Method and system for evaluating health state of lead storage battery

Abstract

The invention discloses a method and system for evaluating the health state of a lead storage battery, and relates to the technical field of storage batteries. According to the evaluation method and system for the health state of the lead storage battery, factory health data of the lead storage battery are obtained and analyzed, a factory health evaluation value of the lead storage battery is obtained, and a health state threshold value of the lead storage battery is determined; obtaining the current health state data of the lead storage battery, and judging the health state of the lead storage battery based on the current health state data of the lead storage battery and the health state threshold value of the lead storage battery; if yes, the lead storage battery is healthy; potential problems of the battery can be accurately judged through comparison of health state thresholds and scoring of abnormal mode data; a comprehensive health state evaluation system is provided, the safety of the battery is guaranteed, and the problem that the health state of the battery is often inconvenient to comprehensively evaluate because the health state of the lead storage battery is judged only by a single parameter in the conventional health state evaluation of the lead storage battery is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of storage batteries, and in particular to a method and system for evaluating the health status of a lead storage battery. Background Art

[0002] As the power system of society gradually develops, the use of lead-acid batteries is becoming more and more widespread. Lead-acid batteries are widely used as uninterruptible power supplies in key equipment such as hospitals, data centers, communication base stations, etc., to ensure instantaneous power support when the main power fails, thereby ensuring the stable operation of the system. As the lead-acid battery is used for a longer time, its performance will gradually decay. Battery performance degradation may lead to overcharging or over-discharging, and in extreme cases may cause safety hazards such as battery overheating, expansion, leakage, and even explosion. By evaluating the health status of the battery, potential safety risks can be discovered early to prevent accidents.

[0003] Existing lead-acid battery health status assessment usually relies on only a single parameter to judge the health status of the lead-acid battery, which is often inconvenient to comprehensively assess the health status of the battery. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a method and system for evaluating the health status of a lead-acid battery, which solves the problem that the existing lead-acid battery health status assessment usually relies on only a single parameter to judge the health status of the lead-acid battery, which is often inconvenient to comprehensively assess the health status of the battery.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a method for evaluating the health status of a lead-acid battery, comprising the following steps: obtaining the factory health data of the lead-acid battery, analyzing the factory health data of the lead-acid battery, obtaining the factory health assessment value of the lead-acid battery, and determining the health status threshold of the lead-acid battery; obtaining the current health status data of the lead-acid battery, and judging the health status of the lead-acid battery based on the current health status data of the lead-acid battery combined with the health status threshold of the lead-acid battery; if the lead-acid battery is judged to be healthy, continuing to obtain the current health status data of the lead-acid battery, and re-judging the health status of the lead-acid battery; if the lead-acid battery is judged to be unhealthy, obtaining the abnormal mode data of the lead-acid battery, and scoring the abnormal level of the lead-acid battery based on the abnormal mode data of the battery; if the abnormal level score is a high level, issuing an abnormal state warning; if the abnormal level score is a low level, issuing an abnormal state delayed warning.

[0006] Furthermore, the factory health data of the lead-acid battery is analyzed to obtain the factory health assessment value of the lead-acid battery, and determine the health status threshold of the lead-acid battery. The specific analysis process is: obtaining the factory parameter health data of the lead-acid battery, the factory parameter health data of the lead-acid battery includes a parameterized initial internal resistance, a parameterized voltage stability and a parameterized maximum charge and discharge efficiency; determining the factory health assessment value of the lead-acid battery based on the factory health data of the lead-acid battery and the factory parameter health data of the lead-acid battery, the factory health data of the lead-acid battery includes an initial internal resistance, voltage stability and maximum charge and discharge efficiency; storing the factory health assessment value of the lead-acid battery as a designated label, comparing the designated label with each set label stored in a database one by one, determining the set label that is the same as the designated label, and obtaining the health status threshold of the lead-acid battery corresponding to the set label stored in the database.

[0007] Further, the health status of the lead-acid battery is judged based on the current health status data of the lead-acid battery in combination with the health status threshold of the lead-acid battery, and the specific analysis process is: obtaining the current health status parameter data of the lead-acid battery, the current health status parameter data of the lead-acid battery includes the battery voltage parameter data, the parameter internal resistance change rate and the parameter battery own temperature; obtaining the lead-acid battery health status allowable deviation data, the lead-acid battery health status allowable deviation data includes the battery voltage allowable deviation value and the battery operating temperature allowable deviation value; determining the current health status assessment value of the lead-acid battery based on the current health status data of the lead-acid battery, the current health status parameter data of the lead-acid battery and the lead-acid battery health status allowable deviation data, the lead-acid battery current health status data includes the current battery voltage, the internal resistance change rate and the battery own temperature; judging whether the current health status assessment value of the lead-acid battery is greater than the health status threshold of the lead-acid battery; if the current health status assessment value of the lead-acid battery is greater than the health status threshold of the lead-acid battery, judging that the lead-acid battery is unhealthy; if the current health status assessment value of the lead-acid battery is not greater than the health status threshold of the lead-acid battery, judging that the lead-acid battery is healthy.

