Improved power battery SOC estimation method

Abstract

The invention discloses an improved power battery SOC (State of Charge) estimation method, which comprises the following steps of: placing a power battery in a standing state, and starting a detection unit when the standing time reaches a preset standing time threshold value Yt; the detection unit calculates an OCV calculated value OCV1 of the power battery; judging whether the OCV1 meets a stability condition or not, and performing stability evaluation; if the OCV calculated value OCV1 meets the stability condition, calculating a theoretical residual electric quantity value SOC1 of the power battery; the detection unit obtains an SOC estimated value SOC2 of the power battery from a battery management system BMS; the detection unit compares the theoretical residual electric quantity value SOC1 of the power battery with the SOC estimated value SOC2, and calculates to obtain an SOC corrected deviation value SOC3; and the detection unit controls the battery management system BMS to carry out correction to obtain an SOC correction value SOC4, and outputs and displays the SOC correction value SOC4 as the current residual electric quantity. The improved power battery SOC estimation method has the advantages that the influence degree of fluctuation of terminal voltage on SOC estimation can be reduced, and the accuracy and reliability of SOC correction are improved.

Description

Technical Field

[0001] The present invention relates to a battery remaining power measurement technology, in particular to an improved method for estimating the state of charge (SOC) of a power battery. Background Art

[0002] A power battery is a power source that provides power for tools, mostly referring to the storage battery that provides power for electric vehicles, electric trains, electric bicycles, and golf carts. In the field of electric transportation, the state of charge (SOC) of a power battery, as the core characterization parameter of the remaining energy of the battery, is not only the direct basis for users to evaluate the endurance ability, but also the key input for the battery management system (BMS) to achieve optimal energy distribution, charge and discharge control, and safety warning. SOC is the ratio of the remaining capacity of the storage battery after being used for a period of time or left unused for a long time to its capacity in a fully charged state, usually expressed as a percentage, with a value range of 0 to 1 (100%); when SOC = 0, it means that the battery is completely discharged and the remaining power is 0; when SOC = 1, it means that the battery is fully charged.

[0003] With the popularization of new energy transportation tools such as electric vehicles, users' demands for the real-time performance, accuracy, and environmental adaptability of estimating the state of charge (SOC) of power batteries are also increasing day by day. However, limited by the complex electrochemical characteristics of the battery and the interference of dynamic working conditions, traditional SOC estimation methods face multiple challenges in practical applications. In the actual use scenario of electric vehicles, SOC estimation needs to take into account high accuracy and low computational resource consumption. The existing SOC estimation methods mainly include the ampere-hour integration method and the open-circuit voltage method.

[0004] The ampere-hour integration method is a method for calculating the SOC of a battery by accumulating the integral of the battery current. Although the ampere-hour integration method is simple to use and has strong real-time performance, it has obvious defects. The small drift of the current sensor and the non-linear change of the battery efficiency will cause the estimation error of SOC to accumulate over time, and the error may exceed 10% after long-term use. In addition, the capacity of the power battery is affected by multiple factors such as temperature, number of cycles, charge and discharge rate, etc. The traditional linear model is difficult to accurately describe its non-linear relationship, while the high-order polynomial or machine learning model is limited by the computing power and storage resources of the microcontroller. These factors together make it difficult for the ampere-hour integration method to achieve high-precision SOC estimation.

[0005] The open-circuit voltage method (OCV) provides high-precision estimation through the OCV-SOC curve of the mapping relationship between the open-circuit voltage of the power battery and the SOC. However, this method relies on the long-term static state of the battery to eliminate the polarization effect, which is seriously out of touch with the actual scenario of short-term parking by users. In addition, battery aging will significantly change the characteristics of the OCV-SOC curve. For example, after 1000 cycles of a ternary lithium battery, the OCV curve shift can reach 20 - 40 mV, resulting in the failure of the correction method based on the factory calibration data. Therefore, the OCV method is difficult to achieve fast and accurate SOC estimation under dynamic working conditions and battery aging conditions, which limits its popularization in practical applications.

[0006] In addition, many problems are also exposed during the SOC correction process. Currently, most of the existing SOC correction methods rely on the terminal voltage data under the static condition. However, in the actual working condition, the terminal voltage fluctuates frequently and is extremely unstable, which leads to certain errors during the SOC correction. Moreover, the existing methods consider relatively single SOC correction factors and are difficult to accurately adapt to the complex and changeable actual application scenarios. Summary of the Invention

[0007] The present invention aims to avoid the deficiencies in the above-mentioned existing technologies and provides an improved method for estimating the SOC of a power battery to reduce the influence of the fluctuation of the terminal voltage on the SOC estimation, improve the accuracy and reliability of the SOC correction, and ensure the safe and stable operation of the battery system.

