SOC charging terminal correction method

Abstract

The invention provides an SOC charging end correction method, and relates to the technical field of battery management, and the method comprises the steps: testing the dynamic voltage and internal resistance characteristics under different temperatures and multiplying powers, building an SOC-OCV curve, combining the temperature and multiplying power internal resistance coefficients, dynamically adjusting the SOC calibration voltage of the charging end, and optimizing the SOC change rate through employing a differentiated ampere-hour integral coefficient, thereby achieving the correction of the SOC charging end. Meanwhile, environment adaptability compensation, battery health monitoring, a user feedback interface and multi-cell consistency calibration are integrated, the system robustness and the user experience are improved, dynamic voltage and internal resistance characteristics under different temperatures and multiplying powers are tested through Sp1 to Sp3, an SOC-OCV curve established by Sp4 is combined, a differential calibration strategy of high and low SOC working conditions is introduced into Sp7, and the system robustness and the user experience are improved. And the SOC calibration voltage at the charging tail end is dynamically adjusted, so that the condition that the SOC directly jumps to 100% is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of battery management, and specifically to a method for correcting the end of SOC charging. Background Art

[0002] With the popularization of electric vehicles, the role of the battery management system (BMS) in improving vehicle performance and user experience has become increasingly prominent. As the core parameter reflecting the remaining capacity of the battery, SOC not only directly affects the prediction of the driving range of electric vehicles but is also closely related to the user's charging experience. Accurate SOC calculation can help users clearly perceive the change in battery power, reasonably plan trips and charging arrangements, thereby enhancing the overall usage experience.

[0003] Although the existing technologies have made certain progress in the calculation of SOC of electric vehicle power batteries and the calibration at the end of charging, the following problems still exist in actual applications, affecting the user's perception of battery power and charging experience:

[0004] SOC jumps to 100% when charging is completed:

[0005] The existing SOC calculation methods are prone to cumulative errors during long-term operation, resulting in a deviation between the estimated value of SOC and the actual value. At the end of charging, the system often directly calibrates SOC to 100% after detecting that the voltage or current reaches a certain fixed threshold. For example, SOC may suddenly jump from 98% to 100% when charging is nearly completed. This sudden change makes the user's perceived change in battery power discontinuous and difficult to accurately judge the reliability of the remaining battery power. Users may thus misjudge the prediction of the driving range, affecting trip planning. In addition, this jump may mask the true error of SOC estimation, resulting in a deviation in the driving range prediction during subsequent discharge, further reducing the user experience.

[0006] SOC waits too long at 99%:

[0007] In the constant current-constant voltage charging strategy at the end of charging, after entering the constant voltage stage, the charging current gradually decreases until it reaches the cut-off current. Since the SOC update rate is directly related to the charging current, the SOC increment becomes very slow when the current is small. This results in SOC possibly staying at 99% for a long time and requires a long waiting time (sometimes up to 30 minutes or more) to finally reach 100%. For example, in some electric vehicles, users may find that SOC has stayed at 99% for more than 20 minutes and the charging has not been completed yet. This phenomenon makes users feel that the charging efficiency is low. Especially in a fast-paced usage scenario, users show obvious dissatisfaction with the long waiting time, seriously affecting the charging experience.

[0008] Therefore, a method for correcting the end of SOC charging is needed to solve the above problems. Summary of the Invention

[0009] Technical problem to be solved

[0010] In view of the deficiencies of the prior art, the present invention provides a method for correcting the end of SOC charging, which solves the problems in the above background art.

[0011] Technical solution

[0012] To achieve the above object, the present invention is realized through the following technical solutions: A method for correcting the end of SOC charging, the method tests the dynamic voltage and internal resistance characteristics at different temperatures and rates, establishes an SOC-OCV curve, combines the temperature and rate internal resistance coefficients, dynamically adjusts the SOC calibration voltage at the end of charging, and uses a differential ampere-hour integration coefficient to optimize the SOC change rate. At the same time, it integrates environmental adaptability compensation, battery health monitoring, user feedback interface and multi-cell consistency calibration to improve system robustness and user experience. The method includes the following steps:

[0013] Sp1. Starting from 80% SOC at different temperatures, perform constant current charging at the last stage rate of the charging MAP ladder charging strategy corresponding to the temperature, and extract the dynamic voltages at different SOCs (90-100) at different temperatures;

[0014] Sp2. At 25°C, starting from 80% SOC, test constant current charging at different rates (0.2C, 0.333C, 1C) until the charging cut-off voltage, and then perform constant voltage charging until 0.05C, and record voltage and current data;

[0015] Sp3. At 25°C, starting from 80% SOC, test constant current charging at different temperatures (10°C, 25°C, 45°C) at 0.333C until the charging cut-off voltage, and then perform constant voltage charging until 0.05C, and record voltage and current data;

[0016] Sp4. Establish a charging SOC-OCV curve at 25°C for subsequent internal resistance calculation;

[0017] Sp5. Calculate the internal resistance at the end of charging at different rates (0.2C, 0.333C, 1C) at 25°C, and the calculation formula is:

[0018] Res2 = (CCV2 - OCV) ÷ Cur2

[0019] Where CCV2 is the voltage collected in Sp2, Cur2 is the current collected in Sp2, and OCV is the OCV in the SOC-OCV curve in Sp4;

[0020] Sp6. Calculate the internal resistance at the end of charging at 0.333C at different temperatures (10°C, 25°C, 45°C), and the calculation formula is:

[0021] Res3 = (CCV3 - OCV) ÷ Cur3

[0022] Where CCV is the voltage collected in Sp3, Cur is the current collected in Sp3, and OCV is the OCV in the SOC-OCV curve in Sp4;

[0023] Sp7. Determine the charging end correction conditions for high and low SOC conditions, and perform SOC correction based on the voltage corresponding to the calibration point. At the same time, dynamically adjust the calibration parameters in combination with environmental humidity and atmospheric pressure data;

[0024] Sp8. Adjust the SOC change rate through the ampere-hour integration coefficient, and display the SOC correction progress in real time through the user feedback interface;

[0025] Sp9. Perform multi-cell consistency calibration at the charging end, and ensure the SOC balance of the battery pack by fine-tuning the charging current of each cell;

[0026] Sp10. Use the SOC correction data for battery health monitoring, and record the change trend of the internal resistance at the charging end to evaluate the battery aging state.

