Method for realizing power battery fault early warning and monitoring by using charging equipment

Abstract

The invention relates to the technical field of battery state monitoring, and provides a method for realizing power battery fault early warning and monitoring by using charging equipment. In the charging process of the power battery, the charging data of the power battery and the charging data of each single battery module are obtained; calculating the capacity, the internal resistance and other characteristic quantities of the whole group of batteries and the single battery modules, and utilizing the relation that the sum of the capacity, the internal resistance and the charging voltage (or the respective variation) of each single battery module is equal to the state characteristic quantities of the capacity, the internal resistance and the charging voltage (or the respective variation) of the whole group of batteries; calculating and analyzing each state characteristic quantity of the whole group of batteries and the single battery modules, and when the change of the state characteristic quantity of the capacity, internal resistance, voltage, temperature and the like of a certain single battery module obviously deviates from the change of most of other single battery modules, judging that the probability of the spontaneous combustion fault of the single battery module is greater than that of other single battery modules; therefore, charging monitoring of fault early warning of the power battery is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of battery state monitoring, in particular to a method for realizing power battery fault early warning monitoring by using a charging device. BACKGROUND

[0002] The state monitoring of power batteries of electric vehicles is a worldwide technical problem, and the battery state monitoring technology can be divided into two categories, including the fault early warning monitoring of battery state changes or fire and explosion, and the battery state monitoring of capacity attenuation and performance state of power batteries.

[0003] The main monitoring state characteristic quantities of the power batteries of electric vehicles in the world today include physical quantities such as power battery capacity, battery internal resistance, charging and discharging current and voltage, and battery temperature. So far, the state monitoring technology of power batteries of electric vehicles has not made an effective breakthrough, and there is currently no particularly effective monitoring technology available. The state monitoring technology of power batteries is mainly difficult in the complex relationship of the nonlinear and time-varying coupling between various state characteristic quantities: under different battery temperatures, the charging and discharging capacity, internal resistance and other states of the power battery are different; different charging currents or voltages, different charging processes, also lead to different power charging and discharging capacities, internal resistances and other battery states, and different initial states of battery voltage and remaining use capacity, the power battery state in the charging process is also different, which all affect the accuracy and feasibility of the state monitoring of power batteries.

[0004] At present, the mainstream power battery state monitoring technology on the market is to use special test instruments, test the state characteristic quantities of the power battery by charging and discharging test, compare the test results with the previous test results or the initial state, analyze the change of the state characteristic quantities of the power battery, and determine whether the state of the power battery is within the normal range. The above technical method requires a large amount of manpower and material resources, otherwise it cannot be widely applied. In view of this, overcoming the defects of the existing technology is a problem to be solved in this technical field. SUMMARY

[0005] The technical problem to be solved by the present application is that the mainstream power battery state monitoring technology on the market uses special test instruments, tests the state characteristic quantities of the power battery by charging and discharging test, compares the test results with the previous test results or the initial state, analyzes the change of the state characteristic quantities of the power battery, and determines whether the state of the power battery is within the normal range, but a large amount of manpower and material resources are required, otherwise it cannot be widely applied. Different battery temperatures result in different appearances of power battery states.

[0006] The present application adopts the following technical scheme:

[0007] In a first aspect, a method for implementing power battery fault early warning monitoring by using a charging device comprises:

[0008] In the process of charging the power battery, charging data of the entire battery and each single battery module of the power battery are acquired, and the values of the capacity, internal resistance, and charging voltage state characteristic quantity of the entire battery and each single battery module are calculated;

[0009] Based on the summation of the capacity, internal resistance, and charging voltage of each single battery module, the relationship that the summation of the capacity, internal resistance, and charging voltage of each single battery module is equal to the capacity, internal resistance, and charging voltage of the entire battery is established, the change deviation state of the state characteristic quantity of each single battery module is calculated and analyzed, and the probability of natural failure is evaluated;

[0010] The threshold value of the change deviation of the state characteristic quantity of each single battery module is set, when the change deviation is greater than or equal to the threshold value, the fault early warning is started, and the power battery fault early warning monitoring is implemented.

[0011] Preferably, the method specifically comprises:

[0012] In the process of charging the power battery, the internal resistance of each single battery module in the power battery is acquired;

[0013] Based on the connection mode of each single battery module in the corresponding grouping battery, the internal resistance of the corresponding grouping battery is calculated;

[0014] According to the first change relationship between the internal resistance of the corresponding single battery module and the internal resistance of the grouping battery in which the single battery module is located, and the change amount between the first change relationship and the second change relationship selected from historical data as a reference, if the change amount exceeds a first preset threshold value, it is determined that the internal resistance of the corresponding single battery module shows an abnormal risk.

[0015] Preferably, the method specifically comprises:

[0016] In the process of charging the power battery, the charging voltage of each single battery module in the power battery is also acquired;

[0017] Based on the connection mode of each single battery module in the corresponding grouping battery, the charging voltage of the corresponding grouping battery is calculated;

[0018] According to the third change relationship between the charging voltage of the corresponding single battery module and the charging voltage of the grouping battery in which the single battery module is located, and the change amount between the third change relationship and the fourth change relationship selected from historical data as a reference, if the change amount exceeds a second preset threshold value, it is determined that the charging voltage of the corresponding single battery module shows an abnormal risk;

[0019] The historical data is the charging data recorded by the charging pile under the condition of providing the same charging voltage and recorded in the corresponding server.

[0020] Preferably, specifically comprising:

[0021] In the process of charging the power battery, the capacity of each single battery module in the power battery is also obtained, and the method further comprises:

[0022] Based on the connection mode of each single battery module in the respective group battery, the capacity of the corresponding group battery is calculated;

[0023] According to the fifth change relationship between the capacity of the corresponding single battery module and the capacity of the group battery in which it is located, and the change amount between the fifth change relationship and the sixth change relationship selected from the historical data as a reference, if it exceeds the third preset threshold, it is determined that the corresponding single battery module has an abnormal risk in capacity performance.

[0024] Preferably, when the relationship between each single battery module in the group is a series relationship, the change amount between the first change relationship between the internal resistance of the corresponding single battery module and the internal resistance of the group battery in which it is located, and the second change relationship selected from the historical data as a reference, is specifically:

[0025] The sum of the internal resistances of each single battery module included in a group battery is theoretically equal to the internal resistance of the group battery; when all single battery modules are in a normal state, the proportion coefficient of the internal resistance of each single battery module relative to the internal resistance of the group battery, that is, the first change relationship; and the proportion coefficient of the internal resistance of each single battery module relative to the internal resistance of the group battery selected from the historical data as a reference, that is, the second change relationship.