[0008] The present invention adopts the following technical solutions to solve the technical problems.

[0009] An improved method for estimating the SOC of a power battery according to the present invention includes the following steps:

[0010] Step 1: Place the power battery in a static state and start timing; when the time for the power battery to be in the static state reaches the preset static time threshold Yt, start the detection unit;

[0011] Step 2: The detection unit obtains the terminal voltage loss value U of the power battery in the battery management system BMS, and then calculates the OCV calculated value OCV1 of the power battery according to the terminal voltage loss value U of the power battery;

[0012] Step 3: Determine whether the OCV calculated value OCV1 obtained in Step 2 meets the stability condition and conduct a stability evaluation;

[0013] Step 4: If the OCV calculated value OCV1 meets the stability condition, the detection unit calculates the theoretical remaining power value SOC1 of the power battery according to the OCV-SOC curve;

[0014] Step 5: The detection unit obtains the SOC estimation value SOC2 of the power battery from the battery management system BMS;

[0015] Step 6: The detection unit compares the theoretical remaining power value SOC1 and the SOC estimation value SOC2 of the power battery, and calculates to obtain the SOC correction deviation value SOC3;

[0016] Step 7: The detection unit controls the battery management system BMS to perform correction according to the SOC correction deviation value SOC3 to obtain the SOC correction value SOC4, outputs the SOC correction value SOC4 and displays it as the current remaining power.

[0017] The structural feature of an improved SOC estimation method for power batteries of the present invention also lies in:

[0018] Further, in the step 1, the time for the power battery to be in a static state is 2 hours.

[0019] Further, in the step 2, during the process that the detection unit obtains the power battery terminal voltage loss value U in the battery management system BMS, the detection unit detects the power battery terminal voltage loss value U within two consecutive preset periods, and calculates the OCV calculated value OCV1 through the terminal voltage values detected within two consecutive preset periods.

[0020] Further, in the step 3, by comparing the difference between the terminal voltage loss values measured by the detection unit within two consecutive preset periods with the preset voltage value U Y to determine whether the OCV calculated value OCV1 meets the stability condition.

[0021] Further, in the step 3, before detecting the power battery terminal voltage loss value U within two consecutive preset periods, first determine whether the terminal voltage values within two consecutive preset periods are reasonable.

[0022] Further, in the step 6, the calculation formula of the SOC correction deviation value SOC3 is shown in the following formula (4);

[0023] SOC3 = SOC1 - SOC2 (4).

[0024] In the formula (4), SOC1 is the theoretical remaining power value of the power battery, and SOC2 is the SOC estimation value.

[0025] Further, in the step 7, before correcting the SOC, first compare the SOC correction deviation value SOC3 with the first preset power value Qpre, and correct the SOC according to the comparison result.

[0026] Further, in step 7, before correcting the SOC, the capacity of the power battery is calibrated first.

[0027] Further, after calibrating the capacity of the power battery, a working condition test is carried out for auxiliary correction.

[0028] Further, in step 7, before calibrating the capacity of the power battery, the charging current curve of the power battery under the constant current charging condition at different temperatures is obtained first.

[0029] Compared with the prior art, the beneficial effects of the present invention are embodied in:

[0030] The present invention discloses an improved method for estimating the SOC of a power battery, including the following steps: placing the power battery in a static state, and starting the detection unit when the static state reaches the preset static time threshold Yt; the detection unit calculates the OCV calculated value OCV1 of the power battery; judging whether OCV1 meets the stability condition for stability evaluation; if the OCV calculated value OCV1 meets the stability condition, calculating the theoretical remaining power value SOC1 of the power battery; the detection unit obtains the SOC estimated value SOC2 of the power battery from the battery management system BMS; the detection unit compares the theoretical remaining power value SOC1 and the SOC estimated value SOC2 of the power battery, and calculates to obtain the SOC correction deviation value SOC3; the detection unit controls the battery management system BMS to perform correction to obtain the SOC correction value SOC4 and outputs and displays it as the current remaining power.

[0031] The improved method for estimating the SOC of the power battery of the present invention has the advantages of being able to reduce the influence degree of the voltage fluctuation at the terminal on the SOC estimation, improving the accuracy and reliability of the SOC correction, etc. Description of the Drawings

[0032] Figure 1 It is a flowchart of an improved method for estimating the SOC of a power battery of the present invention.