[0027] Preferably, the internal resistance coefficients at different rates at 25 °C are calculated in Sp5, and the formula is:

[0028] Ratefact 0.2C = Res 0.2C ÷Res 0.333C ,Ratefact 1C = Res 1C ÷Res 0.333C

[0029] Where Ratefact 0.2C is the internal resistance coefficient at 0.2C rate, Ratefact 1C is the internal resistance coefficient at 1C rate, Res 0.2C is the 0.2C internal resistance, Res 1C is the 1C internal resistance, which is used for subsequent dynamic adjustment of the charging internal resistance.

[0030] Preferably, the internal resistance coefficients at 0.333C at different temperatures are calculated in Sp6, and the formula is:

[0031] Ratefact 10 = Res 10 ÷Res 25 ,Ratefact 45 = Res 45 ÷Res 25

[0032] Where Ratefact 10Internal resistance coefficient at 10°C, Ratefact 45 Internal resistance coefficient at 45°C, Res 10 Internal resistance during charging at 10°C ÷ 0.333C, Res 45 Internal resistance during charging at 45°C ÷ 0.333C.

[0033] Preferably, the correction conditions for the high SOC condition in Sp7 include: minimum acquisition temperature ≥ 0°C, charging current < rated capacity + 0.02C + 2A, cell voltage < voltage corresponding to the SOC calibration point, SOC > SOC calibration point, where the SOC calibration point is [95, 96, 97, 98, 99, 100].

[0034] Preferably, the voltage calculation scheme for the SOC calibration point in the high SOC condition of Sp7 is as follows:

[0035] Voltage corresponding to the SOC calibration point = last - stage charging dynamic correction voltage look - up table (Tmin, SOC calibration point - fixed difference)+(charging current - last - stage charging current at current temperature)×charging internal resistance;

[0036] Charging internal resistance = charging internal resistance look - up table (SOC calibration point - fixed difference)×temperature internal resistance coefficient look - up table (Tmin)×multiplication factor internal resistance coefficient (charging current ÷ rated capacity); Tmin is the minimum acquisition temperature of the battery management system, SOC calibration point = [95, 96, 97, 98, 99, 100], fixed difference = [5310.10.10.1], and the fixed difference is set to prevent mis - calibration.

[0037] Preferably, the correction conditions for the low SOC condition in Sp7 include: minimum acquisition temperature ≥ 0°C, charging current > last - stage charging current + 0.02C + 2A, cell voltage > voltage corresponding to the SOC calibration point, SOC < SOC calibration point - fixed difference.

[0038] Preferably, the voltage calculation scheme for the SOC calibration point in the low SOC condition of Sp7 is as follows:

[0039] Voltage corresponding to the SOC calibration point = last - stage charging dynamic correction voltage look - up table (Tmin, SOC calibration point)+(charging current - last - stage charging current at current temperature)×charging internal resistance;

[0040] Charging internal resistance = charging internal resistance look - up table (Tmin, SOC calibration point)×temperature internal resistance coefficient look - up table (Tmin)×multiplication factor internal resistance coefficient (charging current ÷ rated capacity);

[0041] Tmin is the minimum acquisition temperature of the battery management system, SOC calibration points = [95, 96, 97, 98, 99, 100], fixed differences = [5310.10.10.1], and the fixed differences are set to prevent incorrect calibration.

[0042] Preferably, in the case of high SOC in Sp8, the ampere-hour integration coefficient is 0.2, and the SOC rises at a rate of 0.2 × ampere-hour integration; in the case of low SOC, the ampere-hour integration coefficient is 2.5, and the SOC rises at a rate of 2.5 × ampere-hour integration; the user feedback interface displays the SOC correction status and the estimated time to complete charging through the vehicle dashboard and the mobile application.

[0043] Preferably, in Sp9, the multi-cell consistency calibration dynamically distributes the charging current by real-time monitoring the voltage and SOC differences of each cell, ensuring that the SOC deviation of each cell in the battery pack is less than 0.5%, and improving the overall performance and life of the battery pack.

[0044] Preferably, in Sp10, the battery health monitoring generates a battery aging assessment report by analyzing the change trend of the internal resistance at the end of charging over time, and prompts maintenance suggestions through the user feedback interface; the charging internal resistance is calculated by looking up a table and an internal resistance coefficient, and the formula is:

[0045]

[0046] Where Cur is the current, AhFactor is the ampere-hour integration coefficient, T is the calculation period in seconds, and Cap is the rated capacity of the battery.

[0047] Beneficial Effects

[0048] The present invention provides a method for correcting the SOC at the end of charging. It has the following beneficial effects:

[0049] 1. The present invention tests the dynamic voltage and internal resistance characteristics at different temperatures and rates through Sp1 to Sp3, and combines the SOC-OCV curve established by Sp4. In Sp7, a differential calibration strategy for high and low SOC conditions is introduced to dynamically adjust the SOC calibration voltage at the end of charging, avoiding the situation where the SOC directly jumps to 100%. For example, when the SOC is high, the system gradually adjusts the SOC according to the voltage corresponding to the calibration point, avoiding the sudden change phenomenon of directly jumping from 98% to 100%; when the SOC is low, Sp8 adopts a differential ampere-hour integration coefficient (such as a coefficient of 2.5 in the low condition), accelerating the SOC rising rate, effectively shortening the waiting time of the SOC at 99% (from more than 20 minutes in the traditional method to 5 - 10 minutes), making the SOC change smoother, and the user perceives a continuous and reasonable change in the battery level, significantly improving the charging experience.

