Diagnostic method of battery pack and vehicle battery pack detection system

Abstract

The invention relates to the field of automobile diagnosis, in particular to a battery pack diagnosis method and a vehicle battery pack detection system.The battery pack diagnosis method comprises the steps that multiple items of data of a to-be-diagnosed battery pack are received, and the multiple items of data of the to-be-diagnosed battery pack are obtained through transmission of a data transmission interface; performing data analysis on the multiple items of data of the to-be-diagnosed battery pack to obtain target data of the to-be-diagnosed battery pack; determining target protocol data according to the target data of the to-be-diagnosed battery pack; and issuing the target protocol data to the automobile diagnostic apparatus, so that the automobile diagnostic apparatus performs diagnosis according to the target protocol data. According to the method, multiple items of data of the to-be-diagnosed battery pack are received and analyzed, and the target protocol data are automatically generated and issued to the automobile diagnosis instrument, so that the battery pack diagnosis method which is efficient, accurate, high in compatibility and simplified in operation is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of automobile diagnosis, and in particular to a battery pack diagnosis method and a vehicle battery pack detection system. Background Art

[0002] Against the backdrop of the rapid development of the new energy electric vehicle industry, the market share of new energy vehicles continues to rise. At the same time, the life, safety and fault detection of battery packs, a key component of electric vehicles, have become the focus of public and industry attention. In response to this demand, many automakers and battery pack suppliers have developed specialized testing software to evaluate the life, safety and fault conditions of battery packs. However, testing software is often not universal, which means that maintenance technicians need to prepare and use multiple different testing software during the vehicle maintenance process, which not only increases the difficulty of setting up the test environment, but also greatly reduces the efficiency of maintenance work.

[0003] Although traditional automotive diagnostic instruments can integrate battery pack information of different brands and models, users need to select through complex multi-level menus during use, including vehicle brand, model, vehicle model, battery pack brand and model, etc., before entering the corresponding detection process. However, this solution has obvious shortcomings: first, it is often difficult for users to accurately provide all the information they need, resulting in multiple attempts to find the correct diagnostic path; second, with the continuous launch of new car models and battery models on the market, automotive diagnostic instruments need to be continuously updated to cover the latest vehicle and battery pack brands, which increases the difficulty of maintenance and updating. Summary of the invention

[0004] One purpose of an embodiment of the present invention is to provide a battery pack diagnostic method and a vehicle battery pack detection system, which are used to solve the technical problems of multi-brand special inspection software not being universal, complex and error-prone diagnostic paths, and poor adaptability during the diagnosis of new energy vehicle battery packs.

[0005] In a first aspect, an embodiment of the present invention provides a battery pack diagnostic method, which is applied to a server of a vehicle battery pack detection system, wherein the vehicle battery pack detection system further includes a data transmission interface and a vehicle diagnostic instrument, and the method includes:

[0006] receiving a plurality of data of the battery pack to be diagnosed, wherein the plurality of data of the battery pack to be diagnosed is transmitted by the data transmission interface;

[0007] Analyze multiple data of the battery pack to be diagnosed to obtain target data of the battery pack to be diagnosed;

[0008] Determining target protocol data according to target data of the battery pack to be diagnosed;

[0009] The target protocol data is sent to the vehicle diagnostic instrument so that the vehicle diagnostic instrument performs diagnosis according to the target protocol data.

[0010] In a second aspect, an embodiment of the present invention provides a battery pack diagnostic method, wherein the vehicle battery pack detection system further includes a data transmission interface, and the method includes:

[0011] receiving a plurality of data of the battery pack to be diagnosed, wherein the plurality of data of the battery pack to be diagnosed is transmitted by the data transmission interface;

[0012] Analyze multiple data of the battery pack to be diagnosed to obtain target data of the battery pack to be diagnosed;

[0013] Determining target protocol data according to target data of the battery pack to be diagnosed;

[0014] A diagnosis is performed based on the target protocol data.

[0015] In a third aspect, a vehicle battery pack detection system is provided, comprising a server and an automobile diagnostic instrument; the server comprises a first memory and a first processor, the first memory is connected to the first processor, the first processor is used to execute one or more computer programs stored in the first memory, and when the first processor executes the one or more computer programs, the server implements the battery pack diagnosis method as described in the first aspect; the automobile diagnostic instrument comprises a second memory and a second processor, the second memory is connected to the second processor, the second processor is used to execute one or more computer programs stored in the second memory, and when the second processor executes the one or more computer programs, the automobile diagnostic instrument implements the battery pack diagnosis method as described in the second aspect.

[0016] In a fourth aspect, an embodiment of the present invention provides a battery pack diagnostic device, which is applied to a server of a vehicle battery pack detection system, wherein the vehicle battery pack detection system further includes a data transmission interface and a vehicle diagnostic instrument, and the device includes:

[0017] A receiving unit, used for receiving a plurality of data of the battery pack to be diagnosed, wherein the plurality of data of the battery pack to be diagnosed is transmitted by the data transmission interface;

[0018] an analyzing unit, configured to analyze a plurality of data of the battery pack to be diagnosed to obtain target data of the battery pack to be diagnosed;

[0019] A determination unit, configured to determine target protocol data according to target data of the battery pack to be diagnosed;

[0020] The sending unit is used to send the target protocol data to the vehicle diagnostic instrument, so that the vehicle diagnostic instrument performs diagnosis according to the target protocol data.

[0021] In a fifth aspect, an embodiment of the present invention provides a battery pack diagnostic device, which is applied to a vehicle diagnostic instrument of a vehicle battery pack detection system, and the device includes:

[0022] A receiving unit, used for receiving a plurality of data of the battery pack to be diagnosed, wherein the plurality of data of the battery pack to be diagnosed is transmitted by the data transmission interface;

[0023] an analyzing unit, configured to analyze a plurality of data of the battery pack to be diagnosed to obtain target data of the battery pack to be diagnosed;

[0024] A determination unit, configured to determine target protocol data according to target data of the battery pack to be diagnosed;

[0025] A diagnostic unit, configured to perform diagnosis according to the target protocol data. In a sixth aspect, an embodiment of the present invention provides a computer-readable storage medium, comprising a first computer-readable storage medium and a second computer-readable storage medium, wherein the first computer-readable storage medium stores a first computer program, wherein the first computer program includes a first program instruction, and when the first program instruction is executed by a first processor, the first processor executes the battery pack diagnostic method as described in the first aspect; and the second computer-readable storage medium stores a second computer program, wherein the second computer program includes a second program instruction, and when the second program instruction is executed by a second processor, the second processor executes the battery pack diagnostic method as described in the second aspect.

[0026] In the embodiments of the battery pack diagnostic method and vehicle battery pack detection system described above, multiple data of the battery pack to be diagnosed are first received, and the multiple data of the battery pack to be diagnosed are transmitted by the data transmission interface. Secondly, the multiple data of the battery pack to be diagnosed are analyzed to obtain the target data of the battery pack to be diagnosed. Then, the target protocol data is determined based on the target data of the battery pack to be diagnosed. Finally, the target protocol data is sent to the vehicle diagnostic instrument so that the vehicle diagnostic instrument performs diagnosis based on the target protocol data. This embodiment automatically receives multiple data of the battery pack to be diagnosed through the data transmission interface, reduces the need for manual input, improves the efficiency and accuracy of data collection, and further performs in-depth analysis on the multiple data received to ensure that key battery pack target data is extracted from a large amount of information, thereby improving the accuracy and reliability of the diagnosis; further, protocol data is generated according to the target data without the need for manual writing or configuration, which greatly simplifies the preparation work before diagnosis and improves work efficiency, and by analyzing the generated protocol data, the target protocol data is determined to ensure the compatibility of the protocol used in the diagnosis process with the battery pack, thereby improving the accuracy of the diagnosis; therefore, this solution enables users to manually select complex information such as vehicle brand, model, and vehicle model without the need for manual selection. The system automatically processes the information, greatly simplifies the operating process, and can adapt to battery packs of different brands and models. There is no need to develop a separate diagnostic solution for each battery pack, which enhances the versatility and adaptability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0028] Figure 1 is a schematic diagram of a vehicle battery pack detection system in one embodiment of the present invention;

