Battery pack diagnosis methods and vehicle battery pack test system

Abstract

Battery pack diagnosis methods and a vehicle battery pack test system (10). A battery pack diagnosis method comprises: receiving a plurality of pieces of data of a battery pack (20) to be diagnosed, the plurality of pieces of data of said battery pack (20) being transmitted by a data transmission interface (30); performing data analysis on the plurality of pieces of data of said battery pack (20) to obtain target data of said battery pack (20); on the basis of the target data of said battery pack (20), determining target protocol data; and issuing the target protocol data to an automobile diagnostic tool (50), such that the automobile diagnostic tool (50) performs a diagnosis on the basis of the target protocol data. The present method receives and analyzes the plurality of pieces of data of said battery pack (20), and automatically generates and issues the target protocol data to the automobile diagnostic tool (50), achieving an efficient, accurate, highly compatible and easy-to-operate battery pack diagnosis method.

Description

Battery pack diagnostic methods and vehicle battery pack testing systems

[0001] This application claims priority to Chinese Patent Application No. 2024118703293, filed on December 18, 2024, entitled "Diagnostic Method for Battery Pack and Vehicle Battery Pack Testing System", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of automotive diagnostic technology, specifically to a diagnostic method for a battery pack and a vehicle battery pack testing system. Background Technology

[0003] Against the backdrop of the rapid development of the new energy electric vehicle industry, the market share of new energy vehicles continues to climb. At the same time, the lifespan, safety, and fault detection of battery packs—a key component of electric vehicles—have become a focus of public and industry attention. To address this need, many automakers and battery pack suppliers have developed specialized testing software to assess the lifespan, safety, and fault conditions of battery packs. However, this testing software often lacks universality, forcing repair technicians to prepare and use multiple different software programs during vehicle repairs. This not only increases the difficulty of setting up testing environments but also significantly reduces the efficiency of repair work.

[0004] Traditional automotive diagnostic tools, while capable of integrating battery pack information from different brands and models, require users to navigate through complex, multi-level menus, including vehicle brand, model, vehicle type, and battery pack brand and type, to access the appropriate diagnostic process. However, this approach has significant drawbacks: firstly, users often struggle to accurately provide all the necessary information, leading to multiple attempts to find the correct diagnostic path; secondly, with the continuous introduction of new car models and battery types, diagnostic tools require constant updates to cover the latest vehicle and battery pack brands, increasing the difficulty of maintenance and updates. Summary of the Invention

[0005] One objective of this application is to provide a battery pack diagnostic method and a vehicle battery pack testing system to solve the technical problems of non-universal use of multi-brand diagnostic software, complex and error-prone diagnostic paths, and poor adaptability in the process of diagnosing new energy vehicle battery packs.

[0006] In a first aspect, embodiments of this application provide a method for diagnosing a battery pack, applied to a server of a vehicle battery pack testing system. The vehicle battery pack testing system further includes a data transmission interface and a vehicle diagnostic tool. The method includes:

[0007] Receive multiple data points from the battery pack to be diagnosed, which are obtained by the data transmission interface.

[0008] Data analysis is performed on multiple data points of the battery pack to be diagnosed to obtain the target data of the battery pack to be diagnosed.

[0009] Based on the target data of the battery pack to be diagnosed, determine the target protocol data;

[0010] The target protocol data is sent to the vehicle diagnostic tool so that the vehicle diagnostic tool can perform diagnosis based on the target protocol data.

[0011] In a second aspect, embodiments of this application provide a method for diagnosing a battery pack, wherein the vehicle battery pack testing system further includes a data transmission interface, and the method includes:

[0012] Receive multiple data points from the battery pack to be diagnosed, which are obtained by the data transmission interface.

[0013] Data analysis is performed on multiple data points of the battery pack to be diagnosed to obtain the target data of the battery pack to be diagnosed.

[0014] Based on the target data of the battery pack to be diagnosed, determine the target protocol data;

[0015] Diagnosis is performed based on the target protocol data.

[0016] In a third aspect, a vehicle battery pack testing system is provided, including a server and an automotive diagnostic tool; the server includes a first memory and a first processor, the first memory being connected to the first processor, the first processor being configured to execute one or more computer programs stored in the first memory, wherein when the first processor executes the one or more computer programs, the server implements the battery pack diagnostic method as described in the first aspect; the automotive diagnostic tool includes a second memory and a second processor, the second memory being connected to the second processor, the second processor being configured to execute one or more computer programs stored in the second memory, wherein when the second processor executes the one or more computer programs, the automotive diagnostic tool implements the battery pack diagnostic method as described in the second aspect.

[0017] Fourthly, embodiments of this application provide a diagnostic device for a battery pack, applied to a server of a vehicle battery pack testing system. The vehicle battery pack testing system further includes a data transmission interface and a vehicle diagnostic tool. The device includes:

[0018] A receiving unit is used to receive multiple data points of the battery pack to be diagnosed, which are obtained by the data transmission interface.

[0019] The analysis unit is used to perform data analysis on multiple data points of the battery pack to be diagnosed, and obtain the target data of the battery pack to be diagnosed.

[0020] The determining unit is used to determine target protocol data based on the target data of the battery pack to be diagnosed;

[0021] The sending unit is used to send the target protocol data to the vehicle diagnostic tool so that the vehicle diagnostic tool can perform diagnosis based on the target protocol data.

[0022] Fifthly, embodiments of this application provide a diagnostic device for a battery pack, an automotive diagnostic tool applied to a vehicle battery pack testing system, the device comprising:

[0023] A receiving unit is used to receive multiple data points of the battery pack to be diagnosed, which are obtained by the data transmission interface.

[0024] The analysis unit is used to perform data analysis on multiple data points of the battery pack to be diagnosed, and obtain the target data of the battery pack to be diagnosed.

[0025] The determining unit is used to determine target protocol data based on the target data of the battery pack to be diagnosed;

[0026] A diagnostic unit is configured to perform diagnostics based on the target protocol data. In a sixth aspect, embodiments of this application provide a computer-readable storage medium, including a first computer-readable storage medium and a second computer-readable storage medium. The first computer-readable storage medium stores a first computer program, which includes first program instructions. When executed by a first processor, the first program instructions cause the first processor to perform the battery pack diagnostic method as described in the first aspect. The second computer-readable storage medium stores a second computer program, which includes second program instructions. When executed by a second processor, the second program instructions cause the second processor to perform the battery pack diagnostic method as described in the second aspect.

