Charging and discharging detection method, device and equipment

Abstract

The embodiment of the invention provides a charging and discharging detection method, device and equipment. The method comprises the following steps: acquiring charging and discharging data of to-be-detected equipment, wherein the charging and discharging data comprises battery voltage, charging current, a charging protocol, discharging current, temperature and electric quantity percentage; based on a plurality of preset detection dimensions, extracting to-be-analyzed data corresponding to each detection dimension from the charging and discharging data, and based on the to-be-analyzed data corresponding to each detection dimension and a preset detection standard of each detection dimension, determining a detection result of each detection dimension, the plurality of detection dimensions at least comprise a battery health degree, a capacity voltage curve, a charging protocol conformity and a temperature control mechanism; and based on the detection results of the plurality of detection dimensions, generating a comprehensive charging and discharging health state report or a diagnosis report for the to-be-detected equipment. Automatic and multi-dimensional analysis of the charging and discharging process of the equipment is realized, and the efficiency and the accuracy are improved.

Description

Technical Field

[0001] This application relates to the field of battery technology, and in particular to a charge / discharge detection method, apparatus, and equipment. Background Technology

[0002] In the daily use of electronic devices, the charging and discharging performance of the battery directly affects the device's battery life, safety, and user experience.

[0003] Analyzing the battery charging and discharging process of a device can provide a basis for optimizing battery charging and discharging management. In related technologies, charging and discharging data can be saved by searching system logs for keywords. However, analyzing this data often relies on simple judgments based on human experience, which is inefficient and results in highly subjective analysis. Summary of the Invention

[0004] This application provides a charge / discharge detection method, apparatus, and device, which realizes automated and multi-dimensional analysis of the charging and discharging process of the device, improving efficiency and accuracy.

[0005] In a first aspect, embodiments of this application provide a charge / discharge detection method, including:

[0006] Acquire the charging and discharging data of the device under test, including battery voltage, charging current, charging protocol, discharging current, temperature, and battery percentage;

[0007] Based on multiple preset detection dimensions, the data to be analyzed corresponding to each detection dimension is extracted from the charging and discharging data. Based on the data to be analyzed corresponding to each detection dimension and the preset detection standards for each detection dimension, the detection result of each detection dimension is determined. The multiple detection dimensions include at least: battery health, capacity-voltage curve, charging protocol compliance, and temperature control mechanism.

[0008] Based on the detection results from the multiple detection dimensions, a comprehensive charge and discharge health status report or diagnostic report for the device under test is generated.

[0009] In some implementation methods, generating a comprehensive charge / discharge health status report or diagnostic report for the device under test based on the detection results from the multiple detection dimensions includes:

[0010] Based on the device type and usage scenario of the device to be tested, dynamic weights are assigned to the detection results of the multiple detection dimensions respectively;

[0011] Based on the dynamic weights, the dimensional scores in the detection results of each detection dimension are weighted and fused to obtain the comprehensive health score of the device under test.

[0012] Based on the comprehensive health score and the detection results of each detection dimension, the comprehensive charge and discharge health status report or the diagnostic report is generated.

[0013] In some implementation methods, acquiring the charge / discharge data of the device under test includes:

[0014] The charging and discharging data can be read in real time by calling the standardized data interface of the battery management system built into the device under test; or,

[0015] The charging and discharging data are collected by coupling the external charging and discharging detector into the charging and discharging circuit of the device under test.

[0016] In some implementation methods, the step of extracting data to be analyzed corresponding to each detection dimension from the charge / discharge data based on multiple preset detection dimensions, and determining the detection result of each detection dimension based on the data to be analyzed corresponding to each detection dimension and the preset detection standards for each detection dimension, includes:

[0017] When the detection dimension is charging protocol compliance, the data to be analyzed corresponding to the charging protocol compliance is extracted from the charging and discharging data. The data to be analyzed corresponding to the charging protocol compliance includes: battery voltage, charging current, charging protocol and power percentage during the charging process.

[0018] The corresponding charging standard is determined according to the charging protocol, and it is determined whether the battery voltage, charging current and charge percentage during the charging process meet the charging standard. If they do not meet the charging standard, improvement suggestions are output based on the charging standard.

[0019] In some implementation methods, determining the corresponding charging standard according to the charging protocol and judging whether the battery voltage, charging current, and charge percentage during the charging process conform to the charging standard includes:

[0020] Determine whether the charging protocol is the standard charging protocol of the device under test;

[0021] If the charging protocol is the standard charging protocol of the device to be tested, then extract the first data to be analyzed from the data to be analyzed corresponding to the charging protocol compliance, which shows that the battery voltage is lower than the first voltage threshold, and the second data to be analyzed shows that the battery voltage is greater than or equal to the first voltage threshold.

[0022] Determine whether the charging current and power percentage in the first data to be analyzed conform to the constant current charging standard of the standard charging protocol;

[0023] Determine whether the battery voltage, charging current, and charge percentage in the second data to be analyzed meet the constant voltage charging standard of the standard charging protocol, and whether the charge percentage data from 99% to 100% in the second data to be analyzed meet the full charge charging standard.

[0024] Some implementation methods also include:

[0025] If the charging protocol is not the standard charging protocol of the device under test, then determine whether the charging protocol is a recognizable known protocol;

[0026] If the charging protocol is a known protocol, then determine whether the battery voltage, charging current, and charge percentage during the charging process conform to the charging standards of the known protocol.

[0027] Some implementation methods also include:

[0028] If the charging protocol is an unrecognizable unknown protocol, then determine whether the battery voltage, charging current and charge percentage during the charging process conform to the general charging standard.

[0029] Some implementation methods also include:

[0030] The charging protocol compliance dimension score is determined based on the degree of non-compliance of data such as battery voltage, charging current, and charge percentage during the charging process with charging standards.

[0031] In some implementation methods, the step of extracting data to be analyzed corresponding to each detection dimension from the charge / discharge data based on multiple preset detection dimensions, and determining the detection result of each detection dimension based on the data to be analyzed corresponding to each detection dimension and the preset detection standards for each detection dimension, includes:

[0032] When the detection dimension is the temperature control mechanism, the data to be analyzed corresponding to the temperature control mechanism is extracted from the charging and discharging data. The data to be analyzed corresponding to the temperature control mechanism includes: the temperature during the charging process and the charging current.

[0033] From the data to be analyzed corresponding to the temperature control mechanism, extract the charging current of multiple preset first temperature ranges;

[0034] It determines whether the temperature during the charging process exceeds the maximum temperature threshold, and whether the charging current in each first temperature range meets the preset charging current standard corresponding to the first temperature range. If it does not meet the preset charging current standard, it outputs improvement suggestions based on the preset charging current standard.

[0035] Some implementation methods also include:

[0036] The threshold score is determined based on whether the temperature during the charging process exceeds the maximum temperature threshold.

[0037] The score for each first temperature range is determined based on the proportion of charging currents in each first temperature range that do not meet the preset charging current standard.

[0038] The dimensional score of the temperature control mechanism is determined based on the scores of each first temperature range and the threshold score.

[0039] In some implementation methods, the step of extracting data to be analyzed corresponding to each detection dimension from the charge / discharge data based on multiple preset detection dimensions, and determining the detection result of each detection dimension based on the data to be analyzed corresponding to each detection dimension and the preset detection standards for each detection dimension, includes:

[0040] When the detection dimension is battery health, the data to be analyzed corresponding to battery health is extracted from the charging and discharging data. The data to be analyzed corresponding to battery health includes: battery voltage and discharge current during the process of battery percentage decreasing by a preset ratio, and battery voltage and discharge current when the discharge current is greater than a preset value.

[0041] The actual discharge capacity is determined based on the battery voltage and discharge current during the process of the battery percentage decreasing by a preset percentage, as well as the duration of the battery percentage decreasing by the preset percentage. The first battery health is determined based on the actual discharge capacity and the theoretical capacity.

[0042] The actual battery internal resistance is determined based on the battery voltage and discharge current when the discharge current is greater than the preset value, and the health of the second battery is determined based on the actual battery internal resistance and the theoretical internal resistance.

