Lithium-ion battery internal resistance calculation method, device, electronic device and storage medium

Abstract

The present invention proposes a method, device, electronic device and storage medium for calculating the internal resistance of a lithium-ion battery. The method for calculating the internal resistance of a lithium-ion battery includes: decomposing the internal resistance of the battery to be calculated into charge transfer resistance, mass transfer resistance and ohmic internal resistance. Functional relationships between each internal resistance and factors such as temperature, battery state of charge, and charge and discharge current are established respectively. When calculating the internal resistance of each part, the method of establishing the functional relationship is not only based on mathematical fitting, but also takes into account the influence of temperature, battery state of charge and charge and discharge current on the internal resistance of the battery, which can more accurately predict the internal resistance of the battery. In addition, the present invention also predicts the change law of the internal resistance of the battery throughout its life cycle by establishing a functional relationship between each internal resistance and different aging conditions of the battery, thereby reducing the prediction error of the battery internal resistance in practical applications.

Description

Technical Field

[0001] The present invention relates to the field of electric vehicle battery management systems, and in particular to a method and device for calculating the internal resistance of a lithium-ion battery, an electronic device, and a storage medium. Background Art

[0002] The internal resistance of a lithium-ion battery is one of the most important characteristic parameters of the battery. It directly affects the battery's overpotential and has an impact on the battery's charging performance, discharge performance, and safety performance. For example, excessive internal resistance will cause the charging voltage platform to increase and the discharge voltage platform to decrease, greatly reducing the battery's efficiency. Excessive internal resistance will also make the discharge voltage more likely to trigger the cutoff voltage, thereby affecting the battery's discharge power and the user's driving experience. More importantly, excessive internal resistance will cause increased heat generation during battery use, accelerating temperature rise and exacerbating temperature inconsistencies within the battery pack, thereby posing a safety hazard. Therefore, accurately obtaining the battery's internal resistance value is crucial for more precise battery management and safer battery use.

[0003] Internal resistance is a very complex parameter. It is not only affected by the battery manufacturing process, but also varies with usage conditions or battery state of charge. This makes it very difficult to obtain internal resistance. Currently, the industry mostly obtains internal resistance through experimental testing. For example, CN111999667A describes a method for obtaining internal resistance at different temperatures through experimental testing. This method first obtains the internal resistance values ​​at different temperatures, and then obtains the mathematical relationship between internal resistance and temperature through data fitting. This mathematical relationship can be used to calculate the resistance values ​​at different temperatures. The experimental method is relatively straightforward to obtain internal resistance, but if you want to obtain an accurate internal resistance value, you need to design an extremely complex test condition matrix that covers various battery SOC states (state of charge), ambient temperatures, and operating conditions. CN113109726A describes a method for calculating battery internal resistance using an internal resistance model. This method first calculates the internal resistance using an equivalent circuit model. Based on the calculated internal resistance value, a quadratic polynomial function, a cubic spline fitting function, etc. are used to establish a functional relationship between the internal resistance and temperature, SOC, and discharge current. Finally, based on this functional relationship, the battery internal resistance is quickly calculated. Although this method takes into account the effects of factors such as temperature, SOC and discharge current on internal resistance, it only uses mathematical fitting methods to establish the functional relationship between internal resistance and the above factors. The fitting results obtained by this method cannot be well extended to other operating conditions outside the experimental conditions. In addition, this method fails to take into account the changing law of internal resistance throughout the battery life cycle. Therefore, it will inevitably introduce large deviations in practical applications. Summary of the Invention

[0004] In view of the above-mentioned shortcomings of the prior art, the present invention provides a method, device, electronic device and storage medium for calculating the internal resistance of a lithium-ion battery to solve the above-mentioned technical problems.

[0005] The present invention provides a method for calculating the internal resistance of a lithium-ion battery. The method comprises: obtaining battery operating parameters, the battery operating parameters including temperature, charge and discharge current, concentration potential, a relationship between a change in lithium ion concentration over time, and a relationship between the state of charge, temperature, and ohmic internal resistance of the lithium-ion battery; decomposing the internal resistance of the battery to be calculated into a charge transfer internal resistance, a mass transfer internal resistance, and an ohmic internal resistance; calculating the charge transfer internal resistance based on the temperature and charge and discharge current, calculating the mass transfer internal resistance based on a first relationship between the change in lithium ion concentration over time, the charge and discharge current, and the concentration potential, and calculating the ohmic internal resistance based on the relationship between the state of charge, temperature, and ohmic internal resistance of the lithium-ion battery; and obtaining the internal resistance of the battery to be calculated by combining the mass transfer internal resistance, charge transfer internal resistance, and ohmic internal resistance.