[0033] Figure 2 It is a flowchart of the calculation and stability judgment of OCV1 in an improved method for estimating the SOC of a power battery of the present invention.

[0034] Figure 3 It is a flowchart of the rationality judgment of the terminal voltage value in an improved method for estimating the SOC of a power battery of the present invention.

[0035] Figure 4 It is a flowchart of the correction in an improved method for estimating the SOC of a power battery of the present invention.

[0036] Figure 5 It is a flowchart of multiple corrections in an improved method for estimating the SOC of a power battery of the present invention.

[0037] Figure 6 It is a flowchart for battery capacity calibration and working condition test of an improved method for estimating the state of charge (SOC) of a power battery according to the present invention.

[0038] Figure 7 It is a flowchart of the charging current curve under the constant current charging working condition of the battery of an improved method for estimating the state of charge (SOC) of a power battery according to the present invention at different temperatures.

[0039] Figure 8 It is a flowchart for plotting the curve table of temperature, SOC and battery internal resistance R of the target battery of an improved method for estimating the state of charge (SOC) of a power battery according to the present invention at different temperatures to obtain the internal resistance of the target battery.

[0040] Figure 9 It is a flowchart for SOC correction of an improved method for estimating the state of charge (SOC) of a power battery according to the present invention.

[0041] The present invention will be further described below through specific embodiments in conjunction with the accompanying drawings. Specific Embodiments

[0042] See Figures 1 to 9 , an improved method for estimating the state of charge (SOC) of a power battery according to the present invention, includes the following steps:

[0043] Step 1: Place the power battery in a static state and start timing; when the time for the power battery to be in a static state reaches the preset static time threshold Yt, start the detection unit;

[0044] Step 2: The detection unit obtains the terminal voltage loss value U of the power battery in the battery management system BMS, and then calculates the OCV calculated value OCV1 of the power battery according to the terminal voltage loss value U of the power battery.

[0045] After the power battery is placed in a static state for a certain period of time, start measuring the terminal voltage loss value of the power battery.

[0046] Step 3: Determine whether the OCV calculated value OCV1 obtained in Step 2 meets the stability condition for stability evaluation.

[0047] Step 4: If the OCV calculated value OCV1 meets the stability condition, the detection unit calculates the theoretical remaining power value SOC1 of the power battery according to the OCV-SOC curve.

[0048] Step 5: The detection unit obtains the SOC estimated value SOC2 of the power battery from the battery management system BMS.

[0049] Specifically, the detection unit reads the SOC estimated value SOC2 stored therein from the battery management system BMS through the upper computer.

[0050] Step 6: The detection unit compares the theoretical remaining power value SOC1 and the SOC estimated value SOC2 of the power battery, and calculates to obtain the SOC correction deviation value SOC3;

[0051] In the present invention, the SOC correction deviation value SOC3 is calculated by formula (4).

[0052] Step 7: The detection unit controls the battery management system BMS to perform correction according to the SOC correction deviation value SOC3 to obtain the SOC correction value SOC4, outputs the SOC correction value SOC4 and displays it as the current remaining power.

[0053] Based on the SOC correction deviation value SOC3, the detection unit controls the BMS to correct the SOC of the power battery, so as to realize the approximation of the output current remaining power to the actual remaining power value in the power battery.

[0054] As Figure 1 shown, an improved method for estimating the SOC of a power battery according to the present invention corrects the SOC through the calculated SOC correction deviation value SOC3, obtains the SOC correction value SOC4, and displays the SOC correction value SOC4 as the current power. Through correction, the displayed remaining power is closer to the actual remaining power in the power battery, improving the accuracy of the remaining power of the power battery.

[0055] Specifically, in step 1, the time for the power battery to be in a static state is 2 hours.

[0056] Specifically, in step 2, during the process that the detection unit obtains the power battery terminal voltage loss value U in the battery management system BMS, the detection unit detects the power battery terminal voltage loss value U within two consecutive preset periods, and calculates the OCV calculated value OCV1 through the terminal voltage values detected within two consecutive preset periods.

[0057] As Figure 2 shown, the detection unit detects the terminal voltage U of the power battery within two consecutive preset periods.

[0058] During the detection process, the first terminal voltage loss value U1 of the power battery within the first preset period T1, the second terminal voltage loss value U2 within the second preset period T2, and the OCV calculated value OCV1 are obtained.

[0059] Within the first preset period T1, the first terminal voltage loss value U1 is calculated by the following formula (1).

[0060] U1 = U t1 -U t2 (1);

[0061] In the formula (1), U t1 is the terminal voltage value of the power battery at the start of the first preset period T1, and U t2 is the terminal voltage value of the power battery at the end of the first preset period T1.

