Lithium battery equivalent circuit model parameter online adaptive adjustment method and related device

Abstract

The present invention relates to the field of lithium battery technology, and in particular to an online adaptive adjustment method for equivalent circuit model parameters of lithium batteries, including: obtaining reference values ​​of equivalent circuit model parameters of sample batteries under different working conditions; different working conditions include one or more of different battery temperatures, different states of charge, different current directions, and different current magnitudes; determining target adjustment parameters of a target battery; obtaining correction coefficients of target adjustment parameters using an interval integration method according to actual working conditions; adaptively adjusting target adjustment parameters according to reference values ​​of equivalent circuit model parameters of sample batteries under different working conditions in combination with correction coefficients to obtain final values ​​of equivalent circuit model parameters of target batteries under different working conditions. The method can obtain accurate parameters of equivalent circuit models under different working conditions by adjusting the parameters of the equivalent circuit model of the target battery under actual working conditions, thereby improving the accuracy and reliability of the equivalent circuit model.

Description

Technical Field

[0001] The present invention relates to the technical field of lithium batteries, and in particular to an online adaptive adjustment method for lithium battery equivalent circuit model parameters, electronic equipment and storage medium. Background Art

[0002] The state of charge (SOC) is an important parameter of lithium batteries. Generally, the SOC is estimated through parameters such as voltage, current and temperature, thereby completing functions such as battery charge and discharge control and thermal management.

[0003] In practical applications, it is difficult to achieve accurate online estimation of SOC due to various factors. Currently, the commonly used SOC estimation methods include three categories: traditional methods, model-based methods and intelligent algorithms. Among them, there are two types of models established by model-based methods, one is the electrochemical model and the other is the equivalent circuit model. The equivalent circuit models include the Rint model, the Thevenin model, the second-order RC model, the PNGV model, the GNL model, etc. Among them, the second-order RC equivalent circuit model (i.e., the improved Thevenin model) is the most widely used. However, the existing equivalent circuit model cannot obtain accurate parameters, resulting in low estimation accuracy of the SOC value of the lithium battery and an inability to obtain a more accurate SOC value.

[0004] In addition, the parameters of the current equivalent circuit model are all obtained based on the test data of sample battery cells, but different battery cells have different parameters due to individual differences. In addition, as the battery is used, the battery gradually ages, and the parameters of the aged battery are also changing. The drastic change in battery temperature will also cause its parameters to change. If fixed model parameters are used to estimate the SOC of the lithium battery, it is impossible to obtain an accurate battery voltage estimate, resulting in a large voltage estimation error. Summary of the invention

[0005] In view of this, an embodiment of the present invention provides an online adaptive adjustment method, electronic device and storage medium for parameters of an equivalent circuit model of a lithium battery. The method can obtain accurate parameters of the equivalent circuit model under different operating conditions by adjusting the parameters of the equivalent circuit model of the target battery under actual operating conditions, thereby improving the accuracy and reliability of the equivalent circuit model.

[0006] To solve the above technical problems, the embodiments of the present invention provide the following technical solutions:

[0007] In a first aspect, an embodiment of the present invention provides an online adaptive adjustment method for parameters of a lithium battery equivalent circuit model, the method comprising:

[0008] Obtain reference values ​​of equivalent circuit model parameters of the sample battery under different operating conditions; the different operating conditions include one or more of different battery temperatures, different states of charge, different current directions, and different current magnitudes;

[0009] Determining target adjustment parameters of a target battery;

[0010] According to the actual working conditions, the correction coefficient of the target adjustment parameter is obtained by using the interval integration method;

[0011] According to the reference values ​​of the equivalent circuit model parameters of the sample battery under different working conditions, the target adjustment parameters are adaptively adjusted in combination with the correction coefficient to obtain the final values ​​of the equivalent circuit model parameters of the target battery under different working conditions.

[0012] In some embodiments, the target adjustment parameter includes ohmic internal resistance and / or polarization resistance.

[0013] In some embodiments, determining the target adjustment parameter of the target battery includes:

[0014] The sample battery and the target battery are subjected to a difference test under the same experimental conditions, and a parameter whose difference exceeds a threshold is determined as a target adjustment parameter according to the test curves of the two.

[0015] In some embodiments, the difference test is a hybrid power pulse characteristic test.

[0016] In some embodiments, when the target adjustment parameter is ohmic internal resistance, the step of obtaining the correction coefficient of the target adjustment parameter by using the interval integration method includes:

[0017] Charging or discharging the target battery, and acquiring status data of the target battery at each sampling time in real time, wherein the status data includes battery temperature, state of charge, current direction, current magnitude, and actual voltage value;

[0018] Based on the state data of the target battery at each sampling time, searching for the parameter reference value corresponding to the sample battery at each sampling time, and obtaining the voltage estimation value of the sample battery at each sampling time based on the parameter reference value;

[0019] Subtracting the actual voltage value of the target battery at each sampling moment from the estimated voltage value of the sample battery to obtain a voltage difference value at each sampling moment;

[0020] Performing time integration on the voltage difference within a first range to obtain a voltage accumulation value;

[0021] Performing time integration on the current within a first range to obtain a current accumulated value;

[0022] A ratio of the voltage accumulated value to the current accumulated value is obtained, and a correction coefficient is obtained based on the ratio.

[0023] In some embodiments, when the target adjustment parameter is polarization resistance, the step of obtaining the correction coefficient of the target adjustment parameter by using the interval integration method includes:

[0024] When the charging or discharging of the target battery reaches a preset interruption condition, the charging or discharging of the target battery is interrupted for a second time interval and then the charging or discharging of the target battery is resumed;

[0025] Real-time acquisition of status data of the target battery at each sampling time after the charge or discharge is resumed, wherein the status data includes battery temperature, state of charge, current direction, current magnitude, and actual voltage value;

[0026] Calculate the actual voltage difference of the target battery at the first sampling time and the reference sampling time, and obtain the second slope of the target battery according to the actual voltage difference and the first duration, wherein the reference sampling time is the first sampling time among the sampling times, the first sampling time is any time among the sampling times except the reference sampling time, and the first duration is equal to the absolute value of the difference between the first sampling time and the reference sampling time;

[0027] Based on the state data of the target battery at each sampling time after the charging or discharging is resumed, the parameter reference values ​​corresponding to the sample battery at each sampling time after the charging or discharging is resumed are searched, and based on the parameter reference values, a voltage estimation curve of the sample battery when the charging or discharging is resumed after the charging or discharging is interrupted for a second time interval is obtained; according to the voltage estimation curve, an estimated voltage difference of the sample battery at the first sampling time and the reference sampling time is calculated; according to the estimated voltage difference and the first time length, a first slope of the sample battery is obtained;

[0028] Performing time integration on the first slope within a second range to obtain a first slope accumulated value;

[0029] Performing time integration on the second slope within a second range to obtain a second slope accumulated value;

[0030] The correction coefficient is obtained according to the first slope accumulated value and the second slope accumulated value.

[0031] In some embodiments, the battery temperature when the parameters were last adjusted is recorded, and when the difference between the current battery temperature and the battery temperature when the parameters were last adjusted exceeds a threshold, the parameters are adjusted again.

[0032] In some embodiments, the lithium battery equivalent circuit model includes equivalent circuit models in two states: one is a first equivalent circuit model in a current excitation state, and the other is a second equivalent circuit model in a non-current excitation state; the first equivalent circuit model includes a first parameter; the second equivalent circuit model includes a second parameter; the first parameter is different from the second parameter.