[0006] In one embodiment of the present invention, calculating the charge transfer internal resistance based on the temperature and the charge-discharge current includes: obtaining the charge transfer internal resistance through a gas constant, a Faraday constant, the temperature, and the charge-discharge current.

[0007] In one embodiment of the present invention, the mass transfer internal resistance is calculated based on the relationship between the change of lithium ion concentration and time and the concentration potential, and the concentration potential includes the negative electrode concentration potential, the positive electrode concentration potential and the electrolyte concentration potential, including: obtaining the negative electrode concentration potential through the temperature and the state of charge of the negative electrode of the lithium ion battery; obtaining the positive electrode concentration potential through the temperature and the state of charge of the positive electrode of the lithium ion battery; obtaining the negative electrode concentration potential through the migration number of lithium ions, the concentration of lithium ions in the electrolyte layer on the surface of the positive electrode of the battery, the concentration of lithium ions in the electrolyte layer on the surface of the negative electrode of the battery, the temperature and the relationship between the change of lithium ion concentration with time; obtaining the mass transfer internal resistance according to the first change relationship of the lithium ion concentration with time, the positive electrode concentration potential, the negative electrode concentration potential, the electrolyte concentration potential and the charge and discharge current.

[0008] In one embodiment of the present invention, the negative electrode concentration potential is obtained by using the gas constant, the Faraday constant, the temperature and the state of charge of the negative electrode of the lithium ion battery, including: obtaining the negative electrode concentration potential by the following formula:

[0009]

[0010] in, is the concentration potential of the lithium ion transfer process in the negative electrode, F is the Faraday constant, R is the gas constant, T is the ambient temperature, and x1 is the state of charge of the positive electrode.

[0011] In one embodiment of the present invention, the positive electrode concentration potential is obtained by using the gas constant, the Faraday constant, the temperature and the state of charge of the positive electrode of the lithium ion battery, including: obtaining the positive electrode concentration potential by the following formula:

[0012]

[0013] in, is the concentration potential of the lithium ion transfer process in the positive electrode, F is the Faraday constant, R is the gas constant, T is the ambient temperature, and x2 is the positive electrode charge state.

[0014] In one embodiment of the present invention, the negative electrode concentration potential is obtained by the migration number of lithium ions, the concentration of lithium ions in the electrolyte layer on the surface of the positive electrode of the battery, the concentration of lithium ions in the electrolyte layer on the surface of the negative electrode of the battery, the Faraday constant, the gas constant and the temperature, including: obtaining the initial electrolyte concentration potential by the migration number of lithium ions, the concentration of lithium ions in the electrolyte layer on the surface of the positive electrode of the battery, the concentration of lithium ions in the electrolyte layer on the surface of the negative electrode of the battery, the Faraday constant, the gas constant and the temperature:

[0015]

[0016] in, is the initial concentration potential of the electrolyte, t is the migration number of lithium ions, is the concentration of lithium ions in the electrolyte layer on the positive electrode surface, is the concentration of lithium ions in the electrolyte layer on the surface of the negative electrode, F is the Faraday constant, R is the gas constant, and T is the temperature; the electrolyte concentration potential is obtained according to the first change relationship of the lithium ion concentration over time and the initial electrolyte concentration potential

[0017]

[0018] in, is the electrolyte concentration potential, T is the temperature, and t0 is the battery aging time.

[0019] In one embodiment of the present invention, the mass transfer internal resistance is obtained based on the first change relationship between the lithium ion concentration and time, the positive electrode concentration potential, the negative electrode concentration potential, the electrolyte concentration potential and the charge and discharge current, including: summing the positive electrode concentration potential, the negative electrode concentration potential, and the electrolyte concentration potential to obtain a first total concentration potential; and determining the ratio of the first total concentration potential to the charge and discharge current as the mass transfer internal resistance.

[0020] In one embodiment of the present invention, the ohmic internal resistance is calculated based on a relationship between the state of charge and temperature of a lithium-ion battery and a change in the ohmic internal resistance, including: setting first test parameters, the first test parameters including the state of charge of the lithium-ion battery, a reference ambient temperature, and a preset frequency range, the first test parameters including multiple groups; testing the AC impedance under the first test parameters to obtain multiple groups of AC impedance test results; recording the AC impedance test results as Nyquist plots to obtain multiple Nyquist plots, and obtaining intercepts of the horizontal axis of the high-frequency band in the Nyquist plots by a linear interpolation method; recording the intercepts of the Nyquist plots as the ohmic internal resistance under the corresponding test parameters to obtain multiple reference ohmic internal resistances, and outputting a two-dimensional numerical table of reference ohmic internal resistances; fitting the reference ohmic internal resistances in the two-dimensional numerical table of reference ohmic internal resistances based on a functional relationship between the ohmic internal resistance and the temperature and state of charge of the lithium-ion battery to obtain an ohmic internal resistance fitting coefficient; and substituting the ohmic internal resistance fitting coefficient into the functional relationship between the ohmic internal resistance and the temperature and state of charge of the lithium-ion battery to obtain the ohmic internal resistance.

