A method, apparatus, storage medium, and device for estimating the state of charge (SOC) of a battery.

Abstract

This disclosure pertains to the field of battery power technology and provides a method, apparatus, storage medium, and device for estimating the state of charge (SOC) value of a battery. The method includes: fitting a mathematical relationship between open-circuit voltage (OCV) and state of charge (SOC) and resting time based on a corresponding relationship curve to generate a first fitting formula; fitting a mathematical relationship between static discharge voltage, static discharge time, and SOC based on small-current discharge voltage curves at multiple SOC nodes to generate a second fitting formula; and determining an estimation model based on the initial voltage and initial current values ​​corresponding to different battery states, estimating the current battery SOC value based on the estimation model, and obtaining and outputting the current battery SOC value. This estimation method not only enables rapid estimation of the current battery SOC value through the estimation model but also ensures that the estimated current battery SOC value matches the actual value more closely, thereby significantly improving the accuracy of the estimated current battery SOC value.

Description

Technical Field

[0001] This disclosure pertains to the field of battery power technology, and particularly relates to a method, apparatus, storage medium, and device for estimating the SOC value of a battery. Background Technology

[0002] The state of charge (SOC) of a battery indicates its charge level under standard conditions (25°C, I...). 20 State of Charge (SOC) is the percentage of the battery's dischargeable capacity relative to its actual capacity. The purpose of SOC estimation is to estimate the remaining battery capacity so that the battery can be used efficiently within its operating range. The ampere-hour integration method is commonly used for SOC estimation. This traditional method integrates the battery current over time to obtain the estimated SOC value. However, the traditional ampere-hour integration method uses an open-loop algorithm, which has drawbacks such as significant accumulation of measurement errors due to uncertainties and difficulty in accurately determining the SOC value.

[0003] For situations involving rapid SOC estimation, abnormal power loss, and static SOC correction, the battery open circuit voltage (OCV) method is typically used for quick table lookup. OCV measurement is a direct indicator, utilizing the one-to-one mapping between SOC and OCV. However, when there is no stored SOC value or the stored value is invalid, the battery terminal voltage is unstable when estimating the SOC value through OCV lookup. Using an unstable terminal voltage as the open circuit voltage for table lookup will significantly impact subsequent SOC calculations. Static SOC correction calculations are primarily based on the battery open circuit voltage when the vehicle is off. After the car is turned off, the SOC value is obtained by measuring the terminal voltage as the OCV for table lookup, but this is not truly "resting"; the battery still experiences static power consumption. Using a terminal voltage with static current as the open circuit voltage for table lookup will introduce errors, which are particularly noticeable at high SOC levels.

[0004] Therefore, how to reduce the above-mentioned errors and quickly and accurately estimate the battery SOC value is a technical problem to be solved. Summary of the Invention

[0005] Therefore, it is necessary to address the shortcomings of existing battery SOC estimation methods, which cannot quickly and accurately estimate the current battery SOC value, by providing a battery SOC estimation method, apparatus, storage medium, and device.

[0006] In a first aspect, embodiments of the present invention provide a method for estimating the SOC value of a battery, the method comprising:

[0007] Obtain the curves showing the relationship between open-circuit voltage (OCV) and state of charge (SOC), as well as the small-current discharge voltage curves for multiple SOC nodes.

[0008] Based on the corresponding relationship curve, the mathematical relationship between the OCV and the SOC as a function of resting time is fitted to generate a first fitting formula.

[0009] Based on the low-current discharge voltage curves of the multiple SOC nodes, the mathematical relationship between static discharge voltage, static discharge time and SOC is fitted to generate a second fitting formula.

[0010] Based on the initial voltage and initial current values ​​corresponding to different battery states, an estimation model is determined, and the current battery SOC value is estimated based on the estimation model to obtain and output the current battery SOC value; the different battery states include: the battery is in the state of first power-on, the battery is in the state of re-power-on, and the battery is in the state of rest; the estimation algorithm used by the estimation model includes the first fitting formula and the second fitting formula.

[0011] Optionally, the step of fitting the mathematical relationship between the open-circuit voltage (OCV) and the state of charge (SOC) as a function of resting time based on the corresponding relationship curve to generate a first fitting formula includes:

[0012] At a first interval, the first battery terminal voltage value of the corresponding relationship curve is counted;

[0013] Obtain the first confidence level and the first battery sleep duration;

[0014] Based on the first confidence level, the mathematical relationship between the open-circuit voltage OCV and the state of charge SOC as a function of resting time is fitted to generate the first fitting formula, which takes the open-circuit voltage OCV and the first dormancy time of the battery as inputs and the first battery SOC value as outputs.

[0015] Optionally, the step of fitting the mathematical relationship between the static discharge voltage, static discharge time, and the state of charge (SOC) based on the small current discharge voltage curves of the multiple SOC nodes to generate a second fitting formula includes:

[0016] At second intervals, the second battery terminal voltage values ​​of the small current discharge voltage curves of the multiple SOC nodes are counted.

[0017] Obtain the second confidence level and the second battery sleep duration;

[0018] Based on the second confidence level, the mathematical relationship between the second terminal voltage of the battery and the state of charge (SOC) as a function of resting time is fitted to generate the second fitting formula, which takes the second terminal voltage of the battery and the second dormancy time of the battery as inputs and the SOC value of the second battery as outputs.

[0019] Optionally, the step of determining an estimation model based on the initial voltage and initial current values ​​corresponding to different battery states, and estimating the current battery SOC value based on the estimation model to obtain and output the current battery SOC value includes:

[0020] If the battery is in the first power-on state or the re-power-on state, obtain the initial voltage and initial current values ​​of the battery at the initial moment;

[0021] Based on the current range corresponding to the initial current value, a first correction method is determined for correcting the initial voltage value.