[0043] Based on the first battery health status and the second battery health status, the battery health status is determined, and improvement suggestions are output when the battery health status is lower than the preset battery health status standard.

[0044] Some implementation methods also include:

[0045] The dimension score of the battery health is determined based on the battery health, and the dimension score of the battery health is positively correlated with the battery health.

[0046] In some implementation methods, the step of extracting data to be analyzed corresponding to each detection dimension from the charge / discharge data based on multiple preset detection dimensions, and determining the detection result of each detection dimension based on the data to be analyzed corresponding to each detection dimension and the preset detection standards for each detection dimension, includes:

[0047] When the detection dimension is the capacity-voltage curve, the data to be analyzed corresponding to the capacity-voltage curve is extracted from the charge-discharge data. The data to be analyzed corresponding to the capacity-voltage curve includes: battery voltage, charge percentage and temperature during the discharge process.

[0048] Extract the battery voltage and charge percentage for multiple preset second temperature ranges from the data to be analyzed in the capacity-voltage curve;

[0049] Determine whether the battery voltage and charge percentage in each of the second temperature ranges conform to the capacity-voltage standard curve corresponding to the second temperature range, and if they do not conform to the capacity-voltage standard curve, output improvement suggestions based on the preset capacity-voltage curve.

[0050] Some implementation methods also include:

[0051] The score for each second temperature range is determined based on the proportion of battery voltage and charge percentage that do not conform to the capacity-voltage standard curve corresponding to the second temperature range.

[0052] The dimension score of the capacity-voltage curve is determined based on the score of each second temperature range.

[0053] Secondly, embodiments of this application provide a charge / discharge detection device, comprising:

[0054] The acquisition module is used to acquire the charging and discharging data of the device under test, including battery voltage, charging current, charging protocol, discharging current, temperature, and battery percentage.

[0055] The detection module is used to extract the data to be analyzed corresponding to each detection dimension from the charging and discharging data based on multiple preset detection dimensions, and to determine the detection result of each detection dimension based on the data to be analyzed corresponding to each detection dimension and the preset detection standards for each detection dimension. The multiple detection dimensions include at least: battery health, capacity-voltage curve, charging protocol compliance and temperature control mechanism.

[0056] The report output module is used to generate a comprehensive charge and discharge health status report or diagnostic report for the device under test based on the detection results of the multiple detection dimensions.

[0057] In some implementations, the report output module is used for:

[0058] Based on the device type and usage scenario of the device to be tested, dynamic weights are assigned to the detection results of the multiple detection dimensions respectively;

[0059] Based on the dynamic weights, the dimensional scores in the inspection results of each detection dimension are weighted and fused to obtain the comprehensive health score of the device under test.

[0060] Based on the comprehensive health score and the detection results of each detection dimension, the comprehensive charge and discharge health status report or the diagnostic report is generated.

[0061] In some implementations, the acquisition module is used to:

[0062] The charging and discharging data can be read in real time by calling the standardized data interface of the battery management system built into the device under test; or,

[0063] The charging and discharging data are collected by coupling the external charging and discharging detector into the charging and discharging circuit of the device under test.

[0064] In some implementations, the detection module is used for:

[0065] When the detection dimension is charging protocol compliance, the data to be analyzed corresponding to the charging protocol compliance is extracted from the charging and discharging data. The data to be analyzed corresponding to the charging protocol compliance includes: battery voltage, charging current, charging protocol and power percentage during the charging process.

[0066] The corresponding charging standard is determined according to the charging protocol, and it is determined whether the battery voltage, charging current and charge percentage during the charging process meet the charging standard. If they do not meet the charging standard, improvement suggestions are output based on the charging standard.

[0067] In some implementations, the detection module is used for:

[0068] Determine whether the charging protocol is the standard charging protocol of the device under test;

[0069] If the charging protocol is the standard charging protocol of the device to be tested, then extract the first data to be analyzed from the data to be analyzed corresponding to the charging protocol compliance, which shows that the battery voltage is lower than the first voltage threshold, and the second data to be analyzed shows that the battery voltage is greater than or equal to the first voltage threshold.

[0070] Determine whether the charging current and power percentage in the first data to be analyzed conform to the constant current charging standard of the standard charging protocol;

[0071] Determine whether the battery voltage, charging current, and charge percentage in the second data to be analyzed meet the constant voltage charging standard of the standard charging protocol, and whether the charge percentage data from 99% to 100% in the second data to be analyzed meet the full charge charging standard.

[0072] In some implementations, the detection module is used for:

[0073] If the charging protocol is not the standard charging protocol of the device under test, then determine whether the charging protocol is a recognizable known protocol;

[0074] If the charging protocol is a known protocol, then determine whether the battery voltage, charging current, and charge percentage during the charging process conform to the charging standards of the known protocol.

[0075] In some implementations, the detection module is used for:

[0076] If the charging protocol is an unrecognizable unknown protocol, then determine whether the battery voltage, charging current and charge percentage during the charging process conform to the general charging standard.

[0077] In some implementations, the detection module is used for:

[0078] The charging protocol compliance dimension score is determined based on the degree of non-compliance of data such as battery voltage, charging current, and charge percentage during the charging process with charging standards.

[0079] In some implementations, the detection module is used for:

[0080] When the detection dimension is the temperature control mechanism, the data to be analyzed corresponding to the temperature control mechanism is extracted from the charging and discharging data. The data to be analyzed corresponding to the temperature control mechanism includes: the temperature during the charging process and the charging current.

[0081] From the data to be analyzed corresponding to the temperature control mechanism, extract the charging current of multiple preset first temperature ranges;

[0082] It determines whether the temperature during the charging process exceeds the maximum temperature threshold, and whether the charging current for each first temperature range conforms to the preset charging current standard corresponding to the first temperature range. If it does not conform to the preset charging current standard, it outputs improvement suggestions based on the preset charging current standard.

[0083] In some implementations, the detection module is used for:

[0084] The threshold score is determined based on whether the temperature during the charging process exceeds the maximum temperature threshold.

[0085] The score for each first temperature range is determined based on the proportion of charging currents in each first temperature range that do not meet the preset charging current standard.

[0086] The dimensional score of the temperature control mechanism is determined based on the scores of each first temperature range and the threshold score.

[0087] In some implementations, the detection module is used for:

[0088] When the detection dimension is battery health, the data to be analyzed corresponding to battery health is extracted from the charging and discharging data. The data to be analyzed corresponding to battery health includes: battery voltage and discharge current during the process of battery percentage decreasing by a preset ratio, and battery voltage and discharge current when the discharge current is greater than a preset value.

[0089] The actual discharge capacity is determined based on the battery voltage and discharge current during the process of the battery percentage decreasing by a preset percentage, as well as the duration of the battery percentage decreasing by the preset percentage. The first battery health is determined based on the actual discharge capacity and the theoretical capacity.

[0090] The actual battery internal resistance is determined based on the battery voltage and discharge current when the discharge current is greater than the preset value, and the health of the second battery is determined based on the actual battery internal resistance and the theoretical internal resistance.

[0091] Based on the first battery health status and the second battery health status, the battery health status is determined, and improvement suggestions are output when the battery health status is lower than the preset battery health status standard.

[0092] In some implementations, the detection module is used for:

[0093] The dimension score of the battery health is determined based on the battery health, and the dimension score of the battery health is positively correlated with the battery health.

[0094] In some implementations, the detection module is used for:

[0095] When the detection dimension is the capacity-voltage curve, the data to be analyzed corresponding to the capacity-voltage curve is extracted from the charge-discharge data. The data to be analyzed corresponding to the capacity-voltage curve includes: battery voltage, charge percentage and temperature during the discharge process.

[0096] Extract the battery voltage and charge percentage for multiple preset second temperature ranges from the data to be analyzed in the capacity-voltage curve;

[0097] Determine whether the battery voltage and charge percentage in each of the second temperature ranges conform to the capacity-voltage standard curve corresponding to the second temperature range, and if they do not conform to the capacity-voltage standard curve, output improvement suggestions based on the preset capacity-voltage curve.