[0021] In one embodiment of the present invention, the battery internal resistance to be calculated is obtained by combining the mass transfer internal resistance, the charge transfer internal resistance and the ohmic internal resistance, and further includes: calculating the full life cycle mass transfer internal resistance and the full life cycle ohmic internal resistance; summing the charge transfer internal resistance, the full life cycle mass transfer internal resistance and the full life cycle ohmic internal resistance to obtain the full life cycle internal resistance of the battery to be calculated.

[0022] In one embodiment of the present invention, the whole life cycle mass transfer internal resistance is calculated, including: obtaining the whole life cycle electrolyte concentration potential based on the second change relationship of the lithium ion concentration over time and the initial electrolyte concentration potential

[0023]

[0024] in, is the full life cycle electrolyte concentration potential, t0 is the battery aging time, T is the ambient temperature, x is the negative electrode state of charge, and I is the charge and discharge current; the positive electrode concentration potential, the negative electrode concentration potential, and the full life cycle electrolyte concentration potential are summed to obtain a second total concentration potential; the ratio of the second total concentration potential to the charge and discharge current is determined as the full life cycle mass transfer internal resistance.

[0025] In one embodiment of the present invention, the calculation of the full life cycle mass transfer internal resistance includes: obtaining the initial ohmic internal resistance of the lithium-ion battery through the functional relationship between the ohmic internal resistance and the state of charge and temperature of the lithium-ion battery; and obtaining the relationship between the ohmic internal resistance and the aging of the lithium-ion battery based on the relationship between the thickness of the solid electrolyte membrane and the aging of the lithium-ion battery and the initial ohmic internal resistance:

[0026]

[0027] in, represents the initial ohmic internal resistance of the battery in its initial state, β and θ are constants, and t0 is the battery aging time. The ohmic internal resistance over the entire life cycle is obtained based on the relationship between the ohmic internal resistance and the state of charge and ambient temperature of the lithium-ion battery and the relationship between the change of the ohmic internal resistance and the aging of the lithium-ion battery:

[0028]

[0029] in, The ohmic internal resistance over the entire life cycle is is the ohmic internal resistance at the reference temperature, T is the temperature, x is the battery state of charge, t0 is the battery aging time, a, b, c are the coefficients to be fitted, and β and θ are constants.

[0030] According to one aspect of an embodiment of the present invention, a device for calculating the internal resistance of a lithium-ion battery is provided, comprising: an acquisition module for acquiring a relationship between the change in lithium-ion concentration over time and obtaining the ohmic internal resistance over the entire life cycle; a decomposition module for decomposing the battery internal resistance to be calculated into charge transfer internal resistance, mass transfer internal resistance, and ohmic internal resistance; a calculation module for calculating the charge transfer internal resistance based on the temperature and charge and discharge current, calculating the mass transfer internal resistance based on the relationship between the change in lithium-ion concentration over time, the charge and discharge currents, and the concentration potential, and calculating the ohmic internal resistance based on the relationship between the lithium-ion battery's state of charge and the change in the ohmic internal resistance with temperature; and a combination module for combining the mass transfer internal resistance, charge transfer internal resistance, and ohmic internal resistance to obtain the battery internal resistance to be calculated.

[0031] According to one aspect of an embodiment of the present invention, an electronic device is provided, comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the electronic device implements the method for calculating the internal resistance of a lithium-ion battery as described in any of the above embodiments.

[0032] According to one aspect of an embodiment of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor of a computer, the computer executes the method for calculating the internal resistance of a lithium-ion battery described in any of the above embodiments.

[0033] Beneficial effects of the present invention: The present invention provides a method, device, electronic device and storage medium for calculating the internal resistance of a lithium-ion battery. The method decomposes the internal resistance of the battery to be calculated into charge transfer internal resistance, mass transfer internal resistance and ohmic internal resistance. Functional relationships between each internal resistance and factors such as temperature, battery state of charge, charge and discharge current are established respectively. When calculating the internal resistance of each part, the method of establishing the functional relationship is not just a mathematical fitting method, but the influence of factors such as temperature, battery state of charge and charge and discharge current on the internal resistance of the lithium battery is taken into account, which can more accurately predict the internal resistance of the lithium-ion battery. In addition, the present invention also predicts the change law of the internal resistance under the whole life cycle of the battery by establishing a functional relationship between the internal resistance of each part and different aging conditions of the lithium-ion battery, thereby reducing the prediction error of the internal resistance of the lithium-ion battery in practical applications.