[0008] Furthermore, the lead-acid battery health state allowable deviation data is obtained, and the specific analysis process is as follows: the external ambient temperature and the battery discharge rate are obtained, and the combination is marked as the lead-acid battery health state deviation influence data; a health state deviation influence matching data set stored in a database is obtained, and the health state deviation influence matching data set includes multiple health state deviation influence matching data, and the health state deviation influence matching data includes an external ambient temperature matching value and a battery discharge rate matching value; the lead-acid battery health state deviation influence data is compared with each health state deviation influence matching data stored in the database one by one to determine the minimum lead-acid battery health state comparison value; based on the minimum lead-acid battery health state comparison value, the closest health state deviation influence matching data is determined, and the lead-acid battery health state allowable deviation data corresponding to the closest health state deviation influence matching data is obtained from the database.

[0009] Furthermore, the calculation formula of the current health status assessment value of the lead-acid battery is:

[0010]

[0011] Wherein, HB is the current health status assessment value of the lead-acid battery, sA is the current battery voltage, cA is the battery voltage parameter data, ΔsA is the allowable deviation value of the battery voltage, sB is the battery operating temperature, cB is the parameterized battery operating temperature, ΔsB is the allowable deviation value of the battery operating temperature, sD is the internal resistance change rate, cD is the parameterized internal resistance change rate, and e is a natural constant.

[0012] Furthermore, an abnormality level score is performed on the lead-acid battery based on the battery abnormal mode data, and the specific analysis process is as follows: obtaining the battery abnormal mode parameter data, the battery abnormal mode parameter data including a parameterized voltage fluctuation amplitude, a parameterized temperature rise rate and a parameterized internal resistance change rate; determining the battery abnormal mode evaluation value based on the battery abnormal mode data and the battery abnormal mode parameter data, the battery abnormal mode data including a voltage fluctuation amplitude, a temperature rise rate and an internal resistance change rate; and performing an abnormality level score on the lead-acid battery based on the battery abnormal mode evaluation value.

[0013] Furthermore, an abnormality level score is performed on the lead-acid battery based on the battery abnormal mode evaluation value. The specific analysis process is as follows: the battery abnormal mode evaluation value is compared with the battery abnormal mode evaluation threshold stored in the database to determine whether the battery abnormal mode evaluation value is greater than the battery abnormal mode evaluation threshold stored in the database; if the battery abnormal mode evaluation value is greater than the battery abnormal mode evaluation threshold stored in the database, the abnormal level corresponding to the battery abnormal mode evaluation value is marked as a high level, an abnormal state warning is performed, and the battery abnormality type is determined; if the battery abnormal mode evaluation value is not greater than the battery abnormal mode evaluation threshold stored in the database, the abnormal level corresponding to the battery abnormal mode evaluation value is marked as a low level.

[0014] Furthermore, the calculation formula of the battery abnormal mode evaluation value is:

[0015]

[0016] Wherein, HC is the evaluation value of the abnormal battery mode, sE is the voltage fluctuation amplitude, cE is the parameter voltage fluctuation amplitude, β1 is the weight factor of sE, sF is the temperature rise rate, cF is the parameter temperature rise rate, β2 is the weight factor of sF, sB is the internal resistance change rate, cB is the parameter internal resistance change rate, and β3 is the weight factor of sG.

[0017] Furthermore, the abnormal type of the battery is determined, and the specific analysis process is as follows: obtaining a set of abnormal pattern matching data of a lead-acid battery stored in a database, wherein the abnormal pattern matching data set of the lead-acid battery includes a plurality of abnormal pattern matching data of a lead-acid battery, each abnormal pattern matching data of a lead-acid battery corresponds to an abnormal type, and the abnormal pattern matching data of the lead-acid battery includes a voltage fluctuation amplitude matching value, a temperature rise rate matching value, and an internal resistance change rate matching value; comparing the abnormal pattern data of the lead-acid battery with each abnormal pattern matching data of the lead-acid battery stored in the database one by one, and determining the minimum abnormal comparison value of the lead-acid battery; determining the closest abnormal pattern matching data of the lead-acid battery based on the minimum abnormal comparison value of the lead-acid battery, and obtaining the abnormal type corresponding to the closest abnormal pattern matching data of the lead-acid battery from the database.