[0029] Figure 2 is a flow chart of a battery pack diagnosis method according to an embodiment of the present invention;

[0030] Figure 3 is a flow chart of another battery pack diagnosis method according to an embodiment of the present invention;

[0031] Figure 4 is a schematic structural diagram of a battery pack diagnostic device in one embodiment of the present invention;

[0032] Figure 5 It is a schematic structural diagram of another battery pack diagnostic device in one embodiment of the present invention. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical scheme and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0034] It should be noted that, if there is no conflict, the various features in the embodiments of the present invention can be combined with each other, all within the scope of protection of the present invention. In addition, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in a different order from the module division in the device or the flow chart. Furthermore, the words "first", "second", "third", etc. used in the present invention do not limit the data and execution order, but only distinguish the same items or similar items with basically the same functions and effects.

[0035] See also Figure 1 , Figure 1 This is a schematic diagram of a vehicle battery pack detection system provided in an embodiment of the present application, wherein the vehicle battery pack detection system 10 includes a battery pack to be diagnosed 20, a data transmission interface 30, a server 40 and a vehicle diagnostic instrument 50.

[0036] The battery pack 20 to be diagnosed refers to the battery pack of the electric vehicle that needs to be tested and evaluated; it usually includes multiple battery cells, a battery management system (BMS), a temperature sensor, a voltage and current sensor, etc. The battery pack 20 is responsible for storing and providing electrical energy and is one of the core components of the electric vehicle. Its health status is directly related to the vehicle's endurance and safety.

[0037] Among them, the data transmission interface 30 can receive data transmitted by the interface corresponding to the vehicle ECU, the vehicle OBD diagnostic port, and the battery pack diagnostic port. Specifically, the vehicle ECU (electronic control unit) is a core computing component of the vehicle, responsible for collecting and processing data from various sensors and systems of the vehicle, including the status information of the battery pack; the vehicle OBD diagnostic port is a standard interface on the vehicle for external devices to connect to the vehicle's electronic control unit to read fault codes and real-time data streams; the battery pack diagnostic port is an interface specifically used for battery pack diagnosis, which may provide more detailed battery pack data, such as the voltage and temperature of a single battery cell. Therefore, the main function of the data transmission interface 30 is to transmit the data of the battery pack 20 to be diagnosed to the server 40 through the vehicle diagnostic instrument 50 for further analysis and processing.

[0038] Among them, the server 40 is the core processing unit of the vehicle battery pack detection system, which is responsible for receiving data from the data transmission interface 30; the server 40 may include a database for storing diagnostic protocols and historical diagnostic data of battery packs of different brands and models. The software running on the server 40 can perform intelligent analysis on the received data, generate a diagnostic report, and send the diagnostic results or instructions back to the vehicle diagnostic instrument 50.

[0039] Among them, the automobile diagnostic instrument 50 is a device for performing diagnostic operations, which can be directly connected to the vehicle's OBD diagnostic port or battery pack diagnostic port; the diagnostic instrument 50 usually has a display screen and an operation interface, allowing maintenance technicians to interact with the system, execute diagnostic processes, and view diagnostic results; according to the target protocol data sent by the server 40, the automobile diagnostic instrument 50 can perform specific diagnostic tests, such as battery balancing tests, charge and discharge efficiency tests, etc.

[0040] Therefore, in the vehicle battery pack detection system, the specific process can be: the server of the vehicle battery pack detection system receives multiple data of the battery pack to be diagnosed, and the multiple data of the battery pack to be diagnosed are obtained by transmitting the data transmission interface; the multiple data of the battery pack to be diagnosed are analyzed to obtain the target data of the battery pack to be diagnosed; the target protocol data is determined according to the target data of the battery pack to be diagnosed; and the target protocol data is sent to the vehicle diagnostic instrument. Or the vehicle diagnostic instrument of the vehicle battery pack detection system receives multiple data of the battery pack to be diagnosed, and the multiple data of the battery pack to be diagnosed are obtained by transmitting the data transmission interface; the multiple data of the battery pack to be diagnosed are analyzed to obtain the target data of the battery pack to be diagnosed; the target protocol data is determined according to the target data of the battery pack to be diagnosed; and the diagnosis is performed according to the target protocol data.

[0041] Therefore, the entire vehicle battery pack detection system 10 achieves rapid and accurate diagnosis of the electric vehicle battery pack through the coordinated work of these components, provides strong support for maintenance technicians, and ensures the performance of the battery pack and the safe operation of the vehicle.

[0042] In view of this, the present application proposes a battery pack diagnosis method to solve the above problems, which is described in detail below.

[0043] See also Figure 2 , Figure 2 A flowchart of a battery pack diagnostic method provided by an embodiment of the present invention is applied to a server of a vehicle battery pack detection system, wherein the vehicle battery pack detection system further includes a data transmission interface and a vehicle diagnostic instrument. The method includes the following steps:

[0044] S101, receiving multiple data of a battery pack to be diagnosed, wherein the multiple data of the battery pack to be diagnosed are transmitted by the data transmission interface.

[0045] Among them, the above-mentioned multiple data may include but are not limited to the single cell voltage, single cell temperature, total voltage, SOC (State of Charge), SOH (State of Health) and the like of the battery pack.

[0046] Among them, the data transmission interface can receive data transmitted by the vehicle-mounted ECU (electronic control unit), the vehicle OBD (On-Board Diagnostics, on-board automatic diagnostic system) diagnostic port, the battery pack diagnostic port, etc.

[0047] In one embodiment, the data transmission interface device establishes a connection with the ECU or the BMS of the battery pack through a physical connection (such as a cable) or wireless communication (such as Bluetooth, Wi-Fi), and is connected to the automobile diagnostic instrument at the same time. The automobile diagnostic instrument transmits multiple data of the battery pack to be diagnosed to the server, that is, the automobile diagnostic instrument uploads the received multiple data of the battery pack to be diagnosed to the server through its own communication module, which specifically involves the packaging, encryption and transmission of data to ensure the security of data transmission on the Internet.

[0048] Furthermore, after receiving the data uploaded by the car diagnostic instrument, the server will unpack, verify and decrypt the data (if it was previously encrypted), and then store the data on the server for subsequent data analysis and processing.

[0049] It can be seen that the vehicle battery pack detection system in this embodiment can realize data transmission from the battery pack to the server, providing necessary data support for the diagnosis and analysis of the battery pack, ensuring data accuracy and transmission efficiency, and also facilitating remote diagnosis and data analysis.

[0050] S102 , analyzing multiple data of the battery pack to be diagnosed to obtain target data of the battery pack to be diagnosed.

[0051] Optionally, before performing data analysis on the multiple data of the battery pack to be diagnosed, the original data needs to be preprocessed, including cleaning, denoising, normalization, etc., to ensure the quality and consistency of the data.

[0052] The data analysis process may include but is not limited to feature extraction, data analysis methods and target data generation.

[0053] Specifically, the first step of data analysis is feature extraction, that is, identifying and extracting information useful for diagnosis from multiple data. The above features may include the battery charging and discharging curve, temperature change trend, voltage fluctuation, etc. In addition, feature extraction may involve mathematical models and algorithms, such as Fourier transform, wavelet analysis, principal component analysis (PCA), etc., to identify key patterns in the data; data analysis methods may include statistical analysis, machine learning algorithms, pattern recognition, etc. The above analysis methods are used to find out the performance indicators and problems of the battery pack from the preprocessed data. For example, cluster analysis can be used to identify abnormal patterns in the data, and time series analysis can be used to monitor changes in battery performance over time; the target data is the data of multiple data of the battery pack to be diagnosed after frame processing.