[0033] In some embodiments, a method for obtaining reference values ​​of the first parameter and the second parameter of the sample battery under different working conditions is as follows:

[0034] Based on the first equivalent circuit model, a first relational expression of the terminal voltage of the sample battery is established, wherein the first relational expression includes the first parameter; based on the second equivalent circuit model, a second relational expression of the terminal voltage of the sample battery is established, wherein the second relational expression includes the second parameter;

[0035] Acquire first test data of charging or discharging of the sample battery under set experimental conditions, the first test data including: test time and battery SOC, current and terminal voltage corresponding to the test time; acquire second test data of the battery under set experimental conditions and in a static state, the second test data including: test time and battery SOC, current and terminal voltage corresponding to the test time; the set experimental conditions are fixed battery temperature and charge and discharge current;

[0036] Obtaining an open circuit voltage characteristic curve of the sample battery, wherein the open circuit voltage characteristic curve is a curve of a relationship between an open circuit voltage of a battery and a battery SOC at a specific battery temperature;

[0037] According to the battery SOC and battery temperature in the first test data and the second test data, and in accordance with the open circuit voltage characteristic curve, obtaining the open circuit voltage corresponding to the SOC of each battery;

[0038] Inputting the first test data and the corresponding open circuit voltage into a first relational expression, inputting the second test data and the corresponding open circuit voltage into a second relational expression, and obtaining reference values ​​of the first parameter and the second parameter of the sample battery under set experimental conditions through an identification algorithm;

[0039] Different set experimental conditions are changed to obtain reference values ​​of the first parameter and the second parameter under different working conditions, and the set experimental conditions include at least one of battery temperature, current magnitude and current direction.

[0040] In a second aspect, an embodiment of the present invention provides an electronic device, including:

[0041] A processor and a memory communicatively connected to the processor;

[0042] The memory stores computer program instructions executable by the processor, and when the computer program instructions are called by the processor, the processor executes any one of the online adaptive adjustment methods for lithium battery equivalent circuit model parameters proposed in the first aspect.

[0043] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium, on which is stored computer program instructions executable by a processor, and when the computer program instructions are called by the processor, the processor executes any one of the online adaptive adjustment methods for lithium battery equivalent circuit model parameters proposed in the first aspect.

[0044] Beneficial effects of the embodiments of the present invention: Different from the prior art, the online adaptive adjustment method of the equivalent circuit model parameters of a lithium battery provided by the embodiments of the present invention includes: obtaining reference values ​​of the equivalent circuit model parameters of a sample battery under different operating conditions; different operating conditions include one or more of different battery temperatures, different charge states, different current directions, and different current magnitudes; determining the target adjustment parameters of the target battery; according to the actual operating conditions, obtaining the correction coefficient of the target adjustment parameter by using the interval integration method; according to the reference values ​​of the equivalent circuit model parameters of the sample battery under different operating conditions, the target adjustment parameters are adaptively adjusted in combination with the correction coefficient to obtain the final value of the equivalent circuit model parameters of the target battery under different operating conditions.

[0045] In an embodiment of the present invention, the method uses an interval integration method to obtain the correction coefficient of the target adjustment parameter of the equivalent circuit model of the target battery under actual working conditions, and combines the reference values ​​of the equivalent circuit model parameters of the sample battery under different working conditions to adjust the target adjustment parameters of the equivalent circuit model of the target battery under actual working conditions. The accurate parameters of the equivalent circuit model under different working conditions can be obtained, the accuracy and reliability of the equivalent circuit model can be improved, and the actual power characteristics of the lithium battery can be accurately reflected. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art description. Obviously, the drawings described below only illustrate certain embodiments of the present invention and should not be regarded as limiting the scope of protection. For those of ordinary skill in the art, other related drawings can also be obtained based on these drawings without creative work.

[0047] Figure 1 It is a structural schematic diagram of a second-order RC equivalent circuit model of a battery in the prior art;

[0048] Figure 2 is the voltage response curve of the battery during each pulse in the HPPC test;

[0049] Figure 3 is a structural schematic diagram of a second-order RC equivalent circuit model of a battery in Embodiment 1 of the present invention;

[0050] Figure 4 is a structural schematic diagram of the Thevenin equivalent circuit model of the battery in the second embodiment of the present invention;

[0051] Figure 5 : is a structural schematic diagram of a PNGV model equivalent circuit model of a battery in Embodiment 3 of the present invention;

[0052] Figure 6 1 is a schematic structural diagram of a GNL model equivalent circuit model of a battery in Embodiment 4 of the present invention;

[0053] Figure 7 1 is a flow chart of an online adaptive adjustment method for lithium battery equivalent circuit model parameters in Embodiment 5 of the present invention;

[0054] Figure 8 is a schematic diagram of obtaining the first slope K1 and the second slope K2 in Embodiment 5 of the present invention;

[0055] Fig. 9 is a schematic diagram of the structure of an electronic device provided by Embodiment 6 of the present invention;

[0056] Fig.10 is a schematic diagram of experimental data of an embodiment of the present invention under a charging condition with a relatively stable current;

[0057] Fig.11 It is a schematic diagram of experimental data of an embodiment of the present invention under a discharge condition with a relatively stable current. DETAILED DESCRIPTION

[0058] In order to make the purpose and advantages of the embodiments of the present invention easier to understand, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. The detailed description of the embodiments of the present invention in the drawings below does not limit the scope of protection claimed by the present invention, but only represents the selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0059] It should be noted that, if no conflict is constituted, the various technical features involved in the embodiments of the present invention described below can be combined with each other, and are all within the scope of protection of the present invention. In addition, although the functional modules are divided in the device or structural schematic diagram, and the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in a different order than the module division in the device, or in a different order than in the flow chart. In addition, the "first", "second", "third" and other similar expressions used herein do not limit the data and execution order, but are only for the purpose of convenience of explanation and to distinguish between the same or similar items with basically the same functions and effects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features.

[0060] Unless otherwise defined, the technical terms and scientific terms used in this specification have the same meanings as those generally understood by those of ordinary skill in the art of the present invention. The terms used in this specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. It should be understood that the term "and / or" used in this specification includes any and all combinations of one or more of the related listed items.

[0061] The battery equivalent circuit model is designed to simulate the electrical characteristics of the battery by simplifying the circuit, so as to facilitate the analysis and prediction of battery performance. These models can help us understand the behavior of the battery in different operating scenarios, such as key indicators such as voltage, current, output power and efficiency. Common battery equivalent circuit models include the Rint model (internal resistance model), the Thevenin model (Thevenin model, also known as the first-order RC model), the second-order RC model, the PNGV model (New Generation Vehicle Partner Program model), the GNL model (nonlinear equivalent model), etc. Among them, the second-order RC model can better balance the model accuracy and model complexity, and has won wide recognition and adoption in the industry, becoming the preferred solution in the field of battery management system (BMS) design and performance optimization.

[0062] See also Figure 1 , Figure 1 The schematic diagram of the structure of a typical second-order RC model 100 in the prior art includes: an ohmic internal resistance , the first polarization resistance , the second polarization resistance , first polarization capacitor , the second polarization capacitor and open circuit voltage Specifically, the first polarization resistance Electrochemical polarization internal resistance , the second polarization resistance is the concentration polarization internal resistance , first polarization capacitor Electrochemical polarization capacitance , the second polarization capacitor is the concentration polarization capacitance .

[0063] Open Circuit Voltage (OCV) is the core part of the model. The open circuit voltage of a battery refers to the voltage across the battery when the battery is not connected to any external load, that is, in an open circuit state. In this state, no current flows inside the battery, so the open circuit voltage directly reflects the electrochemical potential difference of the battery under static conditions and is not affected by internal resistance.

[0064] Battery terminal voltage It is the actual output voltage of the model after considering the influence of the battery internal resistance and load. It refers to the voltage measured between the positive and negative electrodes of the battery when the battery bears the load, that is, under normal working conditions. Due to the resistance inside the battery, when current passes through, this part of the resistance will cause a voltage drop, making the actual terminal voltage lower than the open circuit voltage. The change of battery terminal voltage is restricted by many factors, including the state of charge (SOC), operating temperature and discharge rate.

[0065] The parameter that can be directly measured in the second-order RC model in the experiment is usually the current flowing through the battery and terminal voltage , while other resistance and capacitance parameters (ohm internal resistance , the first polarization resistance , the second polarization resistance , first polarization capacitor , the second polarization capacitor ) cannot be directly tested, so parameter identification is required.