[0026] Preferably, when the relationship between each single battery module in the group is a series relationship, the third change relationship between the charging voltage of the corresponding single battery module and the charging voltage of the group battery in which it is located, and the fourth change relationship selected from the historical data as a reference, is specifically:

[0027] The sum of the charging voltages of each single battery module included in a group battery is theoretically equal to the charging voltage of the group battery; when all single battery modules are in a normal state, the proportion coefficient of the charging voltage of each single battery module relative to the charging voltage of the group battery, that is, the third change relationship; and the proportion coefficient of the charging voltage of each single battery module relative to the charging voltage of the group battery selected from the historical data as a reference, that is, the fourth change relationship.

[0028] Preferably, the internal resistance of each single battery module in the power battery is obtained in the process of charging the power battery, specifically comprising:

[0029] record one or more of the charging completion amount, the charging temperature, and the charging current of each monomer battery module at the corresponding collection point while acquiring the internal resistance of each monomer battery module in the power battery;

[0030] The internal resistance of the monomer battery module recorded by the corresponding historical data at the collection point matching one or more of the charging completion amount, the charging temperature, and the charging current also satisfies the internal resistance of the monomer battery module and the internal resistance data of the grouped battery in the group where the monomer battery module is located.

[0031] Preferably, the corresponding historical data is collected by charging piles distributed at different locations and uploaded to a server for storage. After the server acquires the historical charging data of the same power battery, the method further comprises:

[0032] The server analyzes the historical charging data corresponding to the same power battery. For the charging data at the first dimension index value in the dimension index composed of the charging completion amount, the charging temperature, and / or the charging current, if the charging data interval exceeds one or more analysis periods, the charging data at the first dimension index value corresponding to the charging completion amount, the charging temperature, and / or the charging current is discarded or transferred to a low-cost storage for backup.

[0033] If the charging data recorded by the historical once includes not only the first dimension index value but also other dimension index values, the precondition for performing the discarding or transferring of the charging data at the first dimension index value corresponding to the charging completion amount, the charging temperature, and / or the charging current to the low-cost storage for backup is that the server retains charging data at other dimension index values and meets the charging data interval composite analysis period requirement.

[0034] Preferably, the server organizes the historical charging data according to the priority from high to low among the charging completion amount, the charging temperature, and the charging current for the stored data. Specifically:

[0035] The historical charging data is arranged according to the charging completion amount value. Within the interval length of the allowed analysis period, if there are historical charging data exceeding the required number of analyses corresponding to the same charging completion amount, the charging temperature is further used to select the charging data, so that the charging data whose charging temperature differs from the reference charging temperature in the time period by more than a first preset value is temporarily excluded from the calculation of the change amount or transferred to a low-cost storage for backup. If the number of historical charging data corresponding to the same charging completion amount does not exceed the required number of analyses, no temporary exclusion or transfer operation is performed.

[0036] If the number of remaining historical charging data still exceeds the required analysis after the above charging temperature screening, the remaining charging data is further screened according to the charging current, so that the charging data in which the charging current differs from the reference charging current in the time period by more than a second preset value is temporarily excluded from the calculation of the change amount or is transferred to a low storage cost memory for backup.

[0037] Preferably, when it is confirmed that the internal resistance of the corresponding single battery module exhibits an abnormal risk, the charging data under the power battery to which the single battery module belongs is restored from the low storage cost memory, so that secondary diagnostic data is obtained by analysis; and the primary diagnostic data obtained by analyzing the charging data of the corresponding power battery stored in the server is integrated, so that comparison analysis is performed with the historical charging data of other power batteries in the server that exhibit abnormal risks, an influence factor for accelerating the abnormal risks of the power batteries is obtained, and a customized habit improvement report for healthily using the power batteries is pushed to the user.

[0038] In a second aspect, the present application further provides a device for monitoring the state of a power battery by using a charging device, which is used to implement the method for monitoring the failure warning of a power battery by using a charging device according to the first aspect, and the device comprises:

[0039] at least one processor; and a memory connected with the at least one processor in communication; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the processor to implement the method for monitoring the failure warning of a power battery by using a charging device according to the first aspect.

[0040] In a third aspect, the present application further provides a non-volatile computer storage medium, which stores computer executable instructions, and the computer executable instructions are executed by one or more processors to complete the method for monitoring the failure warning of a power battery by using a charging device according to the first aspect.

[0041] By comparing and analyzing the change relationship between the capacity, internal resistance and voltage of the single battery module and the capacity, internal resistance and voltage of the group battery in the group to which the single battery module belongs, and the same historical data of the electric vehicle, the state and state variation of each single battery module are identified, and the single battery module with abnormal state change can be detected. By the method of the embodiment of the present application, the influence factors such as the precision of the monitoring tool, the same electrical quantity environment and process, the same atmospheric environment, the same initial state, etc. can be greatly compressed and weakened, so that the problem that the detection result precision is difficult to control in the existing method, and even the detection result cannot be used, can be solved. BRIEF DESCRIPTION OF DRAWINGS

[0042] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments of the present invention will be briefly described below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0043] Figure 1 This is a schematic flowchart of a method for monitoring and early warning of power battery faults using charging equipment, provided by an embodiment of the present invention.

[0044] Figure 2 This is a schematic flowchart of a method for monitoring and early warning of power battery faults using charging equipment, provided by an embodiment of the present invention.

[0045] Figure 3 This is a schematic flowchart of a method for monitoring and early warning of power battery faults using charging equipment, provided by an embodiment of the present invention.

[0046] Figure 4 This is a schematic diagram of a process for synchronously monitoring the capacity status of a single battery module according to an embodiment of the present invention;

[0047] Figure 5 This is a schematic flowchart of a method for monitoring and early warning of power battery faults using charging equipment, provided by an embodiment of the present invention.

[0048] Figure 6 This is a schematic flowchart of a method for monitoring and early warning of power battery faults using charging equipment, provided by an embodiment of the present invention.

[0049] Figure 7 This is a schematic flowchart of a method for monitoring and early warning of power battery faults using charging equipment, provided by an embodiment of the present invention.

[0050] Figure 8 This is a schematic diagram of a device for monitoring the status of a power battery using a charging device, provided in an embodiment of the present invention.

Detailed Implementation Methods

[0051] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0052] In the description of this invention, the terms "inner", "outer", "longitudinal", "lateral", "upper", "lower", "top", "bottom", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and do not require that this invention must be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting this invention.

