A power system health state calculation method and device

Abstract

The present application belongs to the technical field of power supply health state, and particularly relates to a power supply system health state calculation method and device. The method extracts charging groups from a large amount of charging and discharging data, screens static voltage data from the charging groups and multiple data before the charging groups, determines the real state of charge corresponding to the static voltage data by using the static voltage data and SOC-OCV relationship, corrects and compensates the real state of charge to obtain the real state of charge of the highest single body at the beginning of charging and the real state of charge of the lowest single body at the beginning of charging, combines the charging capacity of the charging to calculate the health state of the highest single body, and finally calculates the health state of the power supply system by considering the consistency between the batteries. Thus, the present application effectively improves the accuracy of power supply system health state calculation.

Description

Technical Field

[0001] This invention belongs to the field of power supply health status technology, specifically relating to a method and apparatus for calculating the health status of a power system. Background Technology

[0002] With the widespread adoption of new energy vehicles, some vehicles are reaching the end of their lifespan, and issues such as battery safety, secondary use, and residual value assessment are receiving increasing attention from the entire industry. However, accurate assessment of battery health has always been a challenge in the industry, as performing a full deep charge on each vehicle requires significant costs. Therefore, there is an urgent need for a data technology based on operational data to accurately assess the battery's State of Healthy (SOH, which is the ratio of actual capacity to rated capacity).

[0003] LFP (lithium iron phosphate) power systems are widely used in new energy vehicles, but due to their material properties, they have a voltage plateau period. During this plateau period, the state of charge (SOC) cannot be accurately estimated, leading to difficulties in SOH calculation. SOH calculation methods based on battery models lack dynamic consideration of real-world operating conditions and aging over time, resulting in inaccurate vehicle SOH calculations. Summary of the Invention

[0004] The purpose of this invention is to provide a method for calculating the health status of a power system, thereby solving the problem of inaccurate health status calculations in existing technologies; at the same time, this invention also provides a power system health status calculation device for implementing the above-mentioned power system health status calculation method.

[0005] To solve the above-mentioned technical problems, the technical solution provided by this invention and the corresponding beneficial effects of the technical solution are as follows:

[0006] The present invention provides a method for calculating the health status of a power system, comprising the following steps:

[0007] 1) Obtain multiple charging and discharging data corresponding to different times of the power system. Each charging and discharging data includes charging / discharging time, displayed state of charge, charging / discharging current, highest single-cell voltage and lowest single-cell voltage. Extract the charging scenario data that meets the requirements from it. The charging scenario data includes multiple charging groups. The data of one charging group is the data of one full charge.

[0008] 2) For a charging group, perform the following calculations:

[0009] Based on the charging current at each time point, determine the charging capacity C for that charging session. N ;

[0010] If the charging current is greater than or equal to the set charging current threshold A1, extract multiple charging and discharging data points preceding this charging group, and select the segment of charging and discharging data where the discharging current is less than the set static current threshold A2 and has the longest duration. Then, based on the highest single-cell voltage V of the last data point in this segment... 静高 / Minimum unit voltage V 静低 And the SOC-OCV relationship, to determine the highest single-cell voltage V of the last data point. 静高 / Minimum unit voltage V 静低 The corresponding highest static voltage and true state of charge (SOC) 静高 / Minimum static voltage True state of charge (SOC) 静低 The true state of charge (SOC) of the highest-charged individual cell at the start of this charging cycle is calculated using the following formula. 高始 And the lowest true state of charge (SOC) of a single cell at the start of charging 低始 :

[0011] SOC 高始 =SOC 静高 +(SOC) 1显 -SOC 静显 SOC 低始 =SOC 静低 +(SOC) 1显 -SOC 静显 )

[0012] In the formula, SOC 静显 This indicates the displayed state of charge (SOC) of the last data point in the aforementioned charge / discharge data segment. 1显 This indicates the displayed charge status of the first data entry in this charging group;

[0013] 3) Calculate the health status (SOH) of the highest-ranking monomer using the following formula. 单 : C 额 Indicates the rated capacity of the highest-ranking single unit;

[0014] 4) Calculate the state of health (SOH) of the power system using the following formula. 系统 : k 一致性 k represents the consistency coefficient. 一致性 =100%-SOC 高始 -SOC 低始 .

[0015] The beneficial effects of the above technical solution are as follows: This invention extracts charging groups from a large amount of charging and discharging data. From these charging groups and the multiple data points preceding them, static voltage data is selected. Using the static voltage data and the SOC-OCV relationship, the true state of charge corresponding to the static voltage data can be determined. After obtaining this true state of charge, it is corrected and compensated to obtain the true state of charge (SOC) of the highest-charging-starting cell. 高始 And the lowest true state of charge (SOC) of a single cell at the start of charging 低始 Combined with the charging capacity C of this charge. N The health status (SOH) of the highest-ranking monomer can then be calculated. 单 Finally, considering the consistency between batteries, the state of health (SOH) of the power system is calculated. 系统 .