[0018] A lead-acid battery health status evaluation system comprises a lead-acid battery factory health module, a lead-acid battery current health status module and a lead-acid battery abnormal mode module, wherein the lead-acid battery factory health module is used to obtain the lead-acid battery factory health data, analyze the lead-acid battery factory health data, obtain the lead-acid battery factory health evaluation value, and determine the lead-acid battery health status threshold; the lead-acid battery current health status module is used to obtain the lead-acid battery current health status data, and judge the health status of the lead-acid battery based on the lead-acid battery current health status data combined with the lead-acid battery health status threshold; the lead-acid battery abnormal mode module is used to obtain the lead-acid battery abnormal mode data, and perform abnormal grade scoring on the lead-acid battery based on the battery abnormal mode data.

[0019] The present invention has the following beneficial effects:

[0020] The lead-acid battery health status evaluation method and system can accurately determine potential battery problems by comparing health status thresholds and scoring abnormal mode data, provide a comprehensive health status evaluation system, ensure battery safety, and solve the problem that existing lead-acid battery health status evaluation usually relies on only a single parameter to determine the health status of the lead-acid battery, which is often inconvenient to comprehensively evaluate the health status of the battery.

[0021] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 The present invention is a flow chart of the method for evaluating the health status of a lead-acid battery.

[0023] Figure 2 The figure is a flow chart of the evaluation system of the health status of the lead-acid battery of the present invention. DETAILED DESCRIPTION

[0024] The embodiments of the present application solve the problem that the existing lead-acid battery health status evaluation usually relies on only a single parameter to judge the health status of the lead-acid battery, which is often inconvenient to comprehensively evaluate the health status of the battery, through a lead-acid battery health status evaluation method and system.

[0025] See also Figure 1 The embodiment of the present invention provides a technical solution: a method for evaluating the health status of a lead-acid battery, comprising the following steps: obtaining the factory health data of the lead-acid battery, analyzing the factory health data of the lead-acid battery to obtain the factory health assessment value of the lead-acid battery, determining the health status threshold of the lead-acid battery, obtaining the factory parameter health data of the lead-acid battery, wherein the factory parameter health data of the lead-acid battery includes a parameterized initial internal resistance, a parameterized voltage stability, and a parameterized maximum charge and discharge efficiency; determining the factory health assessment value of the lead-acid battery based on the factory health data of the lead-acid battery and the factory parameter health data of the lead-acid battery, wherein the factory health data of the lead-acid battery includes an initial internal resistance, a voltage stability, and a maximum charge and discharge efficiency; storing the factory health assessment value of the lead-acid battery as a designated label, comparing the designated label with each set label stored in a database one by one, determining the set label that is the same as the designated label, and obtaining the health status threshold of the lead-acid battery corresponding to the set label stored in the database.

[0026] In this implementation scheme, first, the factory health data of the lead-acid battery is obtained, and the factory health data of the lead-acid battery includes the initial internal resistance, voltage stability and maximum charge and discharge efficiency. The initial internal resistance is obtained by using an impedance analyzer device to perform a low-frequency signal test when the battery leaves the factory, and the internal resistance is obtained by measuring the battery's response to signals of different frequencies. The initial internal resistance reflects the initial value of the battery's internal resistance. Batteries with lower internal resistance generally indicate higher energy efficiency and better health. The voltage stability is obtained by load testing the battery and measuring the voltage change of the battery within a certain load range. Voltage stability refers to the amplitude of the voltage fluctuation of the battery under different loads.

[0027] The maximum charge and discharge efficiency is obtained by testing the charge and discharge efficiency of the battery under different loads through the maximum discharge and charge test of the battery, and calculating the energy conversion rate of the battery. The maximum charge and discharge efficiency represents the efficiency of the battery under maximum charge and discharge conditions. The factory health assessment value of the lead-acid battery is determined based on the factory health data of the lead-acid battery and the factory parameter health data of the lead-acid battery. The factory health assessment value of the lead-acid battery is stored as a specified tag. The preset tags in the database are compared with the specified tags one by one to find the set tags that match them. Each set tag corresponds to a lead-acid battery health status threshold in the database. This threshold provides a standard for subsequent health status determination. By comparing the set tags in the database, a health status threshold can be provided for the battery.

[0028] The calculation formula for the factory health assessment value of lead-acid batteries is:

[0029]

[0030] Wherein, HA is the factory health assessment value of the lead-acid battery, sH is the initial internal resistance, cH is the parameterized initial internal resistance, sY is the voltage stability, cY is the parameterized voltage stability, sJ is the maximum charge and discharge efficiency, and cJ is the parameterized maximum charge and discharge efficiency.

[0031] Internal resistance is an important indicator of battery health. Lower internal resistance indicates that the battery has higher energy conversion efficiency. Therefore, the closer the internal resistance ratio is to 1, the smaller the difference between the internal resistance of the battery and the factory standard, and the better the battery health. The voltage stability of the battery determines whether the battery can maintain a stable voltage output during use. A better battery should have lower voltage fluctuations. The smaller the voltage stability ratio, the closer the battery voltage stability is to the standard, indicating that the battery is in better health. The charge and discharge efficiency affects the battery's energy conversion and storage capacity. Efficient charge and discharge efficiency helps to extend the battery life and improve energy utilization. A higher charge and discharge efficiency ratio indicates that the battery has better charge and discharge performance. The smaller the factory health assessment value of the lead-acid battery, the closer the battery health is to the factory standard.

