Battery type identification and detection method and system based on charging and discharging characteristics

Abstract

The invention relates to the technical field of battery detection, in particular to a battery type identification and detection method and system based on charging and discharging characteristics. The scheme comprises the following steps: acquiring charging and discharging information of each battery in real time; according to the charging and discharging information, a battery platform is determined, and the battery platform is one of a ternary lithium battery, a lead-acid battery and a lithium iron phosphate battery; calculating the slope characteristic of the current battery in real time, judging the similarity between the current battery and a preset battery type, and selecting the battery type with the highest similarity as a matching result; abnormal jump information in the battery is extracted in real time and displayed; analyzing the state of the battery at the current moment according to the change conditions of the current and the voltage; and the temperature of the battery is monitored in real time, and an overheating state is prompted. According to the scheme, the battery type is judged by integrating the voltage platform, the slope feature and the jump feature, combined diagnosis is carried out, analysis can be carried out from different dimensions through multi-feature combination, and the recognition accuracy is greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of battery detection, and more specifically, to a battery type identification and detection method and system based on charge and discharge characteristics. Background Art

[0002] In the field of battery detection, battery type identification and detection based on charge and discharge characteristics plays an extremely critical role. At present, various types of batteries are widely used in many fields, from daily electronic devices to large-scale application scenarios such as electric vehicles and energy storage systems. Different types of batteries, such as lithium-ion batteries, lead-acid batteries, nickel-metal hydride batteries, etc., have significant differences in their charge and discharge characteristics. By analyzing the characteristics of the battery during the charge and discharge process, such as voltage, current, time, and capacity changes, the battery type can be accurately identified, and key parameters such as the battery's health status and remaining capacity can be effectively detected. This detection method based on charge and discharge characteristics can not only provide a basis for the rational use of batteries, avoid equipment damage and performance degradation caused by the wrong use of battery types, but also play a core role in the battery management system, optimize the battery's charge and discharge strategy, extend the battery life, and improve energy efficiency.

[0003] Prior to the technology of the present invention, the existing battery type identification and detection methods based on charge and discharge characteristics mainly judged by monitoring the basic parameters of the battery charge and discharge process, such as the curves of voltage and current changing over time. Some methods use simple threshold comparisons to compare the voltage and current values ​​at a specific stage with pre-set standard values ​​to identify the battery type and evaluate the status. However, this method has many difficulties and key points. The difficulty lies in the fact that the charge and discharge curves of different battery types have a certain degree of similarity, especially under some working conditions, and it is very easy to cause misjudgment by simple parameter comparison alone. In addition, in actual use, the battery will be affected by various factors such as ambient temperature and charge and discharge rate, resulting in fluctuations in the charge and discharge characteristics, further increasing the difficulty of accurate identification. Summary of the invention

[0004] In view of the above problems, the present invention proposes a battery type identification and detection method and system based on charge and discharge characteristics. The battery type is judged by comprehensively considering the voltage platform, slope characteristics and jump characteristics, and a joint diagnosis is performed. The combination of multiple features can analyze from different dimensions, greatly improving the recognition accuracy, and more comprehensively and accurately distinguishing between ternary lithium, lead-acid and lithium iron phosphate batteries.

[0005] According to a first aspect of an embodiment of the present invention, a method for identifying and detecting a battery type based on charge and discharge characteristics is provided.

[0006] In one or more embodiments, preferably, the battery type identification and detection method based on charge and discharge characteristics includes: Obtain the charging and discharging information of each battery in real time; According to the charging and discharging information, a battery platform is determined, where the battery platform is one of a ternary lithium battery, a lead-acid battery, and a lithium iron phosphate battery; Calculate the slope characteristics of the current battery in real time, determine the similarity between the current battery and the preset battery type, and select the battery type with the highest similarity as the matching result; Extract and display abnormal jump information inside the battery in real time; Analyze the current state of the battery according to the changes in current and voltage, where the current state includes charging, discharging and balancing; Monitor battery temperature in real time and indicate overheating.

[0007] In one or more embodiments, preferably, the real-time acquisition of charging and discharging information of each battery specifically includes: Collect voltage and current signals during battery charging and discharging; Transmit real-time data to the data center for recording at a frequency of 10,000 times per second; Obtain the curve of battery voltage and charging current changing with time.

[0008] In one or more embodiments, preferably, the battery platform is determined according to the charge and discharge information, and the battery platform is one of a ternary lithium battery, a lead-acid battery and a lithium iron phosphate battery, specifically including: Get the voltage value of each battery; Set the acquisition window, each window includes the most recent n data points; Set m consecutive windows; The average value μ of the data in each window i and standard deviation σ i ; Setting σ max is the maximum standard deviation allowed within each window; Set E to the maximum fluctuation range of the average value allowed; Determine whether the first calculation formula is satisfied; Determining whether the second calculation formula is satisfied; If both the first calculation formula and the second calculation formula are satisfied, it is considered that the voltage value at the current moment is a platform voltage. Otherwise, the determination is continued until a platform voltage appears. If the platform voltage is between 3.6V and 4.2V, it is considered to be a ternary lithium battery charging platform. If the platform voltage is between 2.3V-2.4V, it is considered to be a lead-acid battery charging platform. If the platform voltage is between 3.2V-3.4V, it is considered to be a lithium iron phosphate battery charging platform. The first calculation formula is:

[0009] Among them, σ j is the standard deviation of the jth window, M is the total number of consecutive windows, and j is the window number; The second calculation formula is:

[0010] Among them, max() is the maximum value selection module, min() is the minimum value selection module, μ M is the average value of the data in the Mth window, and E is the maximum fluctuation range allowed for the average value.

