition.

[0047] Vibration fatigue life: For battery packs in new energy vehicles and other application scenarios, vibration fatigue life is an important evaluation indicator. By simulating the vibration environment under actual working conditions and evaluating the fatigue damage and life of the battery pack under long-term vibration loading, its reliability and durability in actual use can be predicted.

[0048] According to the following aspects, this application collects the operating data of the battery during actual use, such as the changes in parameters such as voltage, current, and temperature, and uses data analysis tools to perform data mining and pattern recognition to discover the laws and trends of battery performance degradation, thereby evaluating the fatigue condition of the battery. The preset battery fatigue condition evaluation standards include four levels: excellent, good, general, and poor. Each level covers the dynamic change range of different battery parameter data. The current battery stability data is matched with the dynamic change range of the parameter data to obtain the battery fatigue information of the current battery.

[0049] Step S14: Match the battery fatigue information with a preset battery fatigue charging standard to obtain a battery charging plan for the battery fatigue information.

[0050] In an embodiment of the present application, the optimal charging scheme corresponding to different levels of battery fatigue is determined by adopting the technical means of big data analysis, and the optimal charging scheme is bound to the corresponding battery fatigue level to form a preset battery fatigue charging standard. The specific big data analysis method records the standard charging method corresponding to the first charging of a new battery. And as the battery stability data changes, the standard charging method is adjusted to different schemes to determine the optimal charging scheme that meets the stable output of the battery. Among them, the optimal charging scheme includes: early charging power and early charging period, mid-term charging power and mid-term charging period, late charging power and late charging period.

[0051] Step S15: Generate a charging control instruction according to the battery charging plan to control the strong and weak current conversion time nodes of the charging pile when charging the new energy bus battery.

[0052] For the embodiment of the present application, when charging the new energy bus, the data of the dual dimensions of operation and charging of the new energy bus are captured comprehensively and accurately. It not only covers the power performance of the battery at different stages of use, but also records the charging data of the charging pile in detail, laying a solid foundation for subsequent accurate analysis. The information sorted by time nodes enables the operating power and charging data of the same new energy bus to correspond seamlessly, providing an intuitive basis for the changes in battery performance over the use cycle. The establishment of this correspondence greatly simplifies the complexity of data analysis and improves the efficiency and accuracy of the analysis. At the same time, it can accurately identify the specific operating status of the battery of each new energy bus during the first and non-first charging. It provides key input for subsequent battery fatigue analysis, making the analysis results closer to actual use, which is of great significance for optimizing battery management strategies and extending battery life. The introduced fatigue analysis method can deeply analyze the attenuation of battery performance with the number of uses. By carefully comparing the initial and non-initial battery operating power, the system can accurately calculate the battery fatigue information, match the battery fatigue information with the preset standard, and automatically generate a personalized battery charging plan. It not only realizes the intelligent control of the charging process, but also dynamically adjusts the charging strategy according to the actual condition of the battery, effectively avoiding damage to the battery due to overcharging or over-discharging, further extending the battery life, and improving charging efficiency and safety. According to the charging control instructions finally generated, the strong and weak current conversion time nodes of the charging pile during the charging process can be accurately controlled. This precise control strategy not only optimizes the charging process and improves charging efficiency, but also reduces unnecessary energy waste and reduces operating costs, thereby improving the battery application efficiency of new energy buses.

[0053] A possible implementation method of an embodiment of the present application is to match the battery fatigue information with a preset battery fatigue charging standard to obtain a battery charging plan for the battery fatigue information, which also includes: determining the abnormal fatigue information of the battery with fatigue abnormality according to the preset battery fatigue charging standard, and then determining the abnormal fatigue limit data corresponding to the abnormal fatigue information of the battery in the preset battery fatigue condition assessment standard, and then judging whether the battery stability data is consistent with the abnormal fatigue limit data. If consistent, then generating battery maintenance information based on the new energy bus battery in the battery stability data and the consistent abnormal data, and sending the battery maintenance information to the target terminal.