[0034] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The accompanying drawings are incorporated into and constitute a part of the specification, illustrating embodiments consistent with the present application and, together with the specification, serving to explain the principles of the present application. It is obvious that the drawings described below are merely some embodiments of the present application, and a person of ordinary skill in the art can derive other drawings based on these drawings without inventive effort. In the drawings:

[0036] Figure 1 is a flow chart of a method for calculating the internal resistance of a lithium-ion battery according to an exemplary embodiment of the present invention;

[0037] Figure 2 is a specific flow chart of a method for calculating the internal resistance of a lithium-ion battery shown in an exemplary embodiment of the present invention;

[0038] Figure 3 1 is a current and potential curve of cyclic voltammetry shown in an exemplary embodiment of the present invention;

[0039] Figure 4 is a specific flow chart of a method for calculating the internal resistance of a lithium-ion battery shown in an exemplary embodiment of the present invention;

[0040] Figure 5 is a specific flow chart of a method for calculating the internal resistance of a lithium-ion battery shown in an exemplary embodiment of the present invention;

[0041] Figure 6 is a specific schematic diagram of a method for calculating the internal resistance of a lithium-ion battery according to an exemplary embodiment of the present invention;

[0042] Figure 7a1 is a graph showing a change in state of charge and voltage of an LFP (lithium ferrous phosphate, LiFePO4) battery under fast charging conditions, according to an exemplary embodiment of the present invention;

[0043] Figure 7b is a graph showing the change in state of charge and current of an LFP (lithium ferrous phosphate, LiFePO4) battery under fast charging conditions according to an exemplary embodiment of the present invention;

[0044] Figure 7c 1 is a graph showing the change in state of charge and resistance of an LFP (lithium ferrous phosphate, LiFePO4) battery under fast charging conditions according to an exemplary embodiment of the present invention;

[0045] Figure 8a is a graph showing the state of charge and voltage of an LFP (lithium ferrous phosphate, LiFePO4) battery under driving conditions according to an exemplary embodiment of the present invention;

[0046] Figure 8b is a graph showing a change in state of charge and current of an LFP (lithium ferrous phosphate, LiFePO4) battery under driving conditions according to an exemplary embodiment of the present invention;

[0047] Figure 8c is a graph showing the change in state of charge and resistance of an LFP (lithium ferrous phosphate, LiFePO4) battery under driving conditions according to an exemplary embodiment of the present invention;

[0048] Figure 9a is a graph showing a change in state of charge and voltage of an NMC (lithium nickel manganese cobalt, LiNixMnyCozO2) battery under driving conditions according to an exemplary embodiment of the present invention;

[0049] Figure 9b is a graph showing a change in state of charge and current of an NMC (lithium nickel manganese cobalt, LiNixMnyCozO2) battery under driving conditions according to an exemplary embodiment of the present invention;

[0050] Figure 9c is a graph showing the change in state of charge and resistance of an NMC (lithium nickel manganese cobalt, LiNixMnyCozO2) battery under driving conditions according to an exemplary embodiment of the present invention;

[0051] Figure 10 A device for calculating the internal resistance of a lithium-ion battery is shown as an exemplary embodiment of the present invention;

[0052] Figure 11 Schematic diagram of the structure of a computer system for implementing an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0053] The following describes the embodiments of the present invention with reference to the accompanying drawings and preferred embodiments. Those skilled in the art will readily appreciate the other advantages and benefits of the present invention from the disclosure herein. The present invention may also be implemented or applied through various other specific embodiments, and the various details in this specification may be modified or altered based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are intended only to illustrate the present invention and are not intended to limit the scope of protection of the present invention.

[0054] It should be noted that the illustrations provided in the following embodiments are merely schematic illustrations of the basic concept of the present invention. Therefore, the illustrations only show components related to the present invention and are not drawn according to the number, shape, and size of components in actual implementation. In actual implementation, the type, quantity, and proportion of each component may be changed arbitrarily, and the component layout may also be more complex.

[0055] In the following description, numerous details are discussed to provide a more thorough explanation of the embodiments of the present invention. However, it will be apparent to those skilled in the art that the embodiments of the present invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring the embodiments of the present invention.