[0011] In one or more embodiments, preferably, the real-time calculation of the slope characteristics of the current battery, and the determination of the similarity between the current battery and the preset battery type, and the selection of the battery type with the highest similarity as the matching result, specifically include: The linear regression slope is calculated by the third calculation formula; Calculating the slope similarity using a fourth calculation formula according to the linear regression slopes of the two data sets; The slope change rate is calculated using the fifth calculation formula. When the slope change rate is greater than a preset value, it is identified as the peak start time, and the maximum value of the data value after the peak start is extracted as the peak highest point; The peak height is calculated using the sixth calculation formula, Using the eighth calculation formula to determine the peak similarity between the current battery and the preset battery type; The ninth calculation formula is used to calculate the comprehensive quantitative similarity; Calculate the battery type with the highest comprehensive similarity to the current battery as the matching result; The third calculation formula is:

[0012] Where m is the linear regression slope, x i is the time point, y i is the data value, n is the data amount; The fourth calculation formula is:

[0013] Wherein, S12 is the slope similarity of the data set, and m1 and m2 are the linear regression slopes of the data set respectively; The fifth calculation formula is:

[0014] Among them, △m i is the slope change rate at the i-th data moment, x iis the i-th time point, y i is the ith data value, x i+1 is the i+1th time point, y i+1 is the i+1th data value; The sixth calculation formula is: H=max(ypeak-ybase) Among them, H is the peak height, ypeak is the highest point of the peak, and ybase is the data value at the time when the peak starts; The seventh calculation formula is: T=tend-tstart Among them, T is the duration, tend is the moment of the peak's highest point, and tstart is the peak start time; The eighth calculation formula is:

[0015] Among them, S F is the peak similarity, H1 and H2 are the peak heights of the current battery and the preset battery type, respectively, and T1 and T2 are the durations of the current battery and the preset battery type, respectively; The ninth calculation formula is: S Z =w1×S 12 +w2×S F Among them, S Z is the comprehensive similarity, w1 and w2 are the first and second weight coefficients respectively.

[0016] In one or more embodiments, preferably, the real-time extraction and display of abnormal jump information inside the battery specifically includes: Observe whether there is voltage jump in the voltage-time waveform; If the amplitude is the same or similar to the preset jump threshold, it is considered that there is a battery abnormality, and the waveform showing the abnormal jump process is marked.

[0017] In one or more embodiments, preferably, the analyzing the current state of the battery according to the change of current and voltage, wherein the current state includes charging, discharging and balancing, specifically includes: Determine that the current direction of the battery is from the outside to the inside, and the voltage continues to increase as a charging state; Determine that the current direction of the battery is from the inside to the outside, and the voltage continues to decrease as a discharge state; Other states are judged as battery balancing processes.

[0018] In one or more embodiments, preferably, the real-time temperature monitoring of the battery and prompting of overheating state specifically include: Collect the current battery temperature in real time; Get the historical battery temperature peak value; When the current battery temperature reaches the historical maximum temperature or reaches 80% of the preset battery steady-state operating maximum temperature, an overheating prompt is issued.

[0019] According to a second aspect of an embodiment of the present invention, a battery type identification and detection system based on charge and discharge characteristics is provided.

[0020] In one or more embodiments, preferably, the battery type identification and detection system based on charge and discharge characteristics includes: Data acquisition module, used to obtain the charging and discharging information of each battery in real time; A platform voltage determination module, used to determine the battery platform according to the charge and discharge information, wherein the battery platform is one of a ternary lithium battery, a lead-acid battery and a lithium iron phosphate battery; The slope characteristic analysis module is used to calculate the slope characteristic of the current battery in real time, determine the similarity between the current battery and the preset battery type, and select the battery type with the highest similarity as the matching result; Abnormal analysis module, used to extract and display abnormal jump information inside the battery in real time; The charge and discharge analysis module is used to analyze the current state of the battery according to the changes in current and voltage, where the state includes charging, discharging and balancing; The overheat analysis module is used to monitor the battery temperature in real time and prompt overheating status.

[0021] According to a third aspect of an embodiment of the present invention, there is provided a computer-readable storage medium on which computer program instructions are stored. When the computer program instructions are executed by a processor, the method as described in any one of the first aspect of the embodiment of the present invention is implemented.

[0022] According to a fourth aspect of an embodiment of the present invention, there is provided an electronic device, comprising a memory and a processor, wherein the memory is used to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement any one of the methods described in the first aspect of the embodiment of the present invention.

[0023] The technical solution provided by the embodiments of the present invention may have the following beneficial effects: In the solution of the present invention, the standardized slope calculation makes the comparison of charging and discharging slopes of different batteries more scientific and reliable, and provides a quantitative basis for judging the battery type.

[0024] In the solution of the present invention, the corresponding rules between current battery characteristics and types are effectively learned and analyzed to improve recognition accuracy and stability.

[0025] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0026] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 The present invention is a flowchart of a method for identifying and detecting battery types based on charge and discharge characteristics according to an embodiment of the present invention.