[0062] Within the second preset period T2, the second terminal voltage loss value U2 is calculated by the following formula (2).

[0063] U2 = U t3 - U t4 (2);

[0064] In the formula (2), U t3 is the terminal voltage value of the power battery at the start of the second preset period T2, and U t4 is the terminal voltage value of the power battery at the end of the second preset period T2.

[0065] The calculated value OCV1 of the OCV of the power battery is calculated by the following formula (3).

[0066] OCV1 = (U t1 + U t3 + U t4 ) / 3 (3).

[0067] In specific implementation, in step 3, by comparing the difference between the terminal voltage loss values measured by the detection unit in two consecutive preset periods with the preset voltage value U Y to determine whether the calculated value OCV1 of the OCV meets the stability condition.

[0068] In specific calculation, by comparing the absolute value of the difference between the first terminal voltage loss value U1 and the second terminal voltage loss value U2, |U1 - U2|, with the preset voltage value U Y to determine the stability of the calculated value OCV1 of the OCV. If |U1 - U2| < U Y , it is determined that the stability of OCV1 is qualified; if |U1 - U2| ≥ U Y , it is determined that the stability of OCV1 is unqualified.

[0069] The value ranges of the preset periods T1 and T2 are from 1 millisecond to 10 milliseconds. The preset voltage value U Y is calculated by the formula U Y = Z * K; where Z is an empirical coefficient (generally taken as 2 mV), and K is the number of battery cells in the power battery. The calculation and stability judgment process of the calculated value OCV1 of the OCV is as Figure 2 shown.

[0070] In specific implementation, in step 3, before detecting the terminal voltage loss value U of the power battery within two consecutive preset cycles, first determine whether the terminal voltage values within two consecutive preset cycles are reasonable.

[0071] Before obtaining the OCV calculated value OCV1, the first terminal voltage loss value U1, and the second terminal voltage loss value U2, it is necessary to determine whether the terminal voltage values of the power battery at different times within two preset cycles are reasonable.

[0072] The process of judging the reasonableness of the terminal voltage value is as follows: The detection unit detects the terminal voltage value U of the power battery at the start of the first preset cycle t1 , the terminal voltage value U at the end of the first preset cycle t2 , the terminal voltage value U at the start of the second preset cycle t3 and the terminal voltage value U at the end of the second preset cycle t4 to determine whether they are all within the value range [U Y , U min , U max of the preset voltage value U

[0073] The minimum value U Y of the preset voltage value U min is calculated by the formula U min = a * K, where U min is the minimum value of the preset voltage value U Y , a is an empirical coefficient (in specific implementation, a can be taken as 2.5V), and K is the number of battery cells in the power battery. The maximum value U Y of the preset voltage value U max is calculated by the formula U max = b * K. Where U max is the maximum value of the preset voltage value U Y , b is an empirical coefficient (in specific implementation, b can be taken as 4.2 volts), and K is the number of battery cells in the power battery. If these terminal voltage values are all within the preset voltage range [U min , U max , it is determined that the terminal voltage values at different times within two preset cycles are all reasonable, and then the OCV calculated value OCV1 can be calculated based on these terminal voltage values at different times. Otherwise, it is determined that the terminal voltage values at different times within two preset cycles are unreasonable, and the corresponding detection steps are repeated. The flow chart of judging the reasonableness of the terminal voltage value is as Figure 3 shown.

[0074] In specific implementation, in step 6, the calculation formula of the SOC correction deviation value SOC3 is shown in the following formula (4);

[0075] SOC3 = SOC1 - SOC2 (4).

[0076] In the formula (4), SOC1 is the theoretical remaining power value of the power battery, and SOC2 is the SOC estimated value.

[0077] In specific implementation, in step 7, before correcting the SOC, first compare the SOC correction deviation value SOC3 with the first preset power value Qpre, and correct the SOC according to the comparison result.

[0078] When correcting the SOC, the detection unit compares the SOC correction deviation value SOC3 with the first preset power value Qpre, and determines the correction scheme according to the comparison situation.

[0079] Among them, the setting of the first preset power value Qpre needs to match the system accuracy requirements, and its value-taking basis includes but is not limited to the following two methods: "the minimum remaining power value displayed on the vehicle dashboard or 0.1% of the rated capacity of the power battery"; that is, the first preset power value Qpre can take the minimum remaining power value displayed on the vehicle dashboard, or 0.1% of the rated capacity of the power battery, or other similar methods can be adopted to define it.