[0027] In the embodiments of the above-mentioned battery pack diagnostic method and vehicle battery pack testing system, firstly, multiple data points of the battery pack to be diagnosed are received. These multiple data points are obtained by the data transmission interface. Secondly, the multiple data points of the battery pack to be diagnosed are analyzed to obtain target data of the battery pack to be diagnosed. Then, 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 can perform diagnosis based on the target protocol data. This embodiment automatically receives multiple data points from the battery pack to be diagnosed via a data transmission interface, reducing the need for manual input and improving the efficiency and accuracy of data collection. Further in-depth analysis of the received data ensures the extraction of key battery pack target data from a large amount of information, thereby improving the accuracy and reliability of the diagnosis. Furthermore, protocol data is generated based on the target data, eliminating the need for manual writing or configuration, greatly simplifying pre-diagnosis preparation and improving work efficiency. By analyzing the generated protocol data, the target protocol data is determined, ensuring the compatibility of the protocol used during diagnosis with the battery pack and enhancing diagnostic accuracy. Therefore, this solution eliminates the need for users to manually select complex information such as vehicle brand, model, and vehicle type; the system processes this automatically, greatly simplifying the operation process. It can also adapt to different brands and models of battery packs, eliminating the need to develop separate diagnostic solutions for each battery pack, thus enhancing the system's versatility and adaptability. Attached Figure Description

[0028] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 is a schematic diagram of a vehicle battery pack detection system according to an embodiment of this application;

[0030] Figure 2 is a flowchart illustrating a diagnostic method for a battery pack according to an embodiment of this application;

[0031] Figure 3 is a flowchart illustrating another method for diagnosing a battery pack according to an embodiment of this application;

[0032] Figure 4 is a schematic diagram of the structure of a diagnostic device for a battery pack according to an embodiment of this application;

[0033] Figure 5 is a schematic diagram of the structure of a diagnostic device for another battery pack in one embodiment of this application. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0035] It should be noted that, unless there is a conflict, the various features in the embodiments of this application can be combined with each other, all of which are within the protection scope of this application. Furthermore, although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than the module division in the device or the order in the flowchart. Moreover, the terms "first," "second," and "third" used in this application do not limit the data or execution order, but only distinguish identical or similar items with essentially the same function and effect.

[0036] Referring to Figure 1, Figure 1 is a schematic diagram of a vehicle battery pack testing system provided in this embodiment of the present application. The vehicle battery pack testing system 10 includes a battery pack to be diagnosed 20, a data transmission interface 30, a server 40, and an automotive diagnostic instrument 50.

[0037] The battery pack to be diagnosed (20) refers to the electric vehicle battery pack that needs to be tested and evaluated; it typically includes multiple battery cells, a battery management system (BMS), temperature sensors, voltage and current sensors, etc. The battery pack (20) is responsible for storing and supplying electrical energy and is one of the core components of an electric vehicle. Its health directly affects the vehicle's range and safety.

[0038] The data transmission interface 30 can receive data from 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 in the vehicle, including battery pack status information; the vehicle OBD diagnostic port is a standard interface on the vehicle used 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 a dedicated interface for battery pack diagnostics, which may provide more detailed battery pack data, such as the voltage and temperature of individual battery cells. 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 via the vehicle diagnostic tool 50 for further analysis and processing.

[0039] The server 40 is the core processing unit of the vehicle battery pack testing system. It is responsible for receiving data from the data transmission interface 30. The server 40 may contain 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 intelligently analyze the received data, generate diagnostic reports, and send the diagnostic results or instructions back to the vehicle diagnostic tool 50.

[0040] Among them, the vehicle diagnostic tool 50 is a device used to perform diagnostic operations. It can be directly connected to the vehicle's OBD diagnostic port or battery pack diagnostic port. The diagnostic tool 50 usually has a display screen and operating interface, allowing the repair technician to interact with the system, perform diagnostic procedures, and view diagnostic results. According to the target protocol data sent by the server 40, the vehicle diagnostic tool 50 can perform specific diagnostic tests, such as battery balancing tests and charge / discharge efficiency tests.

[0041] Therefore, in a vehicle battery pack testing system, the specific process can be as follows: the server of the vehicle battery pack testing system receives multiple data points from the battery pack to be diagnosed, which are obtained through the data transmission interface; the server analyzes the multiple data points to obtain target data for the battery pack; based on the target data, the server determines target protocol data; and the server sends the target protocol data to the vehicle diagnostic tool. Alternatively, the vehicle diagnostic tool of the vehicle battery pack testing system receives multiple data points from the battery pack to be diagnosed, which are obtained through the data transmission interface; the server analyzes the multiple data points to obtain target data; based on the target data, the server determines target protocol data; and the system performs diagnosis based on the target protocol data.

[0042] Therefore, the entire vehicle battery pack testing system 10, through the coordinated work of these components, enables rapid and accurate diagnosis of electric vehicle battery packs, providing strong support for maintenance technicians and ensuring the performance of the battery pack and the safe operation of the vehicle.

[0043] In view of this, this application proposes a diagnostic method for battery packs to solve the above problems. The details are described below.

[0044] Please refer to Figure 2, which is a schematic flowchart of a battery pack diagnostic method provided in an embodiment of this application. The method is applied to a server in a vehicle battery pack testing system, which also includes a data transmission interface and a vehicle diagnostic tool. The method includes the following steps:

[0045] S101. Receive multiple data points from the battery pack to be diagnosed, wherein the multiple data points of the battery pack to be diagnosed are obtained by the data transmission interface.

[0046] Among these, the data may include, but are not limited to, individual cell voltage, individual cell temperature, total voltage, SOC (State of Charge), and SOH (State of Health) of the battery pack.

[0047] The data transmission interface can receive data from the vehicle's ECU (Electronic Control Unit), the vehicle's OBD (On-Board Diagnostics) diagnostic port, and the battery pack diagnostic port.

[0048] In one embodiment, the data transmission interface device establishes a connection with the BMS of the ECU or battery pack via a physical connection (such as a cable) or wireless communication (such as Bluetooth or Wi-Fi), and simultaneously connects to an automotive diagnostic tool. The automotive diagnostic tool transmits multiple data points of the battery pack to be diagnosed to the server. Specifically, the automotive diagnostic tool uploads the received multiple data points of the battery pack to be diagnosed to the server through its own communication module. This involves data packaging, encryption, and transmission to ensure the security of data transmission over the Internet.

[0049] Furthermore, after receiving the data uploaded by the car diagnostic tool, the server will unpack, verify, and decrypt the data (if it was encrypted beforehand), and then store the data on the server for subsequent data analysis and processing.

[0050] As can be seen, 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.

[0051] S102. Perform data analysis on multiple data points of the battery pack to be diagnosed to obtain the target data of the battery pack to be diagnosed.

[0052] Optionally, before performing data analysis on the various data of the battery pack to be diagnosed, it is necessary to preprocess the raw data, including cleaning, noise reduction, normalization, etc., to ensure the quality and consistency of the data.

[0053] The data analysis process may include, but is not limited to, feature extraction, data analysis methods, and target data generation.