[0032] Acquire current health status data of the lead-acid battery, and judge the health status of the lead-acid battery based on the current health status data of the lead-acid battery and a health status threshold of the lead-acid battery; if the lead-acid battery is judged to be healthy, continue to acquire current health status data of the lead-acid battery, and re-judge the health status of the lead-acid battery, and acquire parameter data of the current health status of the lead-acid battery, wherein the parameter data of the current health status of the lead-acid battery includes parameter data of battery voltage, parameter internal resistance change rate and parameter battery own temperature; acquire allowable deviation data of the health status of the lead-acid battery, wherein the allowable deviation data of the health status of the lead-acid battery includes an allowable deviation value of battery voltage and an allowable deviation value of battery operating temperature.

[0033] Determine the current health status assessment value of the lead-acid battery based on the current health status data of the lead-acid battery, the current health status parameter data of the lead-acid battery and the allowable deviation data of the health status of the lead-acid battery, wherein the current health status data of the lead-acid battery includes the current battery voltage, the internal resistance change rate and the battery's own temperature; judge whether the current health status assessment value of the lead-acid battery is greater than the lead-acid battery health status threshold; if the current health status assessment value of the lead-acid battery is greater than the lead-acid battery health status threshold, judge that the lead-acid battery is unhealthy; if the current health status assessment value of the lead-acid battery is not greater than the lead-acid battery health status threshold, judge that the lead-acid battery is healthy.

[0034] In this embodiment, the current battery voltage is obtained, and the output voltage of the battery is obtained by a high-precision voltage sensor. The voltage sensor is usually directly connected to the positive and negative poles of the battery, and is obtained by measuring the voltage value of the battery that changes with the load during the charging and discharging process. The internal resistance change rate is obtained by using an impedance analyzer to monitor the internal resistance change of the battery, and the impedance data of the battery is obtained by a frequency response test method such as EIS, electrochemical impedance spectroscopy, and then the change rate of the internal resistance is calculated. The battery's own temperature is used to monitor the operating temperature of the battery in real time through a temperature sensor installed on the battery. The current health status assessment value of the lead-acid battery is determined based on the current health status data of the lead-acid battery, the current health status parameter data of the lead-acid battery, and the allowable deviation data of the health status of the lead-acid battery. The more the current health status assessment value of the lead-acid battery deviates from the threshold state, if the current health status assessment value is greater than the health status threshold: it means that the health status of the battery is poor, so it is determined to be unhealthy. If the current health status assessment value is not greater than the health status threshold: it means that the battery is still within the health range and is determined to be healthy.

[0035] The calculation formula of the current health status assessment value of the lead-acid battery is:

[0036]

[0037] Wherein, HB is the current health status assessment value of the lead-acid battery, sA is the current battery voltage, cA is the battery voltage parameter data, ΔsA is the allowable deviation value of the battery voltage, sB is the battery operating temperature, cB is the parameterized battery operating temperature, ΔsB is the allowable deviation value of the battery operating temperature, sD is the internal resistance change rate, cD is the parameterized internal resistance change rate, and e is a natural constant.

[0038] |sA-cA| calculates the difference between the current voltage and the standard voltage. By taking the absolute value, the difference can be guaranteed to be always positive. ΔsA refers to the acceptable fluctuation range of the battery voltage. |sB-cB| calculates the difference between the current temperature and the standard temperature. Temperature fluctuations will affect battery performance. ΔsB refers to temperature fluctuations within a reasonable range. The internal resistance change rate is processed by an exponential function. As the internal resistance increases, the decline in battery health becomes more obvious, reflecting the process of battery aging and performance degradation.

[0039] Acquire the lead-acid battery health state allowable deviation data, the lead-acid battery health state allowable deviation data includes the battery voltage allowable deviation value and the battery operating temperature allowable deviation value; acquire the external environment temperature and the battery discharge rate, and combine and mark them as the lead-acid battery health state deviation influence data; acquire the health state deviation influence matching data set stored in the database, the health state deviation influence matching data set includes multiple health state deviation influence matching data, and the health state deviation influence matching data includes the external environment temperature matching value and the battery discharge rate matching value; compare the lead-acid battery health state deviation influence data with each health state deviation influence matching data stored in the database one by one, and determine the minimum lead-acid battery health state comparison value; determine the closest health state deviation influence matching data based on the minimum lead-acid battery health state comparison value, and obtain the lead-acid battery health state allowable deviation data corresponding to the closest health state deviation influence matching data from the database.