[0054] Specifically, if the battery stability data does not match the abnormal fatigue limit data, the battery stability data is sorted in an unsupervised time series based on the time series length in the data dynamic waveform diagram to obtain battery matrix data, and then the battery matrix data is analyzed for data periodicity to generate future battery matrix data, and then the data contained in the future battery matrix data is processed to obtain deduction matrix data, and the obtained deduction matrix data is input into a preset algorithm model for data extrapolation to obtain future battery stability data of different new energy bus batteries within a preset future time, determine the future abnormal time nodes in the future battery stability data that meet the abnormal fatigue limit data, and generate remaining maintenance time information based on the current time node and the future abnormal time node.

[0055] In the embodiment of the present application, the preset algorithm model includes a bidirectional LSTM prediction model.

[0056] Specifically, the basic data distribution of the battery matrix data is explored to determine the relative periodicity of the battery stability data when changes occur, and the length of the time period is determined based on the relative periodicity. Then, the battery matrix data is supervised time series data sorted based on the time period length to obtain data periodicity data. Then, based on the data periodicity data, the change trend of the battery stability data in a preset time period in the future is predicted to generate future battery matrix data.

[0057] The following is an introduction to a new energy bus charging monitoring system provided by an embodiment of the present application. The new energy bus charging monitoring system described below and the new energy bus charging monitoring method described above can be referred to each other. Please refer to Figure 2 , Figure 2 : is a structural diagram of a new energy bus charging monitoring system 20 provided in an embodiment of the present application, including: The information acquisition module 21 is used to acquire vehicle operation information and vehicle charging information. The vehicle operation information includes the initial operation power of the battery during the first operation of different new energy buses and the non-initial operation power of the battery during the non-first operation. The vehicle charging information includes the initial charging data of the charging pile when charging different new energy buses for the first time and the non-initial charging data when charging for the non-first time. The information sorting module 22 is used to sort the vehicle operation information and the vehicle charging information according to the time nodes, and determine the corresponding relationship between the initial operation power and the non-initial operation power in the vehicle operation information of the same new energy bus and the initial charging data and the non-initial charging data in the vehicle charging information; The power determination module 23 is used to determine the initial battery operating power corresponding to the initial charging data when each new energy bus is charged for the first time and the non-initial battery operating power corresponding to the non-initial charging data when charging is not performed for the first time according to the corresponding relationship; A fatigue analysis module 24 is used to perform fatigue analysis on the initial battery operating power and the non-initial battery operating power to obtain battery fatigue information corresponding to each new energy bus battery; A solution determination module 25, used to match the battery fatigue information with a preset battery fatigue charging standard to obtain a battery charging solution for the battery fatigue information; The charging control module 26 is used to generate charging control instructions according to the battery charging plan, and control the strong and weak current conversion time nodes of the charging pile when charging the battery of the new energy bus.

[0058] In a possible implementation method in the embodiment of the present application, the information sorting module 22 sorts the vehicle operation information and the vehicle charging information according to the time nodes, and determines the correspondence between the initial operation power and the non-initial operation power in the vehicle operation information of the same new energy bus and the initial charging data and the non-initial charging data in the vehicle charging information, specifically for: Create multiple data monitoring coordinate systems, where the X-axes of the multiple data monitoring coordinate systems are all different time nodes, and the Y-axes of the multiple data monitoring coordinate systems are different units of operating power and different units of battery charging data. The number of multiple data coordinate systems is consistent with the number of new energy buses to be monitored; Bind multiple data monitoring coordinate systems to each new energy bus in a one-to-one correspondence, and map the initial operating power, non-initial operating power, initial charging data, and non-initial charging data corresponding to each new energy bus to the corresponding data monitoring coordinate system according to the time node, to obtain the operating data coordinate system corresponding to each new energy bus; Determine, according to the operation data coordinate system, an initial operation waveform segment corresponding to the initial operation power, a non-initial operation waveform segment of the non-initial operation power, an initial charging waveform segment corresponding to the initial charging data, and a non-initial charging waveform segment of the non-initial charging data; The initial operation waveform segment, non-initial operation waveform segment, initial charging waveform segment and non-initial charging waveform segment are subjected to distribution correlation binding analysis to determine the correspondence between the initial operation power and non-initial operation power in the vehicle operation information and the initial charging data and non-initial charging data in the vehicle charging information of the same new energy bus.