[0056] Lithium-ion batteries (Li-ion batteries) are secondary batteries (rechargeable batteries) that rely primarily on the movement of lithium ions between the positive and negative electrodes. Lithium-ion batteries are essentially batteries with a concentration gradient. The positive and negative electrode materials have different electrochemical potentials, separated by a separator. Lithium ions (Li+) migrate from the intercalation material electrode with a higher chemical potential to the electrode with a lower potential. Only lithium ions can pass through the separator in the electrolyte, while charge-compensating electrons can only move through an external circuit, thus forming an electric current for output. Discharge Process: In a fully charged lithium-ion battery, lithium ions are embedded in the anode material. The anode (negative electrode) carbon has a layered structure with numerous micropores, and lithium ions are embedded in the micropores of the carbon layer. During discharge, lithium ions (Li+) move from the anode to the cathode through the separator. Electrons cannot pass through the separator and can only move from the negative electrode to the positive electrode through an external circuit. When the battery is charging, lithium ions are released from the cathode, and the released lithium ions move through the electrolyte to the anode. The carbon used as the anode has a layered structure with many micropores. The lithium ions that reach the anode are embedded in the micropores of the carbon layer. The more lithium ions are embedded, the higher the charging capacity.

[0057] See also Figure 1 , Figure 1 FIG1 shows a flow chart of a method for calculating the internal resistance of a lithium-ion battery according to an embodiment of the present application. Figure 1As shown, the speech intention recognition method includes at least steps S110 to S150, which are described in detail as follows:

[0058] Step S110 , obtaining battery operating parameters, which include temperature, charge and discharge current, concentration potential, the relationship between lithium ion concentration and time, and the relationship between ohmic internal resistance and lithium ion battery aging.

[0059] In one embodiment of the present application, the lithium-ion battery is an LFP (lithium ferrous phosphate, LiFePO4) battery. Concentration potential is the potential difference caused by the concentration difference of the electrolyte solution between two electrodes. Lithium-ion battery aging mainly includes the loss of available lithium ions (LLI) and the loss of positive and negative active materials (LAM). Battery aging mechanisms also include internal resistance increase (RI) and electrolyte loss (LE): the increase in internal resistance will directly lead to the attenuation of battery power, and excessive electrolyte loss may directly lead to a capacity drop at the end of the battery life.

[0060] Step S120 , decomposing the battery internal resistance to be calculated into charge transfer internal resistance, mass transfer internal resistance and ohmic internal resistance.

[0061] In one embodiment of the present application, the battery to be calculated is an LFP (lithium ferrous phosphate, LiFePO4) battery. During the charge and discharge process, the internal resistance of the lithium-ion battery can be decomposed into charge transfer resistance, mass transfer resistance, and ohmic resistance according to the different physical and chemical processes occurring inside the battery. That is, the internal resistance of the lithium-ion battery is the sum of the three internal resistances. In one embodiment of the present application, the internal resistance of the lithium-ion battery is calculated using the following formula:

[0062] R tot =R ct +R mt +R Ω Formula (1)

[0063] Among them, R tot is the internal resistance of the lithium-ion battery, R ct is the internal resistance of charge transfer, R mt is the internal resistance to mass transfer, R Ω is the ohmic internal resistance.

[0064] In this embodiment, the charge transfer internal resistance is the resistance to electron transfer in the electrochemical reaction, the mass transfer internal resistance is the internal resistance of lithium ions transported through the electrolyte and electrode material bulk phase, and the ohmic internal resistance is primarily composed of the electrode material, electrolyte, diaphragm resistance, and contact resistance of various components. By considering the impact of multiple factors on the internal resistance of a lithium-ion battery, the calculated internal resistance of the lithium-ion battery is closer to the actual internal resistance of the lithium-ion battery. Furthermore, by detecting changes in the lithium-ion internal resistance, technicians can promptly understand the aging of the lithium-ion battery, thereby performing maintenance on the lithium-ion battery and, to a certain extent, extending the service life of the lithium-ion battery.

[0065] In one embodiment of the present application, the internal resistance of the lithium-ion battery R tot Affected by parameters such as temperature, current, battery state of charge (SOC), aging time, etc., it can be expressed as:

[0066] R tot =f(I,T,x,t0) Formula (2)

[0067] Among them, R tot is the internal resistance of the lithium-ion battery, I is the charge and discharge current, T is the temperature, x is the battery state of charge, and t0 is the battery aging time.

[0068] Step S130, calculate the charge transfer internal resistance based on the temperature and the charge and discharge current, calculate the mass transfer internal resistance based on the first change relationship between the lithium ion concentration and time, the charge and discharge current and the concentration potential, and calculate the ohmic internal resistance based on the change relationship between the state of charge and temperature of the lithium ion battery and the ohmic internal resistance.

[0069] Step S140 , combining the mass transfer internal resistance, the charge transfer internal resistance and the ohmic internal resistance to obtain the battery internal resistance to be calculated.

[0070] In a real-time example of the present application, by establishing a function relationship for calculating the charge transfer internal resistance, establishing a function relationship for calculating the mass transfer internal resistance, and establishing a function relationship for calculating the ohmic internal resistance, the internal resistance of the battery to be calculated is calculated, thereby being able to more accurately predict the battery internal resistance, so that the calculated battery internal resistance is more in line with the actual battery internal resistance in the actual application scenario.