[0040] In this embodiment, excessively high or low external temperature will affect the chemical reaction rate and internal temperature of the battery, thereby affecting the health of the battery. The discharge rate directly affects the charge and discharge efficiency of the battery. Excessive discharge rate may cause problems such as battery overheating and increased internal resistance. The external ambient temperature is usually obtained by a temperature sensor installed around the battery pack or outside the battery. The battery discharge rate is obtained by the battery management system monitoring the discharge current of the battery and the voltage change during discharge. The external ambient temperature and the battery discharge rate are combined into the lead-acid battery health state deviation impact data, and the currently obtained lead-acid battery health state deviation impact data are compared one by one with each health state deviation impact matching data stored in the database. In the comparison process, the closest matching data is found by calculating the comparison value. Based on the minimum comparison value, the closest health state deviation impact matching data is determined. Since the performance of the lead-acid battery is affected by external factors, unnecessary misjudgments caused by environmental changes are avoided by adjusting the deviation range of the battery health assessment.

[0041] The calculation formula for the comparison value of the health status of lead-acid batteries is:

[0042]

[0043] Where BA is the comparison value of the health status of the lead-acid battery, M is the external ambient temperature, cM is the external ambient temperature matching value, V is the battery discharge rate, and cV is the battery discharge rate matching value.

[0044] It reflects the deviation between the current temperature and the temperature matching value, and |M-cM| calculates the absolute difference between the current temperature and the standard temperature. The ratio can be used to quantify the difference between the current discharge rate and the standard discharge rate. A higher discharge rate will increase the internal resistance of the battery, cause overheating, and may even cause premature battery degradation.

[0045] Based on the battery abnormal mode data, the lead-acid battery is scored for abnormality level, and the battery abnormal mode parameter data is obtained, wherein the battery abnormal mode parameter data includes a parameterized voltage fluctuation amplitude, a parameterized temperature rise rate, and a parameterized internal resistance change rate; based on the battery abnormal mode data and the battery abnormal mode parameter data, a battery abnormal mode evaluation value is determined, wherein the battery abnormal mode data includes a voltage fluctuation amplitude, a temperature rise rate, and an internal resistance change rate.

[0046] In this embodiment, the voltage fluctuation amplitude is the voltage fluctuation range in the actual operation of the battery. Excessive voltage fluctuation will affect the normal use of the battery. The voltage fluctuation amplitude can be obtained by monitoring the battery voltage and calculating the voltage variation range, and monitored by the built-in voltage sensor of the battery management system. The temperature rise rate refers to the rate of temperature change of the battery during use. Rapid temperature rise often means that the battery is not working properly. The temperature rise rate is monitored by a temperature sensor by monitoring the rate of temperature change during the battery charging and discharging process. It is obtained by recording the temperature changes at different time points and calculating the increments. The internal resistance change rate refers to the change of the internal resistance during the operation of the battery. Excessive changes in the internal resistance indicate that the battery is aging or has internal damage. The internal resistance change rate is measured by a battery internal resistance tester. The internal resistance change rate is obtained by measuring the battery internal resistance within a certain period and comparing its changes. The battery abnormal mode evaluation value is determined based on the battery abnormal mode data and the battery abnormal mode parameter data.

[0047] The calculation formula of the battery abnormal mode evaluation value is:

[0048]

[0049] Wherein, HC is the evaluation value of the abnormal battery mode, sE is the voltage fluctuation amplitude, cE is the parameter voltage fluctuation amplitude, β1 is the weight factor of sE, sF is the temperature rise rate, cF is the parameter temperature rise rate, β2 is the weight factor of sF, sB is the internal resistance change rate, cB is the parameter internal resistance change rate, and β3 is the weight factor of sG.

[0050] The formula is divided into two parts: logarithmic term and square root term. The first part is the logarithmic term, which is processed by logarithmic transformation of the deviation of voltage fluctuation amplitude and temperature rise rate. and They are the ratios of the actual measured values ​​of the voltage fluctuation amplitude and the temperature rise rate to their parameterized values, respectively, reflecting the deviation of the current parameters from the standard values. By multiplying the weight factors β1 and β2, the influence weights of each parameter can be adjusted to reflect their importance in anomaly detection. Indicates the deviation assessment of the internal resistance change rate. The internal resistance change rate indicates the ratio of the currently measured internal resistance change rate to the standard parameter value, reflecting the degree of deviation of the internal resistance. The weight factor β3 is used to adjust the impact of the internal resistance change rate on the final assessment value.

[0051] The battery abnormal mode evaluation value is compared with the battery abnormal mode evaluation threshold stored in the database to determine whether the battery abnormal mode evaluation value is greater than the battery abnormal mode evaluation threshold stored in the database; if the battery abnormal mode evaluation value is greater than the battery abnormal mode evaluation threshold stored in the database, the abnormal level corresponding to the battery abnormal mode evaluation value is marked as a high level, an abnormal state warning is performed, and the battery abnormality type is determined; if the battery abnormal mode evaluation value is not greater than the battery abnormal mode evaluation threshold stored in the database, the abnormal level corresponding to the battery abnormal mode evaluation value is marked as a low level.