[0080] (1) If the absolute value of the SOC correction deviation value SOC3 is not greater than the first preset power value, that is, ∣SOC3∣ = ∣SOC1 - SOC2∣ ≤ Qpre, the detection unit controls the battery management system BMS to use the sum of the SOC estimated value SOC2 and the SOC correction deviation value SOC3 as the SOC correction value SOC4, and complete the correction at one time, as shown in the following formula (5);

[0081] SOC4 = SOC2 + SOC3 (5)

[0082] (2) If the absolute value of the SOC correction deviation value SOC3 is greater than the first preset power value Qpre, that is, ∣SOC3∣ = ∣SOC1 - SOC2∣ > Qpre, the detection unit controls the battery management system BMS to correct the SOC of the power battery multiple times.

[0083] The single - correction formula for the multiple corrections is shown in the following formula (6).

[0084] SOC correction value SOC4 = SOC2 + △step (6);

[0085] In the formula (6), SOC4 is the corrected SOC correction value, SOC2 is the SOC estimated value, and △step is the single - correction amount for a single correction. Generally, the △step adopted for multiple corrections is a fixed value.

[0086] During multiple corrections, the sum of the single SOC correction values Δstep for each correction is equal to the SOC correction deviation value SOC3, and the absolute value of each single correction amount Δstep for each correction is not greater than the first preset power value Qpre, that is, Δstep ≤ Qpre and the sum of all Δstep for multiple corrections Δtotal = SOC3. Before the first correction, Δtotal = 0, and then Δtotal gradually increases after each correction until it reaches Δtotal = SOC3 at the last correction. This can avoid the sharp jump of the SOC of the power battery caused by too large a single correction power, affecting the execution of the vehicle's power strategy or causing vehicle safety accidents. The SOC correction strategy process is as Figure 4 shown.

[0087] During the process of multiple corrections, the detection unit controls the battery management system BMS to perform the first correction on the SOC of the power battery with a correction value Δstep whose absolute value is not greater than the first preset power value Qpre. Thereafter, the detection unit controls the battery management system BMS to complete subsequent corrections according to the SOC correction deviation value SOC3 and the received information on the stationary condition, charging condition, and discharging condition of the power battery.

[0088] When the SOC correction deviation value SOC3 is greater than zero, that is, SOC3 ≥ 0, when the power battery is in the charging condition, the detection unit controls the battery management system BMS to correct the SOC of the power battery every third preset time period until the sum of the SOC correction values Δstep for the cumulative corrections Δtotal is equal to the SOC correction deviation value SOC3, that is, Δtotal = SOC3, and the correction is completed; if during the correction process, the stationary time of the power battery in the stationary condition reaches the first preset time period, then return to recalculate the OCV calculation value OCV1 and subsequent steps.

[0089] When the SOC correction deviation value SOC3 is less than zero, when the power battery is in the discharging condition, the detection unit controls the battery management system BMS to correct the SOC of the power battery every fourth preset time period until the sum of the SOC correction values Δstep for the cumulative corrections Δtotal is equal to the SOC correction deviation value SOC3, that is, Δtotal = SOC3, and the correction is completed; if during the correction process, the stationary time of the power battery in the stationary condition reaches the first preset time period, similarly return to recalculate the OCV calculation value OCV1 and subsequent steps. The specific process of multiple corrections is as Figure 5 shown.

[0090] During specific implementation, in step 7, before correcting the SOC, the capacity of the power battery is calibrated first.

[0091] Step 7 of the present invention also includes a battery capacity calibration process and an auxiliary correction process for operating condition testing. Before performing SOC correction, the capacity calibration of the power battery is first performed to obtain more accurate battery capacity information. The battery capacity calibration process includes environmental adaptation, standard charging, standard discharge and capacity calibration steps. Environmental adaptation requires that the difference between the internal temperature sampling value of the battery system and the test environment temperature within 1 hour is ≤2°C without turning on the thermal management system, ensuring that the battery is in a stable environmental state. The charging mechanism of standard charging is consistent with the actual operating conditions of the vehicle, simulating the charging process in a real usage scenario. Standard discharge is to discharge at a constant current of 1C until the minimum single cell voltage is 2.8V, and record the discharge capacity. 1C discharge refers to the process in which the battery is continuously discharged for one hour at a current of the nominal capacity. Capacity calibration requires cyclic operation of environmental adaptation, standard charging and standard discharge at least 3 times. When the difference in the 3 discharge capacities is less than 3%, the 3 discharge capacities are recorded, and the average value is taken as the calibration capacity to improve the accuracy of capacity calibration.