[0066] The identification of resistance and capacitance components in a battery model usually involves a series of experiments. Common experimental methods include the following:

[0067] 1) Constant current charge and discharge test: Charge and discharge the battery at a constant current and record the voltage change over time. By analyzing the charge and discharge curves, the battery's ohmic internal resistance and electrochemical polarization resistance can be estimated.

[0068] 2) Pulse test: Apply a short current pulse to the battery and measure the instantaneous change in voltage before and after the pulse. This method can be used to estimate the dynamic internal resistance of the battery, including fast and slow response RC links.

[0069] 3) AC impedance spectroscopy: Apply a small amplitude AC signal (usually at the millivolt level) and measure the impedance of the battery over a wide frequency range. It can provide impedance information of the battery at different time scales, thereby identifying the parameters of the RC link.

[0070] 4) Step response test: Apply a step change in voltage or current to observe the dynamic response of the battery voltage. The step response can reveal the transient characteristics of the battery and help identify the RC time constant.

[0071] 5) Hybrid Pulse Power Characterization (HPPC) test: As a comprehensive dynamic test method, especially combining the features of pulse test and step response test, it includes a series of pulse charge and discharge of the battery at different states of charge (SOC) of the battery, while also considering the regeneration ability of the battery, providing a more comprehensive view of battery performance.

[0072] In the HPPC test, the battery goes through the following steps: 1) charging to a full state; 2) discharging to a specific state of charge; 3) a period of rest to allow the battery to reach thermal equilibrium; 4) applying a series of current pulses, usually including smaller pulses and larger pulses, to simulate the transient working conditions of the battery in actual applications; 5) recording the voltage response curve during each pulse; 6) performing regenerative charging, that is, applying reverse pulses to evaluate the battery's energy recovery capability.

[0073] The voltage response curve during each pulse is as follows Figure 2 As shown, it mainly includes 4 sections:

[0074] AB segment: voltage jump segment when current is loaded; BC segment: voltage slowly changes segment after current is loaded; CD segment: voltage jump segment after current is unloaded; DE segment: voltage slowly changes segment after current is unloaded. In the prior art, parameters are usually obtained through AB segment and CD segment. When the current changes suddenly (AB and CD segments), the voltage at both ends of the lithium battery will drop and rise suddenly, but at this moment, no polarization effect will occur inside the current, so and There will be no change at this moment, so the voltage drop at the battery terminal when the current appears and disappears can be used to calculate the ohmic internal resistance. , which is expressed as the following formula:

[0075] Formula (1)

[0076] In the prior art, the test data of the DE segment is subsequently obtained. * (Tau1) and * (Tau2), obtained through the test data of the BC segment and .

[0077] However, since the current state of the AB and BC segments is different from that of the CD and DE segments, the current of the AB and CD segments is Usually they are not the same value, but the existing technology is equivalent to taking the average value of the AB segment and the CD segment and assigning it to , so a large error is introduced in the early stage of fitting; similarly, the prior art * Assigned to the BC segment * , parameter identification is performed based on the premise that the two are equal. Although the error of the voltage fitting result of the DE segment is small, the error of the voltage fitting result of the BC segment is large. In actual use, accurate fitting results are usually required in the BC segment. The prior art uses the same set of model parameters for the AC segment and the CE segment with different current excitation states, resulting in a large difference between the fitting results and the actual voltage measurement results of the HPPC experiment in the full SOC segment, and also a large difference between the voltage measurement results during constant current charging and discharging. The reason is that the prior art does not fully consider the influence of different current excitation states. Therefore, when the same set of parameter identification results is applied to different current excitation states, there is a large error in the voltage fitting results, especially when applied to battery voltage estimation at low current. When further applied to battery SOC estimation, accurate estimation values ​​cannot be obtained.

[0078] Example 1 (Second-order RC model in two states)

[0079] The embodiment of the present application fully considers the influence of different current excitation states and improves the original equivalent circuit model into an equivalent circuit model with two states, one is the equivalent circuit model with current excitation state, and the other is the equivalent circuit model without current excitation state. The parameters of the equivalent circuit models in the two states are set separately.

[0080] Take the second-order RC model as an example, Figure 3 As shown, the second-order RC model 200 includes two state models: a state with current excitation and a state without current excitation. The model 201 with current excitation includes: a first ohmic internal resistance , the first polarization resistance , the second polarization resistance , the first polarization capacitor , Second polarization capacitor and open circuit voltage ; Model 202 in the non-current excitation state, including: a second ohm internal resistance , the first two polarization resistor , the second polarization resistor , the first two polarization capacitors , the second polarization capacitor and open circuit voltage .

[0081] By setting a set of parameters for the equivalent circuit models in the two states respectively and identifying these two sets of parameters, the behavior of the battery under different temperatures, different SOCs, different current sizes and different charging and discharging directions can be accurately simulated.

[0082] Based on the above two-state second-order RC model, the battery terminal voltage The discretization relationship can be expressed as follows:

[0083] For the state model with current excitation (AC segment), the terminal voltage The first relation is:

[0084] Formula (2)

[0085] Formula (3)

[0086] Formula (4)

[0087] For the state model without current excitation (CE segment), the terminal voltage The second relation is:

[0088] Formula (5)

[0089] Formula (6)

[0090] Formula (7)

[0091] in, is the open circuit voltage of lithium battery, is the terminal voltage of the lithium battery; It is the working current of lithium battery when charging and discharging. is the ohmic internal resistance of the lithium battery under current excitation, is the electrochemical polarization voltage of the lithium battery under current excitation, , They are the polarization internal resistance and electrochemical polarization capacitance of lithium batteries under current excitation. is the concentration difference polarization voltage of the lithium battery under current excitation, , They are respectively the polarization internal resistance and concentration difference polarization capacitance of lithium battery under current excitation; is the ohmic internal resistance of the lithium battery in the state of no current excitation, is the electrochemical polarization voltage of the lithium battery in the state of no current excitation, , They are the polarization internal resistance and electrochemical polarization capacitance of lithium battery in the state of no current excitation, is the concentration difference polarization voltage of the lithium battery in the state of no current excitation, , They are respectively the polarization internal resistance and concentration difference polarization capacitance of lithium battery in the state of no current excitation, and Indicates time.

[0092] The two sets of parameters are identified, and under set experimental conditions (fixed battery temperature and charge / discharge current), the battery test data (battery SOC, terminal voltage, charge / discharge current, etc.) are obtained through experiments. The experiments used can be constant current charge and discharge test, pulse test, AC impedance spectrum, step response test, etc. In this embodiment, HPPC test is preferably used.

[0093] To perform HPPC test on the battery, first set the experimental conditions, such as battery temperature of 25℃ and discharge current of 1C ("C" refers to the rated capacity of the battery. For example, if a 100Ah battery is charged at 1C, the charging current is 100A). Before the test, adjust the battery state of charge to 100%, and then record the battery SOC and terminal voltage according to the following steps. , Current Changes over time.

[0094] The specific process information is as follows:

[0095]

[0096] In the above process step information, the discharge interval step is 5% SOC, and the standing time is 60 minutes. It can be adjusted according to actual conditions, for example: the discharge interval step is 2% SOC, 3% SOC, 10% SOC, etc., and the standing time is 1.5h, 2h, etc.

[0097] The test data of discharge under the set experimental conditions as above is taken as the first test data; the test data under the set experimental conditions and in a static state is taken as the second test data.

[0098] In addition, the open circuit voltage characteristic curve of the battery is obtained. The open circuit voltage characteristic curve is a table showing the relationship between the open circuit voltage of the battery and the battery SOC and the battery temperature. One way is to obtain it by using the test data of the HPPC test as above. The open circuit voltage is the voltage of the battery at point E during each pulse, that is, the voltage before the next round of discharge after each 60 minutes of rest. The HPPC test as above can only obtain the open circuit voltage at each discharge interval step (that is: the corresponding open circuit voltage at SOC=100%, 95%, 90%, ..., 10%, 5%, 0%), so another way can be used, that is, to test the open circuit voltage of the battery to obtain more accurate and more open circuit voltage experimental data (such as: the corresponding open circuit voltage at SOC=100%, 99%, 98%, ..., 3%, 2%, 1%, 0%).