[0052] In this implementation scheme, first, the abnormal mode evaluation value of the battery is compared with the evaluation threshold preset in the database to determine whether the current state of the battery exceeds the normal range. The abnormal mode evaluation threshold of the battery is obtained by collecting the voltage fluctuation amplitude, temperature rise rate and internal resistance change rate data of the battery under different working conditions to establish a battery parameter library containing various operating conditions. After that, the key data range with strong stability and accurate reflection of abnormal conditions is screened out. Determine the evaluation threshold corresponding to the specific abnormal mode. If the abnormal mode evaluation value exceeds the threshold, it means that the battery may be in a lower level of abnormal state, and the corresponding abnormal level is marked as low level, and the abnormal state warning is triggered to prompt potential problems as early as possible. If the abnormal mode evaluation value is lower than or equal to the threshold, the abnormal level is marked as high level.

[0053] Determine the abnormal type of the battery, and the specific analysis process is: obtain a lead-acid battery abnormal pattern matching data set stored in a database, the lead-acid battery abnormal pattern data set includes multiple lead-acid battery abnormal pattern matching data, each lead-acid battery abnormal pattern matching data corresponds to an abnormal type, and the lead-acid battery abnormal pattern matching data includes a voltage fluctuation amplitude matching value, a temperature rise rate matching value, and an internal resistance change rate matching value; compare the lead-acid battery abnormal pattern data with each lead-acid battery abnormal pattern matching data stored in the database one by one to determine the minimum lead-acid battery abnormal comparison value; determine the closest lead-acid battery abnormal pattern matching data based on the minimum lead-acid battery abnormal comparison value, and obtain the abnormal type corresponding to the closest lead-acid battery abnormal pattern matching data from the database.

[0054] In this implementation scheme, first, a set of stored abnormal pattern matching data sets is extracted from the database. The abnormal pattern matching data set includes matching values ​​of voltage fluctuation amplitude, temperature rise rate and internal resistance change rate. Then, the abnormal pattern data of the current battery is compared with each abnormal pattern matching data in the database one by one. Find the matching data closest to the current battery abnormal pattern. By calculating the abnormal comparison value of each comparison result, the minimum comparison value is selected to represent the closest degree of proximity between the current abnormal pattern and a matching data in the database. After determining the minimum comparison value, the abnormal pattern matching data corresponding to the comparison value is extracted from the database. Each abnormal pattern matching data is associated with the corresponding lead-acid battery remaining service life data. Based on the lead-acid battery remaining service life data, the lead-acid battery is given a delayed abnormal state warning.

[0055] The calculation formula for the abnormal comparison value of lead-acid batteries is:

[0056]

[0057] In the formula: BT is the abnormal comparison value of the lead-acid battery, sE is the voltage fluctuation amplitude, sF is the temperature rise rate, sG is the internal resistance change rate, cTE is the voltage fluctuation amplitude matching value, cTF is the temperature rise rate matching value, cTG is the internal resistance change rate matching value, and e is a natural constant.

[0058] The similarities between the voltage fluctuation amplitude, temperature rise rate and internal resistance change rate of the current battery and the corresponding matching values ​​in the database are calculated respectively. Get the similarity of voltage fluctuations. Evaluate the similarity of temperature changes. Evaluate the similarity of the internal resistance change.

[0059] See also Figure 2 , a lead-acid battery health status evaluation system, including a lead-acid battery factory health module, a lead-acid battery current health status module, and a lead-acid battery abnormal mode module, wherein: the lead-acid battery factory health module is used to obtain the lead-acid battery factory health data, analyze the lead-acid battery factory health data, obtain the lead-acid battery factory health assessment value, and determine the lead-acid battery health status threshold; the lead-acid battery current health status module is used to obtain the lead-acid battery current health status data, and judge the health status of the lead-acid battery based on the lead-acid battery current health status data combined with the lead-acid battery health status threshold; the lead-acid battery abnormal mode module is used to obtain the lead-acid battery abnormal mode data, and perform abnormal level scoring on the lead-acid battery based on the battery abnormal mode data.

[0060] In a specific embodiment, the factory health data of the lead-acid battery and the factory parameter health data of the lead-acid battery include sH of 5mΩ, cH of 4mΩ, sY of 0.98, cY of 1.00, sJ of 0.92, and cJ of 1.00. The factory health assessment value of the lead-acid battery is calculated to be 1.93. The label is set to 1.93 to obtain the health status threshold of the lead-acid battery stored in the database corresponding to the set label. It is assumed that the health status threshold of the lead-acid battery obtained is 4.