[0053] The principle and criteria for monitoring the status and spontaneous combustion warning of power batteries: Under any condition, the following relationship should be satisfied between the individual battery modules of the electric vehicle power battery and the entire battery pack formed by them connected in series:

[0054] 1) The sum of the voltages (or their changes) of each individual battery module equals the voltage (or its changes) of the entire battery pack;

[0055] 2) The sum of the internal resistance (or its change) of each individual battery module equals the internal resistance (or its change) of the entire battery pack;

[0056] 3) The sum of the capacities (or changes thereof) of each individual battery module equals the total battery capacity (or changes thereof);

[0057] When the changes in the state characteristics of a single battery module, such as capacity, internal resistance, voltage, and temperature, deviate significantly from the changes of most other single battery modules, the probability of that single battery module spontaneously combusting is greater than that of other single battery modules.

[0058] The relevant data acquisition, transmission, communication, and computing technologies involve connecting a smart device with data acquisition capabilities to the charging data communication interface or communication line of the Battery Management System (BMS) via a charging gun. During the charging process, the BMS collects data on the entire battery pack and individual battery modules of the electric vehicle. This data is then transmitted via a communication system to a dedicated computing device or system with computational analysis capabilities. The system utilizes mathematical models and algorithms developed based on the working principle for computational analysis. Using a dedicated computing device or system, the system employs the principles and criteria for monitoring the state of the power battery and for self-ignition warnings to perform computational analysis on the collected data. By comparing and analyzing historical data from similar electric vehicles, it identifies and judges individual battery modules with abnormal states, thereby achieving monitoring of the electric vehicle's power battery state and for self-ignition warnings.

[0059] Before elaborating on the technical solutions in the embodiments of this invention, let's first introduce the basic concepts involved in the application scenarios:

[0060] I. The detection quantities for condition monitoring include:

[0061] 1) Temperature of the entire battery pack and individual battery modules.

[0062] 2) The charging current, charging voltage, and open-circuit voltage of the entire battery pack.

[0063] 3) Charging current, charging voltage, and open-circuit voltage of individual battery modules.

[0064] 4) Energy freeze data (W) of the entire battery pack at a specified point. i The specified point can be the time point corresponding to a given voltage or current value, or any other specified time point.

[0065] II. Characteristic quantities of condition monitoring, including:

[0066] 1) The internal resistance R of the entire battery pack iz The current internal resistance R is being measured. iz The change relative to the initial value, and the current measured internal resistance R iz The change relative to the previous measurement. Here, i indicates the measurement number of the corresponding entire battery pack; the subscript z indicates the concept of the entire battery pack, as shown in R below. if The subscript f in the text represents the concept of a single battery module. In the subsequent description of this invention, the corresponding subscript i will be used multiple times in different scenarios, and its specific meaning shall be subject to the corresponding interpretation in its respective scenario.

[0067] 2) Internal resistance R of a single battery module if The current internal resistance R is being measured. if The change relative to the initial value, and the current measured internal resistance R if The change relative to the previous measurement.

[0068] 4) The ratio K of the internal resistance of each individual battery module to the internal resistance of the entire battery pack. i1 Ratio result K i1 The change relative to the initial value, the ratio result K i1 The change relative to the previous measurement.

[0069] 5) Total battery capacity (W) iz Present value of capacity W iz Change relative to the initial value, and change relative to the previous measurement.

[0070] 6) Capacity of individual battery modules (W) if Current measured capacity W if Relative to the change in initial value, the current measurement capacity W if The change relative to the previous measurement.

[0071] 7) The ratio K of the capacity of each individual battery module to the capacity of the entire battery pack. i2 Ratio result K i2 The change relative to the initial value, the ratio result Ki2 The change relative to the previous measurement.

[0072] The working principle of power battery state monitoring proposed in this invention is as follows:

[0073] Regardless of the battery temperature, charging current, or initial battery capacity, the charging voltage and internal resistance of each individual battery module and the entire battery pack formed by them should conform to the calculation methods for series voltage and resistance in physics. That is, the sum of the charging voltages of each individual battery module and the sum of the corresponding internal resistances of each individual battery module should equal the charging voltage and internal resistance of the entire battery pack. Therefore, when all individual battery modules are in normal operating condition, the ratio of the charging voltage and internal resistance of each individual battery module to the charging voltage and internal resistance of the entire battery pack should remain approximately constant.

[0074]

[0075]

[0076] Among them, U ij and R ij U represents the measured and calculated values ​​of the charging voltage and internal resistance of the i-th individual battery module during the j-th charging cycle, respectively; zj and R zj U represents the calculated values ​​of the charging voltage and internal resistance of the entire battery pack during the j-th charging test; io and R io U represents the measured and calculated values ​​of the charging voltage and internal resistance of the i-th individual battery module in the o-th reference cycle, respectively; zo and R zo These represent the calculated charging voltage and internal resistance values ​​of the entire battery pack in the o-th reference cycle; K i and C i The parameter thresholds representing the state changes of the i-th individual battery module can be set based on experience; the reference cycle can be the initial state, the previous cycle, or any specified cycle.

[0077] Similarly, various criteria such as the discreteness of temperature change of individual battery modules and the abnormality of the proportion of individual battery module capacity to the total battery capacity can be used to determine abnormal changes in the state of individual battery modules by referring to formulas (1) and (2) above.

[0078] In order to provide the above-mentioned analytical data, this invention provides corresponding data acquisition and processing steps, including:

[0079] Step 1:

[0080] A smart device with data acquisition capabilities is connected to the charging data communication interface or communication line of the power battery management system (BMS) via a charging gun. During the charging process, the BMS collects data on the entire battery pack and individual battery modules of the electric vehicle.

[0081] Step Two:

[0082] The data collected from the entire battery pack and individual battery modules of the electric vehicle are transmitted via a communication system to a dedicated computing device or system with computational analysis capabilities.

[0083] Step 3:

[0084] The mathematical model and algorithm were developed based on the working principle of the power battery state monitoring described above for calculation and analysis.

[0085] Based on the results of the calculation and analysis, and by comparing and analyzing historical data of the same type of electric vehicle, the state and state variation of each individual battery module are identified, and individual battery modules with abnormal state changes are detected, thereby achieving the purpose of monitoring the state of the electric vehicle's power battery.

[0086] In the process of implementing the technical solution of this invention, it is also necessary to consider the necessary conditions for monitoring the charging status of the power battery:

[0087] 1) Accuracy of monitoring tools

[0088] The detection accuracy of charging data from different cycles meets the requirements, using the same monitoring equipment, or a measurement system under the same high-precision testing technology.

[0089] 2) Same electrical quantity environment and process

[0090] The charging data monitoring environment is the same, the charging power supply is a controlled power supply, and the current and voltage values ​​are the same under different power supply environments.