[0022] Based on the first correction method, the initial voltage value is corrected to obtain the corrected voltage value;

[0023] Based on the first correction method, the estimation model is determined, and the estimation algorithm used by the estimation model includes the first fitting formula and the second fitting formula;

[0024] The corrected voltage value and the third sleep duration of the battery are input into the estimation model to estimate the current battery SOC value, and the current battery SOC value is obtained and output.

[0025] Optionally, the step of determining the corresponding estimation model based on the initial voltage and initial current values ​​corresponding to different battery states, and estimating the current battery SOC value based on the estimation model to obtain and output the current battery SOC value includes:

[0026] If the battery is in a static state and the current battery sleep time is longer than the preset battery sleep time, obtain the voltage value and average current value during the sleep period;

[0027] Based on the current range corresponding to the average current value, a second correction method is determined for correcting the voltage value during the sleep period;

[0028] Based on the second correction method, the voltage value during the sleep period is corrected to obtain the corrected voltage value during the sleep period;

[0029] Based on the second correction method, the estimation model is determined. The estimation algorithm used by the estimation model includes the first fitting formula and the second fitting formula. The corrected voltage value during the dormancy period and the fourth dormancy duration of the battery are input into the estimation model to estimate the current battery SOC value, and the current battery SOC value is obtained and output.

[0030] Optionally, the method further includes:

[0031] Obtain the second correction method;

[0032] Determine whether the second correction method is related to the target voltage drop associated with the small current. If the second correction method is related to the target voltage drop, calculate the target voltage drop; otherwise, ignore the processing.

[0033] Optionally, calculating the target pressure drop includes:

[0034] If the battery is in a static state, based on the corresponding relationship curve, the different current open circuit voltages corresponding to the first sleep duration and different SOC nodes of different batteries are obtained; and based on the small current discharge voltage curves of the multiple SOC nodes, the static current and static voltage corresponding to the second sleep duration and different SOC nodes of different batteries are obtained.

[0035] The voltage drop at different SOC nodes of the battery is calculated based on the different current open-circuit voltages corresponding to different SOC nodes and the static voltages corresponding to different SOC nodes.

[0036] Based on the voltage drop and corresponding quiescent current at different SOC nodes of the battery, the impedance values ​​of different SOC nodes are obtained.

[0037] The average impedance value is determined based on the fifth sleep duration of different batteries and different static currents, and the weight is determined based on the average impedance value.

[0038] The target voltage drop is calculated based on the weights, different quiescent currents, and impedance values ​​of different SOC nodes.

[0039] Secondly, embodiments of the present invention provide a battery SOC value estimation device, the device comprising:

[0040] The acquisition module is used to acquire the curves showing the relationship between open-circuit voltage (OCV) and state of charge (SOC), as well as the small-current discharge voltage curves of multiple SOC nodes.

[0041] The first generation module is used to fit the mathematical relationship between the open-circuit voltage OCV and the state of charge SOC as a function of resting time based on the corresponding relationship curve, and generate a first fitting formula.

[0042] The second generation module is used to fit the mathematical relationship between static discharge voltage, static discharge time and the state of charge (SOC) based on the small current discharge voltage curves of the multiple SOC nodes, and generate a second fitting formula.

[0043] The processing module is used to determine the corresponding estimation model based on the initial voltage and initial current values ​​corresponding to different battery states, and to estimate the current battery SOC value based on the estimation model, thereby obtaining and outputting the current battery SOC value. The different battery states include: the battery in its first power-on state, the battery in a re-power-on state, and the battery in a resting state. The estimation formula corresponding to the estimation model includes the first fitting formula and the second fitting formula.

[0044] Thirdly, embodiments of the present invention provide a computer-readable storage medium storing a computer program for performing the above-described method steps.

[0045] Fourthly, embodiments of the present invention provide an electronic device, the electronic device comprising:

[0046] processor;

[0047] Memory used to store the processor's executable instructions;

[0048] The processor is configured to read the executable instructions from the memory and execute the executable instructions to implement the above-described method steps.

[0049] In this embodiment of the invention, the corresponding curves of open-circuit voltage (OCV) and state of charge (SOC) are obtained, as well as the small-current discharge voltage curves of multiple SOC nodes. Based on the corresponding curves, the mathematical relationship between open-circuit voltage (OCV) and state of charge (SOC) as a function of resting time is fitted to generate a first fitting formula. Based on the small-current discharge voltage curves of multiple SOC nodes, the mathematical relationship between static discharge voltage, static discharge time, and state of charge (SOC) is fitted to generate a second fitting formula. Furthermore, based on the initial voltage and initial current values ​​corresponding to different battery states, an estimation model is determined, and the current battery SOC value is estimated based on the estimation model to obtain and output the current battery SOC value. The estimation method provided by this embodiment of the invention can not only quickly estimate the current battery SOC value through the estimation model, but also the estimated current battery SOC value is more consistent with the actual value, thereby greatly improving the accuracy of the estimated current battery SOC value. Attached Figure Description

[0050] Exemplary embodiments of the present invention can be more fully understood by referring to the accompanying drawings. The drawings are provided to further illustrate the embodiments of the present invention and form part of the specification. They are used together with the embodiments of the present invention to explain the invention and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0051] Figure 1 A flowchart illustrating a method for estimating battery SOC value according to an exemplary embodiment of the present invention;

[0052] Figure 2 This is a schematic diagram of the current during low-current discharge and its corresponding state of charge (SOC) in the low-current discharge battery voltage drop test method.

[0053] Figure 3 A schematic diagram of the structure of a battery SOC value estimation device 300 provided according to an exemplary embodiment of the present invention. Detailed Implementation

[0054] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0055] It should be noted that, unless otherwise stated, the technical or scientific terms used in this invention should have the ordinary meaning as understood by one of ordinary skill in the art.

[0056] Furthermore, the terms "first" and "second," etc., are used to distinguish different objects, not to describe a specific order. Additionally, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to those processes, methods, products, or devices.