[0099] According to the battery SOC and battery temperature in the first test data and the second test data, the open circuit voltage corresponding to each battery at a specific SOC and temperature can be obtained according to the open circuit voltage characteristic curve.

[0100] According to the two states of current excitation (AC segment) and no current excitation (CE segment), the first test data and the corresponding open circuit voltage are input into the first terminal voltage relation of formula (2)-formula (4), and the second test data and the corresponding open circuit voltage are input into the second terminal voltage relation of formula (5)-formula (7). The above terminal voltage relation is fitted with the actual test data to obtain the parameter values ​​in the relation.

[0101] Terminal voltage for two-state model The relationship and the corresponding sampling data are used to start the identification algorithm for parameter identification. The identification algorithms include the least squares algorithm, the maximum likelihood function method, the iterative least squares algorithm, the recursive least squares algorithm, the recursive augmented least squares algorithm, the recursive least squares algorithm with the forgetting factor, etc.

[0102] In this embodiment, the nlinfit function in MATLAB is used to perform parameter identification. nlinfit is a function in MATLAB that is used to perform nonlinear least squares regression, which is used to fit data points to a nonlinear mathematical model and minimize the residual sum of squares by adjusting the model parameters. nlinfit uses an iterative algorithm (usually the Loewenberg-Marquardt algorithm) to find the best parameter estimates.

[0103] The initial values ​​of the parameters in the terminal voltage relationship can be determined based on historical experience data or literature data. It is worth noting that the identification of the first parameter and the second parameter does not necessarily mean that all individual parameters are identified independently, but a combination of multiple parameters can be identified. For example, , , and No independent identification is performed, but * and * For example, in some embodiments, the initial value of the parameter in the terminal voltage relationship is set to [ , , , , , , , ]=[0.01, 0.01, 0.01, 0.01, 50, 100, 100, 500], where = * , = * , = * , = * According to the experimental data, the terminal voltage relationship is iteratively calculated using the identification algorithm (the parameter value is continuously changed based on the initial value), and the parameter corresponding to the minimum error between the terminal voltage estimate and the actual value is taken as the result of parameter identification.

[0104] The parameter identification results of the second-order RC model under different SOC states at a specific discharge current (1C) and a specific battery temperature (25°C) are shown in Table 1.

[0105] Table 1 Model parameter identification results (battery temperature 25°C, discharge current 1C)

[0106]

[0107] Subsequently, different set experimental conditions (including at least one of battery temperature, current magnitude, and current direction) are changed, and the above experiments and parameter identification methods are repeated to obtain the first parameters and the second parameters of the second-order RC model under different operating conditions (different temperatures, different current directions, different current magnitudes, and different SOC states).

[0108] When other conditions remain unchanged, only the current of the battery is changed. , and This is a parameter without current excitation, so it is not affected by current changes. Therefore, after fixing this parameter, you only need to identify , , , and .

[0109] By only changing the discharge current, the second-order RC model parameter identification results under different SOC states are shown in Table 2.

[0110] Table 2 Model parameter identification results (battery temperature 25°C, discharge current 0.5C)

[0111]

[0112] Example 2 (Thevenin model with two states)

[0113] This embodiment takes the Thevenin model as an example and improves the original equivalent circuit model into an equivalent circuit model with two states, one is an equivalent circuit model with current excitation, and the other is an equivalent circuit model without current excitation. The parameters of the equivalent circuit models in the two states are set separately.

[0114] like Figure 4 As shown, the Thevenin model 300 includes two state models: a state with current excitation and a state without current excitation. The model 301 with current excitation includes: a first ohmic internal resistance , the first polarization resistance , first polarization capacitor and open circuit voltage ; Model 302 in the non-current excitation state, including: a second ohm internal resistance , the second polarization resistance , the second polarization capacitor and open circuit voltage .

[0115] Based on the above two-state Thevenin model, the battery terminal voltage The discretization relationship can be expressed as follows:

[0116] For the state model with current excitation (AC segment), the terminal voltage The first relation is:

[0117] Formula (8)

[0118] Formula (9)

[0119] For the state model without current excitation (CE segment), the terminal voltage The second relation is:

[0120] Formula (10)

[0121] Formula (11)

[0122] in, is the open circuit voltage of lithium battery, is the terminal voltage of the lithium battery; It is the working current of lithium battery when charging and discharging. is the ohmic internal resistance of the lithium battery under current excitation, is the polarization voltage of the lithium battery under current excitation, , They are respectively the polarization internal resistance and polarization capacitance of lithium battery under current excitation; is the ohmic internal resistance of the lithium battery in the state of no current excitation, is the polarization voltage of the lithium battery in the state of no current excitation, , They are the polarization internal resistance and polarization capacitance of lithium battery in the state of no current excitation, and Indicates time.

[0123] Similarly, these two sets of parameters are identified, and under set experimental conditions (fixed battery temperature and charge and discharge current), the battery test data (battery SOC, terminal voltage, current, etc.) are obtained through experiments. The charge and discharge test data are used as the first test data, and the static test data are used as the second test data.

[0124] In addition, the open circuit voltage characteristic curve of the battery is obtained. According to the battery SOC and battery temperature in the first test data and the second test data, the open circuit voltage corresponding to each battery at a specific SOC and temperature can be obtained according to the open circuit voltage characteristic curve.

[0125] The test data of the battery (terminal voltage, open circuit voltage, current, temperature, SOC, etc.) are obtained through experiments, and the relationship formula (Formula 8-11) derived from the above theory is fitted with the actual test data to obtain the parameter values ​​in the relationship formula. The experiments used can be constant current charge and discharge test, pulse test, AC impedance spectrum, step response test, etc. This embodiment preferably uses HPPC test. The steps and process are similar to those of Example 1, except that the relationship formula is different.

[0126] Finally, the Thevenin model parameter identification result table under different operating conditions (different temperatures, different current directions, different current magnitudes, and different SOC states) is obtained.

[0127] Example 3 (PNGV model in two states)

[0128] This embodiment takes the PNGV model as an example and improves the original equivalent circuit model into an equivalent circuit model with two states, one is an equivalent circuit model with current excitation, and the other is an equivalent circuit model without current excitation. The parameters of the equivalent circuit models in the two states are set separately.

[0129] like Figure 5 As shown, the PNGV model 400 includes two state models: a state with current excitation and a state without current excitation. The model 401 with current excitation includes: an equivalent capacitor , the first ohm internal resistance , the first polarization resistance , first polarization capacitor and open circuit voltage ; Model 402 of the no current excitation state, including: equivalent capacitance , the second ohm internal resistance , the second polarization resistance , the second polarization capacitor and open circuit voltage .

[0130] Based on the above two-state PNGV model, the battery terminal voltage The discretization relationship can be expressed as follows:

[0131] For the state model with current excitation (AC segment), the terminal voltage The first relation is:

[0132] Formula (12)

[0133] Formula (13)

[0134] Formula (14)

[0135] For the state model without current excitation (CE segment), the terminal voltage The second relation is:

[0136] Formula (15)

[0137] Formula (16)

[0138] Formula (17)

[0139] in, is the open circuit voltage of lithium battery, is the terminal voltage of the lithium battery, It is the working current of lithium battery when charging and discharging. is the equivalent capacitance of the lithium battery, is the equivalent voltage of lithium battery; is the ohmic internal resistance of the lithium battery under current excitation, is the polarization voltage of the lithium battery under current excitation, , They are respectively the polarization internal resistance and polarization capacitance of lithium battery under current excitation; is the ohmic internal resistance of the lithium battery in the state of no current excitation, is the polarization voltage of the lithium battery in the state of no current excitation, , They are the polarization internal resistance and polarization capacitance of lithium battery in the state of no current excitation, and Indicates time.