[0091] 3) Same atmospheric environment

[0092] The temperature is the same, or the temperature can be measured and compensated for.

[0093] 4) Same initial state

[0094] Efforts should be made to make the available remaining capacity and initial open-circuit voltage of the power battery similar.

[0095] The technical challenges of power battery status monitoring in existing technologies can be summarized as follows:

[0096] 1) The appearance of a power battery varies under different battery temperatures.

[0097] 2) The appearance of the power battery is different under different charging current processes.

[0098] 3) The appearance of the power battery is different under different charging voltage changes.

[0099] 4) The appearance of the power battery is different under different initial battery voltage conditions.

[0100] 5) The appearance of a power battery after charging differs depending on the initial electrical state of the battery.

[0101] 6) For the same determined power battery state parameters, the corresponding power battery states may be different.

[0102] This invention collects data from the entire battery pack and individual battery modules of an electric vehicle for calculation and analysis, and identifies individual battery modules with abnormal states. By drawing on the principles of the above formulas (1) and (2), a corresponding mathematical model and algorithm are designed to perform calculation and analysis on the collected data. Based on the results of the calculation and analysis, the data is compared and analyzed with historical data of the same type of electric vehicle. By identifying the state and state variation of each individual battery module, individual battery modules with abnormal state changes can be detected, thereby achieving the purpose of monitoring the state of the electric vehicle's power battery.

[0103] The main feature of the power battery monitoring technical solution of the present invention is that, during the charging process of an electric vehicle, charging equipment is used to collect charging data from the battery management system (BMS). A computing and analysis device is used to analyze the charging data to derive the set power battery state characteristics and their changes, and to determine abnormal changes in the state of each individual battery module. Specifically, the data and analysis results collected during the current charging process are compared with the data and analysis results collected during previous charging processes of the electric vehicle's power battery. By identifying the state changes and differences in each individual battery module, individual battery modules with abnormal state changes are detected, thereby achieving the purpose of monitoring the state of the electric vehicle's power battery. The charging data collected includes, but is not limited to, battery temperature, current, voltage, and energy of the entire battery pack and each individual battery module. The analysis results of the charging data include, but are not limited to, the charge / discharge capacity of the entire battery pack and each individual battery module, battery internal resistance, the voltage ratio of the individual battery module to the overall battery pack, the voltage ratio of the individual battery module to the overall battery pack's internal resistance, the voltage ratio of the individual battery module to the overall battery pack's capacity, and the changes in these data relative to similar data from the past of the electric vehicle's power battery, etc.

[0104] Furthermore, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0105] Example 1:

[0106] In this embodiment of the invention, a pre-selected intelligent device and / or dedicated computing device or system with communication capabilities with the battery management system (BMS) is used to collect and analyze charging data from the BMS and charging equipment during the charging process of an electric vehicle. This allows for the identification and judgment of individual battery modules exhibiting abnormal conditions, thereby achieving state monitoring of the electric vehicle's power battery. Figure 1 As shown, the method includes:

[0107] In step 101, during the charging process of the power battery, the charging data of the entire battery pack and each individual battery module are acquired, and the values ​​of the capacity, internal resistance and charging voltage state characteristics of the entire battery pack and each individual battery module are calculated.

[0108] In step 102, based on the summation of the capacity, internal resistance and charging voltage of each individual battery module, and the relationship between these summations and the overall battery capacity, internal resistance and charging voltage, the change and offset of the state characteristic quantities of each individual battery module are calculated and analyzed to assess the probability of natural failure.

[0109] In step 103, a threshold for the change offset of the state characteristic quantity of each individual battery module is set. When the change offset is greater than or equal to the threshold, a fault warning is activated to realize power battery fault warning monitoring.

[0110] The threshold values ​​for the changes in each state characteristic quantity here will vary depending on factors such as the type of power battery, the scale of the power battery, and the battery processing technology. In practice, they are usually set based on test results. Here, no specific parameter value is limited.

[0111] This invention, through calculation of the capacity, internal resistance, and voltage of a single battery module, compares these values ​​with those of the batteries in its group, and analyzes the pairwise changes. This analysis is then compared with historical data from similar electric vehicles. By identifying the state and state variations of each individual battery module, modules with abnormal state changes can be detected. This method significantly reduces the impact of factors such as the precision of monitoring tools, identical electrical quantities and processes, identical atmospheric conditions, and identical initial states, which can hinder the control of accuracy and even render existing methods unusable.

[0112] Example 2:

[0113] This invention embodiment demonstrates the method and process for obtaining the internal resistance of the battery module based on Embodiment 1, such as... Figure 2 As shown, the method of this embodiment of the invention includes:

[0114] In step 201, during the charging process of the power battery, the internal resistance of each individual battery module in the power battery is obtained.

[0115] In the implementation of this invention, the internal resistance data of the aforementioned single battery module can be obtained through a data path built by the charging gun and the electric vehicle charging interface.

[0116] In this embodiment of the invention, the intelligent device with communication function with the battery management system (BMS) can be an integrated device or a separate device. In the separate device configuration, for example, the corresponding intelligent device can be installed in the charging pile (e.g., the charging pile's main control board, smart meter, data collector, or any other intelligent device with communication function with the battery management system (BMS)). The calculation process and corresponding reference data storage method, similar to step 203, can be completed using a server on a network.

[0117] In step 202, the internal resistance of the corresponding group of batteries is calculated based on the connection method of each individual battery module in constituting its respective group of batteries.

[0118] In one optional scheme, the grouped battery is composed of a specified number of individual battery modules connected in series. The grouped battery can be the entirety of an electric vehicle's power battery or a portion thereof. The specified number, when the grouped battery is the entirety of an electric vehicle's power battery, specifically refers to all individual battery modules. When the grouped battery is a portion of an electric vehicle's power battery, the specified number depends on the grouping method used in the design of the power battery. Since different electric vehicle power battery manufacturers use different sizes for individual battery modules, the number of individual battery modules included in a specified group may not be strictly limited. The reason for dividing the battery into different groups is to enable multi-level operation in BMS management and to allow for selective partial replacement when replacing the electric vehicle's power battery.

[0119] In the implementation process, multiple individual battery modules may be connected in parallel as objects for further series connection operations. In this case, the connection method of each individual battery module in forming its respective group of batteries includes the combination of parallel and series connections mentioned above.

[0120] In step 203, based on the internal resistance of the corresponding single-cell battery module, the change between the first change relationship between the two and the internal resistance of the group battery in its group, and the change between the second change relationship selected from historical data as a reference, if the amount of change exceeds the first preset threshold, then it is confirmed that the internal resistance of the corresponding single-cell battery module exhibits an abnormal risk.