[0071] exist Figure 1 In the technical solution of the illustrated embodiment, by considering the influence of factors such as temperature, lithium-ion battery SOC, and charge and discharge current on the internal resistance of the lithium-ion battery, a functional relationship for calculating the charge transfer internal resistance, a functional relationship for calculating the mass transfer internal resistance, and a functional relationship for calculating the ohmic internal resistance are established. The internal resistance of the lithium-ion battery is calculated through the functional relationship of the internal resistances of various parts of the lithium-ion battery, thereby being able to more accurately predict the internal resistance of the lithium-ion battery, so that the estimated internal resistance of the lithium-ion battery is more in line with the battery internal resistance in actual application scenarios.

[0072] In one embodiment of the present application, the charge transfer internal resistance is calculated based on the temperature and the charge and discharge current, including: obtaining the charge transfer internal resistance by using the gas constant, the Faraday constant, the temperature, and the charge and discharge current. In one embodiment of the present application, the charge transfer internal resistance is calculated by the following formula:

[0073]

[0074] Among them, η ct is the battery charge overpotential, and I is the charge and discharge current. ct and I are obtained by the following formula:

[0075]

[0076] Wherein, α is the exchange coefficient, which in this embodiment is 0.5, n is the number of charges transferred, which is 1 in the lithium-ion battery system, F is the Faraday constant, R is the gas constant, and T is the temperature. When the overpotential is large, the calculated value of the second term on the right side of the equal sign in formula (4) is small and can be omitted. Therefore, formula (4) can be simplified to:

[0077]

[0078] η ct Substituting I into formula (3), we get:

[0079]

[0080] Among them, R ct is the charge transfer resistance, I is the charge and discharge current, F is the Faraday constant, R is the gas constant, and α is the exchange coefficient. In this embodiment, R = 8.314, α = 0.5, F = 96500, and n = 1, so the charge transfer internal resistance can be:

[0081]

[0082] See also Figure 2 , Figure 2 An exemplary embodiment of the present application is shown. Figure 1 The flowchart of step S130 of the lithium-ion battery internal resistance calculation method shown in FIG. Figure 2 In the embodiment shown, step S130 in the method for calculating the internal resistance of a lithium-ion battery of this embodiment includes the following steps:

[0083] Step 210 , obtaining the negative electrode concentration potential according to the temperature and the state of charge of the negative electrode of the lithium-ion battery.

[0084] In one embodiment of the present application, the lithium ion transport process is driven by the ion concentration gradient, and the ion concentration gradient will produce a corresponding potential difference, namely the concentration potential. The negative electrode concentration potential is the concentration potential of the lithium ion transport process in the negative electrode. The concentration potential in the battery electrode can be determined by the following formula:

[0085]

[0086] Among them, α A With α B are the activities of substance A and substance B respectively. When the negative electrode is considered, α A is the activity of the negative electrode delithiation state, α B is the activity of the lithium-intercalated state of the negative electrode; when the positive electrode is considered, α A is the activity of the delithiation state of the positive electrode, α B is the activity of the positive electrode lithium insertion state. The relationship between activity and concentration can be expressed as

[0087] α A =f A C A

[0088] α B =f B C B

[0089] Among them, C A is the concentration of lithium ions in the delithiated state, C B is the concentration of lithium ions in the intercalated state, f A , f B is the activity coefficient.

[0090] In one embodiment of the present application, the activity coefficient is 1, the concentration is equal to the activity, and Equation 7 can be rewritten as

[0091]

[0092] In a real-time example of the present application, the lithium-ion battery is in a charging state, and lithium ions are transported inside the negative electrode. The concentration of lithium ions in the de-lithiated state C is calculated by the following formula: A :

[0093]

[0094] The concentration of intercalated lithium ions C is calculated by the following formula: B :

[0095]

[0096] Among them, M C6 is the molecular weight of the graphite negative electrode, ρ C6 is the graphite negative electrode density, x1 is the negative electrode SOC, CA is the concentration of lithium ions in the delithiated state, C B is the concentration of intercalated lithium ions.

[0097] Substituting equations (9) and (10) into equation (8), we can obtain the negative electrode concentration potential as follows:

[0098]

[0099] in, is the concentration potential of the lithium ion transfer process in the negative electrode, F is the Faraday constant, R is the gas constant, T is the ambient temperature, and x1 is the negative electrode SOC.

[0100] Step 220 , obtaining the positive electrode concentration potential according to the temperature and the state of charge of the positive electrode of the lithium-ion battery.