[0092] During specific implementation, the capacity of the power battery is calibrated and then an operating condition test is performed to assist in correction.

[0093] After completing the capacity calibration, perform operating condition test to assist in correction, and cycle through different SOC conditions, such as step charging conditions, WLTC (Worldwide Harmonized Light Vehicles Test Cycle) discharge conditions, and 1C discharge conditions, to test and record the battery SOC accuracy values ​​reflected under different conditions. The step charging condition is a charging map preset in the BMS, which simulates the complex changes in the actual charging process; the WLTC discharge condition simulates the feedback discharge condition of the entire vehicle, which is closer to the actual operation of the vehicle; the 1C discharge condition refers to a method of continuously discharging the battery for a specified time in units of the battery's calibrated capacity, which is used to detect the battery's performance under specific discharge conditions. Through these operating condition test data, the BMS SOC accuracy value estimation model is further optimized, thereby improving the accuracy of the SOC correction. The battery capacity calibration and operating condition test process is as follows: Figure 6 shown.

[0094] In specific implementation, in step 7, before calibrating the capacity of the power battery, a charging current curve of the power battery under constant current charging conditions at different temperatures is first obtained.

[0095] In the battery management system BMS, the correction optimization based on temperature, current and internal resistance is crucial. The core is to accurately obtain relevant data and adjust the battery status in real time based on these data. The charging current curve of the target battery under constant current charging conditions at different temperatures is obtained in advance.

[0096] The specific method for obtaining the charging current curve is as follows: First, let the target battery stand still at room temperature for more than 1 h to allow the battery to reach a stable state. Subsequently, discharge it at a constant current of 0.3C until the battery is fully discharged, and then stand still for more than 1 h to ensure that the battery is fully discharged and in a stable state. After that, adjust the temperature to T01℃, and wait for the battery cell to cool down to T01℃. This step is to ensure that the battery cell reaches thermal equilibrium at the set temperature, and then stand still for more than 1 h. Finally, charge it at a constant current of I1 until the full charge voltage is reached, and stand still for more than 1 h. By cycling through the full discharge and full charge operations, a table of temperature, SOC, and constant charging voltage curve of current I1 at different temperatures is finally obtained. The flowchart of the charging current curve for the target battery under constant current charging conditions at different temperatures is as Figure 7 shown.

[0097] When correcting and optimizing the internal resistance, the internal resistance of the target battery is determined by the table of temperature, SOC, and battery internal resistance R at different temperatures. This curve table is obtained through DC pulse testing. The specific testing process is as follows: Adjust the temperature of the temperature chamber to room temperature and stand still for more than 1 h; Charge the battery cell at a constant current of 0.3C until the full charge voltage is reached and stand still for more than 1 h; Adjust the temperature of the temperature chamber to T1℃, wait for the battery cell to cool down to T1℃, and stand still for more than 1 h; Discharge it at a constant current of 0.3C to SOC1, stand still for more than 1 h, and record the battery cell voltage as V1; Discharge at a constant current of I1 for 60 seconds, record the battery cell voltage as V2, stand still for more than 1 h, and record the battery cell voltage as V3; Charge at a constant current of I1 for 60 seconds, record the battery cell voltage as V4, and stand still for more than 1 h; Calculate the discharge internal resistance R=(V1 - V2) / I1 and the charge internal resistance R=(V4 - V3) / I1 through the formula; Cycle through the above steps to test the table of temperature, SOC, and battery internal resistance R at different temperatures. The flowchart of drawing the internal resistance of the target battery through the table of temperature, SOC, and battery internal resistance R at different temperatures is as Figure 8 shown.

[0098] Determine the real-time battery temperature and current value according to the charging current curve, and determine different calibration points and the reference voltage of the calibration points in combination with the battery temperature, current value, and internal resistance.

[0099] The BMS collects the single-cell temperature T1 and the corresponding battery pack current value I2 during the charging of the target battery, determines the calibration point D2 according to the table of temperature, SOC, and constant charging voltage curve of current I1, and obtains the reference voltage V7, BMS system time t1, and battery capacity Q1 corresponding to the calibration point D2. The reference voltage V7 is calculated through formula (7).

[0100] V7 = V6 + R1*(I2 - I1) (7);

[0101] In the formula (7), V6 is the constant current charging voltage value corresponding to the monomer temperature T1, R1 is the internal resistance of the battery corresponding to the monomer temperature T1, I1 is the constant current charging current value, and I2 is the battery pack current value corresponding to the monomer temperature T1.