[0029] Figure 2 The present invention is a flowchart of obtaining the charging and discharging information of each battery in real time in a battery type identification and detection method based on charging and discharging characteristics according to an embodiment of the present invention.

[0030] Figure 3 It is a flow chart of a battery type identification and detection method based on charge and discharge characteristics in an embodiment of the present invention, in which a battery platform is determined according to the charge and discharge information, and the battery platform is one of a ternary lithium battery, a lead-acid battery and a lithium iron phosphate battery.

[0031] Figure 4 It is a flowchart of a battery type identification and detection method based on charge and discharge characteristics in an embodiment of the present invention, which calculates the slope characteristics of the current battery in real time, determines the similarity between the current battery and the preset battery type, and selects the battery type with the highest similarity as the matching result.

[0032] Figure 5 The present invention is a flowchart showing the real-time extraction of abnormal jump information inside a battery in a battery type identification and detection method based on charge and discharge characteristics in one embodiment of the present invention.

[0033] Figure 6The present invention discloses a method for identifying and detecting battery types based on charge and discharge characteristics in accordance with an embodiment of the present invention, which analyzes the current state of the battery according to the changes in current and voltage, wherein the current state includes a flowchart of charging, discharging and balancing.

[0034] Figure 7 The present invention is a flowchart of a method for identifying and detecting battery types based on charge and discharge characteristics, for real-time monitoring of battery temperature and prompting of overheating.

[0035] Figure 8 It is a structural diagram of a battery type identification and detection system based on charge and discharge characteristics according to an embodiment of the present invention.

[0036] Fig. 9 It is a structural diagram of an electronic device in one embodiment of the present invention. DETAILED DESCRIPTION

[0037] In some of the processes described in the specification and claims of the present invention and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit the "first" and "second" to be different types.

[0038] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0039] In the field of battery detection, battery type identification and detection based on charge and discharge characteristics plays an extremely critical role. At present, various types of batteries are widely used in many fields, from daily electronic devices to large-scale application scenarios such as electric vehicles and energy storage systems. Different types of batteries, such as lithium-ion batteries, lead-acid batteries, nickel-metal hydride batteries, etc., have significant differences in their charge and discharge characteristics. By analyzing the characteristics of the battery during the charge and discharge process, such as voltage, current, time, and capacity changes, the battery type can be accurately identified, and key parameters such as the battery's health status and remaining capacity can be effectively detected. This detection method based on charge and discharge characteristics can not only provide a basis for the rational use of batteries, avoid equipment damage and performance degradation caused by the wrong use of battery types, but also play a core role in the battery management system, optimize the battery's charge and discharge strategy, extend the battery life, and improve energy efficiency.

[0040] Prior to the technology of the present invention, the existing battery type identification and detection methods based on charge and discharge characteristics mainly judged by monitoring the basic parameters of the battery charge and discharge process, such as the curves of voltage and current changing over time. Some methods use simple threshold comparisons to compare the voltage and current values ​​at a specific stage with pre-set standard values ​​to identify the battery type and evaluate the status. However, this method has many difficulties and key points. The difficulty lies in the fact that the charge and discharge curves of different battery types have a certain degree of similarity, especially under some working conditions, and it is very easy to cause misjudgment by simple parameter comparison alone. In addition, in actual use, the battery will be affected by various factors such as ambient temperature and charge and discharge rate, resulting in fluctuations in the charge and discharge characteristics, further increasing the difficulty of accurate identification.

[0041] In the embodiment of the present invention, a battery type identification and detection method and system based on charge and discharge characteristics are provided. The solution judges the battery type by integrating the voltage platform, slope characteristics and jump characteristics, and performs joint diagnosis. The combination of multiple characteristics can analyze from different dimensions, greatly improve the identification accuracy, and more comprehensively and accurately distinguish ternary lithium, lead-acid and lithium iron phosphate batteries.

[0042] According to a first aspect of an embodiment of the present invention, a method for identifying and detecting a battery type based on charge and discharge characteristics is provided.

[0043] Figure 1 The present invention is a flowchart of a method for identifying and detecting battery types based on charge and discharge characteristics according to an embodiment of the present invention.

[0044] In one or more embodiments, preferably, the battery type identification and detection method based on charge and discharge characteristics includes: S101, acquiring charging and discharging information of each battery in real time; S102, determining a battery platform according to the charge and discharge information, wherein the battery platform is one of a ternary lithium battery, a lead-acid battery, and a lithium iron phosphate battery; S103, calculating the slope characteristics of the current battery in real time, and determining the similarity between the current battery and a preset battery type, and selecting the battery type with the highest similarity as a matching result; S104, extracting abnormal jump information inside the battery in real time and displaying it; S105, analyzing the current state of the battery according to the changes in current and voltage, wherein the current state includes charging, discharging and balancing; S106: Monitor the battery temperature in real time and indicate an overheating state.

[0045] In the embodiment of the present invention, waveform data collection is first performed, then the platform voltage is determined, and then the slope characteristic analysis and the jump characteristic analysis are completed, and finally the comprehensive characteristic judgment is completed.

[0046] Figure 2 The present invention is a flowchart of obtaining the charging and discharging information of each battery in real time in a battery type identification and detection method based on charging and discharging characteristics according to an embodiment of the present invention.