[0050] 2. The present invention calculates the internal resistance at the end of charging at different temperatures and rates through Sp5 and Sp6, and combines the internal resistance coefficients in Tables 4 and 5 to dynamically adjust the calibration parameters, solving the problem in the prior art that fixed thresholds are difficult to adapt to changes in working conditions. For example, during high-rate (1C) charging at low temperature (10°C), the system adjusts the calibration voltage according to the internal resistance coefficients (the 1C rate coefficient is 1.2, and the 10°C temperature coefficient is 1.1) to avoid underestimation of SOC calibration; during low-rate (0.2C) charging at high temperature (45°C), the internal resistance coefficients (the 0.2C rate coefficient is 0.8, and the 45°C temperature coefficient is 0.9) ensure that the SOC calibration is not overestimated. In addition, the environmental adaptability coefficient introduced in Supplementary Suggestion 2 (considering humidity and atmospheric pressure) further improves the adaptability of the system in extreme environments (such as high-altitude areas), enabling the SOC calibration to maintain high precision under different working conditions and significantly enhancing the stability and reliability of SOC calculation.

[0051] 3. The present invention integrates a user feedback interface in Sp8, and real-time displays the SOC correction progress and the estimated time to complete charging through the vehicle dashboard and mobile application, solving the problem of insufficient user feedback in the prior art. For example, when the SOC is at 99%, the system will display "SOC is being corrected, and it is estimated that the charging will be completed in 5 minutes", allowing users to clearly understand the reason for waiting and avoiding anxiety caused by long stays. In addition, Supplementary Suggestion 4 introduces a function to predict the SOC change trend, predicts the SOC change trend through historical data and real-time working conditions, and presents the results to users (such as "It is estimated that the SOC will reach 100% in 10 minutes"), further enhancing the user's perception of the battery level. This intuitive feedback mechanism significantly improves the user's trust in the SOC display and enhances the overall charging experience.

[0052] 4. The present invention uses Sp10 to monitor the battery health through SOC correction data and the change trend of the internal resistance at the end of charging, solving the problem in the prior art that it is difficult to adapt to aging batteries. For example, the system records the change of the internal resistance over time (such as the internal resistance increasing from 0.003 ohms to 0.005 ohms), and combines Supplementary Suggestion 8 to predict the remaining battery life (for example, there are 500 remaining cycles), providing scientific maintenance suggestions for users (such as "It is recommended to check the battery after 200 cycles"). In addition, Sp5 and Sp6 adapt to changes in working conditions at different temperatures and rates by dynamically adjusting the internal resistance coefficients, ensuring the accuracy of the SOC calibration for aging batteries. This strategy that comprehensively considers battery aging and changes in working conditions not only improves the long-term reliability of SOC calculation, but also extends the battery life and enhances the robustness of the system.

[0053] 5. The present invention introduces multi-cell consistency calibration in Sp9. By real-time monitoring the SOC differences of each cell and dynamically adjusting the charging current, it ensures that the SOC deviation within the battery pack is less than 0.5%, solving the problem of cell inconsistency in the prior art. For example, when the SOC of cell 1 is 99% and the SOC of cell 2 is 98.4%, the system finely tunes the charging current of cell 2 to 35A and that of cell 1 to 31A. After 5 minutes, the deviation is reduced to 0.3%. In addition, Supplementary Suggestion 3 improves the charging efficiency by optimizing the charging current distribution and reducing energy loss (such as reducing the charging loss by 10%). This consistency calibration not only optimizes the overall performance of the battery pack but also extends its service life, providing users with more reliable power support. Description of the Drawings

[0054] Figure 1 It is a schematic diagram for correcting the high-SOC working condition of the present invention;

[0055] Figure 2 It is a schematic diagram for correcting the low-SOC working condition of the present invention;

[0056] Figure 3 It is a test schematic diagram of the present invention;

[0057] Figure 4 It is a running step diagram of the present invention. Detailed Description of the Invention

[0058] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention. Specific Embodiment 1:

[0060] As Figures 1 to 4 shown, a method for correcting the end of SOC charging. The method tests the dynamic voltage and internal resistance characteristics at different temperatures and rates, establishes the SOC-OCV curve, combines the temperature and rate internal resistance coefficients, dynamically adjusts the SOC calibration voltage at the end of charging, and optimizes the SOC change rate using a differential ampere-hour integration coefficient. At the same time, it integrates environmental adaptability compensation, battery health monitoring, user feedback interface, and multi-cell consistency calibration to improve the system robustness and user experience. The method includes the following steps:

[0061] Sp1. Starting from 80% SOC at different temperatures, perform constant-current charging at the last-stage rate according to the charging MAP step charging strategy corresponding to the temperature, and extract the dynamic voltage at different SOCs (90 - 100) at different temperatures, as shown in Table 1 specifically:

[0062] Table 1

[0063]

[0064]

[0065] Sp2. At 25°C, starting from 80% SOC, test constant current charging at different rates (0.2C, 0.333C, 1C) until the charging cut-off voltage, then constant voltage charging until 0.05C, and record the voltage and current data;

[0066] Sp3. At 25°C, starting from 80% SOC, test constant current charging at different temperatures (10°C, 25°C, 45°C) at 0.333C until the charging cut-off voltage, then constant voltage charging until 0.05C, and record the voltage and current data;

[0067] Sp4. Establish the charging SOC-OCV curve at 25°C for subsequent internal resistance calculation, as shown in Table 2 specifically:

[0068] Table 2 SOC-OCV of Lithium Iron Phosphate Battery Core during Charging

[0069]

[0070] Sp5. Calculate the internal resistance at the end of charging at different rates (0.2C, 0.333C, 1C) at 25°C. The calculation formula is:

[0071] Res2 = (CCV2 - OCV) ÷ Cur2

[0072] Where CCV2 is the voltage collected in Sp2, Cur2 is the current collected in Sp2, OCV is the OCV in the SOC-OCV curve in Sp4, and the charging internal resistance at 25°C / 0.333C is shown in Table 3;

[0073] Table 3 Charging Internal Resistance (25°C / 0.333C)

[0074]

[0075] Sp6. Calculate the internal resistance at the end of charging at 0.333C at different temperatures (10°C, 25°C, 45°C). The calculation formula is:

[0076] Res3 = (CCV3 - OCV) ÷ Cur3

[0077] Where CCV is the voltage collected in Sp3, Cur is the current collected in Sp3, and OCV is the OCV in the SOC-OCV curve in Sp4;

[0078] Sp7. Determine the charging end correction conditions for high and low SOC conditions, perform SOC correction based on the voltage corresponding to the calibration point, and dynamically adjust the calibration parameters in combination with environmental humidity and atmospheric pressure data;

[0079] Sp8. Adjust the SOC change rate through the ampere-hour integration coefficient and display the SOC correction progress in real time through the user feedback interface;

[0080] Sp9. Perform multi-cell consistency calibration at the charging end to ensure the SOC balance of the battery pack by fine-tuning the charging current of each cell;

[0081] Sp10. Use the SOC correction data for battery health monitoring, record the change trend of the internal resistance at the charging end to evaluate the battery aging state.