[0102] The BMS collects the lowest monomer temperature T2 of the target battery and the corresponding battery pack current value I4, determines the calibration point D3 according to the temperature, SOC, and the constant charging voltage curve table of current I1, obtains the reference voltage V9 corresponding to the calibration point D3 and the BMS system time t2, and the reference voltage V9 is calculated by the formula (8).

[0103] V9 = V8 + R2 * (I4 - I1) (8);

[0104] In the formula (8), V8 is the constant current charging voltage value corresponding to the lowest monomer temperature T2, R2 is the internal resistance of the battery corresponding to the lowest monomer temperature T2, I1 is the constant current charging current value, and I4 is the battery pack current value corresponding to the monomer temperature T2.

[0105] Obtain the highest monomer voltage V5 of the target battery. According to the comparison result between the highest monomer voltage V5 and the reference voltages of different calibration points, and the comparison result between the SOC value calculated by the BMS and the SOC values of the calibration points, adjust the SOC growth rate according to the preset correction method to achieve real-time correction of SOC. The SOC value calculated by the BMS is the current remaining power value estimated in real time and dynamically by the BMS, while the SOC values of different calibration points are reference values obtained through the OCV-SOC curve under laboratory or standard conditions in advance.

[0106] When V5 is greater than the reference voltage V7 corresponding to the calibration point D2 and the SOC01 calculated by the BMS at the calibration point D2 is less than the SOC02 of the calibration point D2, that is, when V5 > V7 and SOC01 < SOC02, the calculation formula of the corrected SOC01 is shown in the following formula (9).

[0107]

[0108] When the highest monomer voltage V5 is less than the reference point V9 corresponding to the calibration point D3 and the SOC03 calculated by the BMS at the calibration point D3 is less than the SOC04 of the calibration point D3, that is, when V5 < V9 and SOC03 < SOC04, the calculation formula of the corrected SOC03 is shown in the following formula (10).

[0109]

[0110] In the formulas (9) and (10), SOC01(t1) is the value of SOC01 at time t1, and SOC01(t0) is the value of SOC01 at time t0; SOC03(t2) is the value of SOC03 at time t2, and SOC03(t0) is the value of SOC03 at time t0; t0 is the last BMS system time, and t1 and t2 are the BMS system times in the formulas (7) and (8). f1 and f2 are the acceleration and deceleration coefficients, f1 > 1, f2 < 1, and the specific values of the acceleration coefficients f1 and f2 are calibrated according to the required SOC change rate of the whole vehicle. I1 is the constant current charging current value, I2 is the battery pack current value corresponding to the single cell temperature T1, and I4 is the battery pack current value corresponding to the single cell temperature T2. Q1 is the battery capacity Q1 corresponding to the calibration point D2.

[0111] In the formulas (9) and (10), the SOC values SOC01 and SOC03 calculated by the BMS are the current remaining power values dynamically estimated by the BMS in real time, while the SOC value SOC02 at the calibration point D2 and the SOC04 at the calibration point D3 are reference values obtained through the OCV - SOC curve in the laboratory or under standard conditions in advance.

[0112] In the present invention, the linear interpolation method is used to calculate the theoretical remaining power value SOC1 of the power battery; the specific calculation formula is shown in the following formula (11).

[0113]

[0114] In formula (11), SOC1 is the theoretical remaining power value of the power battery, is the OCV calculated value of the OCV1 power battery, OVC low is the open - circuit voltage reference value when SOC is at the lowest value, OVC high is the open - circuit voltage reference value when SOC is at the highest value, SOC low is the SOC reference value corresponding to OVC low is the SOC reference value corresponding to OVC high is the SOC reference value corresponding to OVC high is the SOC reference value corresponding to it.

[0115] The present invention discloses an improved method for estimating the SOC of a power battery, which has the following advantages.

[0116] (1) Improve the accuracy of SOC correction: By judging the stability of the OCV calculated value, it effectively avoids using unstable terminal voltages for subsequent calculations, can significantly improve the accuracy of calculating the remaining power value and the SOC value to be corrected of the power battery, reduce the correction error, and enhance the reliability of SOC estimation. Compared with the traditional method, the present invention can more accurately reflect the actual remaining power of the battery and provide more reliable power information for users.

[0117] (2) Multi-dimensional optimization and correction process: By comprehensively considering factors such as battery capacity calibration, operating condition tests in different SOC segments, and real-time correction based on temperature, current, and internal resistance, the SOC correction process has been comprehensively optimized, which can more accurately reflect the actual SOC state of the battery and meet the requirements for accurate SOC estimation in different usage scenarios. Whether in the daily driving of electric vehicles or in the charging and discharging process of energy storage systems, more accurate SOC estimation can be provided.