[0047] like Figure 2 As shown, in one or more embodiments, preferably, the real-time acquisition of charging and discharging information of each battery specifically includes: S201, collecting voltage and current signals during battery charging and discharging; S202, transmitting the real-time data to the data center for recording at a frequency of 10,000 times per second; S203: Obtain a curve showing the battery voltage and charging current changing with time.

[0048] In an embodiment of the present invention, the following method is used to realize the collection, transmission and curve acquisition of battery-related data. First, the voltage and current signals of the battery charging and discharging process are collected by connecting a high-precision voltage sensor and a current sensor to the battery charging and discharging circuit. These sensors convert the collected analog signals into digital signals. Then, the real-time data is transmitted to the data center for recording at a frequency of 10,000 times per second using a data transmission module. The data transmission module can use an Ethernet transmission module or a specific wireless transmission module, and by configuring the corresponding parameters, it is ensured that the data can be stably transmitted to the server of the data center at a specified frequency. After the data center receives the data, it uses data analysis software to process the data. The software finally obtains a curve of the battery voltage and charging current changing with time by drawing the voltage data and current data in the time series, for example, with time as the horizontal axis, voltage and current as the vertical axis, respectively, to draw a clear and intuitive curve.

[0049] Figure 3 It is a flow chart of a battery type identification and detection method based on charge and discharge characteristics in an embodiment of the present invention, in which a battery platform is determined according to the charge and discharge information, and the battery platform is one of a ternary lithium battery, a lead-acid battery and a lithium iron phosphate battery.

[0050] like Figure 3 As shown, in one or more embodiments, preferably, the battery platform is determined according to the charge and discharge information, and the battery platform is one of a ternary lithium battery, a lead-acid battery and a lithium iron phosphate battery, specifically including: S301, obtaining the voltage value of each battery, setting a collection window, each window including the most recent n data points; S302, set m continuous windows, the average value μi and standard deviation σi of the data in each window; S303, setting σmax to the maximum standard deviation allowed in each window; S304, setting E to the maximum fluctuation range of the average value allowed; S305, determining whether the first calculation formula is satisfied; S306, determining whether the second calculation formula is satisfied; S307, if the first calculation formula and the second calculation formula are satisfied at the same time, it is considered that the voltage value at the current moment is a platform voltage, otherwise, the determination is continued until a platform voltage appears; S308. If the platform voltage is between 3.6V and 4.2V, it is considered to be a ternary lithium battery charging platform. If the platform voltage is between 2.3V-2.4V, it is considered to be a lead-acid battery charging platform. If the platform voltage is between 3.2V-3.4V, it is considered to be a lithium iron phosphate battery charging platform. The first calculation formula is:

[0051] Among them, σ j is the standard deviation of the jth window, M is the total number of consecutive windows, and j is the window number; The second calculation formula is:

[0052] Among them, max() is the maximum value selection module, min() is the minimum value selection module, μ M is the average value of the data in the Mth window, and E is the maximum fluctuation range allowed for the average value.

[0053] In an embodiment of the present invention, after completing the voltage and current signal acquisition, real-time temperature monitoring and other operations during the battery charging and discharging process, the platform type of the battery is determined based on the acquired charging and discharging information, and the battery platform types include ternary lithium batteries, lead-acid batteries and lithium iron phosphate batteries. First, the data center continuously obtains the voltage value of each battery. In order to facilitate the analysis of the characteristics of the voltage data, an acquisition window is set, and each window contains the most recent n data points. For example, n is 10, that is, each window contains the most recent 10 voltage data points. At the same time, m continuous windows are set, such as m is 5, which means that there are 5 continuous windows for subsequent analysis. For the data in each window, the mean value and standard deviation are calculated. For example, for the first window, 10 voltage data are added and divided by 10 to obtain the mean value, and then the standard deviation of the window is calculated according to the calculation formula of the standard deviation. By analogy, the mean value and standard deviation of each window are calculated. It is pre-set to the maximum standard deviation allowed in each window. The value can be determined according to the characteristics of the battery and a large amount of experimental data. It is assumed that the maximum fluctuation range of the mean value is set, and the example value is 0.03. Next, determine whether the first and second calculation formulas are satisfied. If both formulas are satisfied, the voltage value at the current moment is considered to be a platform voltage. According to the obtained platform voltage, the platform type of the battery is determined. If the platform voltage is between 3.6V and 4.2V, the battery is considered to be a ternary lithium battery charging platform; if the platform voltage is between 2.3V - 2.4V, it is considered to be a lead-acid battery charging platform; if the platform voltage is between 3.2V -3.4V, it is considered to be a lithium iron phosphate battery charging platform. For example, after calculation, the platform voltage is 3.8V. Since 3.6V<3.8V<4.2V, it can be determined that the battery is a ternary lithium battery. Through the above steps, using the collected battery charging and discharging information, after data processing and formula judgment, the platform type of the battery can be accurately determined.

[0054] Figure 4 It is a flowchart of a battery type identification and detection method based on charge and discharge characteristics in an embodiment of the present invention, which calculates the slope characteristics of the current battery in real time, determines the similarity between the current battery and the preset battery type, and selects the battery type with the highest similarity as the matching result.