[0059] Another possible implementation method in the embodiment of the present application is that the information sorting module 22 performs distribution association binding analysis on the initial operation waveform segment, the non-initial operation waveform segment, the initial charging waveform segment and the non-initial charging waveform segment to determine the correspondence between the initial operation power and the non-initial operation power in the vehicle operation information of the same new energy bus and the initial charging data and the non-initial charging data in the vehicle charging information, specifically for: Determine an operating waveform segment existing before an initial time node of the initial charging waveform segment, and bind the existing operating waveform segment to the initial charging waveform segment to obtain a first corresponding relationship between initial charging data and initial operating power and / or non-initial operating power; Determine a first non-initial charging waveform segment adjacent to the initial charging waveform segment, and bind the non-initial operation waveform segment between the initial charging waveform segment and the first non-initial charging waveform segment to the first non-initial charging waveform segment to obtain a second corresponding relationship between the non-initial charging data corresponding to the first non-initial charging waveform segment and the non-initial operation power; Determine a second non-initial charging waveform segment adjacent to the first non-initial charging waveform segment, and bind the non-initial operation waveform segment between the first non-initial charging waveform segment and the second non-initial charging waveform segment to the second non-initial charging waveform segment to obtain a third corresponding relationship between the non-initial charging power and the non-initial operation power corresponding to the second non-initial charging waveform segment; Determine a second non-initial charging waveform segment set that is not adjacent to the initial charging waveform segment, and bind the non-initial operation waveform segment between every two adjacent non-initial charging waveform segments in the second non-initial charging waveform segment set with the non-initial charging waveform segment that is time-postponed from the adjacent non-initial charging waveform segment, to obtain a fourth corresponding relationship between non-initial charging data corresponding to each non-initial charging waveform segment in the second non-initial charging waveform segment set and the non-initial operation power; The correspondence between the initial operating power and the non-initial operating power in the vehicle operating information and the initial charging data and the non-initial charging data in the vehicle charging information of the same new energy bus is determined according to the first corresponding relationship, the second corresponding relationship, the third corresponding relationship and the fourth corresponding relationship.

[0060] In another possible implementation of the embodiment of the present application, the fatigue analysis module 24 performs fatigue analysis on the initial battery operating power and the non-initial battery operating power to obtain the battery fatigue information corresponding to each new energy bus battery, specifically for: Performing feature analysis on a first operation waveform segment corresponding to the initial battery operation power and a plurality of second operation waveform segments corresponding to the non-initial battery operation power to obtain first operation feature data corresponding to the first operation waveform segment and a set of second operation feature data corresponding to the plurality of second operation waveform segments; Based on the fingerprint algorithm, the first running feature data and the second running feature data are combined to generate a first running hash object, and the data format of the first running hash object is converted into a byte stream format to obtain a second running hash object; According to the fingerprint algorithm, the second operation hash object generates a reference operation data fingerprint and a fatigue monitoring operation data fingerprint set, and the fatigue monitoring operation data fingerprint set is compared with the reference operation data fingerprint one by one to obtain the operation change data of each new energy bus battery in different time periods after each charging; According to the operation change data, the output current, voltage and power of each new energy bus battery are identified to obtain the parameter change data of different attribute parameters; Draw a data dynamic waveform diagram of parameter change data of different attribute parameters, and conduct a steady-state analysis on the corresponding new energy bus battery based on the data dynamic waveform diagram to obtain battery stability data; The battery stability data is matched with the preset battery fatigue condition assessment standard to obtain the battery fatigue information corresponding to each new energy bus battery.

[0061] In another possible implementation of the embodiment of the present application, the system 20 further includes: a first determination module, a second determination module, and a maintenance generation module, wherein: A first determination module is used to determine abnormal fatigue information of a battery with abnormal fatigue according to a preset battery fatigue charging standard; A second determination module is used to determine abnormal fatigue limit data corresponding to abnormal fatigue information of the battery in a preset battery fatigue condition assessment standard; The maintenance generation module is used to determine whether the battery stability data is consistent with the abnormal fatigue limit data. If it is consistent, the battery maintenance information is generated based on the new energy bus battery in the battery stability data and the consistent abnormal data, and the battery maintenance information is sent to the target terminal.