[0016] This method takes into account several factors: First, it does not directly use the displayed state of charge at the start of charging as the initial state of charge for subsequent calculations. Instead, it considers the possible charging and discharging behavior between the static voltage value and the start of charging, and uses the state of charge calculated from the compensated static voltage data as the initial state of charge, ensuring the accuracy of subsequent health state calculations. Second, when calculating the health state of individual battery cells, it calculates the health state of the highest-performing cell. This is because the highest-performing cell is generally fully charged, making data acquisition easier and more convenient for subsequent calculations. Finally, considering the consistency among multiple cells, the health state of the power system is calculated, resulting in a more accurate health state.

[0017] Furthermore, it also includes steps 5) to 6).

[0018] 5) Correct the SOC-OCV relationship using the following formula:

[0019]

[0020]

[0021]

[0022] In the formula, SOC represents the state of charge corresponding to the static voltage OCV, A1, A2, B1, and B2 all represent aging parameters, and t represents the usage time.

[0023] 6) Using the corrected SOC-OCV relationship, re-execute steps 2) to 4) to obtain the corrected health state (SOH) of the power system. 系统 .

[0024] The beneficial effects of the above technical solution are as follows: considering the effect of battery aging on the SOC-OCV relationship, the corrected SOC-OCV relationship is used to calculate the state of health (SOH) of the power system. 系统 This ensures the accuracy of health status calculations.

[0025] Furthermore, the usage time t is calculated using the following formula:

[0026]

[0027] In the formula, k1 and k2 both represent the usage time parameter, and SOH represents the health status of the power system, which is the health status of the power system obtained in step 4).

[0028] The beneficial effects of the above technical solution are as follows: the power system's usage time is characterized by the health status of the power system, rather than the current time minus the manufacturing or sales time. This is because inaccurate time and battery replacement make the usage time calculated by this method meaningless. Therefore, the method of the present invention ensures the accuracy of the usage time calculation.

[0029] Furthermore, the time parameters k1 and k2 are determined as follows: Multiple sets of power system usage time and health status data are acquired; the health status data that appears most frequently at a given usage time is taken as the health status corresponding to that usage time; using the different usage times and their corresponding health status data, the formula is... The time parameters k1 and k2 are obtained by fitting the solution.

[0030] The beneficial effects of the above technical solution are: using big data to determine the relationship between the health status of the power system and the usage time, making the fitted usage time parameters more accurate and able to more accurately reflect the relationship between the health status of the power system and the usage time.

[0031] Furthermore, k1=0.6484, k2=0.07414.

[0032] Furthermore, in step 2), if the charging current is less than the set charging current threshold A1, the highest single-cell voltage V is used based on the last data from the previous charging group. z高 / Minimum unit voltage V z低 And the SOC-OCV relationship, will be related to the highest single-cell voltage V in the last data before this charging group. z高 / Minimum unit voltage V z低 The corresponding state of charge is used as the true state of charge (SOC) of the highest-valued individual cell at the start of this charging process. 高始 / Minimum true state of charge (SOC) of a single cell at the start of charging 低始 .

[0033] Further, in step 1), the requirement includes at least one of the following:

[0034] Requirement 1: The ratio of the number of current fluctuations in this charge to the total number of current fluctuations in all charging groups is less than the set fluctuation ratio threshold; fluctuation refers to the absolute value of the difference between the charging current of a data and the charging current of the previous data being greater than the set current deviation threshold.

[0035] Requirement 2: The positions of the highest and second highest voltage cells are greater than 1, or the voltage of the lowest voltage cell is greater than the set low voltage threshold.

[0036] Requirement 3: The total charging time of a charging group is greater than the set time threshold.

[0037] Requirement 4: The difference between the displayed state of charge of the last data entry and the displayed state of charge of the first data entry in a charging group is greater than the set state of charge difference threshold.

[0038] Requirement 5: The displayed state of charge of the last data entry in a charging group is greater than the set threshold for the difference between the end state of charge and the end state of charge.

[0039] The beneficial effect of the above technical solution is that condition 2 can eliminate the situation of sudden changes at the end of the charging process.

[0040] Further, in step 2), the charging capacity C for this charging is determined. N The method is as follows: ① Calculate the charging capacity C between adjacent time points corresponding to two adjacent data points based on the two adjacent data points. x ② Add up the charging capacity between all adjacent time points to obtain the charging capacity C of that charge. N The method used in step ① is as follows: if the interval time Δt corresponding to two adjacent data points is less than the set low threshold for adjacent time, then the charging capacity between adjacent moments corresponding to the two adjacent data points is the charging current multiplied by the interval time Δt; if the interval time corresponding to two adjacent data points is greater than the set high threshold for adjacent time and the state of charge ΔSOC corresponding to the two adjacent data points is less than the set state of charge threshold, then the charging capacity between adjacent moments corresponding to the two adjacent data points is the charging current multiplied by 10 seconds, and the set low threshold for adjacent time is less than the set high threshold for adjacent time; otherwise, the charging capacity between adjacent moments corresponding to the two adjacent data points is the average value of the charging current corresponding to the two data points multiplied by the interval time Δt.