[0055] like Figure 4 As shown, in one or more embodiments, preferably, the real-time calculation of the slope characteristics of the current battery, and the determination of the similarity between the current battery and the preset battery type, and the selection of the battery type with the highest similarity as the matching result, specifically include: S401, calculating the linear regression slope by a third calculation formula; S402, calculating the slope similarity using a fourth calculation formula according to the linear regression slopes of the two data sets; S403, using the fifth calculation formula to calculate the slope change rate, when the slope change rate is greater than a preset value, it is identified as the peak start time, and the maximum value of the data value after the peak start is extracted as the peak highest point; S404, using the sixth calculation formula to calculate the peak height, S405, using the eighth calculation formula to determine the peak similarity between the current battery and the preset battery type; S406, calculating the comprehensive quantitative similarity using the ninth calculation formula; S407, calculating the battery type with the highest comprehensive similarity to the current battery as a matching result; The third calculation formula is:

[0056] Where m is the linear regression slope, x i is the time point, y i is the data value, n is the data amount; The fourth calculation formula is:

[0057] Wherein, S12 is the slope similarity of the data set, and m1 and m2 are the linear regression slopes of the data set respectively; The fifth calculation formula is:

[0058] Among them, △m i is the slope change rate at the i-th data moment, x i is the i-th time point, y i is the ith data value, x i+1 is the i+1th time point, y i+1 is the i+1th data value; The sixth calculation formula is: H=max(ypeak-ybase) Among them, H is the peak height, ypeak is the highest point of the peak, and ybase is the data value at the time when the peak starts; The seventh calculation formula is: T=tend-tstart Among them, T is the duration, tend is the moment of the peak's highest point, and tstart is the peak start time; The eighth calculation formula is:

[0059] Among them, S F is the peak similarity, H1 and H2 are the peak heights of the current battery and the preset battery type, respectively, and T1 and T2 are the durations of the current battery and the preset battery type, respectively; The ninth calculation formula is: S Z =w1×S 12 +w2×S F Among them, S Z is the comprehensive similarity, w1 and w2 are the first and second weight coefficients respectively.

[0060] In an embodiment of the present invention, after completing the voltage and current signal acquisition during the battery charging and discharging process and transmitting the real-time data to the data center for recording, the slope characteristics of the current battery are calculated in real time and the similarity with the preset battery type is determined. First, for the data set of the current battery, the linear regression slope is calculated using the third calculation formula, where xi represents the time point, yi represents the data value (here the data value can be a voltage value or a current value), and n is the amount of data. For example, 100 voltage data are collected within a certain period of time, and the linear regression slope can be calculated by substituting these data into the above formula. Next, the slope similarity between the current battery data set and another data set (which can be a corresponding data set of a preset battery type) is calculated according to the fourth calculation formula, where m1 and m2 are the linear regression slopes of the two data sets, respectively. Afterwards, the slope change rate is calculated using the fifth calculation formula, where xi is the i-th time point, yi is the i-th data value, x{i + 1} is the (i + 1)th time point, and y{i + 1} is the (i + 1)th data value. When the calculated slope change rate is greater than a preset value (for example, the preset value is 0.5, which can be determined based on actual experience and research), it is determined that this is the peak start time. Subsequently, the maximum value of the data value after the peak start is extracted as the peak peak, and then the peak height is calculated according to the sixth calculation formula, where ypeak is the peak peak and ybase is the data value at the peak start time. The duration is calculated using the seventh calculation formula, and tend is the moment of the peak peak. Then, the peak similarity between the current battery and the preset battery type is calculated using the eighth calculation formula. Finally, the comprehensive quantitative similarity is calculated using the ninth calculation formula, where w1 and w2 are the first and second weight coefficients respectively (for example, w1 = 0.6, w2 = 0.4, and the weight coefficients also need to be determined according to the actual situation and research purpose). The above calculation process is performed on multiple preset battery types, and the comprehensive similarities obtained are compared, and the preset battery type with the highest comprehensive similarity is used as the matching result of the current battery.

[0061] Figure 5The present invention is a flowchart showing the real-time extraction of abnormal jump information inside a battery in a battery type identification and detection method based on charge and discharge characteristics in one embodiment of the present invention.

[0062] like Figure 5 As shown, in one or more embodiments, preferably, the real-time extraction of abnormal jump information inside the battery and display thereof specifically includes: S501, observe whether there is a voltage jump phenomenon in the voltage-time waveform; S502: If the amplitude is the same as or close to the preset jump threshold, it is considered that there is a battery abnormality, and the waveform showing the abnormal jump process is marked.

[0063] In an embodiment of the present invention, in terms of abnormal jump information extraction, after the data center receives the real-time voltage-time waveform data, it uses special signal analysis software to monitor the waveform in real time. In specific operations, the voltage values ​​on the voltage-time waveform are read in sequence at extremely short time intervals (e.g., 0.0001 seconds). A jump threshold is pre-set, assuming it is 0.3 volts (this value can be reasonably set based on the specifications, performance parameters, and a large amount of experimental data of the battery). During the reading process, the voltage value at the current moment is compared with the voltage value at the previous moment, and the absolute value of the difference between the two is calculated. If the absolute value is equal to or close to the pre-set jump threshold, such as within the range of 0.28 volts to 0.32 volts, it is determined that there is an abnormal voltage jump phenomenon in the battery. Once it is determined that there is an abnormal jump, the software will immediately mark and display the waveform of the abnormal jump process. There are many ways to mark and display, such as setting the color of the waveform line of the abnormal jump part to a striking red, and adding text annotations at the corresponding position of the waveform to indicate the specific time and approximate amplitude of the abnormal jump; or popping up a small window next to the waveform to display detailed information about the abnormal jump, including the time when the abnormality occurred, the voltage value before and after the jump, etc., so that relevant personnel can quickly and accurately understand the abnormal situation of the battery and take appropriate measures to deal with it in time.