[0057] This invention provides a method and apparatus for estimating the SOC value of a battery, an electronic device, and a computer-readable medium, which are described below with reference to the accompanying drawings.

[0058] Example 1

[0059] Please refer to Figure 1 It illustrates a flowchart of a battery SOC value estimation method provided by some embodiments of the present invention, such as... Figure 1As shown, the method for estimating the battery SOC value may include the following steps:

[0060] Step S101: Obtain the corresponding curve of open circuit voltage OCV and state of charge SOC, and obtain the small current discharge voltage curve of multiple SOC nodes.

[0061] In the battery SOC value estimation method provided in this embodiment of the invention, before obtaining the correspondence curve between open-circuit voltage OCV and state of charge SOC in step S101, and before obtaining the small current discharge voltage curves of multiple SOC nodes, the battery SOC value estimation method further includes the following steps:

[0062] A low-current discharge voltage drop test experiment was designed for the storage battery, and data such as voltage, current, temperature, SOC, and sampling time were continuously sampled.

[0063] The test experiment uses data from experiments conducted at room temperature as an example. The test SOC nodes are set to 100%, 95%, 90%, 80%, 70%, 60%, 50%, 40%, 30%, 20%, 10%, and 0%. The current direction is specified as negative for discharge and positive for charging. The low-current discharge battery voltage drop test should be conducted using a new battery.

[0064] In specific application scenarios, the design of a low-current discharge battery voltage drop test experiment includes the following steps:

[0065] Step a1: Before the experiment, the battery in this embodiment must be fully charged. The specific steps for fully charging the battery include: performing capacity testing, charge acceptance testing, or 24-hour deep discharge testing on the new battery before the experiment; and charging the battery in a water bath at (25±2)℃ using a voltage of 14.8V (AGM battery) and a limiting current I. max =5×I 20 Charge the battery for 24 hours to bring it to a SOC of 100%.

[0066] Step a2: At the test temperature, the experimental battery was left to stand for 24 hours;

[0067] Step a3: The experimental method for testing the voltage drop of a small-current discharged battery consisted of 13 cyclic steps. The diagram below illustrates the small-current discharge current and its corresponding SOC in the small-current discharge voltage drop test method. Figure 2 As shown.

[0068] The specific implementation steps of the low-current discharge battery voltage drop test cycle include:

[0069] Step a31: The first test group includes: the battery is left to stand for 10 seconds at the test temperature (sampling time is 1 second); the battery is discharged at a constant current of 0.05A for 8 hours at the test temperature until the SOC is 99% (sampling time is 1 minute).

[0070] Step a32: The second test group includes: at the test temperature, the battery is discharged at a constant current of 1 / 4C until the SOC is 96% (discharge time is 432 seconds, sampling time is 1 second); at the test temperature, the battery is discharged at a constant current of 0.05A for 8 hours until the SOC is 95% (sampling time is 1 min); at the test temperature, the battery is left to stand for 5 hours (sampling time is 1 min).

[0071] Step a33: The third test group of the test experiment includes: at the test temperature, the battery is discharged at a constant current of 1 / 4C until the SOC is 91% (discharge time is 576 seconds, sampling time is 1 second); at the test temperature, the battery is discharged at a constant current of 0.05A for 8 hours until the SOC is 90% (sampling time is 1 min); at the test temperature, the battery is left to stand for 5 hours (sampling time is 1 min).

[0072] Step a34: The fourth test group of the test experiment includes: at the test temperature, the battery is discharged at a constant current of 1 / 4C until the SOC is 81% (discharge time is 1296 seconds, sampling time is 1 second); at the test temperature, the battery is discharged at a constant current of 0.05A for 8 hours until the SOC is 80% (sampling time is 1 min); at the test temperature, the battery is left to stand for 5 hours (sampling time is 1 min).

[0073] Step a35: Tests in groups 5 to 11 of the test experiment include: repeating the test in group 4 of the test experiment and completing the test experiments to reach the SOC nodes of 70%, 60%, 50%, 40%, 30%, 20%, and 10% in sequence.

[0074] Step a36: Test group 12 includes: at the test temperature, the battery is discharged at a constant current of 1 / 4C until the SOC is 6% (discharge time is 576 seconds, sampling time is 1 second); at the test temperature, the battery is discharged at a constant current of 0.05A for 8 hours until the SOC is 5% (sampling time is 1 min); at the test temperature, the battery is left to stand for 5 hours (sampling time is 1 min).

[0075] Step a37: Test group 13 includes: at the test temperature, the battery is discharged at a constant current of 1 / 4C until the SOC is 1% (discharge time is 576 seconds, sampling time is 1 second); at the test temperature, the battery is discharged at a constant current of 0.05A for 8 hours until the SOC is 0% (sampling time is 1 min); at the test temperature, the battery is left to stand for 5 hours (sampling time is 1 min).

[0076] Step a38: Test the battery at the test temperature, continue discharging at 1 / 4C until the voltage drops below 10.5V, then terminate the discharge (sampling time is 1s).

[0077] Please refer to the schematic diagram of the low-current discharge in the above low-current discharge battery voltage drop test method. Figure 2 .

[0078] It should be noted that battery charging and discharging efficiency is related to current changes. Since constant current charging is often used during battery charging, the current usually changes at the end of the charging process to prevent overcharging. Therefore, the current efficiency at the discharge rate is the main consideration.

[0079] The charge / discharge rate refers to the ratio between the battery's charging or discharging rate and its rated capacity. For example, a battery with a rated capacity of 40Ah has a charge rate of 1C, which means it can be fully charged in one hour at a rate of 40A (40Ah / 1h = 40A). A battery discharging at 1 / 4C means that the discharge rate is 10A.