[0082] In Sp5, calculate the internal resistance coefficients at different rates at 25°C. The formula is:

[0083] Ratefact 0.2C =Res 0.2C ÷Res 0.333C ,Ratefact 1C =Res 1C ÷Res 0.333C

[0084] Where Ratefact 0.2C is the internal resistance coefficient at 0.2C rate, Ratefact 1C is the internal resistance coefficient at 1C rate, Res 0.2C is the internal resistance at 0.2C, Res 1C is the internal resistance at 1C, which is used for the dynamic adjustment of the charging internal resistance later. The rate internal resistance coefficients are shown in Table 4:

[0085] Table 4 Internal Resistance Coefficients

[0086]

[0087] In Sp6, calculate the internal resistance coefficient at 0.333C at different temperatures. The formula is:

[0088] Ratefact 10 =Res 10 ÷Res 25 ,Ratefact 45 =Res 45 ÷Res 25

[0089] Where Ratefact 10 is the internal resistance coefficient at 10°C, Ratefact 45 is the internal resistance coefficient at 45°C, Res 10is the charging internal resistance at 10°C ÷ 0.333C, Res 45 is the charging internal resistance at 45°C ÷ 0.333C. The temperature internal resistance coefficient is shown in Table 5:

[0090] Table 5 Internal Resistance Coefficient

[0091]

[0092] The correction conditions for the high SOC condition in Sp7 include: the minimum acquisition temperature ≥ 0°C, the charging current < rated capacity + 0.02C + 2A, the single cell voltage < the voltage corresponding to the SOC calibration point, SOC > the SOC calibration point, where the SOC calibration point is [95, 96, 97, 98, 99, 100].

[0093] The calculation scheme for the voltage corresponding to the SOC calibration point in the high SOC condition of Sp7 is as follows:

[0094] The voltage corresponding to the SOC calibration point = the last stage charging dynamic correction voltage look-up table (Tmin, SOC calibration point - fixed difference) + (charging current - the last stage charging current at the current temperature) × charging internal resistance;

[0095] The charging internal resistance = the charging internal resistance look-up table (SOC calibration point - fixed difference) × the temperature internal resistance coefficient look-up table (Tmin) × the multiple internal resistance coefficient (charging current ÷ rated capacity); Tmin is the minimum acquisition temperature of the battery management system, the SOC calibration point = [95, 96, 97, 98, 99, 100], the fixed difference = [5310.10.10.1], and the fixed difference is set to prevent mis-calibration.

[0096] The correction conditions for the low SOC condition in Sp7 include: the minimum acquisition temperature ≥ 0°C, the charging current > the last stage charging current + 0.02C + 2A, the single cell voltage > the voltage corresponding to the SOC calibration point, SOC < the SOC calibration point - fixed difference.

[0097] The calculation scheme for the voltage corresponding to the SOC calibration point in the low SOC condition of Sp7 is as follows:

[0098] The voltage corresponding to the SOC calibration point = the last stage charging dynamic correction voltage look-up table (Tmin, SOC calibration point) + (charging current - the last stage charging current at the current temperature) × charging internal resistance;

[0099] The charging internal resistance = the charging internal resistance look-up table (Tmin, SOC calibration point) × the temperature internal resistance coefficient look-up table (Tmin) × the multiple internal resistance coefficient (charging current ÷ rated capacity);

[0100] Tmin is the minimum acquisition temperature of the battery management system, SOC calibration points = [95, 96, 97, 98, 99, 100], fixed differences = [5310.10.10.1], and the fixed differences are set to prevent mis-calibration.

[0101] In Sp8, when the SOC is in a high condition, the ampere-hour integration coefficient is 0.2, and the SOC rises at a rate of 0.2 × ampere-hour integration; when the SOC is in a low condition, the ampere-hour integration coefficient is 2.5, and the SOC rises at a rate of 2.5 × ampere-hour integration; the user feedback interface displays the SOC correction status and the estimated time to complete charging through the vehicle dashboard and the mobile application.

[0102] In Sp9, the multi-cell consistency calibration dynamically distributes the charging current by real-time monitoring the voltage and SOC differences of each cell, ensuring that the SOC deviation of each cell in the battery pack is less than 0.5%, and improving the overall performance and life of the battery pack.

[0103] In Sp10, the battery health monitoring generates a battery aging assessment report by analyzing the changing trend of the internal resistance at the end of charging over time, and prompts maintenance suggestions through the user feedback interface; the charging internal resistance is calculated by looking up a table and an internal resistance coefficient, and the formula is:

[0104]

[0105] Where Cur is the current, AhFactor is the ampere-hour integration coefficient, T is the calculation period in seconds, and Cap is the rated capacity of the battery. Specific Embodiment 2:

[0107] As Figures 1 to 4 shown, based on the content in the above specific embodiments, the following content is further disclosed:

[0108] When the SOC at the end of charging is high, the corrected SOC can smoothly follow the true SOC and reach 100 simultaneously when full, avoiding the situation where the SOC waits for a long time at 99% to complete charging, as shown in Figure 1.

[0109] When the SOC at the end of charging is low, the corrected SOC can smoothly follow the true SOC and reach 100 simultaneously when full, avoiding the situation where the SOC jumps to 100 when charging is completed, as Figure 2 shown.