[0098] In some implementations, the detection module is used for:

[0099] The score for each second temperature range is determined based on the proportion of battery voltage and charge percentage that do not conform to the capacity-voltage standard curve corresponding to the second temperature range.

[0100] The dimension score of the capacity-voltage curve is determined based on the score of each second temperature range.

[0101] Thirdly, embodiments of this application provide a charge / discharge detection device, including:

[0102] A hardware interface module is used to connect to the battery management system data interface of the device under test or to be coupled to the charging and discharging circuit of the device under test in order to obtain the charging and discharging data of the device under test.

[0103] A collaborative analysis processor, connected to the hardware interface module, stores executable instructions internally, which are executed at runtime as described in the first aspect;

[0104] The report output module, connected to the collaborative analysis processor, is used to output the comprehensive charge and discharge health status report or diagnostic report.

[0105] Fourthly, embodiments of this application provide a charge / discharge detection device, comprising:

[0106] case;

[0107] The charge / discharge detection device as described in the second or third aspect is integrated within the housing;

[0108] A human-computer interaction interface is set on the housing and connected to the report output module of the charge and discharge detection device, used to display the comprehensive charge and discharge health status report or diagnostic report;

[0109] A power module is used to supply power to the charge and discharge detection equipment.

[0110] Fifthly, embodiments of this application provide an electronic device, including: a memory and a processor;

[0111] The memory stores computer-executed instructions;

[0112] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and various possible implementations of the first aspect as described above.

[0113] In a sixth aspect, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and various possible implementations thereof.

[0114] In a seventh aspect, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and various possible implementations thereof.

[0115] The charge / discharge detection method, apparatus, and device provided in this application, based on multiple preset detection dimensions and detection standards for each detection dimension, extract corresponding data to be analyzed from the charge / discharge data of the device under test, and analyze the data to be analyzed and the corresponding detection standards to obtain the detection results for that detection dimension. This achieves automated and multi-dimensional analysis of the charge / discharge process. Compared with the prior art that relies on human experience to analyze charge / discharge data, the comprehensive automated analysis method in this application provides more objective detection results, saves labor costs, improves detection efficiency, and improves the accuracy of detection results. Attached Figure Description

[0116] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0117] Figure 1 A schematic flowchart of the charge / discharge detection method provided in this application;

[0118] Figure 2 This is a schematic diagram of the charge / discharge detection device provided in this application;

[0119] Figure 3 A schematic diagram of the structure of the electronic device provided in this application.

[0120] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0121] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0122] The charge / discharge detection method provided in this application extracts corresponding data to be analyzed from the charge / discharge data of the device under test based on multiple preset detection dimensions and detection standards for each detection dimension. Based on the data to be analyzed and the corresponding detection standards, the detection results of the detection dimension are obtained, and a corresponding comprehensive charge / discharge health status report or diagnostic report is generated. This achieves automated and multi-dimensional analysis of the charge / discharge process, improves detection efficiency, and enhances the accuracy of detection results.

[0123] The charge / discharge detection method provided in this application embodiment can be executed by the device under test (DUT). That is, after collecting its own charge / discharge data, the DUT performs detection and analysis on the data based on the method of this application embodiment to obtain the detection result. Alternatively, the charge / discharge detection method provided in this application embodiment can be executed by a charge / discharge detection device other than the DUT. The DUT can send the collected charge / discharge data to the charge / discharge detection device, or the DUT can send the collected charge / discharge data to the cloud. The charge / discharge detection device can then obtain the charge / discharge data from the cloud and perform detection and analysis on the DUT's charge / discharge data to obtain the detection result. This charge / discharge detection device can be, for example, a server or a portable device. In some implementations, the DUT or the charge / discharge detection device can read the DUT's charge / discharge data in real time by calling the standardized data interface of the DUT's built-in battery management system. In some implementations, the DUT or the charge / discharge detection device uses an external charge / discharge detector to couple and collect charge / discharge data in the DUT's charge / discharge circuit. The external charge / discharge detector can include a charging detector and a discharging detector, or it can be an integrated charge / discharge detector.

[0124] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0125] Figure 1 Flowchart of the charge / discharge detection method provided in this application Figure 1 The execution entity of this method can be a charge / discharge detection device, which can be implemented through software and / or hardware. This charge / discharge detection device can be installed in the device under test or in a separate charge / discharge detection device. For example... Figure 1 As shown, the method includes:

[0126] S101. Obtain the charging and discharging data of the device under test. The charging and discharging data includes battery voltage, charging current, charging protocol, discharging current, temperature and charge percentage.

[0127] The charging and discharging data of the device under test can be collected and generated in real time during the charging and discharging process. The device under test can collect data through the system log interface or dedicated sensors and store it as a structured file (such as an Excel spreadsheet). For example, when the device under test is fast charging, charging data is recorded at certain time intervals, such as battery voltage (4.2V), charging current (2A), temperature (30℃), and battery percentage (80%), and the charging protocol is marked as fast charging (QC). In addition, the charging and discharging data also includes timestamps.

[0128] S102. Based on multiple preset detection dimensions, extract the data to be analyzed corresponding to each detection dimension from the charging and discharging data, and determine the detection result of each detection dimension based on the data to be analyzed corresponding to each detection dimension and the preset detection standards of each detection dimension. The multiple detection dimensions include at least: battery health, capacity-voltage curve, charging protocol compliance and temperature control mechanism.

[0129] Each detection dimension is used to detect whether the battery charging and discharging process meets the standards or whether there are any abnormalities from different perspectives. Corresponding detection standards can be pre-configured for each detection dimension. The detection standards for each detection dimension may include thresholds or change patterns that data such as voltage, current, temperature or charge percentage need to meet. The above detection standards can be pre-configured in the form of data so that the charging and discharging detection data can be compared with the data in the pre-configured detection standards.

[0130] Battery health is used to characterize the health status of the battery. As the battery is used for a longer period of time, the battery health will decrease. When the battery health decreases to a certain level, its range, safety and other aspects may not meet the requirements of the device. Therefore, the battery health is tested to evaluate the battery charging and discharging performance.

[0131] The capacity-voltage curve is used to represent the relationship between battery voltage and battery percentage. Under normal circumstances, the relationship between battery voltage and battery percentage conforms to certain design specifications. By testing the actual capacity-voltage curve, it is possible to assess whether the battery percentage is normal.

[0132] Different charging protocols are used during battery charging, resulting in different charging processes. Each charging protocol has its own charging standards, which include requirements for battery voltage, charging current, etc. By checking the compliance of the charging protocol, it is possible to assess whether the charging process meets the standards.

[0133] A temperature control mechanism refers to corresponding charging standards at different temperatures; for example, charging may not be allowed at excessively high or low temperatures. By detecting the temperature control mechanism, it is possible to assess whether the battery charging process conforms to the charging standards at the corresponding temperatures.

[0134] As can be seen from the above explanation of each detection dimension, the data to be analyzed differs for each dimension. For each dimension, the corresponding data to be analyzed can be extracted from the charging and discharging data. For example, the charging and discharging data is stored in an Excel spreadsheet. Data extraction can be performed using the pandas and openpyxl libraries in Python. Then, based on the data to be analyzed and the detection standard for that dimension, the detection result for that dimension is determined. The detection result can include whether the data to be analyzed for that dimension meets the detection standard, and it can also include the dimension score determined based on this standard.

[0135] S103. Based on the detection results from multiple detection dimensions, generate a comprehensive charge and discharge health status report or diagnostic report for the device under test.

[0136] A comprehensive charge / discharge health status report or diagnostic report can include the test results for each testing dimension. For example, it may display data that does not meet the testing standards for each testing dimension. The report may also include a comprehensive evaluation result derived from the integrated processing of the test results for each testing dimension. For instance, it may generate a comprehensive health score for the device under test based on the test results for each dimension, using this score to characterize the overall charge / discharge performance of the device.