[0121] This invention, through the calculation of the internal resistance of a single battery module and its relationship with the internal resistance of the group of batteries in the same group, compares and analyzes the first change relationship between the two with historical data of electric vehicles of the same type. By identifying the state and state variation of each single battery module, single battery modules with abnormal state changes can be detected, achieving a high degree of automation without the need for professional monitoring equipment.

[0122] In the implementation of this invention, in order to measure the internal resistance of a single battery module, current and voltage measurement and energy metering devices need to be installed on the I / O ports of the main control board of the charging pile, such as... Figure 8 As shown, the significance of this device lies in controlling the opening and closing of the switch between the charging power supply and the charging gun. In actual operation, in order to measure the internal resistance of individual battery modules and the internal resistance of the power battery, it is necessary to briefly disconnect the electrical connection between the charging power supply and the charging gun. This allows the current, voltage, and energy metering devices to directly connect to the power battery, thereby enabling the measurement of the internal resistance of individual battery modules and the power battery. In comparison, this invention is the first to propose a solution for measuring the resistance of the power battery from the charging pile side. Compared to existing technologies that measure the resistance of the power battery during use, its measurement results are more accurate and reliable.

[0123] This invention isolates and analyzes the internal resistance separately, and it can also be used as the analytical method for capacitance, internal resistance, and other parameters in Embodiment 1 above.

[0124] The method of this invention can greatly reduce and weaken the influence of factors such as the accuracy of monitoring tools, the same electrical quantity environment and process, the same atmospheric environment, and the same initial state, which cause the problem that the accuracy of detection results is difficult to control or even the detection results are unusable in existing methods.

[0125] In the implementation scheme of this invention, in addition to analyzing the relationship between the internal resistance of the corresponding single battery module and the internal resistance change of its group of batteries, as performed in steps 201-203, monitoring of the charging voltage can also be performed asynchronously or synchronously; for example Figure 3 As shown, the method also includes:

[0126] In step 301, during the charging process of the power battery, the charging voltage of each individual battery module in the power battery is also obtained.

[0127] In step 302, the charging voltage of the corresponding group battery is calculated based on the connection method of each individual battery module in constituting its respective group battery.

[0128] In step 303, based on the charging voltage of the corresponding single battery module, the amount of change between the third change relationship of the charging voltage of the group battery in which it belongs and the fourth change relationship selected from historical data as a reference exceeds the second preset threshold, and it is confirmed that the corresponding single battery module has an abnormal charging voltage risk.

[0129] Historical data refers to the charging data recorded on the corresponding server when the charging pile provides the same charging voltage.

[0130] In a specific implementation, steps 301-303 can be integrated into corresponding steps 201-203 one by one. That is, steps 201 and 301 can be completed synchronously. After their execution, steps 202 and 302 are executed synchronously, and finally steps 203 and 303 are executed synchronously. It should be noted that in computer execution, there is no strict sense of synchronization and parallelism. For example, the synchronous execution of steps 201 and 301 means that they are completed at the same logical level, while the apparent logical level is divided into three levels like steps 201-203.

[0131] In alternative solutions, the aforementioned method for detecting the internal resistance of individual battery modules can be used to simultaneously monitor the capacity status of individual battery modules, such as... Figure 4 As shown, it includes:

[0132] In step 401, during the charging process of the power battery, the capacity of each individual battery module in the power battery is also obtained.

[0133] In step 402, the capacity of the corresponding group battery is calculated based on the connection method of each individual battery module in constituting its respective group battery.

[0134] In step 403, based on the capacity of the corresponding single battery module, the change between the fifth change relationship of the capacity of the group battery in which it belongs and the sixth change relationship selected from historical data as a reference, if the change exceeds the third preset threshold, it is confirmed that the corresponding single battery module has an abnormal capacity risk.

[0135] In a specific implementation, steps 401-403 can be integrated into corresponding steps 201-203. That is, steps 201 and 401 can be completed synchronously. After their execution, steps 202 and 402 are executed synchronously, and finally steps 203 and 403 are executed synchronously. It should be noted that in computer execution, there is no strict concept of synchronization and parallelism. For example, the synchronous execution of steps 201 and 401 means that they are completed at the same logical level, while the apparent logical relationship is divided into three levels similar to steps 201-203.

[0136] The first preset threshold, the third preset threshold, and the first preset threshold described in the above scheme can all be adjusted and set based on testing experience. Since the corresponding risk assessment conditions are different in different power battery scenarios, no special technical limitations are imposed on the first preset threshold, the first preset threshold, and the third preset threshold in the embodiments of the present invention. They can be flexibly set based on the needs of different scenarios and with the help of the experience and test results of those skilled in the art.

[0137] In the implementation of this invention, when the individual battery modules within a group are connected in series, the change between the first relationship between the internal resistance of the corresponding individual battery module and the internal resistance of the group's batteries, and the second relationship selected from historical data as a reference, is specifically manifested as follows:

[0138] The sum of the internal resistances of the individual battery modules contained in a battery group is theoretically equal to the internal resistance of the battery group; when all individual battery modules are in normal condition, the ratio of the internal resistance of each individual battery module to the internal resistance of the battery group is the first change relationship; as the most illustrative example, the corresponding first change relationship can be the formula (2) above. The ratio of the internal resistance of each individual battery module selected historically as a reference to the internal resistance of the grouped batteries is the second variation relationship. As the most illustrative example, the first variation relationship described above is expressed in formula (2). At that time, the second change relationship here can be the one in formula (2) above. At this point, the corresponding first preset threshold is represented by C in formula (2). i The explanations of each parameter value are detailed in the description of the corresponding formula (2) above, and will not be repeated here.

[0139] In the implementation of this invention, when the individual battery modules within a group are connected in series, the charging voltage of the corresponding individual battery module, compared with the charging voltage of the group's batteries, has a third relationship, and a fourth relationship selected from historical data as a reference, specifically as follows:

[0140] The sum of the charging voltages of the individual battery modules contained in a battery group is theoretically equal to the charging voltage of the battery group; when all individual battery modules are in normal condition, the ratio of the charging voltage of each individual battery module to the charging voltage of the battery group is the third variation relationship; as the most illustrative example, the corresponding third variation relationship can be the one in the above formula (1). The fourth variation relationship is the ratio of the charging voltage of each individual battery module selected historically as a reference to the charging voltage of the grouped batteries. As the most illustrative example, the third variation relationship described above is expressed in formula (1). In this case, the fourth change relationship can be found in the above formula (1). At this point, the corresponding second preset threshold is represented by K in formula (1). i The explanations of each parameter value are detailed in the description of the corresponding formula (2) above, and will not be repeated here.