[0118] (3) Enhance the safety and stability of battery use: By reasonably setting the SOC correction strategy, it is possible to avoid the drastic jump of the battery SOC caused by improper SOC correction, effectively prevent the adverse effects on the execution of the vehicle's dynamic performance strategy, and reduce problems such as overcharging and over-discharging of the battery caused by inaccurate SOC estimation.

[0119] (4) Improve user experience: The optimized SOC correction method makes the correction process smoother, and the driver is less likely to notice the SOC correction process of the power battery during vehicle use, improving the vehicle use experience. During the use of electric vehicles, users can obtain a more stable and accurate power display, reducing the anxiety and inconvenience caused by inaccurate power display.

[0120] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present invention. Any reference signs in the claims should not be regarded as limiting the claimed invention.

[0121] In addition, it should be understood that although this specification is described according to embodiments, not every embodiment only contains an independent technical solution. This narrative way of the specification is only for clarity. Those skilled in the art should regard the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. An improved method for estimating the state of charge (SOC) of a power battery, characterized in that, It includes the following steps: Step 1: Place the power battery in a static state and start timing; when the time for the power battery to be in a static state reaches the preset static time threshold Yt, start the detection unit; Step 2: The detection unit obtains the terminal voltage loss value U of the power battery in the battery management system BMS, and then calculates the OCV calculated value OCV1 of the power battery according to the terminal voltage loss value U of the power battery; Step 3: Judge whether the OCV calculated value OCV1 obtained in Step 2 meets the stability condition for stability evaluation; Step 4: If the OCV calculated value OCV1 meets the stability condition, the detection unit calculates the theoretical remaining power value SOC1 of the power battery according to the OCV-SOC curve; Step 5: The detection unit obtains the SOC estimated value SOC2 of the power battery from the battery management system BMS; Step 6: The detection unit compares the theoretical remaining power value SOC1 and the SOC estimated value SOC2 of the power battery, and calculates to obtain the SOC correction deviation value SOC3; Step 7: The detection unit controls the battery management system BMS to perform correction according to the SOC correction deviation value SOC3 to obtain the SOC correction value SOC4, outputs the SOC correction value SOC4 and displays it as the current remaining power.

2. An improved method for estimating the state of charge (SOC) of a power battery according to claim 1, characterized in that, In Step 1, the time for the power battery to be in a static state is 2 hours.

3. An improved method for estimating the state of charge (SOC) of a power battery according to claim 1, characterized in that, In Step 2, during the process that the detection unit obtains the terminal voltage loss value U of the power battery in the battery management system BMS, the detection unit detects the terminal voltage loss value U of the power battery within two consecutive preset periods, and calculates the OCV calculated value OCV1 through the terminal voltage values detected within two consecutive preset periods.

4. An improved method for estimating the state of charge (SOC) of a power battery according to claim 3, characterized in that, In step 3, by comparing the difference between the terminal voltage loss values measured by the detection unit in two consecutive preset periods with the preset voltage value U Y to determine whether the calculated OCV value OCV1 meets the stability condition.

5. An improved method for estimating the state of charge (SOC) of a power battery according to claim 3, characterized in that, In Step 3, before detecting the terminal voltage loss value U of the power battery within two consecutive preset periods, first judge whether the terminal voltage values within two consecutive preset periods are reasonable.

6. An improved method for estimating the state of charge (SOC) of a power battery according to claim 1, characterized in that, In Step 6, the calculation formula of the SOC correction deviation value SOC3 is shown in the following formula (4); SOC3 = SOC1 - SOC2 (4). In the formula (4), SOC1 is the theoretical remaining power value of the power battery, and SOC2 is the SOC estimated value.

7. An improved method for estimating the state of charge (SOC) of a power battery according to claim 1, characterized in that, In Step 7, before correcting the SOC, first compare the SOC correction deviation value SOC3 with the first preset power value Qpre, and correct the SOC according to the comparison result.

8. An improved method for estimating the state of charge (SOC) of a power battery according to claim 7, characterized in that, In Step 7, before correcting the SOC, first perform capacity calibration on the power battery.

9. An improved method for estimating the state of charge (SOC) of a power battery according to claim 8, characterized in that, After performing capacity calibration on the power battery, perform working condition test auxiliary correction.

10. An improved method for estimating the state of charge (SOC) of a power battery according to claim 8, characterized in that, In Step 7, before performing capacity calibration on the power battery, first obtain the charging current curve of the power battery under a constant current charging working condition at different temperatures.

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