[0137] The method in this application embodiment extracts corresponding data to be analyzed from the charging and discharging data of the device under test based on multiple preset detection dimensions and detection standards for each detection dimension. It then analyzes the data to be analyzed and the corresponding detection standards to obtain the detection results for that detection dimension. Finally, it generates a comprehensive charging and discharging health status report or diagnostic report for the device under test based on the detection results of each detection dimension. This achieves automated and multi-dimensional analysis of the charging and discharging process. Compared to existing technologies that rely on human experience to analyze charging and discharging data, the comprehensive automated analysis method in this application embodiment provides more objective detection results, saves labor costs, improves detection efficiency, and enhances the accuracy of the detection results.

[0138] In some embodiments, based on the detection results from multiple detection dimensions, a comprehensive charge / discharge health status report or diagnostic report for the device under test is generated, including:

[0139] Based on the device type and usage scenario of the device under test, dynamic weights are assigned to the test results of multiple test dimensions. According to the dynamic weights, the dimension scores in the test results of each test dimension are weighted and fused to obtain the comprehensive health score of the device under test. Based on the comprehensive health score, the dimension scores of each test dimension and the test results of each test dimension, a comprehensive charge and discharge health status report or diagnostic report is generated.

[0140] The emphasis on each detection dimension may differ depending on the device type. For example, the device under test may be a smart terminal, a robot, or an electric vehicle. The weight of each detection dimension can be configured according to the device type. Furthermore, the emphasis on each detection dimension may also differ depending on the usage scenario. For instance, if the device is always used in an environment with a relatively constant temperature, the weight of the temperature control mechanism can be set relatively low. Similarly, if the device is always charged using the standard charger, the weight of charging protocol compliance can be set relatively low. Taking into account both device type and usage scenario, dynamic weights are assigned to the detection results across multiple dimensions. For example, for smart terminals used in normal temperature environments, the weights for battery health, capacity-voltage curves, charging protocol compliance, and temperature control mechanisms are 0.3, 0.25, 0.25, and 0.2, respectively. Similarly, for robots used in high-temperature environments, the weights are 0.25, 0.2, 0.25, and 0.3, respectively. Furthermore, for smart terminals used in uncertain environments, the weights are 0.25, 0.25, 0.25, and 0.25, respectively. By weighted and fused from these multi-dimensional detection results, the resulting comprehensive health score more fully reflects the multi-dimensional charging and discharging performance, avoiding potential biases from single-dimensional detection. Pre-testing can be conducted for different device types and usage scenarios to ensure appropriate weight settings and thus guarantee the accuracy of the results.

[0141] For the detection results of each detection dimension, the corresponding dimension score can be determined based on the detection standard of that dimension. The more the detection result conforms to the detection standard, the higher the corresponding dimension score. The detection results and corresponding dimension scores of each detection dimension will be described in subsequent embodiments. After determining the dimension scores of each detection dimension, the dimension scores of each detection dimension are weighted and summed based on the dynamic weights of each detection dimension to obtain the comprehensive health score of the device under test. The comprehensive charge and discharge health status report or diagnostic report can display the comprehensive health score and the detection results of each detection dimension, so that the report can comprehensively reflect the comprehensive charge and discharge performance of the device under test and intuitively reflect the performance of each detection dimension.

[0142] The analysis process for each detection dimension will be explained below.

[0143] When the detection dimension is charging protocol compliance, the data to be analyzed corresponding to the charging protocol compliance is extracted from the charging and discharging data. The data to be analyzed corresponding to the charging protocol compliance includes: battery voltage, charging current, charging protocol and battery percentage during the charging process.

[0144] The corresponding charging standard is determined based on the charging protocol, and it is judged whether the battery voltage, charging current and charge percentage during the charging process meet the charging standard. If they do not meet the charging standard, improvement suggestions are output based on the charging standard.

[0145] Different charging protocols set corresponding standards for battery voltage, charging current, and battery percentage. Therefore, when analyzing charging protocol compliance, the battery voltage, charging current, charging protocol, and battery percentage during the charging process are extracted. Based on this data, the analysis determines whether the charging protocol is met and identifies the corresponding charging standard. If the charging standard is not met, the improvement suggestion can be to limit the non-compliant battery voltage, charging current, or battery percentage to the data range corresponding to the charging standard. For example, if the charging current exceeds the standard range specified in the charging standard, the improvement suggestion could be to limit the charging current to the standard range.

[0146] When different chargers are used for charging, the corresponding charging protocols may differ. When analyzing data during the charging process, the first step is to determine whether the charging protocol is the standard charging protocol of the device under test, which essentially means whether the standard charger was used for charging. If the charging protocol is the standard charging protocol of the device under test, then the first data to be analyzed, where the battery voltage is lower than the first voltage threshold, and the second data to be analyzed, where the battery voltage is greater than or equal to the first voltage threshold, are extracted from the data to be analyzed corresponding to the charging protocol compliance. It is then determined whether the charging current and charge percentage in the first data to be analyzed conform to the constant current charging standard of the standard charging protocol. Finally, it is determined whether the battery voltage, charging current, and charge percentage in the second data to be analyzed conform to the constant voltage charging standard of the standard charging protocol, and whether the charge percentage data from 99% to 100% in the second data to be analyzed conforms to the full charge charging standard.

[0147] When the charging protocol is the standard charging protocol, it typically employs segmented charging. This means that constant current charging is used for rapid charging when the battery voltage is low, and constant voltage charging is switched as the battery voltage increases to avoid overcharging. In this embodiment, when the charging protocol is the standard charging protocol of the device under test, the system extracts first data to be analyzed (battery voltage below a first voltage threshold) and second data (battery voltage greater than or equal to the first voltage threshold). The first data to be analyzed should theoretically conform to the constant current charging standard.

[0148] For example, the standard charging protocols include constant current charging and constant voltage charging standards. The constant current charging standard involves constant current charging when the battery voltage is below 4.36V, during which the charging current remains stable (e.g., the change in charging current is less than a threshold), and the battery percentage increases sequentially without jumps. The constant voltage charging standard switches to constant voltage charging when the battery voltage is greater than or equal to 4.36V, during which the charging current gradually decreases, and the battery percentage increases sequentially without jumps until the battery percentage reaches 100%. The constant voltage charging standard also includes a full-charge charging standard: during the 99%-100% battery percentage period, the charging time is less than 30 minutes, the charging current is less than 50mA at full charge, and the battery voltage is between 4.36V and 4.4V. Based on these charging standards, the battery voltage, charging current, and battery percentage in the first and second data sets to be analyzed can be compared with the corresponding values ​​in the charging standard to determine whether they meet the standard. Furthermore, the charging time can be determined based on the timestamps of the charging data to determine if it meets the standard. Data to be analyzed is considered non-compliant if it does not meet the voltage, current, or percentage of charge limits specified in the charging standards mentioned above. For example, if the charging current is 51mA when fully charged, exceeding the standard of "less than 50mA" for fully charged charging current, it does not meet the full-charge charging standard. Similarly, if, during the constant-current charging phase, two consecutive data points show a change in the percentage of charge from 11% to 13%, this jump in percentage is also non-compliant with the constant-current charging standard.

[0149] If the charging protocol is not the standard charging protocol of the device under test, then determine whether the charging protocol is a recognizable known protocol. If the charging protocol is a known protocol, then determine whether the battery voltage, charging current, and battery percentage during the charging process conform to the charging standards of the known protocol. If the charging protocol is an unrecognizable unknown protocol, then determine whether the battery voltage, charging current, and battery percentage during the charging process conform to general charging standards.

[0150] In some scenarios, users may not be using the standard charger when using the device under test. In this case, the charging protocol is not the standard charging protocol. If the charging protocol of the charger the user used is a recognizable and known protocol, the specifications that the battery voltage, charging current, and charge percentage should meet are determined based on the charging standard of that known protocol. For example, if the known protocol is QC, the corresponding charging standard includes a charging current of 2A, with the charge percentage increasing sequentially without jumps. For instance, if the charging data shows a charging current of 2.1A, since this charging current exceeds the 2A limit in the charging standard, it is determined that the charging standard is not met. If the charging protocol is an unrecognizable and unknown protocol, the judgment is based on a general charging standard, which is the minimum standard that the charging process must meet. For example, a general charging standard includes a charging current of 1A, with the charge percentage increasing sequentially without jumps. For instance, if the charging data shows a charging current of 1.2A, since this charging current exceeds the 1A limit in the charging standard, it is determined that the charging standard is not met.