[0062] In another possible implementation of the embodiment of the present application, when the maintenance generation module determines whether the battery stability data is consistent with the abnormal fatigue limit data, it is specifically used to: If the battery stability data does not match the abnormal fatigue limit data, the battery stability data is sorted in an unsupervised time series based on the time series length in the data dynamic waveform diagram to obtain the battery matrix data; Analyze the periodicity of battery matrix data and generate future battery matrix data; Process the data contained in the future battery matrix data to obtain deduction matrix data, and input the obtained deduction matrix data into a preset algorithm model for data calculation to obtain future battery stability data of different new energy bus batteries within a preset time in the future; Determine the future abnormal time nodes in the future battery stability data that meet the abnormal fatigue limit data, and generate the remaining maintenance time information based on the current time node and the future abnormal time node.

[0063] In another possible implementation of the embodiment of the present application, the maintenance generation module is specifically used to perform data periodicity regularity analysis on the battery matrix data and generate future battery matrix data: Conduct basic data distribution exploration on battery matrix data, determine the relative periodicity of battery stability data when changes occur, and determine the length of the time period based on the relative periodicity; The battery matrix data is sorted in a supervised time series based on the length of the time period to obtain the data periodic regularity data; Based on the data cycle regularity data, the battery stability data change trend within the future preset time period is predicted to generate future battery matrix data.

[0064] The present application embodiment provides an electronic device, such as Figure 3 As shown, Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application, Figure 3 The electronic device 300 shown includes: a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, the electronic device 300 may also include a transceiver 304. It should be noted that in actual applications, the transceiver 304 is not limited to one, and the structure of the electronic device 300 does not constitute a limitation on the embodiments of the present application.

[0065] The processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of the embodiments of the present application. The processor 301 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like.

[0066] The bus 302 may include a path to transmit information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0067] The memory 303 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0068] The memory 303 is used to store application code for executing the solution of the embodiment of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the content shown in the above method embodiment.

[0069] Among them, electronic devices include but are not limited to: mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 3 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0070] A computer-readable storage medium provided in an embodiment of the present application is introduced below. The computer-readable storage medium described below and the method described above can be referenced to each other.

[0071] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned new energy bus charging monitoring method are implemented.

[0072] Since the embodiments of the computer-readable storage medium part and the embodiments of the method part correspond to each other, the embodiments of the computer-readable storage medium part refer to the description of the embodiments of the method part.

[0073] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0074] The above are only some implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A new energy bus charging monitoring method, characterized in that: include: Obtain vehicle operation information and vehicle charging information, wherein the vehicle operation information includes the initial operation power of the battery during the first operation of different new energy buses and the non-initial operation power of the battery during the non-first operation, and the vehicle charging information includes the initial charging data of the charging pile when charging different new energy buses for the first time and the non-initial charging data when charging for the non-first time; The vehicle operation information and the vehicle charging information are sorted according to time nodes respectively, and the corresponding relationship between the initial operation power and the non-initial operation power in the vehicle operation information and the initial charging data and the non-initial charging data in the vehicle charging information of the same new energy bus is determined; Determine, according to the corresponding relationship, the initial battery operating power corresponding to the initial charging data when each new energy bus is charged for the first time and the non-initial battery operating power corresponding to the non-initial charging data when charging is not performed for the first time; Performing fatigue analysis on the initial battery operating power and the non-initial battery operating power to obtain battery fatigue information corresponding to each new energy bus battery; Matching the battery fatigue information with a preset battery fatigue charging standard to obtain a battery charging solution for the battery fatigue information; A charging control instruction is generated according to the battery charging scheme to control the strong and weak current conversion time nodes of the charging pile when charging the battery of the new energy bus.