[0064] Figure 6 The present invention discloses a method for identifying and detecting battery types based on charge and discharge characteristics in accordance with an embodiment of the present invention, which analyzes the current state of the battery according to the changes in current and voltage, wherein the current state includes a flowchart of charging, discharging and balancing.

[0065] like Figure 6 As shown, in one or more embodiments, preferably, the current state of the battery is analyzed according to the change of current and voltage, wherein the current state includes charging, discharging and balancing, specifically including: S601, determining that the current direction of the battery is from the outside to the inside, and the voltage continues to increase as a charging state; S602, determining that the current direction of the battery is from the inside to the outside, and the voltage continues to decrease, which is a discharge state; S603: Determine whether the other status is a battery balancing process.

[0066] In an embodiment of the present invention, the analysis of the battery status relies on the voltage and current signals collected during the battery charging and discharging process, and these signals are transmitted to the data center at a frequency of 10,000 times per second for recording. The data center uses high-precision current sensors and voltage sensors to obtain the current and voltage data of the battery in real time, providing a basis for accurately judging the battery status. When the current sensor detects that the current direction is flowing from the outside to the inside of the battery, the analysis system of the data center will continuously monitor the voltage data. The system will compare the voltage values ​​of adjacent time points in chronological order within a set time period (for example, 10 seconds). If the voltage value of each subsequent time point is greater than the voltage value of the previous time point during this time period, and the voltage increase is within a reasonable range (for example, each increase does not exceed 0.1 volt), it is determined that the battery is in a charging state. For example, within a certain 10 seconds, the voltage values ​​are recorded as 3.2V, 3.22V, 3.24V, 3.26V, etc., and the current direction is flowing from the outside to the inside of the battery. At this time, it can be determined that the battery is charging. If the current sensor detects that the current direction is from the inside of the battery to the outside, the analysis system will also continuously monitor the voltage data. In the set 10-second time period, the voltage values ​​at adjacent time points are compared. If the voltage value at each subsequent time point is less than the voltage value at the previous time point, and the voltage drop is within a reasonable range (for example, each drop does not exceed 0.1 volt), the battery is determined to be in a discharging state. For example, if the voltage values ​​recorded within 10 seconds are 3.8V, 3.78V, 3.76V, 3.74V, etc., and the current direction is flowing out of the battery, it can be determined that the battery is discharging. When the current and voltage changes of the battery neither meet the judgment conditions of the charging state nor the judgment conditions of the discharge state, it is determined that the battery is in the balancing process. For example, the current direction is unstable, sometimes flowing from the outside to the inside, and sometimes from the inside to the outside for a period of time; or the voltage value does not show a trend of continuous increase or decrease, but fluctuates within a smaller range (such as the voltage value fluctuates between 3.5V and 3.55V), then it can be determined that the battery is in the balancing process. Through the above real-time monitoring and analysis of current and voltage changes, the current state of the battery can be accurately determined, providing an important basis for the scientific management and maintenance of the battery, ensuring the safe and stable operation of the battery.

[0067] Figure 7The present invention is a flowchart of a method for identifying and detecting battery types based on charge and discharge characteristics, for real-time monitoring of battery temperature and prompting of overheating.

[0068] like Figure 7 As shown, in one or more embodiments, preferably, the real-time temperature monitoring of the battery and prompting of the overheating state specifically include: S701, collecting the current battery temperature in real time; S702, obtaining a historical battery temperature peak value; S703: When the current battery temperature reaches the historical maximum temperature or reaches 80% of the preset battery steady-state maximum temperature, an overheating prompt is issued.

[0069] In an embodiment of the present invention, after completing the voltage and current signal acquisition, transmission and related data processing during the battery charging and discharging process, including slope feature calculation, abnormal jump information extraction and battery status analysis, it is also necessary to monitor the battery temperature in real time and prompt the overheating state. While receiving the real-time voltage and current data, the data center collects the current temperature of the battery in real time through a high-precision temperature sensor. The temperature sensor must have the characteristics of fast response and high-precision measurement to ensure that the subtle changes in the battery temperature can be accurately captured. In order to perform effective temperature monitoring, the system will record and store the historical temperature data of the battery. After each new temperature data is collected, the system will automatically update the historical data record. By analyzing the historical data, the historical battery temperature peak value can be obtained. The system pre-sets a maximum steady-state operating temperature of the battery, which can be reasonably determined based on the battery specifications, performance parameters and a large amount of experimental data. For example, for a certain model of battery, after multiple experiments and tests, it is determined that its maximum steady-state operating temperature is 60°C. During the real-time monitoring process, the system will continuously compare the currently collected battery temperature with the historical temperature peak and 80% of the preset maximum steady-state operating temperature of the battery. Once the current battery temperature reaches the historical maximum temperature, or reaches 80% of the preset battery steady-state maximum temperature (i.e. 60°C × 80% = 48°C), the system will immediately issue an overheating warning. The overheating warning can be diversified to ensure that relevant personnel can be informed of the battery overheating in a timely manner. For example, the system can pop up a striking red warning box on the monitoring interface of the data center, and the box displays a text message "Battery overheating, please deal with it in time"; at the same time, the system can also trigger a sound alarm, emitting a loud and continuous alarm sound; in addition, the overheating information can be sent to the mobile phone or mailbox of the relevant personnel by SMS or email, so that they can obtain information in time and take corresponding measures even if they are not at the monitoring site, such as adjusting the battery charging and discharging parameters, dissipating the heat of the battery, etc., so as to ensure the safe and stable operation of the battery.