[0151] In the above embodiments, by judging the charging protocol during the charging process, the corresponding charging standard is determined, and further analysis is conducted on whether the various charging data during the charging process meet the charging standard, thereby realizing the automated detection of the charging process under different charging protocols.

[0152] Regarding charging protocol compliance, after determining whether the battery voltage, charging current, and battery percentage during the charging process comply with the corresponding charging standards, a dimension score for charging protocol compliance can be determined based on the degree of non-compliance of the data in these parameters. For example, the degree of non-compliance, taking charging current as an example, is determined by the percentage by which the charging current exceeds or falls below the charging standard. For instance, if the charging protocol is an unrecognizable, unknown protocol, and the extracted charging current is 1.1A, exceeding the 1A limit in the charging standard by 10%, then its degree of non-compliance is 10%.

[0153] For example, data that does not conform to charging standards has a non-compliance level of 0 and a dimension score of 10; a non-compliance level greater than 0 and less than or equal to 10% has a dimension score of 9; a non-compliance level greater than 10% and less than or equal to 15% has a dimension score of 8, and so on. In this embodiment of the application, by quantitatively analyzing the data during the charging process, accurate and quantitative detection results of the charging protocol dimension are obtained, without relying on human experience judgment, thus improving efficiency and accuracy.

[0154] When the detection dimension is the temperature control mechanism, the data to be analyzed corresponding to the temperature control mechanism is extracted from the charging and discharging data. The data to be analyzed corresponding to the temperature control mechanism includes: the temperature during the charging process and the charging current.

[0155] From the data to be analyzed corresponding to the temperature control mechanism, extract the charging current of multiple preset first temperature ranges; determine whether the temperature of the charging process exceeds the maximum temperature threshold, and determine whether the charging current of each first temperature range meets the preset charging current standard corresponding to the first temperature range. If it does not meet the preset charging current standard, output improvement suggestions based on the preset charging current standard.

[0156] The temperature control mechanism's detection standards include the highest temperature threshold during charging, such as 45 degrees Celsius; and preset charging current standards corresponding to multiple first temperature ranges. For example, these first temperature ranges are: below 0 degrees Celsius, 0 to 15 degrees Celsius, 15 to 40 degrees Celsius, and above 40 degrees Celsius. Different first temperature ranges correspond to different charging current standards. For instance, charging is not allowed below 0 degrees Celsius and above 40 degrees Celsius, meaning the charging current is 0. Therefore, if the charging current is not 0 within these ranges, it does not meet the charging current standard. The charging current corresponding to 0 to 15 degrees Celsius is no higher than 0.2C, and the charging current corresponding to 15 to 40 degrees Celsius is the charging current corresponding to the charging protocol. Comparing the charging current corresponding to 15 to 40 degrees Celsius with the charging current limit in the charging protocol determines whether it meets the standard. By extracting the charging current for each first temperature range, it is determined whether it meets the corresponding charging current standard. If it does not meet the preset charging current standard, the improvement suggestion output could be to limit the charging current within the data range corresponding to the charging current standard. For example, if multiple charging current data points between 0°C and 15°C are extracted from the charging data, and one of these data points shows a charging current higher than 0.2C, then it is determined that the charging current does not meet the charging current standard. The improvement suggestion could be to limit the charging current between 0°C and 15°C to below 0.2C. By detecting this through a temperature control mechanism, it can be ensured that the battery charging process matches the temperature, thus improving the safety of the charging process.

[0157] After determining whether the charging current in each first temperature range meets the preset charging current standard corresponding to the first temperature range, a threshold score is determined based on whether the temperature during the charging process exceeds the maximum temperature threshold; the score for each first temperature range is determined based on the proportion of charging currents in each first temperature range that do not meet the preset charging current standard; and the dimension score of the temperature control mechanism is determined based on the scores of each first temperature range and the threshold score.

[0158] For example, if the temperature during the charging process exceeds the maximum temperature threshold, the threshold score is negative; if the temperature during the charging process does not exceed the maximum temperature threshold, the threshold score is either positive or negative. For instance, if the temperature during the charging process exceeds the maximum temperature threshold, the threshold score is -0.1; if the temperature during the charging process does not exceed the maximum temperature threshold, the threshold score is +0.1.

[0159] Based on the number of charging current data entries in each first temperature range and the number of data entries that do not meet the preset charging current standard, the proportion of charging current in each first temperature range that does not meet the preset charging current standard is determined. A score for each first temperature range is determined based on this proportion; the higher the proportion, the lower the score. The scores for each first temperature range are weighted and summed to obtain the temperature range score. The temperature range score is then added to a threshold score to obtain the dimension score of the temperature control mechanism.

[0160] For example, data on temperatures between 0 and 15 degrees Celsius, and between 15 and 40 degrees Celsius, were extracted from the charging data. These two temperature ranges were then compared to their corresponding charging current standards. For example, there are 500 data points for the 0-15 degree range; assuming only 1 data point does not meet the charging current standard, the non-compliance rate is 0.2%. Similarly, there are 2000 data points for the 15-40 degree range; assuming no data point does not meet the standard, the non-compliance rate is 0%. For example, a non-compliance rate of 0% in the first temperature range results in a score of 10; a non-compliance rate greater than 0% but less than 0.5% results in a score of 9; a non-compliance rate greater than 0.5% but less than 1% results in a score of 8, and so on. Therefore, the scores for the two temperature ranges are 9 and 10 respectively. Averaging these scores, the temperature range score is 9.5. Assuming the charging temperature does not exceed the maximum temperature threshold (threshold score is +0.1), the temperature control mechanism dimension score is 9.6. Optionally, the temperature score of the temperature control mechanism can be limited to between 0 and 10. For example, if the sum of the temperature range score and the threshold score exceeds 10, it is set to 10; if it is below 0, it is set to 0. In this embodiment, by quantitatively analyzing the data from different temperature ranges during the charging process, accurate and quantitative detection results of the temperature control mechanism dimension are obtained, which does not rely on human experience judgment and improves efficiency and accuracy.

[0161] When the detection dimension is battery health, the data to be analyzed corresponding to battery health is extracted from the charging and discharging data. The data to be analyzed corresponding to battery health includes: battery voltage and discharge current during the process of battery percentage decreasing by a preset ratio, and battery voltage and discharge current when the discharge current is greater than a preset value.

[0162] The actual discharge capacity is determined based on the battery voltage and discharge current during the preset percentage decrease of the battery percentage, as well as the duration of the preset percentage decrease. The first battery health is determined based on the actual discharge capacity and the theoretical capacity. The actual battery internal resistance is determined based on the battery voltage and discharge current when the discharge current is greater than a preset value. The second battery health is determined based on the actual battery internal resistance and the theoretical internal resistance. The overall battery health is determined based on the first and second battery health, and improvement suggestions are output when the battery health is lower than the preset battery health standard.

[0163] For example, the preset percentage is 20%. The preset percentage decrease in battery percentage could be, for instance, from 80% to 60%. The data to be analyzed includes the battery voltage and discharge current during this process. Alternatively, the preset percentage decrease could be, for instance, from 70% to 50%. The data to be analyzed also includes the battery voltage and discharge current during this process. The duration of the preset percentage decrease can also be determined based on the timestamps of the discharge data.

[0164] The average power consumption during the 20% battery percentage drop can be calculated based on the battery voltage and discharge current. Multiplying the average power consumption by the duration of the 20% battery percentage drop gives the actual discharge capacity. Dividing the actual discharge capacity by the theoretical capacity corresponding to the 20% battery percentage drop gives the first battery health status.

[0165] For example, the battery voltage and discharge current when the discharge current is greater than the preset value are the battery voltage and discharge current when the discharge current is greater than 1C. Divide the decrease in battery voltage during the continuous discharge current greater than 1C by the discharge current to obtain the actual battery internal resistance. Divide the theoretical battery internal resistance by the actual theoretical internal resistance to obtain the second battery health status.