[0110] The following is a supplementary design for the above content, and the specific content is as follows:

[0111] Introduce machine learning to optimize the SOC-OCV curve and the internal resistance model

[0112] Supplementary content: On the basis of Sp4 and Sp5, add a step to dynamically update the SOC-OCV curve and internal resistance model by using historical test data (such as dynamic voltage, internal resistance, SOC, etc.) and real-time collected data through machine learning algorithms (such as neural networks or support vector machines).

[0113] Specific steps:

[0114] Sp4.1: Collect historical data under multiple groups of different temperatures, rates, and SOCs to construct a training dataset.

[0115] Sp4.2: Use a machine learning model (such as a BP neural network) to fit the SOC-OCV relationship and the law of internal resistance change to generate a dynamic SOC-OCV curve and an internal resistance prediction model.

[0116] Sp4.3: During actual operation, combine the real-time collected data such as voltage, current, and temperature to dynamically update the model parameters and improve the accuracy of SOC calibration.

[0117] Compared with static look-up tables, the dynamic model can adapt to factors such as battery aging and operating conditions changes, further improving the accuracy and robustness of SOC calibration.

[0118] Expand environmental adaptability to handle extreme operating conditions:

[0119] Supplementary content: In Sp7, add an adaptive calibration strategy for extreme environments (such as high altitude, low temperature and high humidity).

[0120] Specific steps:

[0121] Sp7.1: Test the SOC-OCV curve and internal resistance characteristics under high altitude (low air pressure) and low temperature and high humidity (-20°C, 90% humidity) operating conditions and record the data.

[0122] Sp7.2: Introduce an environmental adaptability coefficient K env , and dynamically adjust the calibration parameters according to the air pressure P, humidity H, and temperature T:

[0123] K env = f(P, H, T)

[0124] where f can be obtained by experimental fitting.

[0125] Sp7.3: Apply K env to the voltage calculation formula for the SOC calibration point:

[0126] V 校准点 = V 查表 + (I 充电 - I 最后一阶 ) × R 充电 × K env

[0127] By introducing an environmental adaptability coefficient, the robustness of the system in extreme environments is enhanced, making it applicable to a wider range of application scenarios (such as high-altitude areas and extremely cold regions).

[0128] Optimize the charging efficiency and reduce energy loss:

[0129] Supplementary content: In Sp9, a charging efficiency optimization strategy is added. By dynamically adjusting the charging current and voltage, energy loss is reduced.

[0130] Specific steps:

[0131] Sp9.1: During the multi-cell consistency calibration, the internal resistance and temperature of each cell are monitored in real time, and the energy loss during the charging process is calculated:

[0132]

[0133] where I i , R i are the charging current and internal resistance of the i-th cell respectively, and Δt is the time step.

[0134] Sp9.2: Through an optimization algorithm (such as genetic algorithm or particle swarm optimization), the charging current of each cell is dynamically adjusted with the goal of minimizing the total energy loss while meeting the constraint that the SOC deviation is less than 0.5%.

[0135] While ensuring the SOC consistency, optimize the charging efficiency, extend the battery life, reduce energy consumption, and enhance the green and energy-saving characteristics of the system. Specific Example Three:

[0137] As Figures 1 to 4 shown, according to the content in the above specific examples, the following specific usage cases are provided:

[0138] Usage Case 1: Charging SOC Calibration of Electric Vehicles in Low-Temperature Environments

[0139] Scenario: An electric vehicle is charging in a low-temperature environment in winter. The initial SOC is 80%, and the user hopes to charge quickly and ensure the accuracy of the SOC.

[0140] Case Description:

[0141] Environment and Working Conditions:

[0142] Temperature: 10°C (the lowest acquisition temperature is 10°C); charging rate: 1C (fast charging); initial SOC: 80%; environmental humidity: 70%, atmospheric pressure: 1010 hPa.

[0143] Scheme Application:

[0144] Sp1: Look up Table 1 (the last-stage charging dynamic correction voltage meter). At 10°C and with an SOC of 95%, the dynamic voltage is 3.445V.

[0145] Sp4: Look up Table 2 (SOC-OCV curve). At 25°C and with an SOC of 95%, the OCV is 3.410V.

[0146] Sp5&Sp6: Calculate the charging internal resistance:

[0147] Look up Table 3 (25°C / 0.333C internal resistance). At an SOC of 95%, the internal resistance is 0.00363553 ohms.

[0148] Look up Table 4 (multiplier internal resistance coefficient). The 1C multiplier coefficient is 1.2.

[0149] Look up Table 5 (temperature internal resistance coefficient). The 10°C temperature coefficient is 1.1.

[0150] After comprehensive adjustment, the charging internal resistance is 0.00479990 ohms.

[0151] Sp7 (Supplemental Suggestion 2): Considering environmental factors (humidity 70%, atmospheric pressure 1010 hPa), the adjustment coefficient is 1.0203, and the final internal resistance is adjusted to 0.00489727 ohms.

[0152] Sp7: SOC calibration (assuming SOC is too high):

[0153] The current SOC is 96%, the single-cell voltage is 3.450V, and the charging current is 100A (rated capacity 100Ah, 1C).

[0154] The calibration point SOC is 95%, the fixed difference is 5. Look up Table 1 (at 10°C and SOC of 90%), the voltage is 3.420V.

[0155] The calculated calibration point voltage is 3.747087V.

[0156] Condition check: The lowest temperature ≥ 0°C (met), the charging current < 102A (not met), the single-cell voltage < 3.747087V (met), SOC > 95% (met).

[0157] It is determined to be an SOC-too-high operating condition.

[0158] Sp8: Adjust the SOC change rate:

[0159] Use an ampere-hour integration coefficient of 0.2, and the SOC rises at a slower rate.

[0160] The user feedback interface displays: "SOC is being corrected. Current SOC: 96%. Estimated charging completion time: 15 minutes."

[0161] Sp9: Multi-cell consistency calibration:

[0162] It is detected that the SOC of cell 1 is 96% and the SOC of cell 2 is 95.2%, with a deviation greater than 0.5%.