[0054] Specifically, the first step in data analysis is feature extraction, which involves identifying and extracting diagnostically useful information from multiple datasets. These features may include battery charge / discharge curves, temperature change trends, voltage fluctuations, etc. Furthermore, feature extraction may involve mathematical models and algorithms, such as Fourier transform, wavelet analysis, and principal component analysis (PCA), to identify key patterns in the data. Data analysis methods can include statistical analysis, machine learning algorithms, pattern recognition, etc. These methods are used to identify battery pack performance indicators and problems from preprocessed data. For example, cluster analysis can be used to identify abnormal patterns in the data, while time series analysis can be used to monitor changes in battery performance over time. The target data is the frame-processed data of multiple datasets from the battery pack to be diagnosed.

[0055] As can be seen, this embodiment extracts useful target data from complex battery pack data. This target data will be used for subsequent diagnosis and analysis to assess 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.

[0056] In one embodiment, the step of analyzing multiple data points of the battery pack to be diagnosed to obtain target data for the battery pack to be diagnosed includes: identifying the frame structure in the multiple data points of the battery pack to be diagnosed; determining the total number of frames for each type of data in the multiple data points of the battery pack to be diagnosed; identifying the set of frame IDs and the set of frame sequence numbers for each type of data in the total number of frames for each type of data; obtaining the set of start parameters and the set of end parameters for each type of data within a frame; obtaining the target value corresponding to each type of data based on the set of start parameters and the set of end parameters for each type of data within a frame; and mapping the set of frame IDs, the set of frame sequence numbers, and the target value corresponding to each type of data to obtain the target data for the battery pack to be diagnosed.

[0057] Data is typically transmitted in frames, each containing a certain number of data bits. Identifying the frame structure determines how the data is organized within the frame, including start and end markers and possible frame synchronization sequences. A data frame usually contains multiple fields, such as frame ID, frame sequence number, data content, and checksum.

[0058] This involves classifying various data points from the battery pack to be diagnosed, such as voltage data, temperature data, and charge / discharge data. Furthermore, it involves determining the total number of frames for each type of data throughout the entire data transmission process.

[0059] The frame ID is a unique identifier for each data frame, used to distinguish different data frames. The frame sequence number indicates the order in which data frames are transmitted.

[0060] The start parameter set and end parameter set define the specific positions of the data within the frame, i.e., the start and end positions of each type of data; the start parameter set consists of the start byte and the start bit; the end parameter set consists of the end byte and the end bit. For example, assuming we are processing the voltage data of a battery cell, the start parameter set might be the 3rd bit of the 5th byte, and the end parameter set might be the 7th bit of the 7th byte.

[0061] This involves associating the frame ID and frame sequence number of each data type with its corresponding target value to form a structured dataset. This allows each data type to be traced back to its precise location within the original data stream, facilitating further analysis and diagnosis.

[0062] The target value is the actual value for each type of data.

[0063] For example, the voltage data dataset 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℃, Temperature 2: 26℃, Temperature 3: 24℃, Temperature 4: 26℃].

[0064] In one embodiment, obtaining the target value corresponding to each type of data based on the start parameter set and end parameter set of each type of data within the frame includes: acquiring the start parameter set and end parameter set of each type of data within the frame to obtain the position segment of each type of data within the frame; and calculating the position segment of each type of data within the frame and the start parameter set and end parameter set of each type of data within the frame according to a preset formula to obtain the target value corresponding to each type of data.

[0065] The position segment represents the range of data to be processed for each type of data. For example, if the starting parameter set is the second bit of the second byte and the ending 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.

[0066] In practice, binary values ​​are extracted bit by bit from the starting parameter set to the ending parameter set. These binary values ​​represent the original voltage readings. For example, if the starting parameter set is the 3rd bit of the 5th byte, extraction starts from the 3rd bit of the 5th byte and ends at the 7th bit of the 7th byte. Each extracted bit is processed using the formula V = Σf(b), where b is the binary value of each bit, f() is the calculation function for each bit, and V is the final summation value.

[0067] Specifically, in processing each extracted bit using the 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 individually. For the binary value b of each bit, a calculation function f() is applied. This function can be simple, such as directly taking the bit value (0 or 1), or it can be a more complex function, such as performing weighted calculations based on the bit's position 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, check bit calculation, or decoding of a specific encoding. The results of processing all bits using the calculation function f() are summed to obtain the total V.

[0068] For example, suppose 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.

[0069] As can be seen, in this embodiment, the target value can be extracted from the original data frame of the battery pack through the data analysis process. This target value can be used for further diagnosis and analysis to evaluate the health status and performance of the battery pack.

[0070] S103. Determine the target protocol data based on the target data of the battery pack to be diagnosed.

[0071] The protocol data is generated according to the rules of the preset model and is a structured data format that contains the necessary information for diagnosing the battery pack, such as the real-time status, historical trends, and fault codes of the battery pack. It also follows specific communication protocols or diagnostic standards to enable transmission and understanding between different systems or devices.

[0072] Among them, the target protocol data is the protocol data that is ultimately used for diagnostic decision-making, report generation, or further processing.

[0073] In one embodiment, determining the target protocol data based on the target data of the battery pack to be diagnosed includes: generating at least one protocol data based on the target data of the battery pack to be diagnosed; and determining the target protocol data based on the at least one protocol data.

[0074] Among them, the target protocol data that best meets the diagnostic needs is selected from the multiple generated protocol data.

[0075] Optionally, if the preset model performs well, then any one of the protocol data in at least one protocol data set can be directly selected as the target protocol data.

[0076] For example, if the preset model can accurately predict and diagnose the state of the battery pack, then the first protocol data generated can be used as the target protocol data without further filtering and verification.

[0077] 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 from 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, wherein the at least one protocol data is generated according to preset rules in the preset model.

[0078] 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 can include, but are not limited to, statistical information, trends, outliers, and patterns, representing the current state of the battery pack. For example, data features might include the battery's voltage range, current fluctuations, temperature changes, and the number of charge / discharge cycles. The feature extraction process may involve data analysis techniques such as principal component analysis (PCA), cluster analysis, and time series analysis.

[0079] The preset model refers to a model built based on historical data and experience. It can predict the state of the battery pack based on the characteristics of the input data. The preset model may include, but is not limited to, machine learning algorithms, such as random forests, neural networks or other statistical methods, to learn the health status of the battery pack from the data characteristics.

[0080] The preset rules can include logical judgments, threshold settings, and classification decisions. The protocol data can be used for: diagnostic reports (providing diagnostic results for the battery pack); control commands (sending instructions to the Battery Management System (BMS) to adjust the battery's operating mode); and data recording (storing historical status information of the battery pack for long-term monitoring and analysis).

[0081] As can be seen, this embodiment improves the accuracy and efficiency of diagnosis by converting raw data into information useful for diagnosing the health status of the battery pack.