[0061] The current health status data of the lead-acid battery and the current health status parameter data of the lead-acid battery show that sA is 12.4V, cA is 12.6V, ΔsA is 0.2V, sB is 35℃, cB is 30℃, ΔcB is 5℃, sD is 0.0015, cD is 0.001, and e is 2.718. The calculated current health status assessment value of the lead-acid battery is 5.581, which means that the lead-acid battery is unhealthy.

[0062] The battery abnormal mode parameter data and the battery abnormal mode parameter data have sE of 0.25, cE of 0.2, β1 of 0.5, sF of 1.5, cF of 1.0, β2 of 0.3, sB of 0.02, cB of 0.015, β3 of 0.7, and e of 2.718. The calculated battery abnormal mode evaluation value is 1.344. The battery abnormal mode evaluation threshold in the database is set to 1.5, and the abnormal level corresponding to the battery abnormal mode evaluation value is marked as a low level.

[0063] Those skilled in the art will appreciate that 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, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0064] The present invention is described with reference to flowcharts and / or block diagrams of systems, 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 1 A device that provides the functions specified in a block or multiple blocks.

[0065] 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.

[0066] 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 in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0067] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0068] 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 method for evaluating the health status of a lead-acid battery, characterized in that: The following steps are involved: Obtaining the factory health data of the lead-acid battery, analyzing the factory health data of the lead-acid battery, obtaining the factory health assessment value of the lead-acid battery, and determining the health status threshold of the lead-acid battery; Obtaining current health status data of the lead-acid battery, and judging the health status of the lead-acid battery based on the current health status data of the lead-acid battery and a health status threshold of the lead-acid battery; If the lead-acid battery is determined to be healthy, continue to obtain the current health status data of the lead-acid battery and re-determine the health status of the lead-acid battery; If the lead-acid battery is determined to be unhealthy, abnormal mode data of the lead-acid battery is obtained, and an abnormality level score is assigned to the lead-acid battery based on the abnormal mode data of the battery; If the abnormality level score is high, an abnormal status warning will be issued; If the abnormality level score is low, a delayed warning of the abnormal state will be issued.

2. A method for evaluating the health status of a lead-acid battery according to claim 1, characterized in that: The factory health data of lead-acid batteries is analyzed to obtain the factory health assessment value of lead-acid batteries and determine the health status threshold of lead-acid batteries. The specific analysis process is as follows: Obtaining factory-determined health data of the lead-acid battery, wherein the factory-determined health data of the lead-acid battery includes a determined initial internal resistance, a determined voltage stability, and a determined maximum charge and discharge efficiency; Determine the lead-acid battery factory health assessment value based on the lead-acid battery factory health data and the lead-acid battery factory parameter health data, wherein the lead-acid battery factory health data includes initial internal resistance, voltage stability and maximum charge and discharge efficiency; The factory health assessment value of the lead-acid battery is stored as a designated tag, and the designated tag is compared one by one with each set tag stored in the database to determine the set tag that is the same as the designated tag, and obtain the health status threshold of the lead-acid battery corresponding to the set tag stored in the database.

3. The method for evaluating the health status of a lead-acid battery according to claim 1, characterized in that: The health status of the lead-acid battery is determined based on the current health status data of the lead-acid battery and the health status threshold of the lead-acid battery. The specific analysis process is as follows: Obtaining the current health status parameter data of the lead-acid battery, wherein the current health status parameter data of the lead-acid battery includes the battery voltage parameter data, the parameter internal resistance change rate and the parameter battery temperature; Acquire the lead-acid battery health state allowable deviation data, wherein the lead-acid battery health state allowable deviation data includes the battery voltage allowable deviation value and the battery operating temperature allowable deviation value; Determine the current health status assessment value of the lead-acid battery based on the current health status data of the lead-acid battery, the current health status parameter data of the lead-acid battery and the allowable deviation data of the health status of the lead-acid battery, wherein the current health status data of the lead-acid battery includes the current battery voltage, the internal resistance change rate and the battery temperature; Determine whether the current health status assessment value of the lead-acid battery is greater than the health status threshold of the lead-acid battery; If the current health status assessment value of the lead-acid battery is greater than the health status threshold of the lead-acid battery, the lead-acid battery is judged to be unhealthy; If the current health status assessment value of the lead-acid battery is not greater than the health status threshold of the lead-acid battery, the lead-acid battery is judged to be healthy.

4. A method for evaluating the health status of a lead-acid battery according to claim 3, characterized in that: Obtain the allowable deviation data of the health status of the lead-acid battery. The specific analysis process is as follows: Obtain the external environment temperature and battery discharge rate, and combine and mark them as lead-acid battery health status deviation impact data; Acquire a health state deviation impact matching data set stored in a database, wherein the health state deviation impact matching data set includes a plurality of health state deviation impact matching data, wherein the health state deviation impact matching data includes an external environment temperature matching value and a battery discharge rate matching value; Compare the health status deviation impact data of the lead-acid battery with each health status deviation impact matching data stored in the database one by one to determine the minimum health status comparison value of the lead-acid battery; The closest health state deviation impact matching data is determined based on the minimum lead-acid battery health state comparison value, and the lead-acid battery health state allowable deviation data corresponding to the closest health state deviation impact matching data is obtained from a database.