[0166] Optionally, weights can be assigned to the first and second battery health scores respectively. A weighted sum is then calculated based on these weights to obtain the final battery health score. For example, if the weights for both the first and second battery health scores are 0.5, the average of the first and second battery health scores is used to obtain the final battery health score. For instance, the first battery health score is 96%, the second battery health score is 86%, and the total battery health score is 91%. When the battery health score is lower than a preset standard, the output improvement suggestion could be, for example, a suggestion to replace the battery. For instance, if the preset standard is 80%, and the battery health score is 91%, the battery health test result is considered passed. If the battery health score is 75%, the battery health test fails, and the improvement suggestion is to replace the battery. A dimension score for the battery health score is determined based on the battery health score, and this dimension score is positively correlated with the battery health score. For example, a battery health score of 96%-100% corresponds to a score of 10 in the battery health dimension; a battery health score of 91%-95% corresponds to a score of 9 in the battery health dimension; a battery health score of 86%-90% corresponds to a score of 8 in the battery health dimension, and so on. In this embodiment, battery health is calculated using two dimensions, resulting in a more accurate battery health detection result.

[0167] When the detection dimension is the capacity-voltage curve, the data to be analyzed corresponding to the capacity-voltage curve is extracted from the charge and discharge data. The data to be analyzed corresponding to the capacity-voltage curve includes: battery voltage, charge percentage and temperature during the discharge process.

[0168] Extract battery voltage and capacity percentage from the data to be analyzed in multiple preset second temperature ranges; determine whether the battery voltage and capacity percentage of each second temperature range conform to the corresponding capacity voltage standard curve of the second temperature range; and output improvement suggestions based on the preset capacity voltage curve if they do not conform to the capacity voltage standard curve.

[0169] The capacity-voltage curve characteristics of a battery are different at different temperatures. In other words, the percentage of charge corresponding to the battery voltage may be different at different temperatures. Different second temperature ranges correspond to a capacity-voltage standard curve, which includes multiple battery voltages and the percentage of charge corresponding to each battery voltage.

[0170] For the detection temperature along the capacity-voltage curve, the discharge data is first divided into different second temperature ranges based on the corresponding temperature. For example, multiple second temperature ranges might be below 10 degrees Celsius, 10 to 45 degrees Celsius, and above 45 degrees Celsius. Each second temperature range corresponds to a capacity-voltage standard curve, representing the standard relationship between battery voltage and charge percentage. After extracting the battery voltage and charge percentage for each second temperature range, they are compared with the capacity-voltage standard curve for that range to determine if the charge percentage meets the standard. Optionally, if the charge percentage does not conform to the capacity-voltage standard curve, an improvement suggestion could be to correct the charge percentage to the data corresponding to the capacity-voltage standard curve.

[0171] For example, if only data for temperatures between 10 and 45 degrees Celsius are extracted from the discharge data, then these data are compared with the capacity-voltage standard curve corresponding to temperatures between 10 and 45 degrees Celsius. Alternatively, if only data for temperatures between 10 and 45 degrees Celsius and data for temperatures above 45 degrees Celsius are extracted from the discharge data, then the data for temperatures between 10 and 45 degrees Celsius are compared with the capacity-voltage standard curve corresponding to temperatures between 10 and 45 degrees Celsius, and the data for temperatures above 45 degrees Celsius are compared with the capacity-voltage standard curve corresponding to temperatures above 45 degrees Celsius.

[0172] For example, when the temperature is above 45 degrees Celsius, the battery voltage standard curve shows a charge percentage of 85% for a battery voltage of 4.2V. However, the actual charge percentage for a battery voltage of 4.2V extracted from the discharge data is 78%. Therefore, the charge percentage is judged to be too low and needs to be modified. The output improvement suggestion is to correct the charge percentage to between 80% and 85%.

[0173] The score for each second temperature range is determined based on the proportion of battery voltage and charge percentage that do not conform to the capacity-voltage standard curve corresponding to that second temperature range; the dimensional score of the capacity-voltage curve is determined based on the score of each second temperature range.

[0174] Based on the number of battery voltage and charge percentage data points for each second temperature range, and the number of data points that do not conform to the capacity-voltage standard curve, the proportion of battery voltage and charge percentage that do not conform to the capacity-voltage standard curve for each second temperature range is determined. The score for each second temperature range is determined based on this proportion; the higher the proportion, the lower the score. For example, if only data between 10°C and 45°C is extracted from the discharge data (meaning the second temperature range includes this range), and there are 2000 data points for battery voltage and charge percentage in this second temperature range, assuming 2 data points do not conform to the capacity-voltage standard curve, the proportion of non-conformity is 0.1%; assuming 0 data points do not conform to the capacity-voltage standard curve, the proportion of non-conformity is 0%. For example, a non-conformity proportion of 0% for the second temperature range results in a score of 10; a non-conformity proportion greater than 0% and less than 0.5% results in a score of 9; a non-conformity proportion greater than 0.5% and less than 1% results in a score of 8, and so on.

[0175] The score for each second temperature range can be determined using the method described above. Then, the scores for each second temperature range are weighted and summed to obtain the dimensional score of the capacity-voltage curve. For example, each second temperature range has the same weight; that is, the scores for each second temperature range are averaged to obtain the dimensional score of the capacity-voltage curve. In this embodiment, by quantitatively analyzing data from different temperature ranges during the discharge process, accurate and quantifiable detection results of the capacity-voltage curve's dimensionality are obtained, without relying on manual experience judgment, thus improving efficiency and accuracy.

[0176] Based on the above example, assuming the weights of battery health, capacity-voltage curve, charging protocol compliance, and temperature control mechanism are 0.3, 0.25, 0.25, and 0.2 respectively, and the dimension scores of battery health, capacity-voltage curve, charging protocol compliance, and temperature control mechanism are 10, 9, 9, and 9.6 respectively, then the final comprehensive health score is 9.42.

[0177] The method in this application embodiment realizes multi-dimensional automated analysis of charging and discharging process data, improving efficiency and accuracy, quantifying battery health data, and achieving comprehensive testing of the device's charging and discharging system. This prevents safety hazards caused by missed tests. Through analysis of various dimensions, professional improvement suggestions are output to ensure the rationality of the charging and discharging design logic, thereby ensuring battery efficiency, extending battery life, improving charging efficiency, and ensuring safety during the charging and usage processes.

[0178] Figure 2 This is a schematic diagram of the charge / discharge detection device provided in this application, as shown below. Figure 2 As shown, the charge / discharge detection device 200 includes:

[0179] The acquisition module 201 is used to acquire the charging and discharging data of the device under test. The charging and discharging data includes battery voltage, charging current, charging protocol, discharging current, temperature and battery percentage.

[0180] The detection module 202 is used to extract the data to be analyzed corresponding to each detection dimension from the charging and discharging data based on multiple preset detection dimensions, and to determine the detection result of each detection dimension based on the data to be analyzed corresponding to each detection dimension and the preset detection standards of each detection dimension. The multiple detection dimensions include at least: battery health, capacity-voltage curve, charging protocol compliance and temperature control mechanism.

[0181] The report output module 203 is used to generate a comprehensive charge and discharge health status report or diagnostic report for the device under test based on the test results from multiple detection dimensions.

[0182] In some implementations, the report output module 203 is used for:

[0183] Based on the device type and usage scenario of the device to be tested, dynamic weights are assigned to the test results of multiple testing dimensions respectively;

[0184] Based on dynamic weights, the dimensional scores in the detection results of each detection dimension are weighted and fused to obtain the comprehensive health score of the device under test.

[0185] Based on the comprehensive health score and the test results of each detection dimension, a comprehensive charge and discharge health status report or diagnostic report is generated.

[0186] In some implementations, the acquisition module 201 is used for:

[0187] By calling the standardized data interface of the battery management system built into the device under test, charging and discharging data can be read in real time; or,

[0188] Charge and discharge data are collected by coupling the external charge and discharge tester into the charge and discharge circuit of the device under test.