2. A new energy bus charging monitoring method according to claim 1, characterized in that: The method of respectively arranging the vehicle operation information and the vehicle charging information according to time nodes, and determining the correspondence between the initial operation power and the non-initial operation power in the vehicle operation information of the same new energy bus and the initial charging data and the non-initial charging data in the vehicle charging information, includes: Create multiple data monitoring coordinate systems, wherein the X-axes of the multiple data monitoring coordinate systems are all different time nodes, the Y-axes of the multiple data monitoring coordinate systems are different units of operating power and different units of battery charging data, and the number of the multiple data coordinate systems is consistent with the number of new energy buses to be monitored; Bind the multiple data monitoring coordinate systems to each new energy bus in a one-to-one correspondence, and map the initial operating power, the non-initial operating power, the initial charging data, and the non-initial charging data corresponding to each new energy bus to the corresponding data monitoring coordinate system according to the time node, to obtain the operating data coordinate system corresponding to each new energy bus; Determine, according to the operation data coordinate system, an initial operation waveform segment corresponding to the initial operation power, a non-initial operation waveform segment of the non-initial operation power, an initial charging waveform segment corresponding to the initial charging data, and a non-initial charging waveform segment of the non-initial charging data; A distribution correlation binding analysis is performed on the initial operation waveform segment, the non-initial operation waveform segment, the initial charging waveform segment and the non-initial charging waveform segment to determine the correspondence between the initial operation power and the non-initial operation power in the vehicle operation information and the initial charging data and the non-initial charging data in the vehicle charging information of the same new energy bus.

3. A new energy bus charging monitoring method according to claim 2, characterized in that: The distribution correlation binding analysis is performed on the initial operation waveform segment, the non-initial operation waveform segment, the initial charging waveform segment, and the non-initial charging waveform segment to determine the correspondence between the initial operation power and the non-initial operation power in the vehicle operation information of the same new energy bus and the initial charging data and the non-initial charging data in the vehicle charging information, including: Determine an operating waveform segment existing before an initial time node of the initial charging waveform segment, and bind the existing operating waveform segment to the initial charging waveform segment to obtain a first corresponding relationship between the initial charging data and the initial operating power and / or the non-initial operating power; Determine a first non-initial charging waveform segment adjacent to the initial charging waveform segment, and bind a non-initial operation waveform segment between the initial charging waveform segment and the first non-initial charging waveform segment with the first non-initial charging waveform segment to obtain a second corresponding relationship between non-initial charging data corresponding to the first non-initial charging waveform segment and the non-initial operation power; Determine a second non-initial charging waveform segment adjacent to the first non-initial charging waveform segment, and bind the non-initial operation waveform segment between the first non-initial charging waveform segment and the second non-initial charging waveform segment with the second non-initial charging waveform segment to obtain a third corresponding relationship between the non-initial charging corresponding to the second non-initial charging waveform segment and the non-initial operation power; Determine a second non-initial charging waveform segment set that is not adjacent to the initial charging waveform segment, and bind a non-initial operation waveform segment between every two adjacent non-initial charging waveform segments in the second non-initial charging waveform segment set with a non-initial charging waveform segment that is positioned later in time than the adjacent non-initial charging waveform segment, to obtain a fourth corresponding relationship between non-initial charging data corresponding to each non-initial charging waveform segment in the second non-initial charging waveform segment set and non-initial operation power; The correspondence between the initial operating power and the non-initial operating power in the vehicle operating information and the initial charging data and the non-initial charging data in the vehicle charging information of the same new energy bus is determined according to the first corresponding relationship, the second corresponding relationship, the third corresponding relationship and the fourth corresponding relationship.

4. A new energy bus charging monitoring method according to claim 1, characterized in that: The fatigue analysis of the initial battery operating power and the non-initial battery operating power is performed to obtain the battery fatigue information corresponding to each new energy bus battery, including: Performing feature analysis on a first operation waveform segment corresponding to the initial battery operation power and a plurality of second operation waveform segments corresponding to the non-initial battery operation power to obtain first operation feature data corresponding to the first operation waveform segment and a set of second operation feature data corresponding to the plurality of second operation waveform segments; Based on a fingerprint algorithm, the first running feature data and the second running feature data are combined to generate a first running hash object, and the data format of the first running hash object is converted into a byte stream format to obtain a second running hash object; According to the fingerprint algorithm, the second operation hash object generates a reference operation data fingerprint and a fatigue monitoring operation data fingerprint set, and the fatigue monitoring operation data fingerprint set is compared with the reference operation data fingerprint one by one to obtain the operation change data of each new energy bus battery in different time periods after each charging; Identify the output current, voltage and power of each new energy bus battery according to the operation change data to obtain parameter change data of different attribute parameters; Draw a data dynamic waveform diagram of parameter change data of different attribute parameters, and perform a steady-state analysis on the corresponding new energy bus battery based on the data dynamic waveform diagram to obtain battery stability data; The battery stability data is matched with a preset battery fatigue condition evaluation standard to obtain the battery fatigue information corresponding to each new energy bus battery.