[0041] The beneficial effects of the above technical solution are: it takes into account various different actual situations to calculate the charging capacity C between adjacent moments. x This ensures the accuracy of the calculations.

[0042] Furthermore, A1 = 5.962E-18, A2 = -0.4201, B1 = 13.19, B2 = 0.009756.

[0043] The present invention provides a power system health status calculation device, comprising a memory and a processor, wherein the processor is configured to execute instructions stored in the memory to implement the power system health status calculation method as described above, and achieve the same beneficial effects as the method. Attached Figure Description

[0044] Figure 1 This is a flowchart of the power system health status calculation method of the present invention;

[0045] Figure 2 This is a schematic diagram of the health status error distribution of the present invention;

[0046] Figure 3 This is a data example diagram of the present invention;

[0047] Figure 4 This is a SOC-OCV curve obtained by fitting new and old batteries according to the present invention;

[0048] Figure 5 This is a schematic diagram of the deviation distribution of the SOC-OCV curve after it changes with the years and the current deviation distribution of the present invention;

[0049] Figure 6 This is a structural diagram of the power system health status calculation device of the present invention. Detailed Implementation

[0050] The following detailed description of a power system health status calculation method and a power system health status calculation device according to the present invention, with reference to the accompanying drawings and embodiments, is provided in detail.

[0051] Method Implementation Examples:

[0052] An embodiment of the power system health status calculation method of the present invention, targeting LFP power systems, uses the Apache Hadoop data platform to store all vehicle data, and the Apache Spark computing platform to calculate the data, using SQL language to extract and calculate the data. The following is in conjunction with... Figure 1 The entire process of the method of the present invention will be described.

[0053] Step 1: Obtain charging and discharging data of the LFP power system from the Apache Hadoop data platform, and extract charging scenario data from it.

[0054] 1. Extract basic data.

[0055] Extract multiple data entries from T-1 to T-3 (T represents today, T-1 represents yesterday, and T-3 represents the day before yesterday). Each data entry includes vehicle ID, charging / discharging time, highest single-cell voltage, lowest single-cell voltage, charging / discharging current, displayed state of charge (SOC), temperature, temperature and voltage position, rated capacity, and battery management system (BMS) status information. The BMS status information indicates the charging / discharging state; for example, a value of 4 indicates the power system is discharging, and a value of 6 indicates the power system is charging.

[0056] Data meeting the following conditions is selected: ① charging state; ② current > A (-800A < A < 800A); ③ SOC > B (0 < B < 10%); ④ temperature > C (-50℃ < C < 50℃); ⑤ the time interval between data entry and data acquisition is between D and E (0s~3600s). It should be noted that the data entry time refers to the moment the data is uploaded to the Apache Hadoop data platform. If the time interval between data entry and data acquisition is too large, it indicates that the data is not reliable. To ensure the accuracy of the calculations in this invention, unreliable data is not considered.

[0057] 2. Add adjacent data information.

[0058] Each data entry includes the time of the previous data entry, the state of charge of the previous data entry, and the current of the previous data entry.

[0059] 3. Calculation of key variables.

[0060] 1) Calculate the interval time Δt: the time of the current data entry minus the time of the previous data entry.

[0061] 2) Calculate the interval state of charge △SOC: The state of charge shown in this data is subtracted from the state of charge shown in the previous data.

[0062] 3) Current fluctuation: If the absolute value of the difference between the charging current of this data and the charging current of the previous data is greater than F (F represents the current deviation threshold, which can be set to 0-10A), it is defined as fluctuation; otherwise, it is not fluctuation.

[0063] 4) Capacity Calculation: When the interval Δt between two data points is less than G (G represents the low threshold for adjacent times, which can be set to 60s~120s), the charging capacity between the two moments corresponding to the two data points is equal to the charging current multiplied by the interval Δt; when the interval Δt between two data points is greater than H (H represents the high threshold for adjacent times, which can be set to 120s~240s) and the state of charge ΔSOC between the two adjacent data points is less than I (I represents the state of charge threshold, which can be set to 1A~5A), the charging capacity between the two moments corresponding to the two data points is equal to the charging current multiplied by 10s; in other cases, the charging capacity between the two moments corresponding to the two data points is equal to the average of the two charging currents multiplied by the time interval Δt.

[0064] 5) Energy Calculation: When the interval Δt between two data points is less than G (G has the same meaning and range as above), the charging energy between the two moments corresponding to the two data points is equal to the charging current multiplied by the interval Δt and then multiplied by the voltage; when the interval Δt between two data points is greater than H (H has the same meaning and range as above) and the state of charge ΔSOC between adjacent data points is less than I (I has the same meaning and range as above), the charging energy between the two moments corresponding to the two data points is equal to the charging current multiplied by 10s and then multiplied by the voltage; in other cases, the charging energy between the two moments corresponding to the two data points is equal to the average value of the two charging currents multiplied by the time interval Δt and then multiplied by the voltage.

[0065] 6) Charging Start Label: When the state of charge interval ΔSOC between two data points is greater than J (0~5%) and the interval time is less than K (0.5h~1.5h), or when the state of charge interval ΔSOC between two data points is less than L (0~5%), it is defined as charging not starting; otherwise, it is defined as charging starting.