[0140] Similarly, these two sets of parameters are identified, and the test data of the battery (terminal voltage, open circuit voltage, current, temperature, SOC, etc.) is obtained through experiments. The relationship equation (Formula 12-17) derived from the above theory is fitted with the actual test data to obtain the parameter values ​​in the relationship equation. The experiments used can be constant current charge and discharge test, pulse test, AC impedance spectrum, step response test, etc. This embodiment preferably uses HPPC test. The steps and process are similar to those of Example 1, except that the relationship equation is different.

[0141] Finally, the PNGV model parameter identification result table under different operating conditions (different temperatures, different current directions, different current magnitudes, and different SOC states) is obtained.

[0142] Example 4 (GNL model in two states)

[0143] This embodiment takes the GNL model as an example and improves the original equivalent circuit model into an equivalent circuit model with two states, one is an equivalent circuit model with current excitation, and the other is an equivalent circuit model without current excitation. The parameters of the equivalent circuit models in the two states are set separately.

[0144] like Figure 6 As shown, the GNL model 500 includes two state models: a state with current excitation and a state without current excitation. The model 501 with current excitation includes: an equivalent capacitor , Self-discharge resistance 、First ohm internal resistance , the first polarization resistance , the second polarization resistance , the first polarization capacitor , Second polarization capacitor and open circuit voltage ; Model 502 of the no current excitation state, including: equivalent capacitance , Self-discharge resistance 、Second ohm internal resistance , the first two polarization resistor , the second polarization resistor , the first two polarization capacitors , the second polarization capacitor and open circuit voltage .

[0145] Based on the above two-state GNL model, the battery terminal voltage The discretization relationship can be expressed as follows:

[0146] For the state model with current excitation and current not equal to 0, the terminal voltage The first relation is:

[0147] Formula (18)

[0148] Formula (19)

[0149] Formula (20)

[0150] Formula (21)

[0151] Formula (22)

[0152] For the state model without current excitation (CE segment), the terminal voltage The second relation is:

[0153] Formula (23)

[0154] Formula (24)

[0155] Formula (25)

[0156] Formula (26)

[0157] Formula (27)

[0158] Formula (28)

[0159] in, is the open circuit voltage of lithium battery, is the terminal voltage of the lithium battery, It is the working current of lithium battery when charging and discharging. is the self-discharge current, is the self-discharge resistance, is the equivalent capacitance of the lithium battery, is the equivalent voltage of lithium battery; is the ohmic internal resistance of the lithium battery under current excitation, is the electrochemical polarization voltage of the lithium battery under current excitation, , They are the polarization internal resistance and electrochemical polarization capacitance of lithium batteries under current excitation. is the concentration difference polarization voltage of the lithium battery under current excitation, , They are respectively the polarization internal resistance and concentration difference polarization capacitance of lithium battery under current excitation; is the ohmic internal resistance of the lithium battery in the state of no current excitation, is the electrochemical polarization voltage of the lithium battery in the state of no current excitation, , They are the polarization internal resistance and electrochemical polarization capacitance of lithium battery in the state of no current excitation, is the concentration difference polarization voltage of the lithium battery in the state of no current excitation, , They are respectively the polarization internal resistance and concentration difference polarization capacitance of lithium battery in the state of no current excitation, and Indicates time.

[0160] Similarly, these two sets of parameters are identified, and the test data of the battery (terminal voltage, open circuit voltage, current, temperature, SOC, etc.) is obtained through experiments. The relationship equations (Formulas 18-28) derived from the above theory are fitted with the actual test data to obtain the parameter values ​​in the relationship equations. The experiments used can be constant current charge and discharge tests, pulse tests, AC impedance spectroscopy, step response tests, etc. This embodiment preferably uses HPPC testing. The steps and processes are similar to those of Example 1, except that the relationship equations are different.

[0161] Finally, the GNL model parameter identification result table under different working conditions (different temperatures, different current directions, different current magnitudes, and different SOC states) is obtained.

[0162] Embodiment 5

[0163] The parameters of the existing lithium battery equivalent circuit model are usually obtained based on the test data of sample battery cells, but different battery cells have different parameters due to individual differences. In addition, as the battery is used, it gradually ages, and the parameters of the aged battery are also changing. The drastic change in battery temperature will also cause its parameters to change. If fixed model parameters are used to estimate the SOC of the lithium battery, it is also impossible to obtain an accurate battery voltage estimate, resulting in a large voltage estimation error.

[0164] To solve the above problems, the parameters of the lithium battery equivalent circuit model are adaptively adjusted online according to the actual working conditions, and the model parameters can be updated in real time during the battery operation to better adapt to battery aging, environmental changes or changes in battery use.

[0165] like Figure 7 As shown, this embodiment provides an online adaptive adjustment method for lithium battery equivalent circuit model parameters, the method comprising:

[0166] S701. Obtain reference values ​​of equivalent circuit model parameters of sample batteries under different operating conditions; different operating conditions include one or more of different battery temperatures, different states of charge, different current directions, and different current magnitudes.

[0167] The equivalent circuit model of the sample battery can adopt any existing lithium battery equivalent circuit model, and the reference values ​​of its model parameters are also obtained by adopting any existing parameter identification method.

[0168] Preferably, the equivalent circuit model of the sample battery adopts the improved lithium battery equivalent circuit model as described in Embodiments 1 to 4, and the method for obtaining the reference values ​​of its model parameters is as described above.

[0169] S702: Determine target adjustment parameters of the target battery.

[0170] Different equivalent circuit models have different model parameters. According to different equivalent circuit models, the target adjustment parameters can be selected based on historical experience. Usually, due to the influence of battery aging, environmental changes or changes in battery usage, the model parameters with large differences include: ohmic internal resistance and polarization resistance; polarization resistance includes concentration polarization internal resistance and electrochemical polarization internal resistance. The target adjustment parameters can be selected from any one or more of the above.

[0171] The target adjustment parameters can also be obtained through experiments, for example: subjecting the sample battery and the target battery to a difference test (such as HPPC test) under the same experimental conditions, and determining the parameter whose difference exceeds a threshold value based on the test curves of the two as the target adjustment parameter, and the threshold value is set based on experience.

[0172] S703. According to the actual working conditions, the correction coefficient of the target adjustment parameter is obtained by using the interval integration method.

[0173] Among them, the interval integration method means: in the process of charging or discharging the target battery, a specific time period is selected to integrate the current and voltage in the process, and the battery current and voltage changes in the selected time period are accurately measured and analyzed, and compared with the current and voltage changes of the sample battery under the same working conditions, so as to obtain the correction coefficient.

[0174] Specifically, when the target adjustment parameter is the ohmic internal resistance, the correction coefficient of the target adjustment parameter is obtained by using the interval integration method, including:

[0175] S7031. Charge or discharge the target battery, and obtain the status data of the target battery at each sampling time in real time, where the status data includes battery temperature, state of charge, current direction, current magnitude, and actual voltage value.

[0176] Specifically, if the target battery is a lithium battery, the battery temperature, state of charge, current direction, current magnitude, actual voltage value, etc. at each sampling moment during the charging or discharging process of the lithium battery are acquired in real time.

[0177] S7032. Based on the state data of the target battery at each sampling moment, find the parameter reference value corresponding to the sample battery at each sampling moment, and obtain the voltage estimation value of the sample battery at each sampling moment based on the parameter reference value.

[0178] The reference values ​​of the model parameters of the sample battery obtained in step S701 are a set of parameters under different operating conditions (different battery temperatures, different states of charge, different current directions, and different current magnitudes). According to the operating conditions (i.e., battery temperature, state of charge, current direction, and current magnitude) at each sampling moment during the charging or discharging process of the target battery, the parameter reference values ​​corresponding to each sampling moment during the charging or discharging process of the sample battery can be obtained from the parameter set, and the voltage estimation value of the sample battery at each sampling moment during the charging or discharging process can be obtained based on the parameter reference values.