[0080] In specific application scenarios, the process of processing experimental data from small-current discharge battery voltage drop tests to obtain the corresponding curves of open-circuit voltage (OCV) and state of charge (SOC) includes the following steps:

[0081] Step b1: Obtain the battery model. The resting time required for the terminal voltage to stabilize after charging and discharging at different temperatures is 300 minutes.

[0082] Step b2: Obtain sampling data of the battery during each cycle, from resting time to resting time, with a sampling interval of 1 minute;

[0083] Step b3: Record the sampling data of the battery at each test SOC node at room temperature into a Time-SOC-OCV table; the sampling data includes the first terminal voltage of the battery to the resting time, and is recorded once every hour;

[0084] Step b4: Based on the records in the Time-SOC-OCV table above, record each test temperature, each test SOC node, and the first battery terminal voltage value after each resting time (the first battery terminal voltage value after the resting time can be considered as the open circuit voltage of the battery) in the Temp-SOC-OCV table, that is: consider it as a one-to-one mapping relationship between open circuit voltage and SOC.

[0085] Step b5: Based on the sampled data in the Temp-SOC-OCV table above, obtain the correspondence between open-circuit voltage OCV and state of charge SOC, and generate and obtain the correspondence curve between open-circuit voltage OCV and state of charge SOC.

[0086] In specific application scenarios, obtaining the low-current discharge voltage curves of multiple SOC nodes includes the following steps:

[0087] Step c1: Obtain sampling data for each of the aforementioned cycles, where the battery's rated capacity is 1% of the charge generated by low-current discharge at the test temperature;

[0088] Step c2: Acquire sampling data for each test temperature and each test SOC node, and record it once every hour; the sampling data includes the battery terminal voltage, battery discharge current, sampling time and current SOC.

[0089] Step c3: Based on the records in the static voltage table, record the battery at each test temperature, each test SOC node, and the second battery terminal voltage value after 8 hours (the second battery terminal voltage value after 8 hours can be considered as the stable voltage during the small current discharge stage of the battery) in a Temp-SOC-V table, that is: consider it as a one-to-one mapping relationship between static voltage and SOC.

[0090] Step c4: Based on the sampling data in the Temp-SOC-V table above, generate and obtain the small current discharge voltage curves of multiple SOC nodes.

[0091] It should be noted that recording the data in a table format makes the data more intuitive, allowing a clear view of the relationship between the State of Charge (SOC) and various factors. This facilitates adjustments to the SOC based on these relationships and by considering different factors. Furthermore, using the Temp-SOC-OCV and Temp-SOC-V tables with a lookup method, the current SOC value can be quickly estimated.

[0092] In the battery SOC estimation method provided in this embodiment of the invention, when the battery is first powered on or re-powered, a correction coefficient is obtained by combining the aforementioned Temp-SOC-OCV table and Temp-SOC-V table. After obtaining the current value of the battery circuit at this moment, the table is looked up using the aforementioned correction coefficient. Since this effectively reduces the error that may be caused by small currents, the final initial SOC value has higher accuracy.

[0093] Step S102: Based on the corresponding relationship curve, fit the mathematical relationship between OCV and SOC as a function of resting time to generate the first fitting formula.

[0094] In one possible implementation, based on the corresponding relationship curve, the mathematical relationship between the open-circuit voltage (OCV) and the state of charge (SOC) as a function of rest time is fitted to generate a first fitting formula, including the following steps:

[0095] At the first interval, count the first battery terminal voltage value of the corresponding relationship curve;

[0096] Obtain the first confidence level and the first battery sleep duration;

[0097] Based on the first confidence level, the mathematical relationship between the open-circuit voltage (OCV) and the state of charge (SOC) as a function of resting time is fitted to generate a first fitting formula with the open-circuit voltage (OCV) and the first resting time of the battery as inputs and the first battery SOC value as output.

[0098] In specific application scenarios, under conditions of no discharge current, based on the sampled data in the aforementioned battery Time-SOC-OCV table, the mathematical relationship between the open-circuit voltage OCV (first battery terminal voltage) and the state of charge SOC as a function of resting time is fitted to generate the first fitting formula, including the following steps:

[0099] Step d1: In Matlab, use the curve fitter to fit the relation. Select multinomial fitting as the fitting type and select the data to fit the surface.

[0100] Step d2: Count the terminal voltage of the battery at rest time recorded every hour. Perform polynomial fitting on the mathematical relationship between open circuit voltage and SOC as a function of rest time with a 95% confidence level to generate a first fitting formula with open circuit voltage and battery first sleep time as input and battery SOC as output. The first fitting formula is shown in the following formula (1):

[0101] SOC = P 00 +P 10 ·OCV+P 01 ·t+P 20 ·OCV2 +P 11 ·OCV·t+P 02 ·t 2 +P 30 ·OCV 3 +P 21 ·OCV 2 ·t+P 12 ·OCV·t 2 +P 40 ·OCV 4 +P 31 ·OCV 3 ·t+P 22 ·OCV 2 ·t 2 +P 50 ·OCV 5 +P 41 ·OCV 4 ·t+P 32 ·OCV 3 ·t 2

[0102] Formula (1);

[0103] In the above formula (1), OCV is the equivalent open-circuit voltage value of the battery dormancy phase terminal voltage; t is the first battery dormancy duration; and parameter P is the polynomial coefficient fitted using Matlab's "curve fitter" with OCV and t as inputs and the battery's SOC as output.

[0104] Step S103: Based on the small current discharge voltage curves of multiple SOC nodes, fit the mathematical relationship between static discharge voltage, static discharge time and SOC to generate a second fitting formula.

[0105] In one possible implementation, based on the small-current discharge voltage curves of multiple SOC nodes, the mathematical relationship between static discharge voltage, static discharge time, and state of charge (SOC) is fitted to generate a second fitting formula, including the following steps:

[0106] At the second interval, the second battery terminal voltage values ​​of the small current discharge voltage curves of multiple SOC nodes are counted.