[0141] In capacity scenarios, the corresponding fifth and sixth change relationships can also be represented by the internal resistance representation above, which will not be elaborated here.

[0142] Example 2:

[0143] Before proposing the technical solution of Embodiment 1 of the present invention, it has been analyzed that the reason why it is difficult to analyze whether the state of a single battery module is abnormal in the prior art is that the environmental state may be different each time it is charged and each time it is tested. Therefore, to use an external detection mechanism to test its stability, a relatively uniform environmental state needs to be provided. This is why professional testing equipment is needed and the testing cost is relatively high. This is precisely the inventiveness of the technical solution described in Embodiment 1 of the present invention.

[0144] However, even in the scheme for detecting whether there are abnormalities in the state of a single battery module as described in Example 1, the influence of environmental conditions will exist to some extent, although the severity of the influence will not significantly interfere with the feasibility of the method proposed in Example 1. Therefore, in order to further improve the accuracy of the detection and analysis of the method described in Example 1, this invention also proposes a series of improvement measures, and further involves efficiency improvement schemes for the corresponding execution steps 201-203 and 301-303.

[0145] like Figure 5 As shown, the specific steps of the method in Example 1 are as follows:

[0146] In step 201', during the charging process of the power battery, the internal resistance of each individual battery module in the power battery is obtained.

[0147] In step 202', while obtaining the internal resistance of each individual battery module in the power battery, one or more of the following are recorded at the corresponding sampling point: the amount of charging completed, the charging temperature, and the charging current of each individual battery module.

[0148] Based on practical research, the internal resistance of each individual battery module is linked to its charging completion rate. For example, the internal resistance of a battery module with a charging completion rate of 30% and 60% is different. Therefore, the charging completion rate of the individual battery module is crucial throughout the analysis process in this embodiment. When comparing the first and second change relationships, the corresponding charging data should be within the allowable deviation range of charging completion rate. Ideally, the comparison data should be based on the charging completion rates of the same individual battery module. Therefore, in conjunction with this embodiment, there is a preferred implementation. Considering the position of the individual battery module within the battery group and the position of the battery group relative to the power battery, which determines their relative order during charging, and further considering the influence of the charging completion rate of the individual battery module on its internal resistance, the selected charging data during the comparison of the first and second change relationships should revert to the total charging completion rate of the corresponding power battery or the charging completion rate of the battery group, serving as a reference for the relative consistency of the individual battery module's charging completion rate in the first and second change relationships. As for the possibility of a more complex solution, in reality, if different battery groups exist, and if there is a possibility of parallel charging between them, then the actual situation will be further subdivided into the individual battery modules within the battery groups. If they are simply connected in series (leading to serial charging), the above analysis method can still be used. However, if parallel charging exists, then the actual situation may need to be further subdivided to the point that the charging completion amount of a specific battery module must be similar in the first and second relationships, and the distribution curves of the charging completion amounts of the corresponding individual battery modules in the first and second relationships must also be similar to meet the reference comparison requirements described later. This is considering that the future on-board charging main controller of electric vehicles will be able to realize battery grouping.

[0149] The corresponding differences in charging temperature will also affect the internal resistance exhibited by a single battery module. However, relative to the amount of charge completed by the single battery module, unless the power battery burns, the charging temperature under normal conditions will not change significantly. Especially in some electric vehicles, the power battery is equipped with a heat dissipation device. Therefore, in a normal charging environment, the differences in charging temperature are more differentiated by the location and the corresponding season. The division of seasons is also linked to different regions. For example, the seasonal temperature changes are not significant in high-latitude and low-latitude regions. However, the seasonal temperature differences in certain regions are large. In this case, it is necessary to link the corresponding GPS positioning and ambient temperature with the charging temperature to establish more accurate data clustering. For example, the second change relationship used as a reference in step 203 of Example 1 and step 204' of this example will be adjusted according to the seasonal ambient temperature under the GPS positioning. For example, when the GPS determines that the seasonal temperature difference of the geographical location is large, the second change relationship used as a reference needs to be adjusted at the appropriate seasonal change nodes.

[0150] Here, the charging current and the charging voltage, which will be discussed later, are actually two related dimensions. When the charging voltage is the same, if the charging current is abnormal, it indicates that the corresponding internal resistance is abnormal. This brings us back to the principle of the method steps in this embodiment, so we will not go into details here.

[0151] In step 203', the internal resistance of the corresponding group battery is calculated based on the connection method of each individual battery module in constituting its respective group battery.

[0152] In step 204', the change amount between the second change relationship selected from historical data as a reference, wherein the historical data also satisfies the internal resistance data of the single battery module and the internal resistance data of the group battery of the group to which it belongs, obtained by the matching collection points of one or more of the above-mentioned charging completion amount, charging temperature, and charging current.

[0153] In step 205', based on the internal resistance of the corresponding single-cell battery module, the change between the first change relationship between the two and the internal resistance of the group battery in its group, and the change between the second change relationship selected from historical data as a reference, if the amount of change exceeds the first preset threshold, then it is confirmed that the internal resistance of the corresponding single-cell battery module exhibits an abnormal risk.

[0154] This invention, through calculation of the internal resistance of a single battery module and comparison with the internal resistance of the batteries in its group, analyzes the first change relationship between the two and compares it with historical data of similar electric vehicles. By identifying the state and state variations of each single battery module, it can detect single battery modules with abnormal state changes, achieving a high degree of automation without the need for specialized monitoring equipment. Compared to Embodiment 1, this invention further subdivides the possible impacts of charging-related factors on the analysis results in complex scenarios, especially the two factors analyzed above: charging completion amount and charging temperature, further improving the accuracy and effectiveness of the implemented solution.

[0155] In conjunction with the embodiments of the present invention, the extended content in step 202' above is described in the form of steps in the embodiments of the present invention, specifically as follows: the corresponding historical data is collected from charging piles distributed in different locations and uploaded to the server for storage. After the server obtains the historical charging data for the same power battery, the method further includes:

[0156] The server analyzes the historical charging data corresponding to the same power battery. For charging data with intervals exceeding one or more analysis cycles in the first dimension index value of charging completion amount, charging temperature and / or charging current, the charging data corresponding to the first dimension index value of charging completion amount, charging temperature and / or charging current will be discarded or transferred to a low-cost storage device for backup.