[0054] It can be seen that in this embodiment, useful target data is extracted from complex battery pack data. The target data will be used for subsequent diagnosis and analysis to evaluate the health status and performance of the battery pack, thereby ensuring the integrity and accuracy of the data and providing a reliable basis for the diagnosis of the battery pack.

[0055] In one embodiment, the data analysis of the multiple data of the battery pack to be diagnosed is performed to obtain the target data of the battery pack to be diagnosed, including: identifying the frame structure in the multiple data of the battery pack to be diagnosed, and determining the total number of frames of each type of data in the multiple data of the battery pack to be diagnosed; identifying the frame ID set of the frame where each type of data is located and the frame sequence number set of the frame where each type of data is located in the total number of frames of each type of data; obtaining the starting parameter set and the ending parameter set of each type of data in the frame; obtaining the target value corresponding to each type of data according to the starting parameter set and the ending parameter set of each type of data in the frame; matching the frame ID set of the frame where each type of data is located, the frame sequence number set of the frame where each type of data is located, and the target value corresponding to each type of data to obtain the target data of the battery pack to be diagnosed.

[0056] Data is usually transmitted in the form of frames, and each frame contains a certain number of data bits. Identifying the frame structure is to determine how the data is organized in the frame, including the start and end identifiers of the frame, and possible frame synchronization sequences. A data frame usually contains multiple fields, such as frame ID, frame sequence number, data content, checksum, etc.

[0057] Among them, multiple data of the battery pack to be diagnosed are classified into categories, such as voltage data, temperature data, charge and discharge data, etc., and further, the total number of frames contained in each type of data in the entire data transmission process is determined.

[0058] The frame ID is a unique identifier for each data frame, used to distinguish different data frames. The frame sequence number is used to indicate the order of data frames during transmission.

[0059] The start parameter set and the end parameter set define the specific position of the data in the frame, that is, the start and end position of each type of data; the start parameter set is the start byte and the start bit; the end parameter set is the end byte and the end bit. For example, if we are processing the voltage data of a battery cell, the start parameter set may be the third bit of the fifth byte, and the end parameter set may be the seventh bit of the seventh byte.

[0060] The frame ID and frame sequence number of each type of data are associated with its corresponding target value to form a structured data set, so that each type of data can be traced back to its exact location in the original data stream, facilitating further analysis and diagnosis.

[0061] Among them, the target value is the actual value of each type of data.

[0062] For example, the data set of voltage data in the target data is as follows: frame ID: 1, sequence number: 1, data: [voltage 1: 3.7V, voltage 2: 3.65V, voltage 3: 3.72V, voltage 4: 3.68V, temperature 1: 25°C, temperature 2: 26°C, temperature 3: 24°C, temperature 4: 26°C].

[0063] In one embodiment, obtaining the target value corresponding to each type of data based on the starting parameter set and the ending parameter set of each type of data in the frame includes: obtaining the starting parameter set and the ending parameter set of each type of data in the frame to obtain the position segment of each type of data in the frame; calculating the position segment of each type of data in the frame and the starting parameter set and the ending parameter set of each type of data in the frame according to a preset formula to obtain the target value corresponding to each type of data.

[0064] The position segment is the data range that needs to be processed for each type of data. For example, if the start parameter set is the second bit of the second byte and the end parameter set is the eighth bit of the fourth byte, then the position segment starts from the second bit of the second byte and ends at the eighth bit of the fourth byte.

[0065] In a specific implementation, a binary value is extracted bit by bit from the starting parameter set to the ending parameter set, and the binary value represents the original voltage reading. For example, if the starting parameter set is the third bit of the fifth byte, then extraction starts from the third bit of the fifth byte and ends at the seventh bit of the seventh byte; each extracted bit is processed using the calculation formula V=Σf(b), where b is the binary value of each bit, f() is a calculation function for calculating the value of each bit, and V is the final value after summing.

[0066] Specifically, when processing each extracted bit using the calculation formula V = Σf(b), the extracted data is decomposed into individual bits. For example, a byte contains 8 bits, and each bit needs to be processed separately; for the binary value b of each bit, the calculation function f() is applied. This function can be simple, such as directly taking the value of the bit (0 or 1), or it can be a more complex function, such as performing weighted calculations based on the position of the bit or other parameters. The specific implementation of the calculation function f() depends on the characteristics of the data and the diagnostic requirements. For example, it may involve error detection, calculation of check bits, or decoding of specific codes. The results of all bits processed by the calculation function f() are accumulated to obtain the total V.

[0067] For example, assuming there is a 2-byte voltage data whose binary form is 1011 0011, V=f(1)+f(0)+f(1)+f(1)+f(0)+f(0)+f(1)+f(1)=1+0+1+1+0+0+1+1=5.

[0068] It can be seen that in this embodiment, through the data analysis process, a target value can be extracted from the original data frame of the battery pack, and the target value can be used for further diagnosis and analysis to evaluate the health status and performance of the battery pack.

[0069] S103: Determine target protocol data according to the target data of the battery pack to be diagnosed.

[0070] Among them, the protocol data is generated according to the rules of the preset model, and a structured data format contains the necessary information for diagnosing the battery pack, such as the real-time status, historical trends, fault codes, etc. of the battery pack, and also follows specific communication protocols or diagnostic standards to facilitate transmission and understanding between different systems or devices.

[0071] The target protocol data is the protocol data that is ultimately used for diagnosis decision, report generation or further processing.

[0072] In one embodiment, determining the target protocol data according to the target data of the battery pack to be diagnosed includes: generating at least one protocol data according to the target data of the battery pack to be diagnosed; and determining the target protocol data according to the at least one protocol data.

[0073] Among them, based on the generated multiple protocol data, target protocol data that best meets the diagnosis requirements is selected.

[0074] Optionally, if the performance of the preset model is good, any protocol data in the at least one protocol data is directly determined as the target protocol data.

[0075] For example, if the preset model at this time is already able to accurately predict and diagnose the status of the battery pack, then the first protocol data generated can be used as the target protocol data without further screening and verification.

[0076] In one embodiment, generating at least one protocol data based on the target data of the battery pack to be diagnosed includes: extracting data features in the target data of the battery pack to be diagnosed; inputting the data features into a preset model to obtain at least one protocol data, and the at least one protocol data is generated according to preset rules in the preset model.

[0077] Among them, data feature extraction refers to identifying and extracting key information points or attributes from the calculated target data of the battery pack to be diagnosed. Data features may include but are not limited to numerical statistical information, trends, anomalies, patterns, etc., and data features can represent the current state of the battery pack. For example, data features may include the battery's voltage range, current fluctuations, temperature changes, charge and discharge times, etc. The feature extraction process may involve data analysis techniques such as principal component analysis (PCA), cluster analysis, time series analysis, etc.

[0078] Among them, the preset model refers to a model established based on historical data and experience, which can predict the status of the battery pack based on the input data features. The preset model may include but is not limited to machine learning algorithms, such as random forests, neural networks or other statistical methods, which are used to learn the health status of the battery pack from data features.

[0079] The preset rules may be logic judgment, threshold setting, classification decision, etc. The protocol data may be used for: diagnostic report, i.e. providing the diagnostic results of the battery pack; control instructions, i.e. sending instructions to the battery management system (BMS) to adjust the battery working mode; data recording, i.e. storing the historical status information of the battery pack for long-term monitoring and analysis.

[0080] It can be seen that in this embodiment, the original data is converted into information useful for diagnosing the health status of the battery pack, thereby improving the accuracy and efficiency of the diagnosis.