5. A new energy bus charging monitoring method according to claim 4, characterized in that: The matching of the battery fatigue information with a preset battery fatigue charging standard to obtain a battery charging solution for the battery fatigue information also includes: Determining abnormal fatigue information of a battery having abnormal fatigue according to the preset battery fatigue charging standard; Determining abnormal fatigue limit data corresponding to the abnormal fatigue information of the battery in the preset battery fatigue condition assessment standard; Determine whether the battery stability data is consistent with the abnormal fatigue limit data. If consistent, generate battery maintenance information based on the new energy bus battery in the battery stability data and the consistent abnormal data, and send the battery maintenance information to the target terminal.

6. A new energy bus charging monitoring method according to claim 5, characterized in that: The determining whether the battery stability data is consistent with the abnormal fatigue limit data includes: If the battery stability data does not match the abnormal fatigue limit data, unsupervised time series data sorting is performed on the battery stability data based on the time series length in the data dynamic waveform diagram to obtain battery matrix data; Performing data periodicity analysis on the battery matrix data to generate future battery matrix data; Processing the data contained in the future battery matrix data to obtain deduction matrix data, and inputting the obtained deduction matrix data into a preset algorithm model for data calculation to obtain future battery stability data of different new energy bus batteries within a preset time in the future; Determine a future abnormal time node in the future battery stability data that meets the abnormal fatigue limit data, and generate remaining maintenance duration information according to the current time node and the future abnormal time node.

7. A new energy bus charging monitoring method according to claim 6, characterized in that: The step of performing data periodicity analysis on the battery matrix data to generate future battery matrix data includes: Performing basic data distribution exploration on the battery matrix data to determine the relative periodicity of the battery stability data when changes occur, and determining the length of the time period based on the relative periodicity; Performing supervised time series data sorting on the battery matrix data based on the time period length to obtain data period regularity data; Based on the data cycle regularity data, the battery stability data change trend within a future preset time period is predicted to generate future battery matrix data.

8. A new energy bus charging monitoring system, characterized in that: include: An information acquisition module, used to acquire vehicle operation information and vehicle charging information, wherein the vehicle operation information includes the initial operation power of the battery during the first operation of different new energy buses and the non-initial operation power of the battery during the non-first operation, and the vehicle charging information includes the initial charging data of the charging pile when charging different new energy buses for the first time and the non-initial charging data when charging for the non-first time; An information sorting module, used to sort the vehicle operation information and the vehicle charging information according to time nodes, and determine the correspondence between the initial operation power and the non-initial operation power in the vehicle operation information and the initial charging data and the non-initial charging data in the vehicle charging information of the same new energy bus; A power determination module, used to determine, according to the corresponding relationship, the initial battery operating power corresponding to the initial charging data when each new energy bus is charged for the first time and the non-initial battery operating power corresponding to the non-initial charging data when charging is not performed for the first time; A fatigue analysis module, used to perform fatigue analysis on the initial battery operating power and the non-initial battery operating power to obtain battery fatigue information corresponding to each new energy bus battery; A scheme determination module, used for matching the battery fatigue information with a preset battery fatigue charging standard to obtain a battery charging scheme for the battery fatigue information; The charging control module is used to generate charging control instructions according to the battery charging scheme, and control the strong and weak current conversion time nodes of the charging pile when charging the battery of the new energy bus.

9. An electronic device, characterized in that: The electronic device includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute a new energy bus charging monitoring method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: include: A computer program is stored which can be loaded by a processor and execute a new energy bus charging monitoring method as described in any one of claims 1-7.

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