[0066] 7) Based on the charging start label, group the charging data and add labels to the groups to identify multiple charging groups.

[0067] 4. Calculate the filtered variables.

[0068] 1) Calculate the minimum time for the vehicle in each charging group, which is defined as the charging start time.

[0069] 2) Calculate the maximum time for the vehicle in each charging group, which is defined as the charging end time.

[0070] 3) Calculate the total number of current jumps. A jump refers to a situation where the difference between the charging current of a data point and the charging current of the previous data point is significant.

[0071] 5. Data acquisition for charging scenarios.

[0072] Keep the data with the number of current fluctuations / total number of current fluctuations < N% (N represents the set fluctuation ratio threshold, and its value can be set from 10% to 80%) after the charging start time and before the charging end time, and the charging start time = data of T - 2 days.

[0073] The reason for extracting the T - 2 data from the data from T - 1 to T - 3 is that a single charging often spans multiple days. For example, a complete charging starts at 10 pm on a certain day and ends at 3 am the next day. Considering this situation, in order to obtain all complete charging data, identify all charging scenarios without omission, and improve the calculation coverage rate, the complete T - 2 data is extracted from all the data from T - 1 day to T - 3 days.

[0074] 6. Summary of charging scenario data.

[0075] 1) Extract the charging scenario data of T - 2 days.

[0076] 2) Extract multiple charging groups from the charging scenario data of T - 2 days. The data of one charging group is the data of one full charge. Calculate the charging start time, charging end time, total capacity, total energy, total charging duration, maximum SOC interval, maximum time interval, maximum current, average current, and maximum single - cell voltage for each charging group of each vehicle.

[0077] 3) Extract the start / end information of each charging group of each vehicle: start / end charging current, start / end state of charge, start / end highest (lowest) temperature, start / end position of highest (lowest) temperature, start / end highest (lowest) voltage, start / end position of highest (lowest) voltage, rated capacity (if the fixed information table contains the rated capacity, take the fixed information table; if the fixed information table does not contain it, obtain it from the BMS).

[0078] 4) Summarize the information in 2) and 3) and retain the charging groups that meet the following requirements: The difference between the displayed state of charge of the last data in a charging group and the displayed state of charge of the first data is greater than 0 (0 represents the set state of charge difference threshold, which can be 20%~100%), the total charging time is greater than P (P represents the set duration threshold, which can be 10min~30min), the displayed state of charge of the last data is greater than Q (Q represents the set end state of charge difference threshold, which can be 95%~100%), the ratio of the number of current jumps in this charge to the total number of current jumps in all charging groups is less than E (E represents the set jump ratio threshold, which can be 0~20%), the positions of the highest and second highest single cells are greater than 1 or the lowest single cell voltage is greater than R (R represents the set low voltage threshold, which can be 2.5V~3.65V). It should be noted that, under normal circumstances, the positions of the highest and second highest cells should be adjacent. If the positions of the highest and second highest cells are greater than 1, it indicates that there is a charging end jump, and the data corresponding to this situation should be excluded.

[0079] Step two: After obtaining the charging scenario data, calculate the health status of the power system for a charging group.

[0080] 1. Calculate the true state of charge (SOC) of the highest-valued cell at the start of this charging cycle. 高始 And the lowest true state of charge (SOC) of a single cell at the start of charging 低始 .

[0081] 1) Extract the first R (10~100) data entries of the charging group and determine whether the charging current of this charging is greater than or equal to the set charging current threshold A1. If it is greater than or equal to, proceed to steps 3)~4); otherwise, proceed to step 2).

[0082] 2) Based on the highest single-cell voltage V of the last data entry in this charging group. z高 and lowest single-cell voltage V z低 Based on the set SOC-OCV relationship, the highest single-cell voltage V is compared with the last data point before the current charging group. z高 The corresponding state of charge is used as the true state of charge (SOC) of the highest-valued individual cell at the start of this charging process. 高始 The lowest single-cell voltage V will be compared with the last data entry before this charging group. z低 The corresponding state of charge is the lowest true state of charge (SOC) of a single cell at the start of this charging process. 低始 .

[0083] 3) From the first R data points, remove the portion with a current greater than A2 (A2 represents the set static current threshold). Divide the continuous data into segments, identify the longest segment (this time needs to be greater than 2 minutes), and take the voltage of the last data point in the longest segment as the static voltage. Calculate the true SOC based on the SOC-OCV relationship. That is, the voltage V of the highest single-cell voltage in the last data point of the charge / discharge data segment is used as the static voltage. 静高 And the SOC-OCV relationship, to determine the highest single-cell voltage V of the last data point. 静高 The corresponding highest static voltage and true state of charge (SOC) 静高 Based on the lowest single-cell voltage V in the last data point of this charge / discharge data segment. 静低 And the SOC-OCV relationship, to determine the lowest single-cell voltage V of the last data point. 静低 The corresponding lowest static voltage and true state of charge (SOC) 静低 .