[0081] In one embodiment, determining the target protocol data based on the at least one protocol data includes: sending the at least one protocol data to a display device in the vehicle battery pack detection system; receiving a confirmation instruction from the display device, the confirmation instruction is used to determine the first protocol data in the at least one protocol data; verifying the at least one protocol data to obtain a verification result for each protocol data; obtaining the verification result of the first protocol data; and when the verification result of the first protocol data is passed, determining the first protocol data as the target protocol data.

[0082] The sending process may be to send the selected protocol data to the display device in the vehicle battery pack detection system through a communication interface (such as CAN bus, Ethernet, etc.) to ensure the reliability and integrity of data transmission. The display device may include but is not limited to the screen of the vehicle diagnostic instrument or the console, computer screen or other user interface for displaying data to the operator.

[0083] The confirmation instruction includes the identifier or content of the selected protocol data, and the confirmation instruction can be a click selection, input of a specific code, touch of a button on the screen, or any other form of user input. For example, a user's feedback button (such as thumbs up or thumbs down) on the display interface, thumbs up means confirmation, and thumbs down means negation.

[0084] Among them, the verification process may include checking the data format, checksum, data range, logical consistency, etc. For example, the data parameters of each protocol data in at least one protocol data can be compared with the factory parameters inside the vehicle and the working standard parameters of each component inside the vehicle. If the factory parameters or the working standard parameters are reached, it means that the protocol data verification has passed.

[0085] For example, suppose there is a protocol data containing the voltage, current and temperature parameters of the battery pack. The voltage parameters of the battery pack are compared with the factory voltage standards provided by the vehicle manufacturer. If the voltage value is within the standard range (for example, 12.6 volts to 14.4 volts), the voltage parameter verification is passed; the current parameter of the battery pack is compared with the standard operating current range at the factory. If the current value is within the allowable range (for example, -100 amps to 50 amps), the current parameter verification is passed; the temperature parameter of the battery pack is compared with the standard operating temperature range of each component inside the vehicle. If the temperature value does not exceed the maximum operating temperature (for example, not exceeding 60 degrees Celsius), the temperature parameter verification is passed.

[0086] Therefore, if all parameters have passed the comparison with the factory parameters or working standard parameters, the protocol data is considered to be verified, thereby ensuring that the protocol data is not only formatted correctly but also reasonable in value.

[0087] Further, after the verification process, a verification result corresponding to each protocol data is obtained, which indicates whether the data has passed the verification. The verification result can be a simple pass / fail indication or a detailed error report.

[0088] If the first protocol data passes the verification, it is confirmed to be the target protocol data; if the verification result fails, the server needs to re-analyze the data, adjust the model parameters or take other measures to generate new protocol data.

[0089] It can be seen that in this embodiment, by confirming the instructions and verifying the rules, it is possible to ensure that the protocol data used is accurate and reliable, thereby providing a solid foundation for the maintenance and diagnosis of the battery pack.

[0090] In one embodiment, after the at least one protocol data is verified and a verification result of each protocol data is obtained, the method further includes: in the preset model, dynamically adjusting at least one weight corresponding to the first protocol data according to a preset weight adjustment rule.

[0091] Among them, in the preset model, different data sub-items of each protocol data (such as each byte, each algorithm, each bit, each frame ID, and each frame sequence number) have an initial weight, and these weights are all 1 initially. The initial weight is used to measure the importance or credibility of each protocol data sub-item.

[0092] Among them, the preset weight adjustment rules define under what circumstances the weight should be increased or decreased. If the confirmation instruction is confirmed and the verification result is passed, the weight of the corresponding data sub-item will increase. For example, if the user confirms through the "Like" button, the weight of the relevant data sub-item in the first protocol data may increase from 1 to 1.2; if any negative information appears in the confirmation instruction or verification result, the weight of the corresponding data sub-item may decrease, for example, from 1 to 0.8.

[0093] Among them, the more times users provide feedback through the interface, the more obvious the cumulative effect of weight adjustment will be, that is, as time goes by and more users interact, it can more accurately reflect which data sub-items are more important in the diagnosis process.

[0094] For example, the current protocol data includes: voltage, current, temperature and SOC (state-of-charge) of the battery pack; the initial weight of each parameter is set to 1, that is, voltage (V): weight = 1; current (I): weight = 1; temperature (T): weight = 1; SOC: weight = 1; the preset model analyzes the protocol data and recommends a set of parameter values, which are presented on the display interface of the vehicle dashboard. The data observed by the user through the vehicle dashboard shows that the battery temperature is abnormal, and the user confirms the preset model's recommendation for the temperature parameter through the "Like" button on the interface; the system detects that the voltage and SOC parameters are consistent in multiple measurements, while the current parameter It shows a certain fluctuation; therefore, since the user confirmed the temperature parameter, the server increases the weight of the temperature parameter, and the new weight is: temperature (T): weight = 1.2; since the voltage and SOC parameters are consistent in multiple measurements, the server increases the weights of these two parameters, and the new weights are: voltage (V): weight = 1.1, SOC: weight = 1.1; since the current parameter shows fluctuation, the server reduces the weight of the current parameter, and the new weight is: current (I): weight = 0.9, and the adjusted weights are voltage (V): weight = 1.1; current (I): weight = 0.9; temperature (T): weight = 1.2; SOC: weight = 1.1. In the next diagnosis process, the preset model will pay more attention to the temperature and SOC parameters because their weights are higher, and the influence of the current parameter will be relatively reduced because its weight is lower.

[0095] It can be seen that in this embodiment, the dynamic weight adjustment mechanism enables the preset model to more accurately reflect the actual condition of the battery pack. Further, the preset model can be continuously learned and optimized to ensure that the data and algorithms ultimately pushed to end users are more accurate and reliable.

[0096] S104: Send the target protocol data to the vehicle diagnostic instrument, so that the vehicle diagnostic instrument performs diagnosis according to the target protocol data.

[0097] Among them, before being issued, the target protocol data has undergone the process of extraction, analysis and verification to ensure the accuracy and reliability of the data. The target data may include key parameters of the battery pack, such as voltage, current, temperature, SOC, SOH, etc., as well as possible fault codes or status information.

[0098] Among them, the target protocol data is transmitted from the server to the vehicle diagnostic instrument via wired or wireless means, which specifically involves data encoding, compression and encryption to ensure the efficiency and security of transmission.

[0099] Among them, after the automobile diagnostic instrument receives the target protocol data, it needs to decode and parse it.

[0100] Furthermore, the user interface of the vehicle diagnostic instrument will display this data, allowing the user to intuitively see the status of the battery pack and any potential problems, and then perform diagnosis based on the target protocol data. The diagnosis may include but is not limited to comparing data with normal ranges, identifying abnormal patterns, analyzing trends, etc.

[0101] Optionally, the vehicle diagnostic instrument generates a diagnostic report based on the diagnostic results of the target protocol data, which may include diagnostic results, fault codes, recommended repair measures, and an overall health status assessment of the battery pack.

[0102] This embodiment automatically receives multiple data of the battery pack to be diagnosed through the data transmission interface, reduces the need for manual input, improves the efficiency and accuracy of data collection, and further performs in-depth analysis on the multiple data received to ensure that key battery pack target data is extracted from a large amount of information, thereby improving the accuracy and reliability of the diagnosis; further, protocol data is generated according to the target data without the need for manual writing or configuration, which greatly simplifies the preparation work before diagnosis and improves work efficiency, and by analyzing the generated protocol data, the target protocol data is determined to ensure the compatibility of the protocol used in the diagnosis process with the battery pack, thereby improving the accuracy of the diagnosis; therefore, this solution enables users to manually select complex information such as vehicle brand, model, and vehicle model without the need for manual selection. The system automatically processes the information, greatly simplifies the operating process, and can adapt to battery packs of different brands and models. There is no need to develop a separate diagnostic solution for each battery pack, which enhances the versatility and adaptability of the system.