[0157] If the historical charging data recorded in a single instance includes not only the first dimension indicator value mentioned above, but also other dimension indicator values, then the prerequisite for discarding or transferring the charging data corresponding to the first dimension indicator value of charging completion, charging temperature and / or charging current to a storage device with a storage rate for backup is that the server retains charging data under other dimension indicator values ​​that meets the requirements of the compound analysis cycle of charging data interval.

[0158] To better connect the logical characteristics of the charging completion amount, charging temperature, and charging current, the following will describe them in detail, in conjunction with the embodiments of the present invention. The server organizes historical charging data according to the priority of the three factors—charging completion amount, charging temperature, and charging current—from high to low, such as... Figure 6 As shown, specifically:

[0159] In step 501, the historical charging data is arranged according to the charging completion amount. Within the allowed analysis cycle interval, if there are historical charging data that exceed the number of times required for analysis for the same charging completion amount, the charging data is further filtered based on the charging temperature. This results in charging data whose charging temperature differs from the reference charging temperature within the same period by more than a first preset value being temporarily removed from the calculation of the change or transferred to a low-cost memory for backup.

[0160] In step 502, if the number of times historical charging data corresponds to the same charging completion amount does not exceed the analysis requirements, no temporary removal or transfer operation is performed.

[0161] In step 503, if the number of times the remaining historical charging data still exceeds the analysis requirements after the above-mentioned charging temperature screening, the remaining charging data is further screened using the charging current, so that charging data whose charging current differs from the reference charging current within the same period by more than a second preset value are temporarily removed from the calculation of the change or transferred to a low-cost memory for backup.

[0162] It should be noted that the charging temperature setting method explained in step 202' above can greatly simplify the amount of parameter data related to charging temperature in the recorded data; however, it is also possible that a temperature sensor is installed on the power battery and the actual temperature value is directly recorded, which is why step 501 above exists.

[0163] In the above process, considering that the monitoring method proposed in this invention is also affected by the charging temperature, in the optimal solution, when selecting to analyze the internal resistance state of a single battery module, it is naturally more valuable to analyze the data from two charging times with similar charging temperatures. This is why step 501 is mentioned above.

[0164] Based on a processing branch proposed in steps 501-503 above, namely, the selection of transferring to a low-cost storage memory for backup in steps 501 and 503, the purpose is actually to be able to analyze the cause of the problem when the internal resistance of a single battery module is found to be abnormal during the final monitoring and analysis, and to further provide suggestions for improving charging methods or habits. Therefore, in conjunction with the embodiments of the present invention, there is also an improved solution, such as... Figure 7 As shown, it includes:

[0165] In step 601, when it is confirmed that the internal resistance of the corresponding single battery module exhibits an abnormal risk, the charging data of the power battery to which the single battery module belongs is restored from the low-cost storage memory, thereby analyzing and obtaining secondary diagnostic data.

[0166] In step 602, the primary diagnostic data obtained by analyzing the charging data of the corresponding power battery stored in the server is integrated, and then compared and analyzed with the historical charging data of other power batteries that have experienced abnormal risks in the server to obtain the influencing factors that accelerate the occurrence of abnormal risks in the power battery.

[0167] The influencing factors here are more derived from big data analysis of other power battery historical charging data. For example, suggestions are made on how to complete a full charge in at least a few charging cycles based on the amount of charge in a single charge, suggestions on reducing the number of electrical devices in the vehicle during charging based on the number of abnormal charging temperatures, and suggestions on specific voltage charging selection based on the charging voltage. These are used to form the health usage report in step 603.

[0168] In step 603, a customized report on improving healthy battery usage habits is pushed to the user.

[0169] In this embodiment of the invention, taking the state of the power battery of an electric vehicle as an example, it is usually obtained by monitoring a set of state characteristic quantities. Specifically, these include battery temperature, current, voltage, and electrical energy of the entire battery pack and each individual battery module, as well as some derived quantities, including the internal resistance and charge / discharge capacity of the entire battery pack and each individual battery module, the voltage ratio of the individual battery module to the voltage of the entire battery pack, the internal resistance ratio of the individual battery module to the internal resistance ratio of the entire battery pack, the capacity ratio of the individual battery module to the capacity ratio of the entire battery pack, and the changes in these data relative to similar data in the past of the electric vehicle's power battery, etc.

[0170] In this embodiment, the charging current is given the lowest priority among the three because, given a fixed charging voltage, a fixed internal resistance, and a fixed degree of charging completion, the charging current is predictable and usually does not show significant differences.

[0171] Example 3:

[0172] like Figure 8 The diagram shown is a schematic of an improved circuit structure for a charging pile provided by the present invention to better implement the solutions proposed in Embodiments 1 and 2 of the present invention.

[0173] In the specific implementation process, in order to better eliminate differences in specifications, charging voltage, charging current, and other indicators among different charging piles; and also to consider a situation where users are traveling long distances and the charging piles they use along the way exhibit inconsistent specifications, in such cases, the use of... Figure 8The improved charging pile structure shown can improve the situation where the number of charging times is less than the preset number proposed in Embodiment 1, which may be encountered in a single analysis cycle.

[0174] For users who own power batteries and have subscribed to a power battery health service, if the server collects insufficient charging data from each user's charging sessions to support a full analysis cycle, it will notify the user by sending a message to access a service that includes battery health information. Figure 8 The device shown is used for charging at designated charging stations to collect and analyze data. This situation often occurs when conventional charging piles are already widespread, but the charging piles capable of supporting the charging data reporting function to the server proposed in Embodiments 1-2 of this invention have not yet been deployed to achieve the required coverage, resulting in a limited amount of charging data for the same power battery actually collected by the server.

[0175] exist Figure 8 In the charging pile structure shown, the charging gun can be disconnected from the conventional charging power output port and connected to a module component with output voltage and output current adjustment functions. Figure 8 It is presented as a "current, voltage measurement and energy metering device" and outputs charging data within the analysis period required by the server, thereby ensuring the accuracy of the corresponding analysis.

[0176] Those skilled in the art will understand that all or part of the steps in the various methods of the embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk, etc.

[0177] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for monitoring and early warning of power battery faults using charging equipment, characterized in that, include: During the charging process of the power battery, the charging data of the entire battery pack and each individual battery module are obtained, and the values ​​of the capacity, internal resistance and charging voltage state characteristics of the entire battery pack and each individual battery module are calculated. Based on the summation of the capacity, internal resistance, and charging voltage of each individual battery module, and the corresponding relationship between these summations and the overall battery capacity, internal resistance, and charging voltage, the changes and deviations of the state characteristic quantities of each individual battery module are calculated and analyzed to assess the probability of natural failure. A threshold is set for the change offset of the state characteristic quantity of each individual battery module. When the change offset is greater than or equal to the threshold, a fault warning is activated to realize the power battery fault warning and monitoring.