[0084] 4) Because the last data entry in step 3) will be charged and discharged between the start time of charging of the charging group, it is necessary to compensate for the state of charge (SOC) to obtain the true SOC of the lowest individual cell at the start of charging. 低始 And the highest true state of charge (SOC) of a single cell at the start of charging 高始 The specific method is as follows:

[0085] SOC 高始 =SOC 静高 +(SOC) 1显 -SOC 静显 SOC 低始 =SOC 静低 +(SOC) 1显 -SOC 静显 )

[0086] In the formula, SOC 静显 This indicates the displayed state of charge (SOC) of the last data point in a charge / discharge data segment during step 3). 1显 This indicates the displayed state of charge (SOC) of the first data entry in this charging group. The purpose of compensation in this step is as follows: because there may be charging and discharging activities between the static voltage value taking time and the charging start time, the SOC may change. Therefore, it is necessary to compensate for the SOC calculated based on the static voltage to ensure that the compensated SOC corresponds to the state before charging.

[0087] The following is a specific example to illustrate the detailed calculation process in steps 3) to 4). For example, regarding... Figure 3The data processing steps are as follows: ① According to the battery management system status, 16:49:14 is the first data point indicating the start of charging. Extract 30 discharge data points prior to this (from 16:38:14 to 16:47:54). ② Remove data points with an absolute current value greater than 5A (discharge is positive, charging is negative). All high currents are excluded to avoid polarization effects. Based on data continuity, the remaining data is divided into three parts: 16:40:14-16:41:54, 16:45:14-16:45:34, and 16:46:54:16:47:54. Note that a correct way to calculate the total duration is: subtract the time corresponding to the previous data point from the time of the last data point. For example, if the battery discharges at 15:00:00 with a current of 100A, discharges at 16:00:00 with a current of 0A, and starts charging at 16:00:20, then the preceding rest time is 1 hour. ③ Calculate the resting time for each segment, and select the segment with the longest resting time, which is 16:40:14-16:41:54 in this case. The highest single-cell voltage (3.17875) and the lowest single-cell voltage (3.15) at the end of this segment are selected as static voltages. According to the SOC-OCV curve, these are converted into the true SOC, corresponding to 15% and 14% respectively (example). ④ At this moment, the BMS displays a state of charge of 20.4%, while before charging, the BMS displays a state of charge of 19.2%. Therefore, the true state of charge (SOC) corresponding to the highest single-cell voltage before charging is... 高始 The lowest possible SOC (State of Charge) corresponds to a single cell and is 15%+ (19.2%-20.4%). 低始 The percentage is: 14% + (19.2% - 20.4%).

[0088] 2. Calculate the charging capacity C for this charge. N .

[0089] 1) Based on the time interval between two adjacent data points Based on the charging current, the charging capacity C between adjacent time points corresponding to two adjacent data points is calculated. x For details on the calculation method, please refer to the "4) Capacity Calculation" section of "3. Calculation of Key Variables" in Step 1.

[0090] 2) Sum the charging capacities between all adjacent time points to obtain the charging capacity for that charge. .

[0091] 3) Calculate the difference between the state of charge at the start of charging and the state of charge of the previous data entry, define this as the compensation capacity, and add it to the calculated charging capacity. The purpose of this compensation is to prevent capacity calculation errors caused by data loss in the early stages of charging. Specifically:

[0092] In practice, data loss may occur at the beginning of charging, so compensation is needed. This means that even though data is missing, the difference in SOC between the two data points can be used to replenish the lost charging capacity. Replenished capacity = Rated capacity (SOC at the start of charging - SOC before charging).

[0093] When the data is normal and there are no missing data, the SOC at the start of charging is equal to the SOC of the previous charge, so the replenished capacity is 0.

[0094] 3. Calculate the health status (SOH) of the highest-ranking monomer. 单 :

[0095]

[0096] In the formula, C 额 This indicates the rated capacity of the highest-ranking unit.

[0097] 4. Calculate the consistency coefficient:

[0098]

[0099] 5. Calculate the State of Health (SOH) of the power system. 系统 :

[0100]

[0101] 6. Based on the State of Health (SOH) of the power system 系统 Calculate vehicle usage time t:

[0102]

[0103] In the formula, k1 and k2 both represent usage time parameters. As can be seen from this formula, the definition of usage time here is not the current time minus the manufacturing or sales date, because inaccurate time and battery replacement render this method of calculating usage time meaningless. Mileage also suffers from similar issues with battery replacement and mileage reset. Instead, usage time is determined using health status. Specifically, the two usage time parameters are determined as follows: ① Obtain multiple sets of different usage times and different health status data for the power system, and take the health status data that appears most frequently for a certain usage time as the corresponding health status. For example, based on the health status distribution approximately every year (±0.2), determine what the actual health status of most vehicles should be. For instance, based on the statistical distribution, (0.988, 0.93) means that the most frequent SOH corresponding to 0.988 years (approximately one year) is 0.93. The maximum probability correspondence between the actual year and SOH is obtained based on the statistical data. ② Using different usage times and their corresponding health status data, the formula is... The time parameters k1 and k2 are obtained by fitting and solving. In this embodiment, k1=0.6484 and k2=0.07414.