[0189] In some implementations, the detection module 202 is used for:

[0190] When the detection dimension is charging protocol compliance, the data to be analyzed corresponding to the charging protocol compliance is extracted from the charging and discharging data. The data to be analyzed corresponding to the charging protocol compliance includes: battery voltage, charging current, charging protocol and battery percentage during the charging process.

[0191] The corresponding charging standard is determined based on the charging protocol, and it is judged whether the battery voltage, charging current and charge percentage during the charging process meet the charging standard. If they do not meet the charging standard, improvement suggestions are output based on the charging standard.

[0192] In some implementations, the detection module 202 is used for:

[0193] Determine whether the charging protocol is the standard charging protocol of the device under test;

[0194] If the charging protocol is the standard charging protocol of the device to be tested, then extract the first data to be analyzed from the data to be analyzed corresponding to the charging protocol compliance, which shows that the battery voltage is lower than the first voltage threshold, and the second data to be analyzed shows that the battery voltage is greater than or equal to the first voltage threshold.

[0195] Determine whether the charging current and capacity percentage in the first set of data to be analyzed conform to the constant current charging standard of the standard charging protocol;

[0196] Determine whether the battery voltage, charging current, and charge percentage in the second set of data to be analyzed meet the constant voltage charging standard of the standard charging protocol, and whether the charge percentage data from 99% to 100% in the second set of data to be analyzed meet the full charge charging standard.

[0197] In some implementations, the detection module 202 is used for:

[0198] If the charging protocol is not the standard charging protocol of the device under test, then determine whether the charging protocol is a recognizable known protocol.

[0199] If the charging protocol is a known protocol, then determine whether the battery voltage, charging current, and charge percentage during the charging process conform to the charging standards of the known protocol.

[0200] In some implementations, the detection module 202 is used for:

[0201] If the charging protocol is an unrecognizable unknown protocol, then determine whether the battery voltage, charging current, and charge percentage during the charging process conform to the general charging standard.

[0202] In some implementations, the detection module 202 is used for:

[0203] The charging protocol compliance dimension score is determined based on the degree of non-compliance of data such as battery voltage, charging current, and charge percentage during the charging process with charging standards.

[0204] In some implementations, the detection module 202 is used for:

[0205] When the detection dimension is the temperature control mechanism, the data to be analyzed corresponding to the temperature control mechanism is extracted from the charging and discharging data. The data to be analyzed corresponding to the temperature control mechanism includes: the temperature during the charging process and the charging current.

[0206] Extract the charging current of multiple preset first temperature ranges from the data to be analyzed corresponding to the temperature control mechanism;

[0207] It determines whether the temperature during the charging process exceeds the maximum temperature threshold, and whether the charging current in each first temperature range meets the preset charging current standard corresponding to the first temperature range. If it does not meet the preset charging current standard, it outputs improvement suggestions based on the preset charging current standard.

[0208] In some implementations, the detection module 202 is used for:

[0209] The threshold score is determined based on whether the temperature during the charging process exceeds the maximum temperature threshold.

[0210] The score for each first temperature range is determined based on the proportion of charging currents that do not meet the preset charging current standard.

[0211] The dimensional score of the temperature control mechanism is determined based on the scores of each first temperature range and the threshold score.

[0212] In some implementations, the detection module 202 is used for:

[0213] When the detection dimension is battery health, the data to be analyzed corresponding to battery health is extracted from the charging and discharging data. The data to be analyzed corresponding to battery health includes: battery voltage and discharge current during the process of battery percentage decreasing by a preset ratio, and battery voltage and discharge current when the discharge current is greater than a preset value.

[0214] The actual discharge capacity is determined based on the battery voltage and discharge current during the process of the battery percentage decreasing by a preset percentage, as well as the duration of the battery percentage decreasing by the preset percentage. The first battery health is determined based on the actual discharge capacity and the theoretical capacity.

[0215] The actual battery internal resistance is determined based on the battery voltage and discharge current when the discharge current is greater than the preset value. The health of the second battery is determined based on the actual battery internal resistance and the theoretical internal resistance.

[0216] The battery health is determined based on the first battery health and the second battery health, and improvement suggestions are output when the battery health is lower than the preset battery health standard.

[0217] In some implementations, the detection module 202 is used for:

[0218] Battery health is determined by dimensional scores, and these dimensional scores are positively correlated with overall battery health.

[0219] In some implementations, the detection module 202 is used for:

[0220] When the detection dimension is the capacity-voltage curve, the data to be analyzed corresponding to the capacity-voltage curve is extracted from the charge and discharge data. The data to be analyzed corresponding to the capacity-voltage curve includes: battery voltage, charge percentage and temperature during the discharge process.

[0221] Extract the battery voltage and charge percentage for multiple preset second temperature ranges from the data to be analyzed in the capacity-voltage curve.

[0222] Determine whether the battery voltage and charge percentage in each second temperature range conform to the capacity-voltage standard curve corresponding to the second temperature range, and if they do not conform to the capacity-voltage standard curve, output improvement suggestions based on the preset capacity-voltage curve.

[0223] In some implementations, the detection module 202 is used for:

[0224] The score for each second temperature range is determined based on the proportion of battery voltage and charge percentage that do not conform to the capacity-voltage standard curve corresponding to the second temperature range.

[0225] The dimension score of the capacity-voltage curve is determined based on the score of each second temperature range.

[0226] The charge / discharge detection device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0227] This application provides a charge / discharge detection device, including:

[0228] The hardware interface module is used to connect to the battery management system data interface of the device under test or to couple to the charging and discharging circuit of the device under test in order to obtain the charging and discharging data of the device under test.

[0229] The co-analysis processor is connected to the hardware interface module and stores executable instructions internally. When the executable instructions are executed, the method described in the foregoing embodiments is executed.

[0230] The report output module, connected to the collaborative analysis processor, is used to output a comprehensive charge / discharge health status report or diagnostic report.

[0231] The charge / discharge detection device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0232] This application provides a charge / discharge detection device, including:

[0233] case;

[0234] As in the aforementioned embodiment, the charge / discharge detection device is integrated within the housing;

[0235] The human-machine interface is set on the housing and connected to the report output module of the charge and discharge detection device to display a comprehensive charge and discharge health status report or diagnostic report;

[0236] The power module is used to supply power to the charge and discharge testing equipment.

[0237] The charge / discharge detection device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0238] Figure 3 A schematic diagram of the structure of the electronic device provided in this application. Figure 3 As shown, the electronic device 300 provided in this embodiment includes at least one processor 301 and a memory 302. Optionally, the electronic device 300 further includes a communication component 303. The processor 301, memory 302, and communication component 303 are connected via a bus 304. This electronic device can be the device under test as described in the foregoing embodiment or a charge / discharge detection device other than the device under test.

[0239] In a specific implementation, at least one processor 301 executes computer execution instructions stored in memory 302, causing at least one processor 301 to perform the above-described method.

[0240] The specific implementation process of processor 301 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0241] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0242] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0243] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0244] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0245] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0246] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0247] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an application-specific integrated circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0248] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0249] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0250] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0251] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0252] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0253] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A charge / discharge detection method, characterized in that, include: Acquire the charging and discharging data of the device under test, including battery voltage, charging current, charging protocol, discharging current, temperature, and battery percentage; Based on multiple preset detection dimensions, the data to be analyzed corresponding to each detection dimension is extracted from the charging and discharging data. Based on the data to be analyzed corresponding to each detection dimension and the preset detection standards for each detection dimension, the detection result of each detection dimension is determined. The multiple detection dimensions include at least: battery health, capacity-voltage curve, charging protocol compliance, and temperature control mechanism. Based on the detection results from the multiple detection dimensions, a comprehensive charge and discharge health status report or diagnostic report for the device under test is generated.

2. The method according to claim 1, characterized in that, Based on the detection results from the multiple detection dimensions, a comprehensive charge / discharge health status report or diagnostic report is generated for the device under test, including: Based on the device type and usage scenario of the device to be tested, dynamic weights are assigned to the detection results of the multiple detection dimensions respectively; Based on the dynamic weights, the dimensional scores in the detection results of each detection dimension are weighted and fused to obtain the comprehensive health score of the device under test. Based on the comprehensive health score and the detection results of each detection dimension, the comprehensive charge and discharge health status report or the diagnostic report is generated.