[0082] 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 testing system; receiving a confirmation instruction from the display device, the confirmation instruction being 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 for each protocol data; obtaining the verification result of the first protocol data; and determining the first protocol data as the target protocol data when the verification result of the first protocol data is passed.

[0083] The data transmission process involves sending selected protocol data to the display device in the vehicle battery pack testing system via 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 an automotive diagnostic tool, a console, a computer screen, or other user interface, used to display data to the operator.

[0084] The confirmation instruction contains the identifier or content of the selected protocol data. This confirmation instruction can be a click to select, entering a specific code, touching a button on the screen, or any other form of user input. For example, a user's feedback button on the display interface (such as a like or dislike) indicates that a like signifies confirmation, while a dislike signifies rejection.

[0085] The verification process may include checking 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 of the vehicle and the working standard parameters of each component in the vehicle. If the factory parameters or working standard parameters are met, it means that the protocol data verification is successful.

[0086] For example, suppose there is a protocol that includes battery pack voltage, current, and temperature parameters. The battery pack voltage parameters are compared to the factory-standard voltage provided by the vehicle manufacturer. If the voltage value is within the standard range (e.g., 12.6 volts to 14.4 volts), the voltage parameter verification is passed. The battery pack current parameters are compared to the factory-standard operating current range. If the current value is within the allowable range (e.g., -100 amps to 50 amps), the current parameter verification is passed. The battery pack temperature parameters are compared to the standard operating temperature range of each component inside the vehicle. If the temperature value does not exceed the maximum operating temperature (e.g., not exceeding 60 degrees Celsius), the temperature parameter verification is passed.

[0087] Therefore, once all parameters have been compared with factory parameters or standard operating parameters, the protocol data is considered to have passed verification, thus ensuring that the protocol data is not only correctly formatted but also numerically reasonable.

[0088] Furthermore, after verification processing, a verification result is obtained for each piece of protocol data, indicating whether the data has passed verification. The verification result can be a simple pass / fail indication or a detailed error report.

[0089] If the first protocol data passes the verification, it is confirmed as 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.

[0090] As can be seen, this embodiment can ensure that the protocol data used is accurate and reliable by confirming instructions and verification rules, thereby providing a solid foundation for the maintenance and diagnosis of the battery pack.

[0091] In one embodiment, after verifying the at least one protocol data to obtain the verification result of each protocol data, the method further includes: dynamically adjusting at least one weight corresponding to the first protocol data in the preset model according to a preset weight adjustment rule.

[0092] In the preset model, each data sub-item of the protocol data (such as each byte, each algorithm, each bit, each frame ID, and each frame sequence number) has an initial weight. These weights are all initially 1. The initial weights are used to measure the importance or credibility of each protocol data sub-item.

[0093] The preset weight adjustment rules define under what circumstances the weight should be increased or decreased. If the confirmation instruction is "OK" and the verification result is "Pass", the weight of the corresponding data sub-item will increase. For example, if the user confirms via the "Like" button, the weight of the relevant data sub-item in the first protocol data may increase from 1 to 1.2. If either the confirmation instruction or the verification result contains a negative message, the weight of the corresponding data sub-item may decrease, for example, from 1 to 0.8.

[0094] The more times users provide feedback through the interface, the more significant the cumulative effect of weight adjustments becomes. In other words, with the passage of time and more user interaction, it can more accurately reflect which data sub-items are more important in the diagnostic process.

[0095] For example, the current protocol data includes: battery pack voltage, current, temperature, and SOC (State of Charge); the initial weight of each parameter is set to 1, i.e., voltage (V): weight = 1; current (I): weight = 1; temperature (T): weight = 1; SOC: weight = 1; a preset model analyzes the protocol data and recommends a set of parameter values, which are displayed on the vehicle's dashboard. The user observes an abnormal battery temperature on the dashboard and confirms the preset model's recommendation of temperature parameters by clicking the "like" button on the interface; the system detects that the voltage and SOC parameters remain consistent across multiple measurements, while the current parameter... The system exhibits some fluctuations; therefore, since the user confirmed the temperature parameter, the server increases the weight of the temperature parameter, with the new weight: Temperature (T): Weight = 1.2. Because the voltage and SOC parameters remained consistent across multiple measurements, the server increases the weights of these two parameters, with the new weights: Voltage (V): Weight = 1.1, SOC: Weight = 1.1. Because the current parameter shows fluctuations, the server decreases the weight of the current parameter, with the new weight: Current (I): Weight = 0.9. 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 diagnostic process, the preset model will place greater emphasis on the temperature and SOC parameters because of their higher weights, while the influence of the current parameter will be relatively reduced due to its lower weight.

[0096] As can be seen, the dynamic weight adjustment mechanism in this embodiment enables the preset model to more accurately reflect the real condition of the battery pack. Further preset models can be continuously learned and optimized to ensure that the data and algorithms finally delivered to end users are more accurate and reliable.

[0097] S104. The target protocol data is sent to the vehicle diagnostic tool so that the vehicle diagnostic tool can perform diagnosis based on the target protocol data.

[0098] Prior to distribution, the target protocol data has undergone extraction, analysis, and verification to ensure its accuracy and reliability. The target data may include key parameters of the battery pack, such as voltage, current, temperature, SOC, SOH, and possible fault codes or status information.

[0099] The target protocol data is transmitted from the server to the vehicle diagnostic tool via wired or wireless means, specifically involving data encoding, compression, and encryption to ensure transmission efficiency and security.

[0100] After receiving the target protocol data, the automotive diagnostic tool needs to decode and parse it.

[0101] Furthermore, the user interface of the vehicle diagnostic tool will display this data, allowing users to intuitively see the status of the battery pack and any potential problems. In turn, diagnostics can be performed based on the target protocol data, including but not limited to comparing data with normal ranges, identifying abnormal patterns, and analyzing trends.

[0102] Optionally, the vehicle diagnostic tool generates a diagnostic report based on the diagnostic results of the target protocol data. This report may include diagnostic results, fault codes, recommended repair measures, and an overall health assessment of the battery pack.

[0103] This embodiment automatically receives multiple data points from the battery pack to be diagnosed via a data transmission interface, reducing the need for manual input and improving the efficiency and accuracy of data collection. Further in-depth analysis of the received data ensures the extraction of key battery pack target data from a large amount of information, thereby improving the accuracy and reliability of the diagnosis. Furthermore, protocol data is generated based on the target data, eliminating the need for manual writing or configuration, greatly simplifying pre-diagnosis preparation and improving work efficiency. By analyzing the generated protocol data, the target protocol data is determined, ensuring the compatibility of the protocol used during diagnosis with the battery pack and enhancing diagnostic accuracy. Therefore, this solution eliminates the need for users to manually select complex information such as vehicle brand, model, and vehicle type; the system processes this automatically, greatly simplifying the operation process. It can also adapt to different brands and models of battery packs, eliminating the need to develop separate diagnostic solutions for each battery pack, thus enhancing the system's versatility and adaptability.