[0104] 7. Then, based on the usage time t, calculate the new SOC-OCV relationship:

[0105]

[0106]

[0107]

[0108] In the formula, SOC represents the state of charge corresponding to the static voltage OCV, and A1, A2, B1, and B2 all represent aging parameters.

[0109] 8. After obtaining the new SOC-OCV relationship, repeat steps 1-5 of step two to obtain the latest state of charge (SOH) of the power system. 系统 This approach is taken because the SOC-OCV relationship curves of new and old batteries differ to some extent, such as... Figure 4 As shown, this method uses the SOC-OCV relationship curve that varies with usage time to address the impact of battery aging on calculation accuracy.

[0110] The health status error distribution calculated using the method of this invention is as follows: Figure 2 As shown, the test range exceeded 40,000 cycles, with ±4% coverage of 87% of vehicles, and a weighted accuracy of 2.13% (weighted accuracy is the sum of the absolute value of the error multiplied by the corresponding percentage). Figure 5 The diagram shows the annual variation of the SOC-OCV curve and its current deviation distribution. This diagram is based on the assumption that, within a short period (3 months) at normal temperature, the calculated SOH deviation for the same vehicle should not be too large, in order to evaluate the overall results of the method of this invention. The maximum SOH minus the minimum SOH over 3 months is defined as the SOH deviation for each vehicle. A distribution diagram of the SOH deviation is plotted for all vehicles, as shown below. Figure 5 As shown in the diagram, after each iteration of the algorithm, the deviation distribution of SOH before and after the iteration is compared to determine the improvement effect of the algorithm. Moreover, the closer the deviation distribution is to the y-axis, the better the overall quality of the method.

[0111] In summary, this method has the following characteristics: 1) It extracts charging data based on battery state bits, identifies a single charging process, calculates key variables in the charging process, and filters the scenarios. 2) It identifies and extracts static voltage data before charging, solving the problem of identifying battery static voltage, and converts it into the corresponding true state of charge based on the SOC-OCV curve, compensating for state of charge loss and charging data loss to ensure the accuracy of health state calculation. 3) It performs aging processing to correct the impact of SOC-OCV relationship curve aging on the calculated health state value. 4) Overall, it achieves high-precision health state calculation for power systems, which can be used in the core pricing model of power system insurance business and early warning of abnormal vehicle degradation.

[0112] Device Example:

[0113] An embodiment of the power system health status calculation device of the present invention, such as... Figure 6 As shown, the system includes a memory, a processor, and an internal bus. The processor and memory communicate and exchange data with each other via the internal bus. The memory includes at least one software function module stored in the memory. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby implementing the power system health status calculation method described in the method embodiment of the present invention.

[0114] The processor can be a microprocessor (MCU), a programmable logic device (FPGA), or other processing devices. The memory can be any type of memory that stores information using electrical energy, such as RAM and ROM; it can also be any type of memory that stores information using magnetic energy, such as hard disks, floppy disks, magnetic tapes, magnetic core memory, bubble memory, and USB flash drives; it can also be any type of memory that stores information using optical methods, such as CDs and DVDs; and of course, it can also be other types of memory, such as quantum memory and graphene memory.

Claims

1. A power system health state calculation method, characterized by, Includes the following steps: 1) Obtain multiple charging and discharging data corresponding to different times of the power system. Each charging and discharging data includes charging / discharging time, displayed state of charge, charging / discharging current, highest single-cell voltage and lowest single-cell voltage. Extract the charging scenario data that meets the requirements from it. The charging scenario data includes multiple charging groups. The data of one charging group is the data of one full charge. 2) For a charging group, perform the following calculations: According to each time and the corresponding charging current, the charging capacity C of the charging is determined N ; If the charging current is greater than or equal to the set charging current threshold A1, extract multiple charging and discharging data points preceding this charging group, and select the segment of charging and discharging data where the discharging current is less than the set static current threshold A2 and has the longest duration. Then, based on the highest single-cell voltage V of the last data point in this segment... 静高 / Minimum unit voltage V 静低 And the SOC-OCV relationship, to determine the highest single-cell voltage V of the last data point. 静高 / Minimum unit voltage V 静低 The corresponding highest static voltage and true state of charge (SOC) 静高 / Minimum static voltage True state of charge (SOC) 静低 The true state of charge (SOC) of the highest-charged individual cell at the start of this charging cycle is calculated using the following formula. 高始 And the lowest true state of charge (SOC) of a single cell at the start of charging 低始 : SOCIETY 高始 =SOC 静高 +(SOC 1显 -SOC 静显 ), SOC 低始 =SOC 静低 +(SOC 1显 -SOC 静显 ) In the formula, SOC 静显 This indicates the displayed state of charge (SOC) of the last data point in the aforementioned charge / discharge data segment. 1显 This indicates the displayed charge status of the first data entry in this charging group; 3) Calculate the health status (SOH) of the highest-ranking monomer using the following formula. 单 : C 额 Indicates the rated capacity of the highest-ranking single unit; 4) Calculate the state of health (SOH) of the power system using the following formula. 系统 : k 一致性 k represents the consistency coefficient. 一致性 =100%-SOC 高始 -SOC 低始 .