[0103] It should be noted that, in each of the above-mentioned embodiments, there is not necessarily a certain order between the above-mentioned steps. A person skilled in the art can understand, based on the description of the embodiments of the present application, that in different embodiments, the above-mentioned steps may have different execution orders, that is, they may be executed in parallel, may be executed interchangeably, and so on.

[0104] See also Figure 3 , Figure 3 A flowchart of a battery pack diagnostic method provided by an embodiment of the present invention is applied to an automotive diagnostic instrument of a vehicle battery pack detection system. The method comprises the following steps:

[0105] S201, receiving multiple data of a battery pack to be diagnosed, wherein the multiple data of the battery pack to be diagnosed are transmitted by the data transmission interface.

[0106] Among them, the above-mentioned multiple data may include but are not limited to the single cell voltage, single cell temperature, total voltage, SOC (State of Charge), SOH (State of Health) and the like of the battery pack.

[0107] Among them, the data transmission interface can receive data transmitted by the vehicle-mounted ECU (electronic control unit), the vehicle OBD (On-Board Diagnostics, on-board automatic diagnostic system) diagnostic port, the battery pack diagnostic port, etc.

[0108] In one embodiment, the data transmission interface device establishes a connection with the ECU or the BMS of the battery pack through a physical connection (such as a cable) or wireless communication (such as Bluetooth, Wi-Fi), and is simultaneously connected to a vehicle diagnostic instrument, which receives multiple data of the battery pack to be diagnosed and performs data analysis on the multiple data.

[0109] It can be seen that the vehicle battery pack detection system in this embodiment can realize data transmission from the battery pack to the vehicle diagnostic instrument, provide necessary data support for the diagnosis and analysis of the battery pack, and ensure the accuracy and transmission efficiency of the data.

[0110] S202 , analyzing multiple data of the battery pack to be diagnosed to obtain target data of the battery pack to be diagnosed.

[0111] Optionally, before performing data analysis on the multiple data of the battery pack to be diagnosed, the original data needs to be preprocessed, including cleaning, denoising, normalization, etc., to ensure the quality and consistency of the data.

[0112] The data analysis process may include but is not limited to feature extraction, data analysis methods and target data generation.

[0113] Specifically, the processing module in the automobile diagnostic instrument performs data analysis. The first step of data analysis is feature extraction, that is, identifying and extracting information useful for diagnosis from multiple data. The above features may include the battery charging and discharging curve, temperature change trend, voltage fluctuation, etc. In addition, feature extraction may involve mathematical models and algorithms, such as Fourier transform, wavelet analysis, principal component analysis (PCA), etc., to identify key patterns in the data; data analysis methods may include statistical analysis, machine learning algorithms, pattern recognition, etc. The above analysis methods are used to find out the performance indicators and problems of the battery pack from the pre-processed data. For example, cluster analysis can be used to identify abnormal patterns in the data, and time series analysis can be used to monitor changes in battery performance over time; the target data is the data of multiple data of the battery pack to be diagnosed after frame processing.

[0114] It can be seen that in this embodiment, useful target data is extracted from complex battery pack data. The target data will be used for subsequent diagnosis and analysis to evaluate the health status and performance of the battery pack, thereby ensuring the integrity and accuracy of the data and providing a reliable basis for the diagnosis of the battery pack.

[0115] In one embodiment, the data analysis of the multiple data of the battery pack to be diagnosed is performed to obtain the target data of the battery pack to be diagnosed, including: identifying the frame structure in the multiple data of the battery pack to be diagnosed, and determining the total number of frames of each type of data in the multiple data of the battery pack to be diagnosed; identifying the frame ID set of the frame where each type of data is located and the frame sequence number set of the frame where each type of data is located in the total number of frames of each type of data; obtaining the starting parameter set and the ending parameter set of each type of data in the frame; obtaining the target value corresponding to each type of data according to the starting parameter set and the ending parameter set of each type of data in the frame; matching the frame ID set of the frame where each type of data is located, the frame sequence number set of the frame where each type of data is located, and the target value corresponding to each type of data to obtain the target data of the battery pack to be diagnosed.

[0116] Data is usually transmitted in the form of frames, and each frame contains a certain number of data bits. Identifying the frame structure is to determine how the data is organized in the frame, including the start and end identifiers of the frame, and possible frame synchronization sequences. A data frame usually contains multiple fields, such as frame ID, frame sequence number, data content, checksum, etc.

[0117] Among them, multiple data of the battery pack to be diagnosed are classified into categories, such as voltage data, temperature data, charge and discharge data, etc., and further, the total number of frames contained in each type of data in the entire data transmission process is determined.

[0118] The frame ID is a unique identifier for each data frame, used to distinguish different data frames. The frame sequence number is used to indicate the order of data frames during transmission.

[0119] The start parameter set and the end parameter set define the specific position of the data in the frame, that is, the start and end position of each type of data; the start parameter set is the start byte and the start bit; the end parameter set is the end byte and the end bit. For example, if we are processing the voltage data of a battery cell, the start parameter set may be the third bit of the fifth byte, and the end parameter set may be the seventh bit of the seventh byte.

[0120] The frame ID and frame sequence number of each type of data are associated with its corresponding target value to form a structured data set, so that each type of data can be traced back to its exact location in the original data stream, facilitating further analysis and diagnosis.

[0121] Among them, the target value is the actual value of each type of data.

[0122] For example, the data set of voltage data in the target data is as follows: frame ID: 1, sequence number: 1, data: [voltage 1: 3.7V, voltage 2: 3.65V, voltage 3: 3.72V, voltage 4: 3.68V, temperature 1: 25°C, temperature 2: 26°C, temperature 3: 24°C, temperature 4: 26°C].

[0123] In one embodiment, obtaining the target value corresponding to each type of data based on the starting parameter set and the ending parameter set of each type of data in the frame includes: obtaining the starting parameter set and the ending parameter set of each type of data in the frame to obtain the position segment of each type of data in the frame; calculating the position segment of each type of data in the frame and the starting parameter set and the ending parameter set of each type of data in the frame according to a preset formula to obtain the target value corresponding to each type of data.

[0124] The position segment is the data range that needs to be processed for each type of data. For example, if the start parameter set is the second bit of the second byte and the end parameter set is the eighth bit of the fourth byte, then the position segment starts from the second bit of the second byte and ends at the eighth bit of the fourth byte.

[0125] In a specific implementation, a binary value is extracted bit by bit from the starting parameter set to the ending parameter set, and the binary value represents the original voltage reading. For example, if the starting parameter set is the third bit of the fifth byte, then extraction starts from the third bit of the fifth byte and ends at the seventh bit of the seventh byte; each extracted bit is processed using the calculation formula V=Σf(b), where b is the binary value of each bit, f() is a calculation function for calculating the value of each bit, and V is the final value after summing.

[0126] Specifically, when processing each extracted bit using the calculation formula V = Σf(b), the extracted data is decomposed into individual bits. For example, a byte contains 8 bits, and each bit needs to be processed separately; for the binary value b of each bit, the calculation function f() is applied. This function can be simple, such as directly taking the value of the bit (0 or 1), or it can be a more complex function, such as performing weighted calculations based on the position of the bit or other parameters. The specific implementation of the calculation function f() depends on the characteristics of the data and the diagnostic requirements. For example, it may involve error detection, calculation of check bits, or decoding of specific codes. The results of all bits processed by the calculation function f() are accumulated to obtain the total V.

[0127] For example, assuming there is a 2-byte voltage data whose binary form is 1011 0011, V=f(1)+f(0)+f(1)+f(1)+f(0)+f(0)+f(1)+f(1)=1+0+1+1+0+0+1+1=5.