[0070] According to a second aspect of an embodiment of the present invention, a battery type identification and detection system based on charge and discharge characteristics is provided.

[0071] Figure 8 It is a structural diagram of a battery type identification and detection system based on charge and discharge characteristics according to an embodiment of the present invention.

[0072] In one or more embodiments, preferably, the battery type identification and detection system based on charge and discharge characteristics includes: The data acquisition module 801 is used to obtain the charging and discharging information of each battery in real time; A platform voltage determination module 802, for determining a battery platform according to the charge and discharge information, wherein the battery platform is one of a ternary lithium battery, a lead-acid battery and a lithium iron phosphate battery; The slope characteristic analysis module 803 is used to calculate the slope characteristic of the current battery in real time, determine the similarity between the current battery and the preset battery type, and select the battery type with the highest similarity as the matching result; The abnormal analysis module 804 is used to extract and display the abnormal jump information inside the battery in real time; The charge and discharge analysis module 805 is used to analyze the current state of the battery according to the change of current and voltage, wherein the current state includes charging, discharging and balancing; The overheat analysis module 806 is used to monitor the temperature of the battery in real time and prompt the overheat state.

[0073] In the embodiment of the present invention, a system suitable for different structures is realized through a series of modular designs. The system can achieve closed-loop, reliable and efficient execution through collection, analysis and control.

[0074] According to a third aspect of an embodiment of the present invention, there is provided a computer-readable storage medium on which computer program instructions are stored. When the computer program instructions are executed by a processor, the method as described in any one of the first aspect of the embodiment of the present invention is implemented.

[0075] According to a fourth aspect of an embodiment of the present invention, an electronic device is provided. Fig. 9 It is a structural diagram of an electronic device in one embodiment of the present invention. Fig. 9The electronic device shown is a battery type identification and detection device based on charge and discharge characteristics, which includes a general computer hardware structure, which at least includes a processor 901 and a memory 902. The processor 901 and the memory 902 are connected via a bus 903. The memory 902 is suitable for storing instructions or programs executable by the processor 901. The processor 901 can be an independent microprocessor or a collection of one or more microprocessors. Thus, the processor 901 executes the instructions stored in the memory 902 to execute the method flow of the embodiment of the present invention as described above to realize data processing and control of other devices. The bus 903 connects the above-mentioned multiple components together, and at the same time connects the above-mentioned components to the display controller 904 and the display device and the input / output (I / O) device 905. The input / output (I / O) device 905 can be a mouse, a keyboard, a modem, a network interface, a touch input device, a somatosensory input device, a printer, and other devices known in the art. Typically, the input / output device 905 is connected to the system through an input / output (I / O) controller 906.

[0076] The technical solution provided by the embodiments of the present invention may have the following beneficial effects: In the solution of the present invention, the standardized slope calculation makes the comparison of charging and discharging slopes of different batteries more scientific and reliable, and provides a quantitative basis for judging the battery type.

[0077] In the solution of the present invention, the corresponding rules between current battery characteristics and types are effectively learned and analyzed to improve recognition accuracy and stability.

[0078] It should be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program codes.

[0079] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1A device that provides the functions specified in a block or multiple blocks.

[0080] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0081] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0082] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A battery type identification and detection method based on charge and discharge characteristics, characterized in that: The method includes: Get the charging and discharging information of each battery in real time; According to the charging and discharging information, a battery platform is determined, where the battery platform is one of a ternary lithium battery, a lead-acid battery, and a lithium iron phosphate battery; Calculate the slope characteristics of the current battery in real time, determine the similarity between the current battery and the preset battery type, and select the battery type with the highest similarity as the matching result; Extract and display abnormal jump information inside the battery in real time; Analyze the current state of the battery according to the changes in current and voltage, where the current state includes charging, discharging and balancing; Monitor battery temperature in real time and indicate overheating.

2. A battery type identification and detection method based on charge and discharge characteristics as claimed in claim 1, characterized in that: The real-time acquisition of charging and discharging information of each battery specifically includes: Collect voltage and current signals during battery charging and discharging; Transmit real-time data to the data center for recording at a frequency of 10,000 times per second; Obtain the curve of battery voltage and charging current changing with time.