[0179] S7033. Subtract the actual voltage value of the target battery at each sampling moment from the estimated voltage value of the sample battery to obtain the voltage difference value at each sampling moment.

[0180] The voltage difference at each sampling moment is equal to the actual voltage value of the target battery at each sampling moment minus the estimated voltage value of the sample battery at each sampling moment.

[0181] S7034. Perform time integration on the voltage difference within the first range to obtain a voltage accumulation value.

[0182] S7035. Perform time integration on the current within the first range to obtain a current accumulated value.

[0183] The first range is the duration range of charging or discharging of the target battery. The voltage difference is time-integrated within the first range, that is, the voltage difference of the target battery at each sampling moment within the first range is added to obtain a voltage accumulation value.

[0184] The current is time-integrated within the first range, that is, the current values ​​of the target battery at each sampling moment within the first range are added to obtain a current accumulated value.

[0185] The first range may be a range of SOC between 20% and 80%, for example, 30% to 40%.

[0186] S7036. Obtain a ratio of the voltage accumulated value to the current accumulated value, and obtain a correction coefficient based on the ratio.

[0187] The ratio of the voltage accumulated value to the current accumulated value is divided by the ohmic internal resistance reference value to obtain the offset coefficient, and the correction coefficient is equal to the sum of the offset coefficient and the preset correction value, and the preset correction value is 1.

[0188] Specifically, when the target adjustment parameter is polarization resistance, the correction coefficient of the target adjustment parameter is obtained by using the interval integration method, including:

[0189] S70301. When charging or discharging of a target battery reaches a preset interruption condition, interrupting charging or discharging of the target battery for a second time interval and then resuming charging or discharging of the target battery.

[0190] The preset interruption condition may be that the SOC of the battery reaches a preset SOC threshold, the battery temperature reaches a preset temperature threshold, etc.

[0191] For lithium batteries, the preset SOC threshold is selected to be a value between 20% and 80%; the second interruption time is about 3 seconds. For example, when the charging or discharging of the lithium battery reaches 20%, the charging or discharging of the lithium battery is interrupted for 3 seconds. When the charging or discharging interruption time reaches 3 seconds, the charging or discharging of the lithium battery is resumed.

[0192] S70302. Acquire in real time the state data of the target battery at each sampling time after the charge or discharge is resumed, the state data including the battery temperature, charge state, current direction, current magnitude and actual voltage value.

[0193] After the charging or discharging of the lithium battery is resumed, the battery temperature, state of charge, current direction, current magnitude and actual voltage value of the lithium battery at each sampling time after the charging or discharging is resumed are obtained in real time.

[0194] S70303. Calculate the actual voltage difference between the target battery at the first sampling moment and the reference sampling moment, and obtain the second slope K2 of the target battery according to the actual voltage difference and the first duration. The reference sampling moment is the first sampling moment among all sampling moments, the first sampling moment is any moment among all sampling moments except the reference sampling moment, and the first duration is equal to the absolute value of the difference between the first sampling moment and the reference sampling moment.

[0195] The voltage difference between the target battery at the first sampling time and the reference sampling time is equal to the actual voltage value of the target battery at the first sampling time minus the actual voltage value of the target battery at the reference sampling time.

[0196] The reference sampling time is the first sampling time among all sampling times, the first sampling time is any time among all sampling times except the reference sampling time, and the first duration is equal to the absolute value of the difference between the first sampling time and the reference sampling time.

[0197] In some embodiments, the second slope K2 is equal to the ratio of the actual voltage difference of the target battery at the first sampling time and the reference sampling time to the first time period.

[0198] S70304. Based on the state data of the target battery at each sampling moment after resuming charging or discharging, find the parameter reference values ​​corresponding to the sample battery at each sampling moment after resuming charging or discharging, and obtain the voltage estimation curve of the sample battery when charging or discharging is resumed after the second time interval after the charging or discharging is interrupted based on the parameter reference values; calculate the estimated voltage difference of the sample battery at the first sampling moment and the reference sampling moment according to the voltage estimation curve; obtain the first slope of the sample battery according to the estimated voltage difference and the first time duration.

[0199] The reference values ​​of the model parameters of the sample battery obtained in step S701 are a set of parameters under different working conditions (different battery temperatures, different states of charge, different current directions, and different current magnitudes). According to the working conditions (i.e., battery temperature, state of charge, current direction, and current magnitude) at each sampling moment after the target battery is charged or discharged and the charging or discharging is resumed after the second time interval, the parameter reference values ​​corresponding to each sampling moment of the sample battery under the corresponding working conditions can be obtained from the parameter set, and the voltage estimation curve at each sampling moment after the sample battery is charged or discharged and the charging or discharging is resumed after the second time interval can be obtained based on the parameter reference values. Then, the estimated voltage difference of the sample battery at the first sampling moment and the reference sampling moment is calculated based on the voltage estimation curve, and then the first slope K1 of the sample battery can be obtained based on the absolute value and the first duration of the voltage difference of the sample battery at the first sampling moment and the reference sampling moment.

[0200] In some embodiments, the first slope K1 is equal to the ratio of the absolute value of the voltage difference of the sample battery between the first sampling time and the reference sampling time to the first time duration.

[0201] For the first slope K1 and the second slope K2, the schematic diagram obtained is as follows Figure 8 As shown, Figure 8 The reference sampling time shown is the first sampling time after the lithium battery resumes charging, and the time range from sampling time a to sampling time b is the second range.

[0202] S70305. Perform time integration on the first slope within the second range to obtain a first slope accumulated value.

[0203] S70306. Perform time integration on the second slope within the second range to obtain a second slope accumulated value.

[0204] The second range is any one of the duration ranges of the target battery after the target battery resumes charging or discharging. The first slope is time-integrated within the second range, that is, the first slope K1 of each first sampling moment of the sample battery within the second range is added to obtain the first slope cumulative value.

[0205] The second slope is time-integrated within the second range, that is, the second slope K2 of the target battery at each first sampling moment within the second range is added to obtain a second slope accumulated value.

[0206] S70307. Obtain a correction coefficient according to the first slope accumulated value and the second slope accumulated value.

[0207] The correction coefficient is equal to the ratio of the second slope accumulated value to the first slope accumulated value.

[0208] S704 , adaptively adjusting the target adjustment parameters according to the reference values ​​of the equivalent circuit model parameters of the sample battery under different working conditions in combination with the correction coefficient to obtain the final values ​​of the equivalent circuit model parameters of the target battery under different working conditions.

[0209] Based on the correction coefficient of the target adjustment parameter under a certain working condition obtained in step S703, the target adjustment parameter of all working conditions of the target battery can be corrected. In some embodiments, the final value of the equivalent circuit model parameter of the target battery under different working conditions is equal to the reference value of the equivalent circuit model parameter of the sample battery under different working conditions multiplied by the correction coefficient of the target adjustment parameter of the target battery under different working conditions.

[0210] Generally, the operating conditions of the battery include the following:

[0211] 1) Charging conditions with relatively stable current

[0212] Usually the current when the battery is charging is relatively stable. For example, for lithium-ion batteries, the charging process is generally divided into pre-charging stage, constant current charging stage, constant voltage charging stage and floating charging stage. Among them, the constant current charging stage accounts for the largest proportion of the entire charging stage, roughly covering the range of the battery from empty state to SOC of about 80%-90%.

[0213] 2) Discharge condition with relatively stable current

[0214] For example: when using an energy storage power supply to charge a drone, the current output by the energy storage power supply will be relatively stable over a period of time.

[0215] 3) The current changes violently and then there is a long interruption / no current condition

[0216] For example, when an electric car is driving in sports mode (0 feedback), the driver actively releases the accelerator (about 30 seconds).

[0217] 4) Discharge conditions with drastic current changes

[0218] For example: When an electric vehicle driver steps on the accelerator pedal to accelerate, the battery must provide more current to meet the needs of the motor, which will cause a sudden surge in discharge current.