2. The method for calculating the health status of a power system according to claim 1, characterized in that, It also includes steps 5) to 6). 5) Correct the SOC-OCV relationship using the following formula: In the formula, SOC represents the state of charge corresponding to the static voltage OCV, A1, A2, B1, and B2 all represent aging parameters, and t represents the usage time. 6) Using the corrected SOC-OCV relationship, re-execute steps 2) to 4) to obtain the corrected health state (SOH) of the power system. 系统 .

3. The method for calculating the health status of a power system according to claim 2, characterized in that, The usage time t is calculated using the following formula: In the formula, k1 and k2 both represent the usage time parameter, and SOH represents the health status of the power system, which is the health status of the power system obtained in step 4).

4. The method for calculating the health status of a power system according to claim 3, characterized in that, The time parameters k1 and k2 are determined as follows: Acquire multiple sets of power system data for different usage times and different health states, and take the health state data that appears most frequently for a certain usage time as the health state corresponding to that usage time. Using different usage times and corresponding health status data, the formula was analyzed. The time parameters k1 and k2 are obtained by fitting the solution.

5. The method for calculating the health status of a power system according to claim 4, characterized in that, k1=0.6484, k2=0.07414.

6. The method for calculating the health status of a power system according to claim 1, characterized in that, In step 2), if the charging current is less than the set charging current threshold A1, the highest single-cell voltage V is used based on the last data from the previous charging group. z高 / Minimum unit voltage V z低 And the SOC-OCV relationship, will be related to the highest single-cell voltage V in the last data before this charging group. z高 / Minimum unit voltage V z低 The corresponding state of charge is used as the true state of charge (SOC) of the highest-valued individual cell at the start of this charging process. 高始 / Minimum true state of charge (SOC) of a single cell at the start of charging 低始 .

7. The method for calculating the health status of a power system according to claim 1, characterized in that, In step 1), the requirement includes at least one of the following: Requirement 1: The ratio of the number of current fluctuations in this charge to the total number of current fluctuations in all charging groups is less than the set fluctuation ratio threshold; fluctuation refers to the absolute value of the difference between the charging current of a data and the charging current of the previous data being greater than the set current deviation threshold. Requirement 2: The positions of the highest and second highest voltage cells are greater than 1, or the voltage of the lowest voltage cell is greater than the set low voltage threshold. Requirement 3: The total charging time of a charging group is greater than the set time threshold. Requirement 4: The difference between the displayed state of charge of the last data entry and the displayed state of charge of the first data entry in a charging group is greater than the set state of charge difference threshold. Requirement 5: The displayed state of charge of the last data entry in a charging group is greater than the set threshold for the difference between the end state of charge and the end state of charge.

8. The method for calculating the health status of a power system according to claim 1, characterized in that, In step 2), the charging capacity C for this charge is determined. N The method is as follows: ① Calculate the charging capacity C between adjacent time points corresponding to two adjacent data points based on the two adjacent data points. x ② Add up the charging capacity between all adjacent time points to obtain the charging capacity C of that charge. N ; The method used in step ① is as follows: if the interval time Δt corresponding to two adjacent data points is less than the set low threshold for adjacent time, then the charging capacity between adjacent moments corresponding to the two adjacent data points is the charging current multiplied by the interval time Δt; if the interval time corresponding to two adjacent data points is greater than the set high threshold for adjacent time and the state of charge ΔSOC corresponding to the two adjacent data points is less than the set state of charge threshold, then the charging capacity between adjacent moments corresponding to the two adjacent data points is the charging current multiplied by 10 seconds, and the set low threshold for adjacent time is less than the set high threshold for adjacent time; otherwise, the charging capacity between adjacent moments corresponding to the two adjacent data points is the average value of the charging current corresponding to the two data points multiplied by the interval time Δt.

9. The method for calculating the health status of a power system according to claim 2, characterized in that, A1=5.962E-18, A2=-0.4201, B1=13.19, B2=0.009756.