[0107] Obtain the second confidence level and the second battery sleep duration;

[0108] Based on the second confidence level, the mathematical relationship between the battery's second terminal voltage and the state of charge (SOC) as a function of resting time is fitted to generate a second fitting formula that takes the battery's second terminal voltage and the battery's second dormancy time as inputs and the second battery SOC value as outputs.

[0109] In specific application scenarios, based on the small current discharge voltage curves of multiple SOC nodes, the mathematical relationship between static discharge voltage, static discharge time, and state of charge (SOC) is fitted to generate a second fitting formula, including the following steps:

[0110] The voltage of the second battery terminal is counted based on the small current discharge voltage curve data recorded every hour. The mathematical relationship between the second battery terminal voltage and SOC over time is fitted with a polynomial at a 95% confidence level to generate a second fitting formula with the second battery terminal voltage and the second dormancy time of the battery as input and the battery SOC as output. The second fitting formula is shown in the following formula (2):

[0111] SOC = P 00 +P 10 ·V+P 01 ·t+P 20 ·V 2 +P 11 ·V·t+P 02 ·t 2 +P 30 ·V 3 +P 21 ·V 2 ·t+P 12 ·V·t 2 +P 40 ·V 4 +P 31 ·V 3 ·t+P 22 ·V 2 ·t 2 +P 50 ·V 5 +P 41 ·V 4 ·t+P 32 ·V 3 ·t 2

[0112] Formula (2);

[0113] In the above formula (2), V: the second terminal voltage of the battery in the dormant phase with static current; t: the second dormant duration of the battery with static current; parameter P: the polynomial coefficients fitted using Matlab's "curve fitter" with V and t as inputs and the battery's SOC as output.

[0114] Step S104: Based on the initial voltage and initial current values ​​corresponding to different battery states, determine the estimation model, and estimate the current battery SOC value based on the estimation model to obtain and output the current battery SOC value; the different battery states include: the battery is in the state of first power-on, the battery is in the state of re-power-on, and the battery is in the state of rest; the estimation algorithm used by the estimation model includes the first fitting formula and the second fitting formula.

[0115] In one possible implementation, an estimation model is determined based on the initial voltage and initial current values ​​corresponding to different battery states. The current battery SOC value is then estimated based on this estimation model, and the current battery SOC value is obtained and output. This includes the following steps:

[0116] If the battery is in the first power-on state or the re-power-on state, obtain the initial voltage and initial current values ​​of the battery at the initial moment;

[0117] Based on the current range corresponding to the initial current value, determine the first correction method to correct the initial voltage value;

[0118] Based on the first correction method, the initial voltage value is corrected to obtain the corrected voltage value;

[0119] Based on the first correction method, an estimation model is determined, and the estimation algorithm used by the estimation model includes a first fitting formula and a second fitting formula.

[0120] The corrected voltage value and the third sleep duration of the battery are input into the estimation model to estimate the current battery SOC value, and the current battery SOC value is obtained and output.

[0121] In practical applications, when the battery is in its first power-on state or a re-power-on state, the initial voltage and initial current values ​​of the battery at the initial moment are obtained. If the initial current value is between -0.02A and 0.01A, the initial voltage value at t=0 is substituted into the above formula (1) to obtain and output the current battery SOC value. If the initial current value is between -0.1A and -0.02A, the voltage difference is calculated and obtained using the data from the aforementioned Temp-SOC-OCV and Temp-SOC-V tables. The voltage difference is added to the initial voltage to obtain the corrected voltage, and the corrected voltage is used as the open-circuit voltage. The open-circuit voltage is input into the aforementioned formula (1) to obtain and output the current battery SOC value. Similarly, by changing the current and discharge time experimental values ​​in the small current discharge battery voltage drop test experiment, different discharge curves are obtained. Based on the obtained discharge curves, the initial SOC value with an initial discharge current greater than 0.1A can be calculated.

[0122] In one possible implementation, the battery SOC value estimation method provided in this embodiment of the invention may further include the following steps:

[0123] Obtain the second correction method;

[0124] Determine whether the second correction method is related to the target voltage drop associated with the small current. If the second correction method is related to the target voltage drop, calculate the target voltage drop; otherwise, ignore the process.

[0125] In one possible implementation, calculating the target pressure drop includes the following steps:

[0126] If the battery is in a static state, based on the corresponding relationship curve, the different current open circuit voltages corresponding to the first sleep duration and different SOC nodes of different batteries can be obtained; and based on the small current discharge voltage curves of multiple SOC nodes, the static current and static voltage corresponding to the second sleep duration and different SOC nodes of different batteries can be obtained.

[0127] The voltage drop at different SOC nodes of the battery is calculated based on the different current open-circuit voltages corresponding to different SOC nodes and the static voltages corresponding to different SOC nodes.

[0128] Based on the voltage drop and corresponding quiescent current at different SOC nodes of the battery, the impedance values ​​of different SOC nodes are obtained.

[0129] The average impedance value was determined based on the fifth sleep duration of different batteries and different quiescent currents, and the weights were determined based on the average impedance value.

[0130] The target voltage drop is calculated based on the weights, different quiescent currents, and impedance values ​​of different SOC nodes.

[0131] In one possible implementation, based on the initial voltage and initial current values ​​corresponding to different battery states, a corresponding estimation model is determined, and the current battery SOC value is estimated based on the estimation model to obtain and output the current battery SOC value, including the following steps:

[0132] If the battery is in a static state and the current battery sleep time is longer than the preset battery sleep time, obtain the voltage value and average current value during the sleep period;

[0133] Based on the current range corresponding to the average current value, a second correction method is determined for correcting the voltage value during the sleep period;

[0134] Based on the second correction method, the voltage value during the sleep period is corrected to obtain the corrected voltage value during the sleep period;

[0135] Based on the second correction method, an estimation model is determined. The estimation algorithm used by the estimation model includes the first fitting formula and the second fitting formula. The corrected voltage value during the dormancy period and the battery's fourth dormancy duration are input into the estimation model to estimate the current battery SOC value, and the current battery SOC value is obtained and output.