[0101] In one embodiment of the present application, the positive electrode concentration potential is the concentration potential of the lithium ion transport process in the positive electrode, which is determined by the following formula:

[0102]

[0103] in, is the concentration potential of the lithium ion transfer process in the positive electrode, F is the Faraday constant, R is the gas constant, T is the ambient temperature, and x2 is the positive electrode SOC.

[0104] Step 230 , obtaining the electrolyte concentration potential by the migration number of lithium ions, the concentration of lithium ions in the electrolyte layer on the surface of the battery positive electrode, the concentration of lithium ions in the electrolyte layer on the surface of the battery negative electrode, the temperature, and the first variation relationship between the lithium ion concentration and time.

[0105] In one embodiment of the present application, the initial electrolyte concentration potential is obtained by the migration number of lithium ions, the concentration of lithium ions in the electrolyte layer on the surface of the positive electrode of the battery, the concentration of lithium ions in the electrolyte layer on the surface of the negative electrode of the battery, the Faraday constant, the gas constant, and the temperature:

[0106]

[0107] in, is the initial concentration potential of the electrolyte, F is the Faraday constant, R is the gas constant, T is the temperature, t + is the migration number of lithium ions, is the concentration of lithium ions in the electrolyte layer on the positive electrode surface, is the concentration of lithium ions in the electrolyte layer on the negative electrode surface; the change in lithium ion concentration can be described by Fick's second law, that is:

[0108]

[0109] Among them, C Liis the concentration of lithium ions, t is the time, and D is the diffusion coefficient. Where D is a function of temperature and can be expressed as:

[0110]

[0111] Among them, D0 is the pre-exponential factor, E a is the activation energy, R is the gas constant, and T is the temperature. Substituting equation (15) into equation (14), the final expression for the change in lithium ion concentration is:

[0112]

[0113] Among them, D0 is the pre-exponential factor, E a is the activation energy, C Li is the concentration of lithium ions, R is the gas constant, T is the temperature, and t is the time.

[0114] In one embodiment of the present application, the lithium-ion battery is a button battery. Figure 3 The current and potential curves of cyclic voltammetry are obtained by calibrating the diffusion coefficient of lithium ions through cyclic voltammetry experiments. In this embodiment, button cells with positive and negative electrodes at different SOCs are prepared using metallic lithium as the counter electrode. At different temperatures, a constant voltage change rate is applied to the button cells to be tested, and the current values ​​are observed and recorded. Figure 2 The current and concentration potential curves of the cyclic voltammetry are shown; the following equations are solved to obtain the diffusion coefficients of lithium ions in the positive and negative electrode materials at different SOCs under different temperature conditions:

[0115]

[0116] Among them, I p is the peak value of charge and discharge current, D is the diffusion coefficient, v is the voltage change rate, n is the coefficient, C0 is the lithium ion concentration constant, Peak potential.

[0117]

[0118] By combining equations (17) and (18), we can obtain the diffusion coefficients of lithium ions in the positive and negative electrode materials at different SOCs.

[0119] Substitute the diffusion coefficients of lithium ions in the positive and negative electrode materials at different SOCs into formula (15) to calculate the activation energy and pre-exponential factor. Substitute the activation energy and pre-exponential factor into formula (16), and integrate formula (16) to obtain the first change relationship of lithium ion concentration with time:

[0120] C(t)=f C (t,T) Formula (19)

[0121] The electrolyte concentration potential is obtained based on the first change relationship of lithium ion concentration over time and the initial electrolyte concentration potential.

[0122]

[0123] in, is the electrolyte concentration potential, T is the temperature, and t0 is the battery aging time.

[0124] Step 240 , obtaining the mass transfer internal resistance according to the positive electrode concentration potential, the negative electrode concentration potential, the electrolyte concentration potential, and the charge and discharge current.

[0125] In one embodiment of the present application, the positive electrode concentration potential, the negative electrode concentration potential, and the electrolyte concentration potential are summed to obtain a first total concentration potential; the ratio of the first total concentration potential to the charge and discharge currents is determined as the mass transfer internal resistance. In this embodiment, the mass transfer internal resistance is calculated using the following formula:

[0126]

[0127] Among them, R mt is the internal resistance to mass transfer, Positive electrode concentration potential, Negative electrode concentration potential, Electrolyte concentration potential, I is the charge and discharge current. In this example, x1 = x2, R = 8.314, F = 96500, and the mass transfer internal resistance is calculated as:

[0128]

[0129] Among them, R mt is the internal resistance of mass transfer, T is the temperature, I is the charge and discharge current, t0 is the battery aging time, x1 is the negative electrode SOC, and x2 is the positive electrode SOC.