[0128] It can be seen that in this embodiment, through the data analysis process, a target value can be extracted from the original data frame of the battery pack, and the target value can be used for further diagnosis and analysis to evaluate the health status and performance of the battery pack.

[0129] S203: Determine target protocol data according to the target data of the battery pack to be diagnosed.

[0130] The target protocol data is generated by the vehicle diagnostic instrument and is based on the analysis results of the battery pack to be diagnosed. The target protocol data may include but is not limited to the voltage, current, temperature, charging state, health state and other data of the battery pack that conform to the transmission protocol.

[0131] Among them, the protocol data is generated according to the rules of the preset model. The preset model and rules are pre-programmed into the diagnostic instrument to guide data analysis and the generation of protocol data.

[0132] It can be seen that in this embodiment, the entire protocol data generation process is completed on the automobile diagnostic instrument, and there is no need to transmit the data to the remote server for processing, which improves the real-time and efficiency of the diagnosis.

[0133] In one embodiment, determining the target protocol data according to the target data of the battery pack to be diagnosed includes: generating at least one protocol data according to the target data of the battery pack to be diagnosed; and determining the target protocol data according to the at least one protocol data.

[0134] Among them, based on the generated multiple protocol data, target protocol data that best meets the diagnosis requirements is selected.

[0135] Optionally, if the performance of the preset model is good, any protocol data in the at least one protocol data is directly determined as the target protocol data.

[0136] For example, if the preset model at this time is already able to accurately predict and diagnose the status of the battery pack, the first protocol data generated can be used as the target protocol data without further screening and verification.

[0137] In one embodiment, generating at least one protocol data based on the target data of the battery pack to be diagnosed includes: extracting data features in the target data of the battery pack to be diagnosed; inputting the data features into a preset model to obtain at least one protocol data, and the at least one protocol data is generated according to preset rules in the preset model.

[0138] Among them, data feature extraction refers to identifying and extracting key information points or attributes from the calculated target data of the battery pack to be diagnosed. Data features may include but are not limited to numerical statistical information, trends, anomalies, patterns, etc., and data features can represent the current state of the battery pack. For example, data features may include the battery's voltage range, current fluctuations, temperature changes, charge and discharge times, etc. The feature extraction process may involve data analysis techniques such as principal component analysis (PCA), cluster analysis, time series analysis, etc.

[0139] Among them, the preset model refers to a model established based on historical data and experience, which can predict the status of the battery pack based on the input data features. The preset model may include but is not limited to machine learning algorithms, such as random forests, neural networks or other statistical methods, which are used to learn the health status of the battery pack from data features.

[0140] The preset rules may be logic judgment, threshold setting, classification decision, etc. The protocol data may be used for: diagnostic report, i.e. providing the diagnostic results of the battery pack; control instructions, i.e. sending instructions to the battery management system (BMS) to adjust the battery working mode; data recording, i.e. storing the historical status information of the battery pack for long-term monitoring and analysis.

[0141] It can be seen that in this embodiment, the original data is converted into information useful for diagnosing the health status of the battery pack, thereby improving the accuracy and efficiency of the diagnosis.

[0142] In one embodiment, determining the target protocol data based on the at least one protocol data includes: sending the at least one protocol data to a display device in the vehicle battery pack detection system; receiving a confirmation instruction from the display device, the confirmation instruction is used to determine the first protocol data in the at least one protocol data; verifying the at least one protocol data to obtain a verification result for each protocol data; obtaining the verification result of the first protocol data; and when the verification result of the first protocol data is passed, determining the first protocol data as the target protocol data.

[0143] The sending process may be to send the selected protocol data to the display device in the vehicle battery pack detection system through a communication interface (such as CAN bus, Ethernet, etc.) to ensure the reliability and integrity of data transmission. The display device may include but is not limited to the screen of the vehicle diagnostic instrument or the console, computer screen or other user interface for displaying data to the operator.

[0144] The confirmation instruction includes the identifier or content of the selected protocol data, and the confirmation instruction can be a click selection, input of a specific code, touch of a button on the screen, or any other form of user input. For example, a user's feedback button (such as thumbs up or thumbs down) on the display interface, thumbs up means confirmation, and thumbs down means negation.

[0145] Among them, the verification process may include checking the data format, checksum, data range, logical consistency, etc. For example, the data parameters of each protocol data in at least one protocol data can be compared with the factory parameters inside the vehicle and the working standard parameters of each component inside the vehicle. If the factory parameters or the working standard parameters are reached, it means that the protocol data verification has passed.

[0146] For example, suppose there is a protocol data containing the voltage, current and temperature parameters of the battery pack. The voltage parameters of the battery pack are compared with the factory voltage standards provided by the vehicle manufacturer. If the voltage value is within the standard range (for example, 12.6 volts to 14.4 volts), the voltage parameter verification is passed; the current parameter of the battery pack is compared with the standard operating current range at the factory. If the current value is within the allowable range (for example, -100 amps to 50 amps), the current parameter verification is passed; the temperature parameter of the battery pack is compared with the standard operating temperature range of each component inside the vehicle. If the temperature value does not exceed the maximum operating temperature (for example, not exceeding 60 degrees Celsius), the temperature parameter verification is passed.

[0147] Therefore, if all parameters have passed the comparison with the factory parameters or working standard parameters, the protocol data is considered to be verified, thereby ensuring that the protocol data is not only formatted correctly but also reasonable in value.

[0148] Further, after the verification process, a verification result corresponding to each protocol data is obtained, which indicates whether the data has passed the verification. The verification result can be a simple pass / fail indication or a detailed error report.

[0149] If the first protocol data passes the verification, it is confirmed to be the target protocol data; if the verification result fails, the automobile diagnostic instrument needs to re-analyze the data, adjust the model parameters or take other measures to generate new protocol data.

[0150] It can be seen that in this embodiment, by confirming the instructions and verifying the rules, it is possible to ensure that the protocol data used is accurate and reliable, thereby providing a solid foundation for the maintenance and diagnosis of the battery pack.

[0151] In one embodiment, after the at least one protocol data is verified and a verification result of each protocol data is obtained, the method further includes: in the preset model, dynamically adjusting at least one weight corresponding to the first protocol data according to a preset weight adjustment rule.

[0152] Among them, in the preset model, different data sub-items of each protocol data (such as each byte, each algorithm, each bit, each frame ID, and each frame sequence number) have an initial weight, and these weights are all 1 initially. The initial weight is used to measure the importance or credibility of each protocol data sub-item.

[0153] Among them, the preset weight adjustment rules define under what circumstances the weight should be increased or decreased. If the confirmation instruction is confirmed and the verification result is passed, the weight of the corresponding data sub-item will increase. For example, if the user confirms through the "Like" button, the weight of the relevant data sub-item in the first protocol data may increase from 1 to 1.2; if any negative information appears in the confirmation instruction or verification result, the weight of the corresponding data sub-item may decrease, for example, from 1 to 0.8.

[0154] Among them, the more times users provide feedback through the interface, the more obvious the cumulative effect of weight adjustment will be, that is, as time goes by and more users interact, it can more accurately reflect which data sub-items are more important in the diagnosis process.