[0136] In practical applications, the method for calculating the target pressure drop can be described as follows:

[0137] The static current of the vehicle in parking mode is the discharge current (negative value). Based on the data in the aforementioned Time-SOC-OCV table, the open-circuit voltage corresponding to different battery dormancy durations and different SOC stages is obtained. The static current voltage corresponding to different battery dormancy durations and different SOC stages is obtained through the data in the aforementioned Time-SOC-V table. Subtracting the open-circuit voltage from the static current voltage, the voltage drop StatCurrVol of small current discharge at different SOC nodes is obtained, as shown in the following formula (3). The impedance value StatCurrR of the battery at different SOC nodes during static current discharge is calculated through the following formula (3).

[0138] StatCurrR=StatCurrVol1÷Current formula (3);

[0139] In the above formula (3), StatCurrR is the impedance value of the battery at different SOC nodes during static current discharge; StatCurrVol1 is the voltage drop at different SOC nodes during small current discharge; and Current is the static current.

[0140] The weight W is determined based on the average impedance value obtained by combining different battery dormancy time and current magnitude, and the target voltage drop DeltaVol2 caused by the presence of small current is calculated as shown in the following formula (4);

[0141] DeltaVol2=W*StatCurrR*Current formula (4);

[0142] In the above formula (4), W is the weight, StatCurrR is the impedance value of the battery at different SOC nodes during static current discharge; Current is the current value during hibernation, and DeltaVol2 is the target voltage drop caused by the presence of a small current.

[0143] When the battery is in a dormant phase and the dormant time is more than 60 minutes, and the average static current per hour is ≤ -0.1A, the current value during the dormant period is obtained and substituted into the aforementioned formula (4) to obtain the target voltage drop.

[0144] Add the voltage value during the dormancy period to the aforementioned target voltage drop DeltaVol2 to obtain the corrected voltage. Use the corrected voltage as the open circuit voltage and substitute it into the aforementioned formula (1) to obtain the battery SOC value for static correction.

[0145] When the battery is in a dormant state for more than 60 minutes and the average static current is ≥-0.1A and ≤-0.02A, the static correction is performed using the aforementioned formula (2); when the battery is in a dormant state for more than 60 minutes and the average static current is ≥-0.02A, the static correction is performed using the aforementioned formula (1).

[0146] After SOC correction is triggered, the SOC cannot directly jump to the corrected SOC. Due to the hysteresis characteristics of battery voltage, the open-circuit voltages corresponding to charging and discharging are not equal when the battery resting time is limited. Similarly, the terminal voltages with static power consumption corresponding to charging and discharging are also unstable when the battery resting time is limited. The relationship between voltage and SOC value will only tend to stabilize when the battery resting time reaches 300 minutes, and the corrected OCV at this time can be regarded as the true SOC.

[0147] During static correction, the SOC is calculated based on the ratio of the current battery sleep time to the battery rest time. During wake-up static correction, the reliability of the SOC correction value is gradually increased by the proportion of the battery sleep time until the calculated SOC and the corrected SOC value are equal.

[0148] It should be noted that the first, second, third, fourth, and fifth sleep durations of the battery, as well as the first confidence level, second confidence level, first interval duration, and second interval duration, can all be adjusted based on the needs of different application scenarios, and no specific limitations are made here.

[0149] The estimation method provided by the embodiments of the present invention can not only quickly estimate the current battery SOC value through the estimation model, but also the estimated current battery SOC value is more consistent with the actual value, thereby greatly improving the accuracy of the estimated current battery SOC value; in addition, the estimation method provided by the embodiments of the present invention can also effectively improve battery efficiency and lifespan.

[0150] In the above embodiments, a method for estimating battery SOC value is provided. Correspondingly, the present invention also provides a device for estimating battery SOC value. The battery SOC value estimation device provided in the embodiments of the present invention can implement the above-described battery SOC value estimation method. The battery SOC value estimation device can be implemented by software, hardware, or a combination of software and hardware. For example, the battery SOC value estimation device may include integrated or separate functional modules or units to perform the corresponding steps in the above methods.

[0151] Example 2

[0152] Please refer to Figure 3 This diagram illustrates a battery SOC estimation apparatus provided by some embodiments of the present invention. Since the apparatus embodiments are substantially similar to the method embodiments, the description is relatively simple; relevant details can be found in the description of the method embodiments. The apparatus embodiments described below are merely illustrative.

[0153] like Figure 3 As shown, the battery SOC estimation device 300 may include:

[0154] The acquisition module 301 is used to acquire the corresponding curve of open circuit voltage OCV and state of charge SOC, as well as the small current discharge voltage curve of multiple SOC nodes.

[0155] The first generation module 302 is used to fit the mathematical relationship between the open-circuit voltage OCV and the state of charge SOC as a function of resting time based on the corresponding relationship curve, and generate the first fitting formula.

[0156] The second generation module 303 is used to fit the mathematical relationship between static discharge voltage, static discharge time and state of charge (SOC) based on the small current discharge voltage curves of multiple SOC nodes, and generate a second fitting formula.

[0157] The processing module 304 is used to determine the corresponding estimation model based on the initial voltage and initial current values ​​corresponding to different battery states, and to estimate the current battery SOC value based on the estimation model, and to obtain and output the current battery SOC value. The different battery states include: the battery is in the state of first power-on, the battery is in the state of re-power-on, and the battery is in the state of rest. The estimation formulas corresponding to the estimation model include the first fitting formula and the second fitting formula.