5. The method for evaluating the health status of a lead-acid battery according to claim 3, characterized in that: The calculation formula of the current health status assessment value of the lead-acid battery is: Wherein, HB is the current health status assessment value of the lead-acid battery, sA is the current battery voltage, cA is the battery voltage parameter data, ΔsA is the allowable deviation value of the battery voltage, sB is the battery operating temperature, cB is the parameterized battery operating temperature, ΔsB is the allowable deviation value of the battery operating temperature, sD is the internal resistance change rate, cD is the parameterized internal resistance change rate, and e is a natural constant.

6. A method for evaluating the health status of a lead-acid battery according to claim 1, characterized in that: Based on the battery abnormality pattern data, the lead-acid battery is scored for abnormality level. The specific analysis process is as follows: Acquiring battery abnormal mode parameter data, wherein the battery abnormal mode parameter data includes a parameter voltage fluctuation amplitude, a parameter temperature rise rate, and a parameter internal resistance change rate; Determine a battery abnormal mode evaluation value based on battery abnormal mode data and battery abnormal mode parameter data, wherein the battery abnormal mode data includes voltage fluctuation amplitude, temperature rise rate and internal resistance change rate; The lead-acid battery is scored for abnormality level based on the battery abnormality pattern evaluation value.

7. A method for evaluating the health status of a lead-acid battery according to claim 6, characterized in that: Based on the abnormal mode evaluation value of the battery, the lead-acid battery is scored for abnormality level. The specific analysis process is as follows: Compare the battery abnormal mode evaluation value with the battery abnormal mode evaluation threshold stored in the database to determine whether the battery abnormal mode evaluation value is greater than the battery abnormal mode evaluation threshold stored in the database; If the battery abnormal mode evaluation value is greater than the battery abnormal mode evaluation threshold stored in the database, the abnormal level corresponding to the battery abnormal mode evaluation value is marked as a high level, an abnormal state warning is issued, and the battery abnormality type is determined; If the battery abnormal mode evaluation value is not greater than the battery abnormal mode evaluation threshold stored in the database, the abnormal level corresponding to the battery abnormal mode evaluation value is marked as a low level.

8. A method for evaluating the health status of a lead-acid battery according to claim 6, characterized in that: The calculation formula of the battery abnormal mode evaluation value is: Wherein, HC is the evaluation value of the abnormal battery mode, sE is the voltage fluctuation amplitude, cE is the parameter voltage fluctuation amplitude, β1 is the weight factor of sE, sF is the temperature rise rate, cF is the parameter temperature rise rate, β2 is the weight factor of sF, sB is the internal resistance change rate, cB is the parameter internal resistance change rate, and F3 is the weight factor of sG.

9. A method for evaluating the health status of a lead-acid battery according to claim 1, characterized in that: Determine the type of battery abnormality. The specific analysis process is as follows: Acquire a lead-acid battery abnormal pattern matching data set stored in a database, wherein the lead-acid battery abnormal pattern data set includes a plurality of lead-acid battery abnormal pattern matching data, each lead-acid battery abnormal pattern matching data corresponds to an abnormal type, and the lead-acid battery abnormal pattern matching data includes a voltage fluctuation amplitude matching value, a temperature rise rate matching value, and an internal resistance change rate matching value; Compare the abnormal pattern data of the lead-acid battery with the abnormal pattern matching data of each lead-acid battery stored in the database one by one to determine the minimum abnormal comparison value of the lead-acid battery; The closest lead-acid battery abnormality pattern matching data is determined based on the minimum lead-acid battery abnormality comparison value, and the abnormality type corresponding to the closest lead-acid battery abnormality pattern matching data is obtained from the database.

10. A lead-acid battery health status evaluation system, applied to a lead-acid battery health status evaluation method according to any one of claims 1 to 9, characterized in that: It includes the lead-acid battery factory health module, the lead-acid battery current health status module, and the lead-acid battery abnormal mode module, among which: The lead-acid battery factory health module is used to obtain the lead-acid battery factory health data, analyze the lead-acid battery factory health data, obtain the lead-acid battery factory health assessment value, and determine the lead-acid battery health status threshold; The lead-acid battery current health status module is used to obtain the current health status data of the lead-acid battery, and judge the health status of the lead-acid battery based on the current health status data of the lead-acid battery combined with the health status threshold of the lead-acid battery; The lead-acid battery abnormal mode module is used to obtain the lead-acid battery abnormal mode data and to score the abnormal level of the lead-acid battery based on the battery abnormal mode data.

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