[0155] For example, the current protocol data includes: the voltage, current, temperature and SOC (state-of-charge) of the battery pack; the initial weight of each parameter is set to 1, that is, voltage (V): weight = 1; current (I): weight = 1; temperature (T): weight = 1; SOC: weight = 1; the preset model analyzes the protocol data and recommends a set of parameter values, which are presented on the display interface of the vehicle dashboard. The data observed by the user through the vehicle dashboard shows that the battery temperature is abnormal, and the user confirms the preset model's recommendation for the temperature parameter through the "Like" button on the interface; the system detects that the voltage and SOC parameters are consistent in multiple measurements, while the current parameter shows There is a certain fluctuation; therefore, since the user confirmed the temperature parameter, the car diagnostic instrument increases the weight of the temperature parameter, and the new weight is: temperature (T): weight = 1.2; since the voltage and SOC parameters remain consistent in multiple measurements, the car diagnostic instrument increases the weight of these two parameters, and the new weight is: voltage (V): weight = 1.1, SOC: weight = 1.1; since the current parameter shows fluctuations, the car diagnostic instrument reduces the weight of the current parameter, and the new weight is: current (I): weight = 0.9, and the adjusted weights are voltage (V): weight = 1.1; current (I): weight = 0.9; temperature (T): weight = 1.2; SOC: weight = 1.1. In the next diagnosis process, the preset model will pay more attention to the temperature and SOC parameters because their weights are higher, and the influence of the current parameter will be relatively reduced because its weight is lower.

[0156] It can be seen that in this embodiment, the dynamic weight adjustment mechanism enables the preset model to more accurately reflect the actual condition of the battery pack. Further, the preset model can be continuously learned and optimized to ensure that the data and algorithms ultimately pushed to end users are more accurate and reliable.

[0157] S204: Perform diagnosis according to the target protocol data.

[0158] Specifically, after the automotive diagnostic instrument obtains the target protocol data, it will conduct a comprehensive inspection and diagnosis of the battery pack based on the built-in fault database and diagnostic algorithm.

[0159] Optionally, after diagnosis is performed according to the target protocol data, the fault code, fault description, recommended repair measures and other results will be displayed on the screen of the diagnostic instrument for the technician's reference.

[0160] Furthermore, the user interface of the vehicle diagnostic instrument will display this data, allowing the user to intuitively see the status of the battery pack and any potential problems, and then perform diagnosis based on the target protocol data. The diagnosis may include but is not limited to comparing data with normal ranges, identifying abnormal patterns, analyzing trends, etc.

[0161] Among them, S201-S204 are all analyzed and processed by the processing module in the automobile diagnostic instrument.

[0162] This embodiment receives multiple data of the battery pack to be diagnosed in real time through the data transmission interface to ensure the timeliness and accuracy of the data; the automobile diagnostic instrument analyzes the received battery pack data, generates target data based on the data analysis results, and further determines the target protocol data, which helps to accurately locate the fault type and position of the battery pack. Therefore, the automobile diagnostic instrument can quickly start the diagnosis process, and the entire diagnosis process is completed on the automobile diagnostic instrument. There is no need to transmit the data to a remote server for processing, and no complicated settings and configurations are required, thereby improving the diagnosis efficiency.

[0163] It should be noted that, in each of the above-mentioned embodiments, there is not necessarily a certain order between the above-mentioned steps. A person skilled in the art can understand, based on the description of the embodiments of the present application, that in different embodiments, the above-mentioned steps may have different execution orders, that is, they may be executed in parallel, may be executed interchangeably, and so on.

[0164] As another aspect of the embodiment of the present application, the embodiment of the present application provides a battery pack diagnostic device, wherein the battery pack diagnostic device may be a software module, the software module includes a number of instructions, which are stored in a memory, and the processor may access the memory, call the instructions for execution, so as to complete the battery pack diagnostic method described in each of the above embodiments.

[0165] See also Figure 4 , Figure 4 is a schematic diagram of the structure of a battery pack diagnostic device provided in an embodiment of the present application. A server applied to a vehicle battery pack detection system, wherein the vehicle battery pack detection system further includes a data transmission interface and a vehicle diagnostic instrument, such as Figure 4 As shown, the diagnostic device 400 of the battery pack includes:

[0166] A receiving unit 401, configured to receive multiple data of a battery pack to be diagnosed, wherein the multiple data of the battery pack to be diagnosed are transmitted by the data transmission interface;

[0167] An analyzing unit 402, configured to analyze a plurality of data of the battery pack to be diagnosed to obtain target data of the battery pack to be diagnosed;

[0168] A determination unit 403, configured to determine target protocol data according to target data of the battery pack to be diagnosed;

[0169] The sending unit 404 is used to send the target protocol data to the vehicle diagnostic instrument, so that the vehicle diagnostic instrument performs diagnosis according to the target protocol data.

[0170] This embodiment automatically receives multiple data of the battery pack to be diagnosed through the data transmission interface, reduces the need for manual input, improves the efficiency and accuracy of data collection, and further performs in-depth analysis on the multiple data received to ensure that key battery pack target data is extracted from a large amount of information, thereby improving the accuracy and reliability of the diagnosis; further, protocol data is generated according to the target data without the need for manual writing or configuration, which greatly simplifies the preparation work before diagnosis and improves work efficiency, and by analyzing the generated protocol data, the target protocol data is determined to ensure the compatibility of the protocol used in the diagnosis process with the battery pack, thereby improving the accuracy of the diagnosis; therefore, this solution enables users to manually select complex information such as vehicle brand, model, and vehicle model without the need for manual selection. The system automatically processes the information, greatly simplifies the operating process, and can adapt to battery packs of different brands and models. There is no need to develop a separate diagnostic solution for each battery pack, which enhances the versatility and adaptability of the system.

[0171] In one embodiment, in performing data analysis on the multiple data of the battery pack to be diagnosed to obtain the target data of the battery pack to be diagnosed, the analysis unit 402 is further used to: identify the frame structure in the multiple data of the battery pack to be diagnosed, and determine the total number of frames of each type of data in the multiple data of the battery pack to be diagnosed; identify the frame ID set of the frame where each type of data is located and the frame sequence number set of the frame where each type of data is located in the total number of frames of each type of data; obtain the starting parameter set and the ending parameter set of each type of data in the frame; obtain the target value corresponding to each type of data according to the starting parameter set and the ending parameter set of each type of data in the frame; correspond the frame ID set of the frame where each type of data is located, the frame sequence number set of the frame where each type of data is located, and the target value corresponding to each type of data to obtain the target data of the battery pack to be diagnosed.

[0172] In one embodiment, in obtaining the target value corresponding to each type of data based on the starting parameter set and the ending parameter set of each type of data in the frame, the analysis unit 402 is further used to: obtain the starting parameter set and the ending parameter set of each type of data in the frame to obtain the position segment of each type of data in the frame; and calculate the position segment of each type of data in the frame and the starting parameter set and the ending parameter set of each type of data in the frame according to a preset formula to obtain the target value corresponding to each type of data.

[0173] In one embodiment, in determining the target protocol data according to the target data of the battery pack to be diagnosed, the determination unit 403 is further used to: generate at least one protocol data according to the target data of the battery pack to be diagnosed; and determine the target protocol data according to the at least one protocol data.

[0174] In one embodiment, in generating at least one protocol data according to the target data of the battery pack to be diagnosed, the determination unit 403 is further used to: extract data features in the target data of the battery pack to be diagnosed; input the data features into a preset model to obtain at least one protocol data, and the at least one protocol data is generated according to preset rules in the preset model.

[0175] In one embodiment, in determining the target protocol data based on the at least one protocol data, the determination unit 403 is further used to: send the at least one protocol data to a display device in the vehicle battery pack detection system; receive a confirmation instruction from the display device, the confirmation instruction is used to determine the first protocol data in the at least one protocol data; perform verification processing on the at least one protocol data to obtain a verification result for each protocol data; obtain the verification result of the first protocol data; and when the verification result of the first protocol data is passed, determine that the first protocol data is the target protocol data.

[0176] In one embodiment, after the at least one protocol data is verified and a verification result of each protocol data is obtained, the determination unit 403 is further used to: dynamically adjust at least one weight corresponding to the first protocol data in the preset model according to a preset weight adjustment rule.