[0158] In some embodiments of the present invention, the first generation module 302 is specifically used for:

[0159] At the first interval, count the first battery terminal voltage value of the corresponding relationship curve;

[0160] Obtain the first confidence level and the first battery sleep duration;

[0161] Based on the first confidence level, the mathematical relationship between the open-circuit voltage (OCV) and the state of charge (SOC) as a function of resting time is fitted to generate a first fitting formula with the open-circuit voltage (OCV) and the first resting time of the battery as inputs and the first battery SOC value as output.

[0162] In some embodiments of the present invention, the second generation module 303 is specifically used for:

[0163] At the second interval, the second battery terminal voltage values ​​of the small current discharge voltage curves of multiple SOC nodes are counted.

[0164] Obtain the second confidence level and the second battery sleep duration;

[0165] Based on the second confidence level, the mathematical relationship between the battery's second terminal voltage and the state of charge (SOC) as a function of resting time is fitted to generate a second fitting formula that takes the second terminal voltage and the battery's second dormancy time as inputs and the second battery SOC value as outputs.

[0166] In some embodiments of the present invention, the processing module 304 is specifically used for:

[0167] If the battery is in the first power-on state or the re-power-on state, obtain the initial voltage and initial current values ​​of the battery at the initial moment;

[0168] Based on the current range corresponding to the initial current value, determine the first correction method to correct the initial voltage value;

[0169] Based on the first correction method, the initial voltage value is corrected to obtain the corrected voltage value;

[0170] Based on the first correction method, an estimation model is determined, and the estimation algorithm used by the estimation model includes a first fitting formula and a second fitting formula.

[0171] The corrected voltage value and the third sleep duration of the battery are input into the estimation model to estimate the current battery SOC value, and the current battery SOC value is obtained and output.

[0172] In some embodiments of the present invention, the processing module 304 is specifically used for:

[0173] If the battery is in a static state and the current sleep time is longer than the preset battery sleep time, obtain the voltage value and average current value during the sleep period;

[0174] Based on the current range corresponding to the average current value, a second correction method is determined for correcting the voltage value during the sleep period;

[0175] Based on the second correction method, the voltage value during the sleep period is corrected to obtain the corrected voltage value during the sleep period;

[0176] Based on the second correction method, an estimation model is determined. The estimation algorithm used by the estimation model includes the first fitting formula and the second fitting formula. The corrected voltage value during the dormancy period and the battery's fourth dormancy duration are input into the estimation model to estimate the current battery SOC value, and the current battery SOC value is obtained and output.

[0177] In some embodiments of the present invention, the acquisition module 301 is further configured to acquire a second correction method;

[0178] The processing module 304 is also used to: determine whether the second correction method is related to the target voltage drop related to the small current; if the second correction method is related to the target voltage drop, then calculate the target voltage drop; otherwise, ignore the processing.

[0179] In some embodiments of the present invention, the processing module 304 is specifically used for:

[0180] If the battery is in a static state, based on the corresponding relationship curve, the different current open circuit voltages corresponding to the first sleep duration and different SOC nodes of different batteries can be obtained; and based on the small current discharge voltage curves of multiple SOC nodes, the static current and static voltage corresponding to the second sleep duration and different SOC nodes of different batteries can be obtained.

[0181] The voltage drop at different SOC nodes of the battery is calculated based on the different current open-circuit voltages corresponding to different SOC nodes and the static voltages corresponding to different SOC nodes.

[0182] Based on the voltage drop and corresponding quiescent current at different SOC nodes of the battery, the impedance values ​​of different SOC nodes are obtained.

[0183] The average impedance value was determined based on the fifth sleep duration of different batteries and different quiescent currents, and the weights were determined based on the average impedance value.

[0184] The target voltage drop is calculated based on the weights, different quiescent currents, and impedance values ​​of different SOC nodes.

[0185] In some embodiments of the present invention, the battery SOC value estimation device 300 provided in the present invention is based on the same inventive concept and has the same beneficial effects as the battery SOC value estimation method provided in the foregoing embodiments of the present invention.

[0186] In some embodiments of the present invention, the battery SOC value estimation device 300 provided in the present invention is based on the same inventive concept and has the same beneficial effects as the battery SOC value estimation method provided in the foregoing embodiments of the present invention.

[0187] Example 3

[0188] This invention provides a computer device including a memory and a processor. The processor is used to read instructions stored in the memory, which can execute a battery SOC value estimation method in any of the above method embodiments.

[0189] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0190] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0191] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0192] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0193] Example 4

[0194] This embodiment provides a computer-readable storage medium storing computer-executable instructions that can execute a control method for adjusting the heating and ventilation of a target car seat in any of the above method embodiments. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium may also include combinations of the above types of memory.

[0195] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for estimating the SOC value of a battery, characterized in that, The method includes: Obtain the curves showing the relationship between open-circuit voltage (OCV) and state of charge (SOC), as well as the small-current discharge voltage curves for multiple SOC nodes. Based on the corresponding curve, the mathematical relationship between the open-circuit voltage OCV and the state of charge SOC as a function of resting time is fitted to generate a first fitting formula. The first fitting formula is generated by fitting the mathematical relationship between the open-circuit voltage (OCV) and the state of charge (SOC) as a function of rest time based on the corresponding curve, including: At a first interval, the first battery terminal voltage value of the corresponding relationship curve is counted; Obtain the first confidence level and the first battery sleep duration; Based on the first confidence level, the mathematical relationship between the open-circuit voltage OCV and the state of charge SOC as a function of rest time is fitted to generate the first fitting formula with the open-circuit voltage OCV and the first dormancy time of the battery as input and the first battery SOC value as output. Based on the low-current discharge voltage curves of the multiple SOC nodes, the mathematical relationship between static discharge voltage, static discharge time and the state of charge (SOC) is fitted to generate a second fitting formula. The low-current discharge voltage curve based on the multiple SOC nodes is used to fit the mathematical relationship between the static discharge voltage, static discharge time, and the state of charge (SOC) to generate a second fitting formula, including: At second intervals, the second battery terminal voltage values ​​of the small current discharge voltage curves of the multiple SOC nodes are counted. Obtain the second confidence level and the second battery sleep duration; Based on the second confidence level, the mathematical relationship between the second terminal voltage of the battery and the state of charge (SOC) as a function of rest time is fitted to generate the second fitting formula, which takes the second terminal voltage of the battery and the second dormancy time of the battery as input and the SOC value of the second battery as output. Based on the initial voltage and initial current values ​​corresponding to different battery states, an estimation model is determined, and the current battery SOC value is estimated based on the estimation model to obtain and output the current battery SOC value; the different battery states include: the battery is in the state of first power-on, the battery is in the state of re-power-on, and the battery is in the state of rest; the estimation algorithm used by the estimation model includes the first fitting formula and the second fitting formula.