2. The method for power battery fault early warning and monitoring using charging equipment according to claim 1, characterized in that, Specifically, it includes: During the charging process of the power battery, the internal resistance of each individual battery module in the power battery is obtained; Based on the connection method of each individual battery module in its respective group of batteries, the internal resistance of the corresponding group of batteries is calculated. Based on the internal resistance of the corresponding single-cell battery module, compared with the internal resistance of the group battery in its group, the amount of change between the first relationship between the two and the second relationship selected from historical data as a reference exceeds the first preset threshold, then it is confirmed that the internal resistance of the corresponding single-cell battery module shows an abnormal risk.

3. The method for power battery fault early warning and monitoring using charging equipment according to claim 1, characterized in that, Specifically, it includes: During the charging process of the power battery, the charging voltage of each individual battery module in the power battery is also obtained; Based on the connection method of each individual battery module in its respective group of batteries, the charging voltage of the corresponding group of batteries is calculated. Based on the charging voltage of the corresponding single battery module, the amount of change between the third change relationship of the charging voltage of the group battery in which it belongs and the fourth change relationship selected from historical data as a reference exceeds the second preset threshold, and it is confirmed that the corresponding single battery module has an abnormal charging voltage risk. Historical data refers to the charging data recorded on the corresponding server when the charging pile provides the same charging voltage.

4. The method for power battery fault early warning and monitoring using charging equipment according to claim 1, characterized in that, Specifically, it includes: If, during the charging process of the power battery, the capacity of each individual battery module in the power battery is also obtained, then the method further includes: Based on the connection method of each individual battery module in its respective battery group, the capacity of the corresponding battery group is calculated. Based on the capacity of the corresponding single battery module, the change between the fifth change relationship of the capacity of the group of batteries in its group and the sixth change relationship selected from historical data as a reference, if the change exceeds the third preset threshold, it is confirmed that the corresponding single battery module has an abnormal capacity risk.

5. The method for power battery fault early warning and monitoring using charging equipment according to claim 1, characterized in that, When the individual battery modules within a group are connected in series, the change between the first relationship between the internal resistance of the corresponding individual battery module and the internal resistance of the group's batteries, and the second relationship selected from historical data as a reference, is specifically manifested as follows: The sum of the internal resistances of the individual battery modules contained in a battery group is theoretically equal to the internal resistance of the battery group; when all individual battery modules are in normal condition, the ratio of the internal resistance of each individual battery module to the internal resistance of the battery group is the first relationship; and the ratio of the internal resistance of the corresponding individual battery modules selected historically as a reference to the internal resistance of the battery group is the second relationship.

6. The method for power battery fault early warning and monitoring using charging equipment according to claim 3, characterized in that, When the individual battery modules within a group are connected in series, the charging voltage of the corresponding individual battery module, compared with the charging voltage of the group's batteries, exhibits a third relationship, and a fourth relationship selected from historical data as a reference, specifically as follows: The sum of the charging voltages of the individual battery modules contained in a battery group is theoretically equal to the charging voltage of the battery group; when all individual battery modules are in normal condition, the ratio of the charging voltage of each individual battery module to the charging voltage of the battery group is the third relationship; and the ratio of the charging voltage of the corresponding individual battery modules selected historically as a reference to the charging voltage of the battery group is the fourth relationship.

7. The method for power battery fault early warning monitoring using charging equipment according to claim 1, characterized in that, The process of obtaining the internal resistance of each individual battery module in the power battery during the charging process specifically includes: While obtaining the internal resistance of each individual battery module in the power battery, record one or more of the following at the corresponding collection point: the amount of charging completed, the charging temperature, and the charging current of each individual battery module. The corresponding historical data also satisfy the data of the internal resistance of the single battery module and the internal resistance of the group of batteries in the same group, which are obtained by collecting one or more of the above-mentioned charging completion amount, charging temperature, and charging current.

8. The method for power battery fault early warning and monitoring using charging equipment according to claim 7, characterized in that, The corresponding historical data is collected from charging piles distributed in different locations and uploaded to a server for storage. After the server obtains the historical charging data for the same power battery, the method further includes: The server analyzes the historical charging data corresponding to the same power battery. For the charging data intervals under the first dimension index value in the dimension index consisting of charging completion amount, charging temperature and / or charging current that exceed one or more analysis cycles, the charging data under the first dimension index value corresponding to charging completion amount, charging temperature and / or charging current will be discarded or transferred to a low storage cost memory for backup. If the historical charging data recorded in a single instance includes not only the first dimension indicator value mentioned above, but also other dimension indicator values, then the prerequisite for discarding or transferring the charging data corresponding to the first dimension indicator value of charging completion, charging temperature and / or charging current to a storage device with a storage rate for backup is that the server retains charging data under other dimension indicator values ​​that meets the requirements of the compound analysis cycle of charging data interval.

9. The method for power battery fault early warning and monitoring using charging equipment according to claim 8, characterized in that, The server organizes historical charging data according to the following priority order: charging completion amount, charging temperature, and charging current, from highest to lowest. Specifically: The historical charging data is arranged according to the charging completion amount. Within the allowed analysis period interval, if there are historical charging data for the same charging completion amount that exceed the number of times required for analysis, the charging data is further filtered based on the charging temperature. Charging data whose charging temperature differs from the reference charging temperature within the period by more than a first preset value is temporarily removed from the calculation of the change or transferred to a low-cost memory for backup. If the number of times the historical charging data for the same charging completion amount does not exceed the number required for analysis, no temporary removal or transfer operation is performed. If, after the above-mentioned charging temperature screening, the number of times the remaining historical charging data still exceeds the analysis requirements, then the remaining charging data will be further screened using the charging current, so that charging data whose charging current differs from the reference charging current within this period by more than a second preset value will be temporarily removed from the calculation of the change or transferred to a low-cost storage memory for backup.

10. The method for power battery fault early warning and monitoring using charging equipment according to claim 1, characterized in that, When it is confirmed that the internal resistance of the corresponding single battery module exhibits an abnormal risk, the charging data of the power battery to which the single battery module belongs is restored from the low-cost storage memory, thereby analyzing and obtaining secondary diagnostic data. It integrates the primary diagnostic data obtained by analyzing the charging data of the corresponding power battery stored in the server, and compares and analyzes it with the historical charging data of other power batteries that have experienced abnormal risks in the server to obtain the influencing factors that accelerate the occurrence of abnormal risks in power batteries, and pushes a customized report on improving the healthy use of power batteries to users.

Images