[0163] Fine-tune the charging current of cell 2 to 105 A and the current of cell 1 drops to 95 A. After 5 minutes, the deviation is reduced to 0.3%.

[0164] Sp10: Battery health monitoring:

[0165] Record that the internal resistance at the end of charging is 0.00489727 ohms, which is 5% higher than last month, indicating that the battery is slightly aged and suggesting regular inspection to the user.

[0166] Effect:

[0167] After SOC calibration, it is corrected from 96% to 95% to avoid overestimation.

[0168] Multi-cell consistency calibration improves the performance of the battery pack and extends its lifespan.

[0169] Users can understand the charging progress through the interface and have a better experience.

[0170] Use Case 2: SOC Calibration of Energy Storage System in High Temperature Environment

[0171] Scenario: A photovoltaic energy storage system is charging in a high temperature environment in summer. The initial SOC is 85%, and it is necessary to ensure the accuracy of SOC to optimize energy management.

[0172] Case description:

[0173] Environment and working conditions:

[0174] Temperature: 45 °C (the lowest acquisition temperature is 45 °C)

[0175] Charging rate: 0.2C (slow charging)

[0176] Initial SOC: 85%

[0177] Ambient humidity: 50%, atmospheric pressure: 1013 hPa

[0178] Scheme application:

[0179] Sp1: Refer to Table 1. At 45 °C, when the SOC is 98%, the dynamic voltage is 3.420 V.

[0180] Sp4: Refer to Table 2. At 25 °C, when the SOC is 98%, the OCV is 3.420 V.

[0181] Sp5&Sp6: Calculate the charging internal resistance:

[0182] Referring to Table 3, when the SOC is 98%, the internal resistance is 0.00499576 ohms.

[0183] Referring to Table 4, the 0.2C rate coefficient is 0.8.

[0184] Referring to Table 5, the temperature coefficient at 45°C is 0.9.

[0185] After comprehensive adjustment, the charging internal resistance is 0.00359695 ohms.

[0186] Sp7 (Supplemental Suggestion 2): Environmental factors (humidity 50%, atmospheric pressure 1013 hPa), the adjustment coefficient is 1, and the final internal resistance remains unchanged.

[0187] Sp7: SOC calibration (assuming the SOC is low):

[0188] The current SOC is 97%, the single-cell voltage is 3.425 V, and the charging current is 20 A (rated capacity 100 Ah, 0.2C).

[0189] The calibrated SOC is 98%, the fixed difference is 0.1, referring to Table 1 (at 45°C, SOC is 98%), the voltage is 3.420 V.

[0190] The calculated voltage at the calibration point is 3.421 V.

[0191] Condition check: The minimum temperature ≥ 0°C (satisfied), the charging current > 35.3 A (not satisfied), the single-cell voltage > 3.421 V (satisfied), SOC < 97.9% (satisfied).

[0192] It is determined to be a low SOC condition.

[0193] Sp8: Adjust the SOC change rate:

[0194] Use the ampere-hour integration coefficient of 2.5, and the SOC rises at a relatively fast rate.

[0195] The user feedback interface shows: "SOC is being corrected, current SOC: 97%, estimated charging completion time: 30 minutes."

[0196] Sp9: Multi-cell consistency calibration:

[0197] It is detected that the SOC of cell 1 is 97% and the SOC of cell 2 is 96.4%, and the deviation is greater than 0.5%.

[0198] Fine-tune the charging current of cell 2 to 22 A, and the current of cell 1 drops to 18 A. After 10 minutes, the deviation is reduced to 0.2%.

[0199] Sp10: Battery health monitoring:

[0200] The recorded internal resistance of the charging terminal is 0.00359695 ohms, which is 2% lower than the initial value, indicating that the internal resistance is normal at high temperatures and there is no obvious aging.

[0201] Effect:

[0202] After SOC calibration, it is corrected from 97% to 98% to avoid underestimation.

[0203] The system runs stably in a high-temperature environment, and the accuracy of SOC is improved.

[0204] Calibration of the consistency of multiple battery cells ensures the efficient operation of the energy storage system.

[0205] Use Case 3: SOC Calibration of an Electric Motorcycle in an Extreme High-Altitude Environment

[0206] Scenario: An electric motorcycle is charging in a high-altitude area (low air pressure) with an initial SOC of 90%, and it needs to adapt to the extreme environment and ensure the accuracy of SOC.

[0207] Case Description:

[0208] Environment and Operating Conditions:

[0209] Temperature: 25°C (the lowest collected temperature is 25°C)

[0210] Charging rate: 0.333C (normal charging)

[0211] Initial SOC: 90%

[0212] Environmental humidity: 40%, atmospheric pressure: 800 hPa (high altitude)

[0213] Scheme Application:

[0214] Sp1: Refer to Table 1. At 25°C and an SOC of 99%, the dynamic voltage is 3.445 V.

[0215] Sp4: Refer to Table 2. At 25°C and an SOC of 99%, the OCV is 3.425 V.

[0216] Sp5&Sp6: Calculate the charging internal resistance:

[0217] Refer to Table 3. At an SOC of 99%, the internal resistance is 0.00474752 ohms.

[0218] Refer to Table 4. The 0.333C rate coefficient is 1.0.

[0219] Refer to Table 5. The 25°C temperature coefficient is 1.0.

[0220] After comprehensive adjustment, the charging internal resistance is 0.00474752 ohms.

[0221] Sp7 (Supplemental Recommendation 2): Environmental factors (humidity 40%, atmospheric pressure 800 hPa), adjustment coefficient is 1.0213, and the final internal resistance is adjusted to 0.00484777 ohms.

[0222] Sp7: SOC calibration (assuming SOC is on the high side):

[0223] The current SOC is 99.5%, the single-cell voltage is 3.440 V, and the charging current is 33.3 A (rated capacity 100 Ah, 0.333 C).

[0224] The calibrated SOC is 99%, the fixed difference is 0.1. Looking up Table 1 (at 25°C, SOC is 98.9%), the voltage is 3.444 V.

[0225] The calibrated voltage is calculated to be 3.444 V.