2. The estimation method according to claim 1, characterized in that, The process involves determining an estimation model based on the initial voltage and current values ​​corresponding to different battery states, estimating the current battery SOC value based on the estimation model, and obtaining and outputting the current battery SOC value, including: If the battery is in the first power-on state or the re-power-on state, obtain the initial voltage and initial current values ​​of the battery at the initial moment; Based on the current range corresponding to the initial current value, a first correction method is determined for correcting the initial voltage value. Based on the first correction method, the initial voltage value is corrected to obtain the corrected voltage value; Based on the first correction method, the estimation model is determined, and the estimation algorithm used by the estimation model includes the first fitting formula and the second fitting formula; The corrected voltage value and the third sleep duration of the battery are input into the estimation model to estimate the current battery SOC value, and the current battery SOC value is obtained and output.

3. The estimation method according to claim 1, characterized in that, The process of determining the corresponding estimation model based on the initial voltage and initial current values ​​corresponding to different battery states, estimating the current battery SOC value based on the estimation model, and obtaining and outputting the current battery SOC value includes: If the battery is in a static state and the current battery sleep time is longer than the preset battery sleep time, obtain the voltage value and average current value during the sleep period; Based on the current range corresponding to the average current value, a second correction method is determined for correcting the voltage value during the sleep period; Based on the second correction method, the voltage value during the sleep period is corrected to obtain the corrected voltage value during the sleep period; Based on the second correction method, the estimation model is determined. The estimation algorithm used by the estimation model includes the first fitting formula and the second fitting formula. The corrected voltage value during the dormancy period and the fourth dormancy duration of the battery are input into the estimation model to estimate the current battery SOC value, and the current battery SOC value is obtained and output.

4. The estimation method according to claim 3, characterized in that, The method further includes: Obtain the second correction method; Determine whether the second correction method is related to the target voltage drop associated with the small current. If the second correction method is related to the target voltage drop, calculate the target voltage drop; otherwise, ignore the processing.

5. The estimation method according to claim 4, characterized in that, The calculation of the target pressure drop includes: If the battery is in a static state, based on the corresponding relationship curve, the different current open circuit voltages corresponding to the first sleep duration and different SOC nodes of different batteries are obtained; and based on the small current discharge voltage curves of the multiple SOC nodes, the static current and static voltage corresponding to the second sleep duration and different SOC nodes of different batteries are obtained. The voltage drop at different SOC nodes of the battery is calculated based on the different current open-circuit voltages corresponding to different SOC nodes and the static voltages corresponding to different SOC nodes. Based on the voltage drop and corresponding quiescent current at different SOC nodes of the battery, the impedance values ​​of different SOC nodes are obtained. The average impedance value is determined based on the fifth sleep duration of different batteries and different static currents, and the weight is determined based on the average impedance value. The target voltage drop is calculated based on the weights, different quiescent currents, and impedance values ​​of different SOC nodes.

6. A device for estimating the SOC value of a battery, characterized in that, The device includes: The acquisition module is used to acquire the curves showing the relationship between open-circuit voltage (OCV) and state of charge (SOC), as well as the small-current discharge voltage curves of multiple SOC nodes. The first generation module is used to fit the mathematical relationship between the OCV and the SOC as a function of resting time based on the corresponding relationship curve, and generate a first fitting formula. The first generation module is specifically used for: At a first interval, the first battery terminal voltage value of the corresponding relationship curve is counted; Obtain the first confidence level and the first battery sleep duration; Based on the first confidence level, the mathematical relationship between the open-circuit voltage OCV and the state of charge SOC as a function of rest time is fitted to generate the first fitting formula with the open-circuit voltage OCV and the first dormancy time of the battery as input and the first battery SOC value as output. The second generation module is used to fit the mathematical relationship between static discharge voltage, static discharge time and SOC based on the small current discharge voltage curves of the multiple SOC nodes, and generate a second fitting formula. The second generation module is specifically used for: At second intervals, the second battery terminal voltage values ​​of the small current discharge voltage curves of the multiple SOC nodes are counted. Obtain the second confidence level and the second battery sleep duration; Based on the second confidence level, the mathematical relationship between the second terminal voltage of the battery and the state of charge (SOC) as a function of rest time is fitted to generate the second fitting formula, which takes the second terminal voltage of the battery and the second dormancy time of the battery as input and the SOC value of the second battery as output. The processing module is used to determine the corresponding estimation model based on the initial voltage and initial current values ​​corresponding to different battery states, and to estimate the current battery SOC value based on the estimation model, thereby obtaining and outputting the current battery SOC value. The different battery states include: the battery is in the state of first power-on, the battery is in the state of re-power-on, and the battery is in the state of rest. The estimation formula corresponding to the estimation model includes the first fitting formula and the second fitting formula.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program for performing the estimation method according to any one of claims 1 to 5.

8. An electronic device, characterized in that, The electronic device includes: processor; Memory for storing the executable instructions of the processor; The processor is configured to read the executable instructions from the memory and execute the executable instructions to implement the estimation method according to any one of claims 1 to 5.

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