[0104] It should be noted that in the above embodiments, there is no necessarily a certain order between the steps. Those skilled in the art can understand from the description of the embodiments of this application that the above steps may have different execution orders in different embodiments, that is, they may be executed in parallel or in turn, etc.

[0105] Please refer to Figure 3, which is a schematic flowchart of a battery pack diagnostic method provided in an embodiment of this application. The method is applied to an automotive diagnostic instrument in a vehicle battery pack testing system and includes the following steps:

[0106] S201. Receive multiple data points from the battery pack to be diagnosed, wherein the multiple data points of the battery pack to be diagnosed are obtained by the data transmission interface.

[0107] Among these, the data may include, but are not limited to, individual cell voltage, individual cell temperature, total voltage, SOC (State of Charge), and SOH (State of Health) of the battery pack.

[0108] The data transmission interface can receive data from the vehicle's ECU (Electronic Control Unit), the vehicle's OBD (On-Board Diagnostics) diagnostic port, and the battery pack diagnostic port.

[0109] In one embodiment, the data transmission interface device establishes a connection with the BMS of the ECU or battery pack via a physical connection (such as a cable) or wireless communication (such as Bluetooth or Wi-Fi), and simultaneously connects to an automotive diagnostic tool. The automotive diagnostic tool receives multiple data points from the battery pack to be diagnosed and performs data analysis on these multiple data points.

[0110] As can be seen, the vehicle battery pack testing system in this embodiment can realize data transmission from the battery pack to the vehicle diagnostic instrument, providing necessary data support for the diagnosis and analysis of the battery pack, and ensuring the accuracy and efficiency of data transmission.

[0111] S202. Perform data analysis on multiple data points of the battery pack to be diagnosed to obtain the target data of the battery pack to be diagnosed.

[0112] Optionally, before performing data analysis on the various data of the battery pack to be diagnosed, it is necessary to preprocess the raw data, including cleaning, noise reduction, normalization, etc., to ensure the quality and consistency of the data.

[0113] The data analysis process may include, but is not limited to, feature extraction, data analysis methods, and target data generation.

[0114] Specifically, the data analysis is performed by the processing module in the automotive diagnostic tool. The first step in data analysis is feature extraction, which involves identifying and extracting diagnostically useful information from multiple datasets. These features may include battery charge / discharge curves, temperature change trends, voltage fluctuations, 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. These analysis methods are used to find the battery pack's performance indicators and problems from the preprocessed data. For example, cluster analysis can be used to identify abnormal patterns in the data, while time series analysis can be used to monitor changes in battery performance over time. The target data is the data of multiple datasets of the battery pack to be diagnosed after frame processing.

[0115] As can be seen, this embodiment extracts useful target data from complex battery pack data. This target data will be used for subsequent diagnosis and analysis to assess 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.

[0116] In one embodiment, the step of analyzing multiple data points of the battery pack to be diagnosed to obtain target data for the battery pack to be diagnosed includes: identifying the frame structure in the multiple data points of the battery pack to be diagnosed; determining the total number of frames for each type of data in the multiple data points of the battery pack to be diagnosed; identifying the set of frame IDs and the set of frame sequence numbers for each type of data in the total number of frames for each type of data; obtaining the set of start parameters and the set of end parameters for each type of data within a frame; obtaining the target value corresponding to each type of data based on the set of start parameters and the set of end parameters for each type of data within a frame; and mapping the set of frame IDs, the set of frame sequence numbers, and the target value corresponding to each type of data to obtain the target data for the battery pack to be diagnosed.

[0117] Data is typically transmitted in frames, each containing a certain number of data bits. Identifying the frame structure determines how the data is organized within the frame, including start and end markers and possible frame synchronization sequences. A data frame usually contains multiple fields, such as frame ID, frame sequence number, data content, and checksum.

[0118] This involves classifying various data points from the battery pack to be diagnosed, such as voltage data, temperature data, and charge / discharge data. Furthermore, it involves determining the total number of frames for each type of data throughout the entire data transmission process.

[0119] The frame ID is a unique identifier for each data frame, used to distinguish different data frames. The frame sequence number indicates the order in which data frames are transmitted.

[0120] The start parameter set and end parameter set define the specific positions of the data within the frame, i.e., the start and end positions of each type of data; the start parameter set consists of the start byte and the start bit; the end parameter set consists of the end byte and the end bit. For example, assuming we are processing the voltage data of a battery cell, the start parameter set might be the 3rd bit of the 5th byte, and the end parameter set might be the 7th bit of the 7th byte.

[0121] This involves associating the frame ID and frame sequence number of each data type with its corresponding target value to form a structured dataset. This allows each data type to be traced back to its precise location within the original data stream, facilitating further analysis and diagnosis.

[0122] The target value is the actual value for each type of data.

[0123] For example, the voltage data dataset 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℃, Temperature 2: 26℃, Temperature 3: 24℃, Temperature 4: 26℃].

[0124] In one embodiment, obtaining the target value corresponding to each type of data based on the start parameter set and end parameter set of each type of data within the frame includes: acquiring the start parameter set and end parameter set of each type of data within the frame to obtain the position segment of each type of data within the frame; and calculating the position segment of each type of data within the frame and the start parameter set and end parameter set of each type of data within the frame according to a preset formula to obtain the target value corresponding to each type of data.

[0125] The position segment represents the range of data to be processed for each type of data. For example, if the starting parameter set is the second bit of the second byte and the ending 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.

[0126] In practice, binary values ​​are extracted bit by bit from the starting parameter set to the ending parameter set. These binary values ​​represent the original voltage readings. For example, if the starting parameter set is the 3rd bit of the 5th byte, extraction starts from the 3rd bit of the 5th byte and ends at the 7th bit of the 7th byte. Each extracted bit is processed using the formula V = Σf(b), where b is the binary value of each bit, f() is the calculation function for each bit, and V is the final summation value.

[0127] Specifically, in processing each extracted bit using the 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 individually. For the binary value b of each bit, a calculation function f() is applied. This function can be simple, such as directly taking the bit value (0 or 1), or it can be a more complex function, such as performing weighted calculations based on the bit's position 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, check bit calculation, or decoding of a specific encoding. The results of processing all bits using the calculation function f() are summed to obtain the total V.

[0128] For example, suppose 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.

[0129] As can be seen, in this embodiment, the target value can be extracted from the original data frame of the battery pack through the data analysis process. This target value can be used for further diagnosis and analysis to evaluate the health status and performance of the battery pack.

[0130] S203. Determine the target protocol data based on the target data of the battery pack to be diagnosed.

[0131] The target protocol data is generated by the vehicle diagnostic tool 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, data conforming to the transmission protocol regarding the battery pack's voltage, current, temperature, charging status, and health status.