[0226] Condition check: Minimum temperature ≥ 0°C (met), charging current < 102 A (met), single-cell voltage < 3.444 V (met), SOC > 99% (met).

[0227] It is determined to be a high-SOC operating condition.

[0228] Sp8 (Supplemental Recommendation 4): Adjust the SOC change rate and predict:

[0229] Use an ampere-hour integration coefficient of 0.2, and the SOC rises at a slower rate.

[0230] Predict the SOC change trend, and it is expected that the SOC will be corrected to 99% after 10 minutes.

[0231] The user feedback interface shows: "SOC is being corrected. Current SOC: 99.5%. It is expected to be completed after 10 minutes."

[0232] Sp9: Multi-cell consistency calibration:

[0233] It is detected that the SOC of cell 1 is 99.5% and the SOC of cell 2 is 98.8%, and the deviation is greater than 0.5%.

[0234] Fine-tune the charging current of cell 2 to 35 A and the current of cell 1 to 31 A. After 8 minutes, the deviation is reduced to 0.4%.

[0235] Sp10 (Supplemental Recommendation 8): Battery health monitoring:

[0236] Record the internal resistance at the end of charging as 0.00484777 ohms, and predict the remaining battery life to be 500 cycles.

[0237] The user interface prompts: "The battery is in good health. It is recommended to check every 200 cycles."

[0238] Effect:

[0239] The SOC calibration is accurate in high altitude environments, corrected from 99.5% to 99%.

[0240] Environmental adaptability compensation ensures the normal operation of the system under low pressure.

[0241] The SOC prediction function enhances the user experience, and the battery life prediction provides maintenance suggestions.

[0242] Use Case 4: SOC Calibration of Portable Energy Storage Devices under Abnormal Conditions

[0243] Scenario: A portable energy storage device encounters over-temperature abnormality during charging. The initial SOC is 92%, and it is necessary to safely calibrate the SOC and protect the battery.

[0244] Case Description:

[0245] Environment and Conditions:

[0246] Temperature: 60°C (the lowest acquisition temperature is 60°C, over-temperature)

[0247] Charge rate: 0.333C

[0248] Initial SOC: 92%

[0249] Environmental humidity: 55%, atmospheric pressure: 1013 hPa

[0250] Solution Application:

[0251] Sp1: Refer to Table 1, use the data at 45°C (the highest available temperature). When the SOC is 96%, the dynamic voltage is 3.410 V.

[0252] Sp4: Refer to Table 2. When the SOC is 96%, the OCV is 3.413 V.

[0253] Sp5&Sp6: Calculate the charging internal resistance:

[0254] Refer to Table 3. When the SOC is 96%, the internal resistance is 0.00390919 ohm.

[0255] Refer to Table 4. The 0.333C rate coefficient is 1.0.

[0256] Refer to Table 5. The temperature coefficient at 45°C is 0.9 (no data at 60°C, estimated).

[0257] After comprehensive adjustment, the charging internal resistance is 0.00351827 ohm.

[0258] Sp7 (Supplementary Suggestion 2): Environmental factors (humidity 55%, atmospheric pressure 1013 hPa), adjustment factor is 1.005, final internal resistance is 0.00353586 ohms.

[0259] Sp7 (Supplementary Suggestion 5): Detect abnormal operating conditions:

[0260] The temperature is 60°C, exceeding the threshold of 60°C, and it is determined as overheating.

[0261] Stop charging, and the interface issues a warning: "The temperature is too high, charging has been paused. Please check the device."

[0262] Sp8: The SOC calibration is paused, and the user feedback interface shows: "SOC: 92%, charging paused. Please reduce the temperature and try again."

[0263] Sp9: The multi-cell consistency calibration is not performed because the charging has been paused.

[0264] Sp10: Battery health monitoring:

[0265] Record this abnormal operating condition, and recommend that the user check the cooling system to avoid long-term high-temperature operation.

[0266] Effect:

[0267] The overheating protection mechanism takes effect in a timely manner to avoid battery damage. The user can understand the reason for the abnormality through the interface, and the system security is improved. Charging can be resumed later and the SOC calibration can be completed.

[0268] The above four use cases demonstrate the application of the SOC charging end correction method in different scenarios:

[0269] Case 1: Fast charging of electric vehicles in low-temperature environments, with accurate SOC calibration and good user experience.

[0270] Case 2: Slow charging of energy storage systems in high-temperature environments, with stable system operation.

[0271] Case 3: Charging of electric motorcycles in high-altitude environments, with strong adaptability and improved experience through intelligent prediction.

[0272] Case 4: Protect the battery of portable devices under abnormal operating conditions, with high safety.

[0273] It should be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising a reference structure" does not exclude the presence of additional identical elements in the process, method, article or device comprising the element.

[0274] Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for correcting the end of SOC charging, characterized in that: The method establishes an SOC-OCV curve by testing the dynamic voltage and internal resistance characteristics at different temperatures and rates, combines the temperature and rate internal resistance coefficients, dynamically adjusts the SOC calibration voltage at the end of charging, and optimizes the SOC change rate using a differential ampere-hour integration coefficient. Meanwhile, it integrates environmental adaptability compensation, battery health monitoring, user feedback interface, and multi-cell consistency calibration to improve system robustness and user experience. The method includes the following steps: Sp1. Starting from 80% SOC at different temperatures, perform constant current charging at the last-stage rate of the charging MAP ladder charging strategy corresponding to the temperature, and extract the dynamic voltage at different SOC (90 - 100) at different temperatures. Sp2. At 25°C, starting from 80% SOC, test constant current charging at different rates (0.2C, 0.333C, 1C) until the charging cut-off voltage, and then perform constant voltage charging until 0.05C, and record the voltage and current data. Sp3. At 25°C, starting from 80% SOC, test constant current charging at 0.333C to the charging cut-off voltage at different temperatures (10°C, 25°C, 45°C), and then perform constant voltage charging until 0.05C, and record the voltage and current data. Sp4. Establish a charging SOC-OCV curve at 25°C for subsequent internal resistance calculation. Sp5. Calculate the internal resistance at the end of charging at different rates (0.2C, 0.333C, 1C) at 25°C. The calculation formula is: Res2 = (CCV2 - OCV) ÷ Cur2 Where CCV2 is the voltage collected in Sp2, Cur2 is the current collected in Sp2, and OCV is the OCV in the SOC-OCV curve in Sp4. Sp6. Calculate the internal resistance at the end of charging at 0.333C at different temperatures (10°C, 25°C, 45°C). The calculation formula is: Res3 = (CCV3 - OCV) ÷ Cur3 Where CCV is the voltage collected in Sp3, Cur is the current collected in Sp3, and OCV is the OCV in the SOC-OCV curve in Sp4. Sp7. Judge the charging end correction conditions for high and low SOC conditions, and perform SOC correction according to the voltage corresponding to the calibration point. Meanwhile, dynamically adjust the calibration parameters in combination with environmental humidity and atmospheric pressure data. Sp8. Adjust the SOC change rate through the ampere-hour integration coefficient, and display the SOC correction progress in real time through the user feedback interface. Sp9. Perform multi-cell consistency calibration at the end of charging, and ensure the SOC balance of the battery pack by finely adjusting the charging current of each cell. Sp10. Use the SOC correction data for battery health monitoring, and record the change trend of the internal resistance at the end of charging to evaluate the battery aging state.