3. A battery type identification and detection method based on charge and discharge characteristics as claimed in claim 1, characterized in that: The battery platform is determined according to the charge and discharge information, and the battery platform is one of a ternary lithium battery, a lead-acid battery and a lithium iron phosphate battery, specifically including: Get the voltage value of each battery; Set the acquisition window, each window includes the most recent n data points; Set m consecutive windows; The average value μ of the data in each window i and standard deviation σ i ; Setting σ max is the maximum standard deviation allowed within each window; Set E to the maximum fluctuation range of the average value allowed; Determine whether the first calculation formula is satisfied; Determining whether the second calculation formula is satisfied; If both the first calculation formula and the second calculation formula are satisfied, it is considered that the voltage value at the current moment is a platform voltage. Otherwise, the determination is continued until a platform voltage appears. If the platform voltage is between 3.6V and 4.2V, it is considered to be a ternary lithium battery charging platform. If the platform voltage is between 2.3V-2.4V, it is considered to be a lead-acid battery charging platform. If the platform voltage is between 3.2V-3.4V, it is considered to be a lithium iron phosphate battery charging platform. The first calculation formula is: ； Among them, σ j is the standard deviation of the jth window, M is the total number of consecutive windows, and j is the window number; The second calculation formula is: ； Among them, max() is the maximum value selection module, min() is the minimum value selection module, μ M is the average value of the data in the Mth window, and E is the maximum fluctuation range allowed for the average value.

4. A battery type identification and detection method based on charge and discharge characteristics as claimed in claim 1, characterized in that: The real-time calculation of the slope characteristics of the current battery, and the determination of the similarity between the current battery and the preset battery type, and the selection of the battery type with the highest similarity as the matching result specifically include: The linear regression slope is calculated by the third calculation formula; Calculating the slope similarity using a fourth calculation formula according to the linear regression slopes of the two data sets; The slope change rate is calculated using the fifth calculation formula. When the slope change rate is greater than a preset value, it is identified as the peak start time, and the maximum value of the data value after the peak start is extracted as the peak highest point; The peak height is calculated using the sixth calculation formula, Using the eighth calculation formula to determine the peak similarity between the current battery and the preset battery type; The ninth calculation formula is used to calculate the comprehensive quantitative similarity; Calculate the battery type with the highest comprehensive similarity to the current battery as the matching result; The third calculation formula is: ； Where m is the linear regression slope, x i is the time point, y i is the data value, n is the data amount; The fourth calculation formula is: ； Wherein, S12 is the slope similarity of the data set, and m1 and m2 are the linear regression slopes of the data set respectively; The fifth calculation formula is: ； Among them, △m i is the slope change rate at the i-th data moment, x i is the i-th time point, y i is the ith data value, x i+1 is the i+1th time point, y i+1 is the i+1th data value; The sixth calculation formula is: H=max(ypeak-ybase) Among them, H is the peak height, ypeak is the highest point of the peak, and ybase is the data value at the time when the peak starts; The seventh calculation formula is: T=tend-tstart Among them, T is the duration, tend is the moment of the peak's highest point, and tstart is the peak start time; The eighth calculation formula is: ； Among them, S F is the peak similarity, H1 and H2 are the peak heights of the current battery and the preset battery type, respectively, and T1 and T2 are the durations of the current battery and the preset battery type, respectively; The ninth calculation formula is: S Z =w1×S 12 +w2×S F Among them, S Z is the comprehensive similarity, w1 and w2 are the first and second weight coefficients respectively.

5. A battery type identification and detection method based on charge and discharge characteristics as claimed in claim 1, characterized in that: The real-time extraction and display of abnormal jump information inside the battery specifically includes: Observe whether there is voltage jump in the voltage-time waveform; If the amplitude is the same or similar to the preset jump threshold, it is considered that there is a battery abnormality, and the waveform showing the abnormal jump process is marked.

6. A battery type identification and detection method based on charge and discharge characteristics as claimed in claim 1, characterized in that: The current state of the battery is analyzed according to the change of current and voltage, wherein the current state includes charging, discharging and balancing, specifically including: Determine that the current direction of the battery is from the outside to the inside, and the voltage continues to increase as a charging state; Determine that the current direction of the battery is from the inside to the outside, and the voltage continues to decrease as a discharge state; Other states are judged as battery balancing processes.

7. A battery type identification and detection method based on charge and discharge characteristics as claimed in claim 1, characterized in that: The real-time temperature monitoring of the battery and the prompting of overheating state specifically include: Collect the current battery temperature in real time; Get the historical battery temperature peak value; When the current battery temperature reaches the historical maximum temperature or reaches 80% of the preset battery steady-state operating maximum temperature, an overheating prompt is issued.

8. A battery type identification and detection system based on charge and discharge characteristics, characterized in that: The system is used to implement the method according to any one of claims 1 to 7, and the system comprises: Data acquisition module, used to obtain the charging and discharging information of each battery in real time; A platform voltage determination module, used to determine the battery platform according to the charge and discharge information, wherein the battery platform is one of a ternary lithium battery, a lead-acid battery and a lithium iron phosphate battery; The slope characteristic analysis module is used to calculate the slope characteristic of the current battery in real time, determine the similarity between the current battery and the preset battery type, and select the battery type with the highest similarity as the matching result; Abnormal analysis module, used to extract and display abnormal jump information inside the battery in real time; The charge and discharge analysis module is used to analyze the current state of the battery according to the changes in current and voltage, where the state includes charging, discharging and balancing; The overheat analysis module is used to monitor the battery temperature in real time and prompt overheating status.

9. A computer-readable storage medium storing computer program instructions, characterized in that: The computer program instructions implement the method according to any one of claims 1 to 7 when executed by a processor.

10. An electronic device comprising a memory and a processor, characterized in that: The memory is used to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method according to any one of claims 1-7.

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