[0219] The above-mentioned method of using the interval integration method to obtain the correction coefficient of the target adjustment parameter and perform online adaptive adjustment on the lithium battery equivalent circuit model parameters in actual working conditions is usually applicable to working conditions 1) and 2), but not to working condition 3).

[0220] Regardless of operating condition 1) or operating condition 2), the above interval integration method does not require intervention or interruption of the charging and discharging conditions.

[0221] like Fig.10 As shown, Fig.10 The figure is a schematic diagram of experimental data under the charging condition with relatively stable current. Taking 2000s as the dividing point, all data before 2000s are relevant data before model parameter adjustment (calibration), and all data after 2000s are relevant data after model parameter adjustment (calibration). Fig.10 A is the battery charge rate (maintained at 0.5C), Fig.10 B is the battery temperature; Fig.10 In C, the estimated voltage before 2000s is the estimated voltage before the model parameters are adjusted, and the estimated voltage after 2000s is the estimated voltage after the model parameters are adjusted. Fig.10 As shown in Figure C, after 2000s, the estimated voltage and the real voltage tend to be consistent. Fig.10 Where D is the correction factor.

[0222] like Fig.11 As shown, Fig.11 The figure is a schematic diagram of experimental data under the discharge condition with relatively stable current. Taking 700s as the dividing point, all data before 700s are relevant data before the model parameter adjustment (calibration), and all data after 700s are relevant data after the model parameter adjustment (calibration). Fig.11 A is the battery charge rate (maintained at 0.5C), Fig.11 B is the battery temperature; Fig.11 In C, the estimated voltage before 700s is the estimated voltage before the model parameters are adjusted, and the estimated voltage after 700s is the estimated voltage after the model parameters are adjusted. Fig.11 As shown in Figure C, after 700s, the estimated voltage and the real voltage tend to be consistent. Fig.11 Where D is the correction factor.

[0223] For working conditions 3) and 4), when the current fluctuates violently, there is a large error between the real voltage and the sampled voltage, so the interval integral comparison between the estimated voltage and the sampled voltage is meaningless.

[0224] In order to reduce the amount of calculation for online adjustment of the parameters of the lithium battery equivalent circuit model, when the operating conditions of the target battery are relatively stable, the model parameters can be adjusted only once; but when the battery temperature changes drastically, the current battery temperature is recorded and compared with the battery temperature at the last parameter adjustment. If the temperature difference exceeds the threshold (for example, 5°C), the parameters of the target battery need to be adjusted again, and the adjustment method is the same as above.

[0225] In summary, the online adaptive adjustment method of the lithium battery equivalent circuit model parameters provided by the embodiment of the present invention includes: obtaining reference values ​​of the equivalent circuit model parameters of the sample battery under different operating conditions; the different operating conditions include one or more of different battery temperatures, different charge states, different current directions, and different current magnitudes; determining the target adjustment parameters of the target battery; according to the actual operating conditions, obtaining the correction coefficient of the target adjustment parameter by using the interval integration method; according to the reference values ​​of the equivalent circuit model parameters of the sample battery under different operating conditions, the target adjustment parameters are adaptively adjusted in combination with the correction coefficient to obtain the final value of the equivalent circuit model parameters of the target battery under different operating conditions.

[0226] In an embodiment of the present invention, the method uses an interval integration method to obtain the correction coefficient of the target adjustment parameter of the equivalent circuit model of the target battery under actual operating conditions, and combines the reference values ​​of the equivalent circuit model parameters of the sample battery under different operating conditions to adjust the target adjustment parameters of the equivalent circuit model of the target battery under actual operating conditions (especially under stable charging and stable discharging conditions). The method can obtain accurate parameters of the equivalent circuit model under different operating conditions, improve the accuracy and reliability of the equivalent circuit model, and accurately reflect the actual power characteristics of the lithium battery.

[0227] Embodiment 6

[0228] This embodiment provides an electronic device. Fig. 9 , Fig. 9 A schematic structural diagram of an electronic device 900 provided in some embodiments of the present invention is shown.

[0229] For example, Fig. 9 As shown, the electronic device 900 includes at least one processor 910 and a memory 920 ( Fig. 9 In the example of a bus system connection and a processor, the components in the electronic device 900 are coupled together through a bus system 930, and the bus system 930 is used to realize the connection and communication between these components. It is easy to understand that the bus system 930 includes not only a data bus, but also a power bus, a control bus, and a status signal bus. However, for the sake of clarity and brevity, the following description is omitted. Fig. 9 In the figure, various buses are labeled as bus system 930. Those skilled in the art will understand that Fig. 9 The structure shown in the embodiment is only for illustration and does not impose any limitation on the structure of the electronic device 900. For example, the electronic device 900 may also include Fig. 9 More or fewer components as shown, or with Fig. 9 Different configurations are shown.

[0230] Specifically, the processor 910 is used to provide computing and control capabilities to control the electronic device 900 to perform corresponding tasks. For example, the electronic device 900 is controlled to perform any of the online adaptive adjustment methods for lithium battery equivalent circuit model parameters provided in the fifth embodiment of the present invention, or to perform any of the steps in any possible implementation methods of the online adaptive adjustment method for lithium battery equivalent circuit model parameters provided in the fifth embodiment of the present invention. Those skilled in the art can understand that the processor 910 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0231] The memory 920, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer executable programs, instructions and modules, for example, programs, instructions and modules corresponding to the online adaptive adjustment method of the lithium battery equivalent circuit model parameters in the embodiment of the present invention. In some embodiments, the memory 920 may include a storage program area and a storage data area, and the storage program area may store an operating system, an application required for at least one function; the storage data area may store data created according to the use of the processor 910, etc. The processor 910 executes various functional applications and data processing of the electronic device 900 by running the non-transitory software programs, instructions and modules stored in the memory 920, so as to implement any of the online adaptive adjustment methods of the lithium battery equivalent circuit model parameters provided in the fifth embodiment of the present invention, or perform any of the steps in any possible implementation of the online adaptive adjustment method of the lithium battery equivalent circuit model parameters provided in the fifth embodiment of the present invention. In some embodiments, the memory 920 may include a high-speed random access memory, and may also include a non-transitory memory. For example, at least one disk storage device, a flash memory device or other non-transitory solid-state storage device. In some embodiments, the memory 920 may also include a memory remotely arranged relative to the processor 910, and these remote memories may be connected to the processor 910 via a network. It is understood that examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0232] It is easy to understand that the implementation subject of any of the online adaptive adjustment methods for lithium battery equivalent circuit model parameters provided in the embodiments of the present invention can be any suitable type of electronic device with certain computing and control capabilities. In some implementations, the online adaptive adjustment method for any of the lithium battery equivalent circuit model parameters provided in the embodiments of the present invention can be implemented by a processor calling a computer program instruction stored in a memory.

[0233] An embodiment of the present invention provides a computer-readable storage medium, on which computer program instructions executable by a processor are stored. When the computer program instructions are called by the processor, the processor executes any one of the online adaptive adjustment methods for lithium battery equivalent circuit model parameters provided by the embodiment of the present invention, or executes steps in any possible implementation method of any one of the online adaptive adjustment methods for lithium battery equivalent circuit model parameters provided by the embodiment of the present invention.

[0234] In some embodiments, the storage medium may be a flash memory, a hard disk, an optical disk, a register, a magnetic surface storage, a removable disk, a CD-ROM, a random access memory (RAM), a read-only memory (ROM), an electrically programmable ROM, and an electrically erasable programmable ROM, or any other form of storage medium known in the technical field, or may be various devices including one or any combination of the above storage media.

[0235] In some embodiments, computer program instructions may be in the form of a program, software, software module, script or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a stand-alone program or as a module, component, subroutine or other unit suitable for use in a computing environment.

[0236] As an example, computer program instructions may, but need not, correspond to a file in a file system, may be stored as part of a file storing other programs or data, such as in one or more scripts in a HyperText Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files storing one or more modules, subroutines, or code portions).