2. The method for correcting the end of SOC charging according to claim 1, characterized in that: The internal resistance coefficient at different rates at 25°C calculated in Sp5 has the formula: Ratefact 0.2C = Res 0.2C ÷ Res 0.333C , Ratefact 1C = Res 1C ÷ Res 0.333C Among them, Ratefact 0.2C is the internal resistance coefficient at a rate of 0.2C, and Ratefact 1C is the internal resistance coefficient at a rate of 1C. Res 0.2C is the internal resistance at 0.2C, and Res 1C is the internal resistance at 1C, which is used for the dynamic adjustment of the charging internal resistance in the following steps.

3. A method for correcting the end of SOC charging according to claim 1, characterized in that: The internal resistance coefficient at 0.333C at different temperatures calculated in Sp6 has the formula: Ratefact 10 = Res 10 ÷ Res 25 , Ratefact 45 = Res 45 ÷ Res 25 Among them, Ratefact 10 is the internal resistance coefficient at 10°C, Ratefact 45 is the internal resistance coefficient at 45°C, Res 10 is the charging internal resistance at 10°C÷0.333C, Res 45 is the charging internal resistance at 45°C÷0.333C.

4. The SOC charging end correction method according to claim 1, characterized in that: The correction conditions for the high SOC operating condition in Sp7 include: the minimum acquisition temperature ≥ 0°C, the charging current < rated capacity + 0.02C + 2A, the cell voltage < the voltage corresponding to the SOC calibration point, and SOC > the SOC calibration point, where the SOC calibration point is [95, 96, 97, 98, 99, 100].

5. A method for correcting the end of SOC charging according to claim 1, characterized in that: The calculation scheme for the voltage corresponding to the SOC calibration point in the high SOC operating condition of Sp7 is as follows: The voltage corresponding to the SOC calibration point = the last-stage charging dynamic correction voltage look-up table (Tmin, SOC calibration point - fixed difference) + (charging current - the last-stage charging current at the current temperature) × charging internal resistance; The charging internal resistance = the charging internal resistance look-up table (SOC calibration point - fixed difference) × the temperature internal resistance coefficient look-up table (Tmin) × the rate internal resistance coefficient (charging current ÷ rated capacity); Tmin is the minimum acquisition temperature of the battery management system, the SOC calibration point = [95, 96, 97, 98, 99, 100], and the fixed difference = [5310.10.10.1]. The fixed difference is set to prevent mis-calibration.

6. A method for correcting the end of SOC charging according to claim 1, characterized in that: The correction conditions for the low SOC operating condition in Sp7 include: the minimum acquisition temperature ≥ 0°C, the charging current > the last-stage charging current + 0.02C + 2A, the cell voltage > the voltage corresponding to the SOC calibration point, and SOC < the SOC calibration point - fixed difference.

7. A method for correcting the end of SOC charging according to claim 1, characterized in that: The calculation scheme for the voltage corresponding to the SOC calibration point in the low SOC operating condition of Sp7 is as follows: The voltage corresponding to the SOC calibration point = the last-stage charging dynamic correction voltage look-up table (Tmin, SOC calibration point) + (charging current - the last-stage charging current at the current temperature) × charging internal resistance; The charging internal resistance = the charging internal resistance look-up table (Tmin, SOC calibration point) × the temperature internal resistance coefficient look-up table (Tmin) × the rate internal resistance coefficient (charging current ÷ rated capacity); Tmin is the minimum acquisition temperature of the battery management system, the SOC calibration point = [95, 96, 97, 98, 99, 100], and the fixed difference = [5310.10.10.1]. The fixed difference is set to prevent mis-calibration.

8. A method for correcting the end of SOC charging according to claim 1, characterized in that: In Sp8, the ampere-hour integration coefficient for the high SOC operating condition is 0.2, and the SOC rises at a rate of 0.2 × ampere-hour integration; the ampere-hour integration coefficient for the low SOC operating condition is 2.5, and the SOC rises at a rate of 2.5 × ampere-hour integration; the user feedback interface displays the SOC correction status and the estimated charging completion time through the vehicle dashboard and the mobile application.

9. A method for correcting the end of SOC charging according to claim 1, characterized in that: In Sp9, the multi-cell consistency calibration dynamically distributes the charging current by real-time monitoring the voltage and SOC differences of each cell.

10. A method for correcting the end of SOC charging according to claim 1, characterized in that: In Sp10, the battery health monitoring generates a battery aging assessment report by analyzing the changing trend of the charging end internal resistance over time, and prompts maintenance suggestions through the user feedback interface; The charging internal resistance is calculated by look-up table and internal resistance coefficient, and the formula is: where Cur is the current, AhFactor is the ampere-hour integration coefficient, T is the calculation period in units of S, and Cap is the battery rated capacity.

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