[0132] The protocol data is generated according to the rules of the preset model, which is pre-programmed into the diagnostic instrument to guide data analysis and protocol data generation.

[0133] As can be seen, in this embodiment, the entire protocol data generation process is completed on the vehicle diagnostic instrument, without the need to transmit the data to a remote server for processing, thus improving the real-time performance and efficiency of the diagnosis.

[0134] In one embodiment, determining the target protocol data based on the target data of the battery pack to be diagnosed includes: generating at least one protocol data based on the target data of the battery pack to be diagnosed; and determining the target protocol data based on the at least one protocol data.

[0135] Among them, the target protocol data that best meets the diagnostic needs is selected from the multiple generated protocol data.

[0136] Optionally, if the preset model performs well, then any one of the protocol data in at least one protocol data set can be directly selected as the target protocol data.

[0137] For example, if the preset model can accurately predict and diagnose the state of the battery pack, then the first protocol data generated can be used as the target protocol data without further filtering and verification.

[0138] 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 from 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, wherein the at least one protocol data is generated according to preset rules in the preset model.

[0139] 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 can include, but are not limited to, statistical information, trends, outliers, and patterns, representing the current state of the battery pack. For example, data features might include the battery's voltage range, current fluctuations, temperature changes, and the number of charge / discharge cycles. The feature extraction process may involve data analysis techniques such as principal component analysis (PCA), cluster analysis, and time series analysis.

[0140] The preset model refers to a model built based on historical data and experience. It can predict the state of the battery pack based on the characteristics of the input data. The preset model may include, but is not limited to, machine learning algorithms, such as random forests, neural networks or other statistical methods, to learn the health status of the battery pack from the data characteristics.

[0141] The preset rules can include logical judgments, threshold settings, and classification decisions. The protocol data can be used for: diagnostic reports (providing diagnostic results for the battery pack); control commands (sending instructions to the Battery Management System (BMS) to adjust the battery's operating mode); and data recording (storing historical status information of the battery pack for long-term monitoring and analysis).

[0142] As can be seen, this embodiment improves the accuracy and efficiency of diagnosis by converting raw data into information useful for diagnosing the health status of the battery pack.

[0143] 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 testing system; receiving a confirmation instruction from the display device, the confirmation instruction being 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 for each protocol data; obtaining the verification result of the first protocol data; and determining the first protocol data as the target protocol data when the verification result of the first protocol data is passed.

[0144] The data transmission process involves sending selected protocol data to the display device in the vehicle battery pack testing system via 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 an automotive diagnostic tool, a console, a computer screen, or other user interface, used to display data to the operator.

[0145] The confirmation instruction contains the identifier or content of the selected protocol data. This confirmation instruction can be a click to select, entering a specific code, touching a button on the screen, or any other form of user input. For example, a user's feedback button on the display interface (such as a like or dislike) indicates that a like signifies confirmation, while a dislike signifies rejection.

[0146] The verification process may include checking 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 of the vehicle and the working standard parameters of each component in the vehicle. If the factory parameters or working standard parameters are met, it means that the protocol data verification is successful.

[0147] For example, suppose there is a protocol that includes battery pack voltage, current, and temperature parameters. The battery pack voltage parameters are compared to the factory-standard voltage provided by the vehicle manufacturer. If the voltage value is within the standard range (e.g., 12.6 volts to 14.4 volts), the voltage parameter verification is passed. The battery pack current parameters are compared to the factory-standard operating current range. If the current value is within the allowable range (e.g., -100 amps to 50 amps), the current parameter verification is passed. The battery pack temperature parameters are compared to the standard operating temperature range of each component inside the vehicle. If the temperature value does not exceed the maximum operating temperature (e.g., not exceeding 60 degrees Celsius), the temperature parameter verification is passed.

[0148] Therefore, once all parameters have been compared with factory parameters or standard operating parameters, the protocol data is considered to have passed verification, thus ensuring that the protocol data is not only correctly formatted but also numerically reasonable.

[0149] Furthermore, after verification processing, a verification result is obtained for each piece of protocol data, indicating whether the data has passed verification. The verification result can be a simple pass / fail indication or a detailed error report.

[0150] If the first protocol data passes the verification, it is confirmed as the target protocol data; if the verification result fails, the vehicle diagnostic tool needs to re-analyze the data, adjust the model parameters, or take other measures to generate new protocol data.

[0151] As can be seen, this embodiment can ensure that the protocol data used is accurate and reliable by confirming instructions and verification rules, thereby providing a solid foundation for the maintenance and diagnosis of the battery pack.

[0152] In one embodiment, after verifying the at least one protocol data to obtain the verification result of each protocol data, the method further includes: dynamically adjusting at least one weight corresponding to the first protocol data in the preset model according to a preset weight adjustment rule.

[0153] In the preset model, each data sub-item of the protocol data (such as each byte, each algorithm, each bit, each frame ID, and each frame sequence number) has an initial weight. These weights are all initially 1. The initial weights are used to measure the importance or credibility of each protocol data sub-item.

[0154] The preset weight adjustment rules define under what circumstances the weight should be increased or decreased. If the confirmation instruction is "OK" and the verification result is "Pass", the weight of the corresponding data sub-item will increase. For example, if the user confirms via the "Like" button, the weight of the relevant data sub-item in the first protocol data may increase from 1 to 1.2. If either the confirmation instruction or the verification result contains a negative message, the weight of the corresponding data sub-item may decrease, for example, from 1 to 0.8.

[0155] The more times users provide feedback through the interface, the more significant the cumulative effect of weight adjustments becomes. In other words, with the passage of time and more user interaction, it can more accurately reflect which data sub-items are more important in the diagnostic process.

[0156] For example, the current protocol data includes: battery pack voltage, current, temperature, and SOC (State of Charge); the initial weight of each parameter is set to 1, i.e., voltage (V): weight = 1; current (I): weight = 1; temperature (T): weight = 1; SOC: weight = 1; a preset model analyzes the protocol data and recommends a set of parameter values, which are displayed on the vehicle's dashboard. The user observes an abnormal battery temperature on the dashboard and confirms the preset model's recommendation of temperature parameters by clicking the "like" button on the interface; the system detects that the voltage and SOC parameters remain consistent across multiple measurements, while the current parameter shows... There are certain fluctuations; therefore, since the user confirmed the temperature parameter, the diagnostic tool increases the weight of the temperature parameter, new weight: Temperature (T): weight = 1.2; since the voltage and SOC parameters remained consistent across multiple measurements, the diagnostic tool increases the weight of these two parameters, new weight: Voltage (V): weight = 1.1, SOC: weight = 1.1; since the current parameter shows fluctuations, the diagnostic tool decreases the weight of the current parameter, new weight: Current (I): weight = 0.9, resulting in the adjusted weights: Voltage (V): weight = 1.1; Current (I): weight = 0.9; Temperature (T): weight = 1.2; SOC: weight = 1.1. In the next diagnostic process, the preset model will place greater emphasis on the temperature and SOC parameters because of their higher weights, while the influence of the current parameter will be relatively reduced due to its lower weight.