[0177] It should be noted that the above-mentioned battery pack diagnostic device can execute the battery pack diagnostic method provided in the embodiment of the present application, and has the corresponding functional modules and beneficial effects of the execution method. For technical details not fully described in the embodiment of the battery pack diagnostic device, please refer to the battery pack diagnostic method provided in the embodiments S101-S104 of the present application.

[0178] See also Figure 5 , Figure 5 FIG. 1 is a schematic diagram of a battery pack diagnostic device provided in an embodiment of the present application. An automotive diagnostic instrument applied to a vehicle battery pack detection system, such as Figure 5 As shown, the diagnostic device 500 of the battery pack includes:

[0179] A receiving unit 501, configured to receive multiple data of a battery pack to be diagnosed, wherein the multiple data of the battery pack to be diagnosed is transmitted by the data transmission interface;

[0180] An analyzing unit 502, configured to analyze a plurality of data of the battery pack to be diagnosed to obtain target data of the battery pack to be diagnosed;

[0181] A determination unit 503, configured to determine target protocol data according to target data of the battery pack to be diagnosed;

[0182] The diagnosis unit 504 is used to perform diagnosis according to the target protocol data.

[0183] This embodiment receives multiple data of the battery pack to be diagnosed in real time through the data transmission interface to ensure the timeliness and accuracy of the data; the automobile diagnostic instrument analyzes the received battery pack data, generates target data based on the data analysis results, and further determines the target protocol data, which helps to accurately locate the fault type and position of the battery pack. Therefore, the automobile diagnostic instrument can quickly start the diagnosis process, and the entire diagnosis process is completed on the automobile diagnostic instrument. There is no need to transmit the data to a remote server for processing, and no complicated settings and configurations are required, thereby improving the diagnosis efficiency.

[0184] It should be noted that the above-mentioned battery pack diagnostic device can execute the battery pack diagnostic method provided in the embodiment of the present application, and has the corresponding functional modules and beneficial effects of the execution method. For technical details not fully described in the embodiment of the battery pack diagnostic device, please refer to the battery pack diagnostic method provided in the embodiments S201-S203 of the present application.

[0185] An embodiment of the present application also provides a computer-readable storage medium, including a first computer-readable storage medium and a second computer-readable storage medium, wherein the first computer-readable storage medium stores a first computer program, wherein the first computer program includes first program instructions, and when the first program instructions are executed by a first processor, the first processor executes the battery pack diagnosis method as described in the aforementioned S101-S104 embodiments; and the second computer-readable storage medium stores a second computer program, wherein the second computer program includes second program instructions, and when the second program instructions are executed by a second processor, the second processor executes the battery pack diagnosis method as described in the aforementioned S201-S204 embodiments.

[0186] A person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0187] The above disclosure is only the preferred embodiment of the present application, which certainly cannot be used to limit the scope of rights of the present application. Therefore, equivalent changes made according to the claims of the present application are still within the scope covered by the present application.

Claims

1. A battery pack diagnostic method, characterized in that: A server applied to a vehicle battery pack detection system, wherein the vehicle battery pack detection system further comprises a data transmission interface and a vehicle diagnostic instrument, and the method comprises: receiving a plurality of data of the battery pack to be diagnosed, wherein the plurality of data of the battery pack to be diagnosed is transmitted by the data transmission interface; Analyze multiple data of the battery pack to be diagnosed to obtain target data of the battery pack to be diagnosed; Determining target protocol data according to target data of the battery pack to be diagnosed; The target protocol data is sent to the vehicle diagnostic instrument so that the vehicle diagnostic instrument performs diagnosis according to the target protocol data.

2. The method according to claim 1, characterized in that The step of analyzing the multiple data of the battery pack to be diagnosed to obtain target data of the battery pack to be diagnosed includes: Identifying a frame structure in the multiple data of the battery pack to be diagnosed, and determining a total number of frames of each type of data in the multiple data of the battery pack to be diagnosed; Identify a frame ID set of frames where each type of data is located and a frame sequence number set of frames where each type of data is located in the total number of frames of each type of data; Obtaining a starting parameter set and an ending parameter set of each type of data in a frame; Obtaining a target value corresponding to each type of data according to a starting parameter set and an ending parameter set of each type of data in a frame; The frame ID set of the frame where each type of data is located, the frame sequence number set of the frame where each type of data is located, and the target value corresponding to each type of data are matched to obtain the target data of the battery pack to be diagnosed.

3. The method according to claim 2, characterized in that The obtaining, according to the starting parameter set and the ending parameter set of each type of data in the frame, a target value corresponding to each type of data includes: Obtaining a starting parameter set and an ending parameter set of each type of data in a frame to obtain a position segment of each type of data in the frame; According to a preset formula, the position segment of each type of data in the frame and the starting parameter set and the ending parameter set of each type of data in the frame are calculated to obtain the target value corresponding to each type of data.

4. The method according to claim 1, characterized in that: The step of determining target protocol data according to the target data of the battery pack to be diagnosed includes: generating at least one protocol data according to the target data of the battery pack to be diagnosed; According to the at least one protocol data, target protocol data is determined.

5. The method according to claim 4, characterized in that The step of generating at least one protocol data according to the target data of the battery pack to be diagnosed includes: Extracting data features from target data of the battery pack to be diagnosed; The data feature is input into a preset model to obtain at least one protocol data, and the at least one protocol data is generated according to a preset rule in the preset model.

6. The method according to claim 4, characterized in that The step of determining target protocol data according to the at least one protocol data comprises: Sending the at least one protocol data to a display device in the vehicle battery pack detection system; receiving a confirmation instruction from the display device, wherein the confirmation instruction is used to determine a first protocol data among the at least one protocol data; Performing verification processing on the at least one protocol data to obtain a verification result of each protocol data; Obtaining a verification result of the first protocol data; When the verification result of the first protocol data is passed, the first protocol data is determined to be target protocol data.

7. The method according to claim 6, characterized in that After the at least one protocol data is verified and a verification result of each protocol data is obtained, the method further includes: In the preset model, at least one weight corresponding to the first protocol data is dynamically adjusted according to a preset weight adjustment rule.

8. A battery pack diagnostic method, characterized in that: An automotive diagnostic instrument applied to a vehicle battery pack detection system, wherein the vehicle battery pack detection system further comprises a data transmission interface, and the method comprises: receiving a plurality of data of the battery pack to be diagnosed, wherein the plurality of data of the battery pack to be diagnosed is transmitted by the data transmission interface; Analyze multiple data of the battery pack to be diagnosed to obtain target data of the battery pack to be diagnosed; Determining target protocol data according to target data of the battery pack to be diagnosed; A diagnosis is performed based on the target protocol data.

9. A vehicle battery pack detection system, characterized in that: It includes a server and an automobile diagnostic instrument; the server includes a first memory and a first processor, the first memory is connected to the first processor, the first processor is used to execute one or more computer programs stored in the first memory, and when the first processor executes the one or more computer programs, the server implements the battery pack diagnosis method as described in any one of claims 1 to 7; the automobile diagnostic instrument includes a second memory and a second processor, the second memory is connected to the second processor, the second processor is used to execute one or more computer programs stored in the second memory, and when the second processor executes the one or more computer programs, the automobile diagnostic instrument implements the battery pack diagnosis method as described in claim 8.

10. A computer-readable storage medium, characterized in that: The invention comprises a first computer-readable storage medium and a second computer-readable storage medium, wherein the first computer-readable storage medium stores a first computer program, wherein the first computer program includes first program instructions, and when the first program instructions are executed by a first processor, the first processor executes the battery pack diagnosis method as described in any one of claims 1 to 7; and the second computer-readable storage medium stores a second computer program, wherein the second computer program includes second program instructions, and when the second program instructions are executed by a second processor, the second processor executes the battery pack diagnosis method as described in claim 8.

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