10. A power system health status calculation device, characterized in that, The system includes a memory and a processor, wherein the processor executes instructions stored in the memory to implement a power system health state calculation method, including the following steps: 1) Obtain multiple charging and discharging data corresponding to different times of the power system. Each charging and discharging data includes charging / discharging time, displayed state of charge, charging / discharging current, highest single-cell voltage and lowest single-cell voltage. Extract the charging scenario data that meets the requirements from it. The charging scenario data includes multiple charging groups. The data of one charging group is the data of one full charge. 2) For a charging group, perform the following calculations: Based on the charging current at each time point, determine the charging capacity C for that charging session. N ; If the charging current is greater than or equal to the set charging current threshold A1, extract multiple charging and discharging data points preceding this charging group, and select the segment of charging and discharging data where the discharging current is less than the set static current threshold A2 and has the longest duration. Then, based on the highest single-cell voltage V of the last data point in this segment... 静高 / Minimum unit voltage V 静低 And the SOC-OCV relationship, to determine the highest single-cell voltage V of the last data point. 静高 / Minimum unit voltage V 静低 The corresponding highest static voltage and true state of charge (SOC) 静高 / Minimum static voltage True state of charge (SOC) 静低 The true state of charge (SOC) of the highest-charged individual cell at the start of this charging cycle is calculated using the following formula. 高始 And the lowest true state of charge (SOC) of a single cell at the start of charging 低始 : SOCIETY 高始 =SOC 静高 +(SOC 1显 -SOC 静显 ), SOC 低始 =SOC 静低 +(SOC 1显 -SOC 静显 ) In the formula, SOC 静显 This indicates the displayed state of charge (SOC) of the last data point in the aforementioned charge / discharge data segment. 1显 This indicates the displayed charge status of the first data entry in this charging group; 3) Calculate the health status (SOH) of the highest-ranking monomer using the following formula. 单 : C 额 Indicates the rated capacity of the highest-ranking single unit; 4) Calculate the state of health (SOH) of the power system using the following formula. 系统 : k 一致性 k represents the consistency coefficient. 一致性 =100%-SOC 高始 -SOC 低始 .

11. The power system health status calculation device according to claim 10, characterized in that, It also includes steps 5) to 6). 5) Correct the SOC-OCV relationship using the following formula: In the formula, SOC represents the state of charge corresponding to the static voltage OCV, A1, A2, B1, and B2 all represent aging parameters, and t represents the usage time. 6) Using the corrected SOC-OCV relationship, re-execute steps 2) to 4) to obtain the corrected health state (SOH) of the power system. 系统 .

12. The power system health state computing apparatus according to claim 11, wherein The usage time t is calculated using the following formula: In the formula, k1 and k2 both represent the usage time parameter, and SOH represents the health status of the power system, which is the health status of the power system obtained in step 4).

13. The power system health state computing apparatus according to claim 12, characterized by, The time parameters k1 and k2 are determined as follows: Acquire multiple sets of power system data for different usage times and different health states, and take the health state data that appears most frequently for a certain usage time as the health state corresponding to that usage time. The usage time parameters k1 and k2 are obtained by fitting the formula using different usage time and corresponding health state data.

14. The power system health state computing apparatus according to claim 13, wherein k1=0.6484, k2=0.07414.

15. The power system health state computation apparatus according to claim 10, wherein In step 2), if the charging current is less than the set charging current threshold A1, the highest single-cell voltage V is used based on the last data from the previous charging group. z高 / Minimum unit voltage V z低 And the SOC-OCV relationship, will be related to the highest single-cell voltage V in the last data before this charging group. z高 / Minimum unit voltage V z低 The corresponding state of charge is used as the true state of charge (SOC) of the highest-valued individual cell at the start of this charging process. 高始 / Minimum true state of charge (SOC) of a single cell at the start of charging 低始 .

16. The power system health state computation apparatus according to claim 10, wherein In step 1), the requirement includes at least one of the following: Requirement 1: The ratio of the number of current fluctuations in this charge to the total number of current fluctuations in all charging groups is less than the set fluctuation ratio threshold; fluctuation refers to the absolute value of the difference between the charging current of a data and the charging current of the previous data being greater than the set current deviation threshold. Requirement 2: The positions of the highest and second highest voltage cells are greater than 1, or the voltage of the lowest voltage cell is greater than the set low voltage threshold. Requirement 3: The total charging time of a charging group is greater than the set time threshold. Requirement 4: The difference between the displayed state of charge of the last data entry and the displayed state of charge of the first data entry in a charging group is greater than the set state of charge difference threshold. Requirement 5: The displayed state of charge of the last data entry in a charging group is greater than the set threshold for the difference between the end state of charge and the end state of charge.

17. The power system health state computation apparatus according to claim 10, wherein In step 2), the charging capacity C for this charge is determined. N The method is as follows: ① Calculate the charging capacity C between adjacent time points corresponding to two adjacent data points based on the two adjacent data points. x ② Add up the charging capacity between all adjacent time points to obtain the charging capacity C of that charge. N ; The method used in step ① is as follows: if the interval time Δt corresponding to two adjacent data points is less than the set low threshold for adjacent time, then the charging capacity between adjacent moments corresponding to the two adjacent data points is the charging current multiplied by the interval time Δt; if the interval time corresponding to two adjacent data points is greater than the set high threshold for adjacent time and the state of charge ΔSOC corresponding to the two adjacent data points is less than the set state of charge threshold, then the charging capacity between adjacent moments corresponding to the two adjacent data points is the charging current multiplied by 10 seconds, and the set low threshold for adjacent time is less than the set high threshold for adjacent time; otherwise, the charging capacity between adjacent moments corresponding to the two adjacent data points is the average value of the charging current corresponding to the two data points multiplied by the interval time Δt.

18. The power system health state computation apparatus according to claim 11, wherein, A1=5.962E-18, A2=-0.4201, B1=13.19, B2=0.009756.

Images