[0157] As can be seen, the dynamic weight adjustment mechanism in this embodiment enables the preset model to more accurately reflect the real condition of the battery pack. Further preset models can be continuously learned and optimized to ensure that the data and algorithms finally delivered to end users are more accurate and reliable.

[0158] S204. Perform a diagnosis based on the target protocol data.

[0159] Specifically, after the vehicle diagnostic tool obtains the target protocol data, it will perform a comprehensive test and diagnosis of the battery pack based on the built-in fault database and diagnostic algorithms.

[0160] Optionally, after diagnosis based on the target protocol data, the results, such as fault codes, fault descriptions, and suggested maintenance measures, will be displayed on the screen of the diagnostic instrument for technicians to refer to.

[0161] Furthermore, the user interface of the vehicle diagnostic tool will display this data, allowing users to intuitively see the status of the battery pack and any potential problems. In turn, diagnostics can be performed based on the target protocol data, including but not limited to comparing data with normal ranges, identifying abnormal patterns, and analyzing trends.

[0162] Among them, S201-S204 are all analyzed and processed by the processing module in the vehicle diagnostic tool.

[0163] In this embodiment, multiple data points from the battery pack to be diagnosed are received in real time via a data transmission interface, ensuring the timeliness and accuracy of the data. The automotive diagnostic tool analyzes the received battery pack data, generates target data based on the analysis results, and further determines the target protocol data, which helps to accurately locate the fault type and location of the battery pack. Therefore, the automotive diagnostic tool can quickly start the diagnostic process, and the entire diagnostic process is completed on the automotive diagnostic tool without the need to transmit data to a remote server for processing or with complex settings and configurations, thereby improving diagnostic efficiency.

[0164] It should be noted that in the above embodiments, there is no necessarily a certain order between the steps. Those skilled in the art can understand from the description of the embodiments of this application that the above steps may have different execution orders in different embodiments, that is, they may be executed in parallel or in turn, etc.

[0165] As another aspect of the embodiments of this application, this application provides a diagnostic device for a battery pack. The diagnostic device for the battery pack can be a software module, which includes several instructions stored in a memory. A processor can access the memory, call the instructions, and execute them to complete the battery pack diagnostic methods described in the various embodiments above.

[0166] Referring to Figure 4, which is a schematic diagram of a battery pack diagnostic device provided in an embodiment of this application, the device is a server applied to a vehicle battery pack testing system. The vehicle battery pack testing system also includes a data transmission interface and a vehicle diagnostic tool. As shown in Figure 4, the battery pack diagnostic device 400 includes:

[0167] The receiving unit 401 is used to receive multiple data points of the battery pack to be diagnosed, which are obtained by the data transmission interface.

[0168] Analysis unit 402 is used to perform data analysis on multiple data of the battery pack to be diagnosed, and obtain target data of the battery pack to be diagnosed;

[0169] The determining unit 403 is used to determine target protocol data based on the target data of the battery pack to be diagnosed;

[0170] The sending unit 404 is used to send the target protocol data to the vehicle diagnostic tool so that the vehicle diagnostic tool can perform diagnosis based on the target protocol data.

[0171] This embodiment automatically receives multiple data points from the battery pack to be diagnosed via a data transmission interface, reducing the need for manual input and improving the efficiency and accuracy of data collection. Further in-depth analysis of the received data ensures the extraction of key battery pack target data from a large amount of information, thereby improving the accuracy and reliability of the diagnosis. Furthermore, protocol data is generated based on the target data, eliminating the need for manual writing or configuration, greatly simplifying pre-diagnosis preparation and improving work efficiency. By analyzing the generated protocol data, the target protocol data is determined, ensuring the compatibility of the protocol used during diagnosis with the battery pack and enhancing diagnostic accuracy. Therefore, this solution eliminates the need for users to manually select complex information such as vehicle brand, model, and vehicle type; the system processes this automatically, greatly simplifying the operation process. It can also adapt to different brands and models of battery packs, eliminating the need to develop separate diagnostic solutions for each battery pack, thus enhancing the system's versatility and adaptability.

[0172] In one embodiment, in the step of analyzing multiple data points of the battery pack to be diagnosed to obtain target data of the battery pack to be diagnosed, the analysis unit 402 is further configured to: identify the frame structure in the multiple data points of the battery pack to be diagnosed; determine the total number of frames for each type of data in the multiple data points of the battery pack to be diagnosed; identify the set of frame IDs and the set of frame sequence numbers of the frames containing each type of data in the total number of frames containing each type of data; obtain the set of start parameters and the set of end parameters for each type of data within the frame; obtain the target value corresponding to each type of data based on the set of start parameters and the set of end parameters for each type of data within the frame; and match the set of frame IDs, the set of frame sequence numbers, and the target value corresponding to each type of data to obtain the target data of the battery pack to be diagnosed.

[0173] In one embodiment, in obtaining the target value corresponding to each type of data based on the start parameter set and end parameter set of each type of data within the frame, the analysis unit 402 is further configured to: obtain the start parameter set and end parameter set of each type of data within the frame to obtain the position segment of each type of data within the frame; and calculate the position segment of each type of data within the frame and the start parameter set and end parameter set of each type of data within the frame according to a preset formula to obtain the target value corresponding to each type of data.

[0174] In one embodiment, in determining the target protocol data based on the target data of the battery pack to be diagnosed, the determining unit 403 is further configured to: generate at least one protocol data based on the target data of the battery pack to be diagnosed; and determine the target protocol data based on the at least one protocol data.

[0175] In one embodiment, in the step of generating at least one protocol data based on the target data of the battery pack to be diagnosed, the determining unit 403 is further configured to: extract data features from 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, wherein the at least one protocol data is generated according to preset rules in the preset model.

[0176] In one embodiment, the determining unit 403, in determining the target protocol data based on the at least one protocol data, is further configured to: send the at least one protocol data to a display device in the vehicle battery pack testing system; receive a confirmation instruction from the display device, the confirmation instruction being used to determine a first protocol data among 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 determine the first protocol data as the target protocol data when the verification result of the first protocol data is passed.

[0177] In one embodiment, after verifying the at least one protocol data to obtain the verification result of each protocol data, the determining unit 403 is further configured to: dynamically adjust at least one weight corresponding to the first protocol data in the preset model according to a preset weight adjustment rule.

[0178] It should be noted that the above-mentioned battery pack diagnostic device can execute the battery pack diagnostic method provided in the embodiments of this application, and has the corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in the embodiments of the battery pack diagnostic device can be found in the battery pack diagnostic method provided in embodiments S101-S104 of this application.