3. The method according to claim 1 or 2, characterized in that, The acquisition of charge and discharge data of the device under test includes: The charging and discharging data can be read in real time by calling the standardized data interface of the battery management system built into the device under test; or, The charging and discharging data are collected by coupling the external charging and discharging detector into the charging and discharging circuit of the device under test.

4. The method according to claim 1, characterized in that, The process involves extracting data to be analyzed corresponding to each detection dimension from the charge / discharge data based on multiple preset detection dimensions, and determining the detection result for each detection dimension based on the data to be analyzed corresponding to each detection dimension and the preset detection standards for each detection dimension, including: When the detection dimension is charging protocol compliance, the data to be analyzed corresponding to the charging protocol compliance is extracted from the charging and discharging data. The data to be analyzed corresponding to the charging protocol compliance includes: battery voltage, charging current, charging protocol and power percentage during the charging process. The corresponding charging standard is determined according to the charging protocol, and it is determined whether the battery voltage, charging current and charge percentage during the charging process meet the charging standard. If they do not meet the charging standard, improvement suggestions are output based on the charging standard.

5. The method according to claim 4, characterized in that, The step of determining the corresponding charging standard according to the charging protocol and judging whether the battery voltage, charging current, and charge percentage during the charging process conform to the charging standard includes: Determine whether the charging protocol is the standard charging protocol of the device under test; If the charging protocol is the standard charging protocol of the device to be tested, then extract the first data to be analyzed from the data to be analyzed corresponding to the charging protocol compliance, which shows that the battery voltage is lower than the first voltage threshold, and the second data to be analyzed shows that the battery voltage is greater than or equal to the first voltage threshold. Determine whether the charging current and power percentage in the first data to be analyzed conform to the constant current charging standard of the standard charging protocol; Determine whether the battery voltage, charging current, and charge percentage in the second data to be analyzed meet the constant voltage charging standard of the standard charging protocol, and whether the charge percentage data from 99% to 100% in the second data to be analyzed meet the full charge charging standard.

6. The method according to claim 5, characterized in that, Also includes: If the charging protocol is not the standard charging protocol of the device under test, then determine whether the charging protocol is a recognizable known protocol; If the charging protocol is a known protocol, then determine whether the battery voltage, charging current and charge percentage during the charging process conform to the charging standard of the known protocol; If the charging protocol is an unrecognizable unknown protocol, then determine whether the battery voltage, charging current and charge percentage during the charging process conform to the general charging standard.

7. The method according to any one of claims 4-6, characterized in that, Also includes: The charging protocol compliance dimension score is determined based on the degree of non-compliance of data such as battery voltage, charging current, and charge percentage during the charging process with charging standards.

8. The method according to claim 1 or 2, characterized in that, The process involves extracting data to be analyzed corresponding to each detection dimension from the charge / discharge data based on multiple preset detection dimensions, and determining the detection result for each detection dimension based on the data to be analyzed corresponding to each detection dimension and the preset detection standards for each detection dimension, including: When the detection dimension is the temperature control mechanism, the data to be analyzed corresponding to the temperature control mechanism is extracted from the charging and discharging data. The data to be analyzed corresponding to the temperature control mechanism includes: the temperature during the charging process and the charging current. From the data to be analyzed corresponding to the temperature control mechanism, extract the charging current of multiple preset first temperature ranges; It determines whether the temperature during the charging process exceeds the maximum temperature threshold, and whether the charging current in each first temperature range meets the preset charging current standard corresponding to the first temperature range. If it does not meet the preset charging current standard, it outputs improvement suggestions based on the preset charging current standard.

9. The method according to claim 8, characterized in that, Also includes: The threshold score is determined based on whether the temperature during the charging process exceeds the maximum temperature threshold. The score for each first temperature range is determined based on the proportion of charging currents that do not meet the preset charging current standard in each first temperature range. The dimensional score of the temperature control mechanism is determined based on the scores of each first temperature range and the threshold score.

10. The method according to claim 1 or 2, characterized in that, The process involves extracting data to be analyzed corresponding to each detection dimension from the charge / discharge data based on multiple preset detection dimensions, and determining the detection result for each detection dimension based on the data to be analyzed corresponding to each detection dimension and the preset detection standards for each detection dimension, including: When the detection dimension is battery health, the data to be analyzed corresponding to battery health is extracted from the charging and discharging data. The data to be analyzed corresponding to battery health includes: battery voltage and discharge current during the process of battery percentage decreasing by a preset ratio, and battery voltage and discharge current when the discharge current is greater than a preset value. The actual discharge capacity is determined based on the battery voltage and discharge current during the process of the battery percentage decreasing by a preset percentage, as well as the duration of the battery percentage decreasing by the preset percentage. The first battery health is determined based on the actual discharge capacity and the theoretical capacity. The actual battery internal resistance is determined based on the battery voltage and discharge current when the discharge current is greater than the preset value, and the health of the second battery is determined based on the actual battery internal resistance and the theoretical internal resistance. The battery health is determined based on the first battery health and the second battery health, and improvement suggestions are output when the battery health is lower than a preset battery health standard.

11. The method according to claim 10, characterized in that, Also includes: The dimension score of the battery health is determined based on the battery health, and the dimension score of the battery health is positively correlated with the battery health.

12. The method according to claim 1 or 2, characterized in that, The process involves extracting data to be analyzed corresponding to each detection dimension from the charge / discharge data based on multiple preset detection dimensions, and determining the detection result for each detection dimension based on the data to be analyzed corresponding to each detection dimension and the preset detection standards for each detection dimension, including: When the detection dimension is the capacity-voltage curve, the data to be analyzed corresponding to the capacity-voltage curve is extracted from the charge-discharge data. The data to be analyzed corresponding to the capacity-voltage curve includes: battery voltage, charge percentage and temperature during the discharge process. Extract the battery voltage and charge percentage for multiple preset second temperature ranges from the data to be analyzed in the capacity-voltage curve; Determine whether the battery voltage and charge percentage in each of the second temperature ranges conform to the capacity-voltage standard curve corresponding to the second temperature range, and if they do not conform to the capacity-voltage standard curve, output improvement suggestions based on the capacity-voltage standard curve.

13. The method according to claim 12, characterized in that, Also includes: The score for each second temperature range is determined based on the proportion of battery voltage and charge percentage that do not conform to the capacity-voltage standard curve corresponding to the second temperature range. The dimension score of the capacity-voltage curve is determined based on the score of each second temperature range.

14. A charge / discharge detection device, characterized in that, include: The acquisition module is used to acquire the charging and discharging data of the device under test, including battery voltage, charging current, charging protocol, discharging current, temperature and battery percentage. The detection module is used to extract the data to be analyzed corresponding to each detection dimension from the charging and discharging data based on multiple preset detection dimensions, and to determine the detection result of each detection dimension based on the data to be analyzed corresponding to each detection dimension. The multiple detection dimensions include at least: battery health, capacity-voltage curve, charging protocol compliance and temperature control mechanism. The report output module is used to generate a comprehensive charge and discharge health status report or diagnostic report for the device under test based on the detection results of the multiple detection dimensions.

15. A charge / discharge detection device, characterized in that, include: A hardware interface module is used to connect to the battery management system data interface of the device under test or to be coupled to the charging and discharging circuit of the device under test in order to obtain the charging and discharging data of the device under test. A collaborative analysis processor, connected to the hardware interface module, internally stores executable instructions, which, when executed, perform the method as described in any one of claims 1-13; The report output module, connected to the collaborative analysis processor, is used to output the comprehensive charge and discharge health status report or diagnostic report.

16. A charge / discharge detection device, characterized in that, include: case; The charge / discharge detection device as described in claim 14 or 15, wherein the charge / discharge detection device is integrated within the housing; A human-computer interaction interface is set on the housing and connected to the report output module of the charge and discharge detection device, used to display the comprehensive charge and discharge health status report or diagnostic report; A power module is used to supply power to the charge and discharge detection equipment.

17. An electronic device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-13.

18. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-13.

19. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-13.

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