[0237] As an example, the computer program instructions may be deployed to be executed on a computing device (including devices such as smart terminals and servers), or on multiple computing devices located at one location, or on multiple computing devices distributed at multiple locations and interconnected by a communication network. It is easy to understand that all or part of the steps of the method described in the embodiments provided by the present invention above can be directly implemented using electronic hardware or processor executable computer program instructions, or a combination of the two.

[0238] Those skilled in the art will appreciate that the embodiments provided by the present invention are only illustrative, and the order of writing the steps in the method of the embodiment does not mean a strict execution order and does not constitute any limitation on the implementation process. The order can be adjusted, merged and deleted according to actual needs, and the modules or sub-modules, units or sub-units in the device or system of the embodiment can be merged, divided and deleted according to actual needs. For example, the division of units is only a logical function division, and there can be other division methods in actual implementation. For another example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed.

[0239] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a general hardware platform, and of course can also be implemented by hardware. Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0240] It should be noted that the above embodiments are intended to illustrate the technical concept and features of the present invention, and their purpose is to enable people familiar with this technology to understand the content of the present invention and implement it accordingly, and cannot be used to limit the scope of protection of the present invention. Ordinary technicians in this field can understand that all or part of the processes of the above embodiments can be implemented according to the technical solutions recorded in the embodiments of the present invention, or some of the technical features can be equivalently replaced. It can be understood that these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and should be regarded as equal changes and modifications based on the embodiments of the present invention, and should all fall within the scope of the claims of the present invention.

Claims

1. An online adaptive adjustment method for parameters of a lithium battery equivalent circuit model, characterized in that: The method comprises: Obtain reference values ​​of equivalent circuit model parameters of the sample battery under different operating conditions; the different operating conditions include one or more of different battery temperatures, different states of charge, different current directions, and different current magnitudes; Determining target adjustment parameters of a target battery, wherein the target adjustment parameters include ohmic internal resistance and / or polarization resistance; According to the actual working condition, the correction coefficient of the target adjustment parameter is obtained by using the interval integration method, wherein the interval integration method is to integrate the current and voltage in a specific time period to measure the current change and voltage change of the target battery in the specific time period, and compare them with the current change and voltage change of the sample battery under the actual working condition to obtain the correction coefficient of the target adjustment parameter; When the target adjustment parameter is ohmic internal resistance, the method of obtaining the correction coefficient of the target adjustment parameter by using the interval integration method includes: Charging or discharging the target battery, and acquiring status data of the target battery at each sampling time in real time, wherein the status data includes battery temperature, state of charge, current direction, current magnitude, and actual voltage value; Based on the state data of the target battery at each sampling time, searching for the parameter reference value corresponding to the sample battery at each sampling time, and obtaining the voltage estimation value of the sample battery at each sampling time based on the parameter reference value; Subtracting the actual voltage value of the target battery at each sampling moment from the estimated voltage value of the sample battery to obtain a voltage difference value at each sampling moment; Performing time integration on the voltage difference within a first range to obtain a voltage accumulation value; Performing time integration on the current within a first range to obtain a current accumulated value; Obtaining a ratio of the voltage accumulated value to the current accumulated value, and obtaining a correction coefficient based on the ratio; According to the reference values ​​of the equivalent circuit model parameters of the sample battery under different working conditions, the target adjustment parameters are adaptively adjusted in combination with the correction coefficient to obtain the final values ​​of the equivalent circuit model parameters of the target battery under different working conditions.

2. The method according to claim 1, characterized in that Determining the target adjustment parameter of the target battery includes: The sample battery and the target battery are subjected to a difference test under the same experimental conditions, and a parameter whose difference exceeds a threshold is determined as a target adjustment parameter according to the test curves of the two.

3. The method according to claim 2, characterized in that The difference test is a mixed power pulse characteristic test.

4. The method according to claim 1, characterized in that When the target adjustment parameter is polarization resistance, the method of obtaining the correction coefficient of the target adjustment parameter by using the interval integration method includes: When the charging or discharging of the target battery reaches a preset interruption condition, the charging or discharging of the target battery is interrupted for a second time interval and then the charging or discharging of the target battery is resumed; Real-time acquisition of status data of the target battery at each sampling time after the charge or discharge is resumed, wherein the status data includes battery temperature, state of charge, current direction, current magnitude, and actual voltage value; Calculate the actual voltage difference of the target battery at the first sampling time and the reference sampling time, and obtain the second slope of the target battery according to the actual voltage difference and the first duration, wherein the reference sampling time is the first sampling time among the sampling times, the first sampling time is any time among the sampling times except the reference sampling time, and the first duration is equal to the absolute value of the difference between the first sampling time and the reference sampling time; Based on the state data of the target battery at each sampling time after the charging or discharging is resumed, the parameter reference values ​​corresponding to the sample battery at each sampling time after the charging or discharging is resumed are searched, and based on the parameter reference values, a voltage estimation curve of the sample battery when the charging or discharging is resumed after the charging or discharging is interrupted for a second time interval is obtained; according to the voltage estimation curve, an estimated voltage difference of the sample battery at the first sampling time and the reference sampling time is calculated; according to the estimated voltage difference and the first time length, a first slope of the sample battery is obtained; Performing time integration on the first slope within a second range to obtain a first slope accumulated value; Performing time integration on the second slope within a second range to obtain a second slope accumulated value; The correction coefficient is obtained according to the first slope accumulated value and the second slope accumulated value.

5. The method according to claim 1, characterized in that The battery temperature when the parameters were last adjusted is recorded, and when the difference between the current battery temperature and the battery temperature when the parameters were last adjusted exceeds a threshold, the parameters are adjusted again.

6. The method according to claim 1, characterized in that The lithium battery equivalent circuit model includes equivalent circuit models in two states: one is a first equivalent circuit model in a current excitation state, and the other is a second equivalent circuit model in a non-current excitation state; the first equivalent circuit model includes a first parameter; the second equivalent circuit model includes a second parameter; the first parameter is different from the second parameter.

7. The method according to claim 6, characterized in that The method for obtaining the reference values ​​of the first parameter and the second parameter of the sample battery under different working conditions is as follows: Based on the first equivalent circuit model, a first relational expression of the terminal voltage of the sample battery is established, wherein the first relational expression includes the first parameter; based on the second equivalent circuit model, a second relational expression of the terminal voltage of the sample battery is established, wherein the second relational expression includes the second parameter; Acquire first test data of charging or discharging of the sample battery under set experimental conditions, the first test data including: test time and battery SOC, current and terminal voltage corresponding to the test time; acquire second test data of the battery under set experimental conditions and in a static state, the second test data including: test time and battery SOC, current and terminal voltage corresponding to the test time; the set experimental conditions are fixed battery temperature and charge and discharge current; Obtaining an open circuit voltage characteristic curve of the sample battery, wherein the open circuit voltage characteristic curve is a curve of a relationship between an open circuit voltage of a battery and a battery SOC at a specific battery temperature; According to the battery SOC and battery temperature in the first test data and the second test data, and in accordance with the open circuit voltage characteristic curve, obtaining the open circuit voltage corresponding to the SOC of each battery; Inputting the first test data and the corresponding open circuit voltage into a first relational expression, inputting the second test data and the corresponding open circuit voltage into a second relational expression, and obtaining reference values ​​of the first parameter and the second parameter of the sample battery under set experimental conditions through an identification algorithm; Different set experimental conditions are changed to obtain reference values ​​of the first parameter and the second parameter under different working conditions, and the set experimental conditions include at least one of battery temperature, current magnitude and current direction.

8. An electronic device, characterized in that: include: A processor and a memory communicatively connected to the processor; The memory stores computer program instructions executable by the processor, and when the computer program instructions are called by the processor, the processor executes the online adaptive adjustment method of the lithium battery equivalent circuit model parameters as described in any one of claims 1-7.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions executable by a processor, and when the computer program instructions are called by the processor, the processor executes the online adaptive adjustment method for lithium battery equivalent circuit model parameters as described in any one of claims 1-7.

Images