[0179] Referring to Figure 5, which is a schematic diagram of a battery pack diagnostic device provided in an embodiment of this application, the vehicle diagnostic instrument applied to a vehicle battery pack testing system, as shown in Figure 5, includes:

[0180] The receiving unit 501 is used to receive multiple data points of the battery pack to be diagnosed, which are obtained by the data transmission interface.

[0181] Analysis unit 502 is used to perform data analysis on multiple data of the battery pack to be diagnosed, and obtain target data of the battery pack to be diagnosed;

[0182] The determining unit 503 is used to determine target protocol data based on the target data of the battery pack to be diagnosed;

[0183] The diagnostic unit 504 is used to perform diagnostics based on the target protocol data.

[0184] In this embodiment, multiple data points from the battery pack to be diagnosed are received in real time via a data transmission interface, ensuring the timeliness and accuracy of the data. The automotive diagnostic tool analyzes the received battery pack data, generates target data based on the analysis results, and further determines the target protocol data, which helps to accurately locate the fault type and location of the battery pack. Therefore, the automotive diagnostic tool can quickly start the diagnostic process, and the entire diagnostic process is completed on the automotive diagnostic tool without the need to transmit data to a remote server for processing or with complex settings and configurations, thereby improving diagnostic efficiency.

[0185] It should be noted that the above-described battery pack diagnostic device can execute the battery pack diagnostic method provided in the embodiments of this application, and has the corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in the embodiments of the battery pack diagnostic device can be found in the battery pack diagnostic method provided in embodiments S201-S203 of this application.

[0186] This application embodiment also provides a computer-readable storage medium, including a first computer-readable storage medium and a second computer-readable storage medium. The first computer-readable storage medium stores a first computer program, which includes first program instructions. When the first program instructions are executed by a first processor, the first processor performs the battery pack diagnostic method as described in the aforementioned embodiments S101-S104. The second computer-readable storage medium stores a second computer program, which includes second program instructions. When the second program instructions are executed by a second processor, the second processor performs the battery pack diagnostic method as described in the aforementioned embodiments S201-S204.

[0187] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0188] The above-disclosed embodiments are merely preferred embodiments of this application and should not be construed as limiting the scope of this application. Therefore, any equivalent variations made in accordance with the claims of this application shall still fall within the scope of this application.

Claims

A diagnostic method for a battery pack, characterized in that, A server for a vehicle battery pack testing system, the vehicle battery pack testing system further including a data transmission interface and a vehicle diagnostic tool, the method comprising: Receive multiple data points from the battery pack to be diagnosed, which are obtained by the data transmission interface. Data analysis is performed on multiple data points of the battery pack to be diagnosed to obtain the target data of the battery pack to be diagnosed. Based on the target data of the battery pack to be diagnosed, determine the target protocol data; The target protocol data is sent to the vehicle diagnostic tool so that the vehicle diagnostic tool can perform diagnosis based on the target protocol data. The method according to claim 1, characterized in that, The step of analyzing multiple data points of the battery pack to be diagnosed to obtain target data for the battery pack to be diagnosed includes: Identify the frame structure in multiple data items of the battery pack to be diagnosed, and determine the total number of frames for each type of data in the multiple data items of the battery pack to be diagnosed; Identify the set of frame IDs and the set of frame sequence numbers of the frames containing each type of data in the total number of frames for each type of data; Obtain the start parameter set and end parameter set of each type of data within the frame; Based on the start parameter set and end parameter set of each type of data within the frame, the target value corresponding to each type of data is obtained; The target data of the battery pack to be diagnosed is obtained by matching the set of frame IDs of the frames containing each type of data, the set of frame sequence numbers of the frames containing each type of data, and the target value corresponding to each type of data. The method according to claim 2, characterized in that, The step of obtaining the target value corresponding to each type of data based on the start parameter set and end parameter set of each type of data within the frame includes: Obtain the start parameter set and end parameter set of each type of data within the frame to determine the position segment of each type of data within the frame; According to the preset formula, the position segment of each type of data within the frame and the start parameter set and end parameter set of each type of data within the frame are calculated to obtain the target value corresponding to each type of data. The method according to claim 1, characterized in that, The step of determining the target protocol data based on the target data of the battery pack to be diagnosed includes: Based on the target data of the battery pack to be diagnosed, at least one protocol data is generated; Based on the at least one protocol data, determine the target protocol data. The method according to claim 4, characterized in that, The step of generating at least one protocol data based on the target data of the battery pack to be diagnosed includes: Extract data features from the target data of the battery pack to be diagnosed; The data features are input into a preset model to obtain at least one protocol data, which is generated according to preset rules in the preset model. The method according to claim 4, characterized in that, Determining the target protocol data based on the at least one protocol data includes: The at least one protocol data is sent to the display device of the vehicle battery pack detection system; Receive a confirmation instruction from the display device, the confirmation instruction being used to determine a first protocol data among the at least one protocol data; The at least one protocol data is verified to obtain the verification result for each protocol data. Obtain the 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 the target protocol data. The method according to claim 6, characterized in that, After performing verification processing on the at least one protocol data to obtain the verification result for each protocol data, the method further includes: In the preset model, at least one weight corresponding to the first protocol data is dynamically adjusted according to preset weight adjustment rules. A diagnostic method for a battery pack, characterized in that, An automotive diagnostic tool applied to a vehicle battery pack testing system, the vehicle battery pack testing system further including a data transmission interface, the method comprising: Receive multiple data points from the battery pack to be diagnosed, which are obtained by the data transmission interface. Data analysis is performed on multiple data points of the battery pack to be diagnosed to obtain the target data of the battery pack to be diagnosed. Based on the target data of the battery pack to be diagnosed, determine the target protocol data; Diagnosis is performed based on the target protocol data. A vehicle battery pack testing system, characterized in that, The system includes a server and an automotive diagnostic tool. The server includes a first memory and a first processor, the first memory being connected to the first processor. The first processor is configured to execute one or more computer programs stored in the first memory, wherein when the first processor executes the one or more computer programs, the server implements the diagnostic method for a battery pack as described in any one of claims 1-7. The automotive diagnostic tool includes a second memory and a second processor, the second memory being connected to the second processor. The second processor is configured to execute one or more computer programs stored in the second memory, wherein when the second processor executes the one or more computer programs, the automotive diagnostic tool implements the diagnostic method for a battery pack as described in claim 8. A computer-readable storage medium, characterized in that, The device includes a first computer-readable storage medium and a second computer-readable storage medium. The first computer-readable storage medium stores a first computer program, which includes first program instructions that, when executed by a first processor, cause the first processor to perform the diagnostic method for a battery pack as described in any one of claims 1-7. The second computer-readable storage medium stores a second computer program, which includes second program instructions that, when executed by a second processor, cause the second processor to perform the diagnostic method for a battery pack as described in claim 8.

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