[0130] exist Figure 2 In the technical solution of the illustrated embodiment, when calculating the mass transfer internal resistance, the concentration difference potential is decomposed into the positive electrode concentration difference potential, the negative electrode concentration difference potential and the electrolyte concentration difference potential, so that the potential of each part is calculated separately. Taking into account the influence of multiple factors on the concentration difference potential, the error in calculating the concentration difference potential can be reduced, so that the mass transfer internal resistance can be obtained more accurately.

[0131] See also Figure 4 , Figure 4 An exemplary embodiment of the present application is shown. Figure 1 The flowchart of step S130 of the lithium-ion battery internal resistance calculation method shown in FIG. Figure 2 In the embodiment shown, step S130 in the method for calculating the internal resistance of a lithium-ion battery of this embodiment further includes the following steps:

[0132] Step 410 , setting first test parameters, the first test parameters including the state of charge of the lithium-ion battery, the reference ambient temperature, and a preset frequency range, and the first test parameters include multiple groups.

[0133] In one embodiment of the present application, the lithium-ion battery is an LFP (lithium ferrous phosphate, LiFePO4) battery. The SOC of the lithium-ion battery is adjusted to x0, the reference ambient temperature is T0, and the preset frequency range is 100KHz-0.1Hz. This is the first set of first test parameters; the SOC of the battery is adjusted to x1, the reference ambient temperature is T1, and the preset frequency range is 100KHz-0.1Hz. This is the second set of first test parameters. The SOC of the battery is adjusted to x3, the reference ambient temperature is T3, and the preset frequency range is 100KHz-0.1Hz. This is the third set of first test parameters. By setting multiple sets of test parameters to test the AC impedance of the battery, the ohmic internal resistance can be obtained more accurately.

[0134] Step 420 , testing the AC impedance under the first test parameter to obtain multiple sets of AC impedance test results.

[0135] In step 430 , the AC impedance test result is recorded as a Nyquist diagram to obtain multiple Nyquist diagrams, and the intercept of the high-frequency horizontal axis in the Nyquist diagram is obtained by a linear interpolation method.

[0136] In one embodiment of the present application, when the electrode system is disturbed by an AC signal of a sinusoidal voltage (current), a corresponding current (voltage) response signal is generated, and the impedance or admittance of the electrode can be obtained from these signals. The impedance spectrum generated by a series of sinusoidal wave signals of different frequencies is called electrochemical impedance spectroscopy (EIS), also known as AC impedance spectroscopy, and is called AC impedance (AC Impedance) in electrochemical workstation tests. Impedance measurement was originally a method for studying the frequency response characteristics of linear circuit networks in electricity. It was applied to the study of electrode processes and became an experimental method in electrochemical research. In a three-electrode system, the impedance of the working electrode is measured. The information in EIS is often represented by a Nyquist plot. In the Nyquist plot, the negative imaginary component of the impedance (y-axis) and the real component of the impedance (x-axis) are used to plot.

[0137] Step 440 : Fitting the reference ohmic internal resistance in the two-dimensional numerical table of reference ohmic internal resistance based on the functional relationship between the ohmic internal resistance, the temperature, and the state of charge of the lithium-ion battery to obtain an ohmic internal resistance fitting coefficient.

[0138] Step 450 , substituting the ohmic internal resistance fitting coefficient into the functional relationship between the ohmic internal resistance, the temperature, and the state of charge of the lithium-ion battery to obtain the ohmic internal resistance.

[0139] In one embodiment of the present application, the ohmic internal resistance fitting coefficient is substituted into the relationship between the state of charge and temperature of the lithium-ion battery and the change of the ohmic internal resistance to obtain the ohmic internal resistance:

[0140]

[0141] Among them, R Ω is the ohmic internal resistance, is the ohmic internal resistance at the reference temperature, T is the temperature, and x is the battery state of charge. a, b, and c are the ohmic internal resistance fitting coefficients.

[0142] exist Figure 4 In the technical solution of the illustrated embodiment, multiple reference ohmic internal resistances are obtained by analyzing the Nyquist diagram, and the reference ohmic internal resistances are fitted to more accurately obtain the ohmic internal resistance, thereby more accurately obtaining the internal resistance of the lithium-ion battery.

[0143] In one embodiment of the present application, the internal resistance of the lithium-ion battery is calculated by formula (1), R = 8.314, F = 96500, x1 = x2 = x, and the internal resistance of the lithium-ion battery is obtained:

[0144]

[0145] Where T is temperature, I is charge and discharge current, t0 is battery aging time, x1 is negative electrode SOC, and x2 is positive electrode SOC. is the ohmic internal resistance at the reference temperature, x is the SOC of the lithium-ion battery, and a, b, and c are the ohmic internal resistance fitting coefficients.

[0146] See also Figure 5 , Figure 5 An exemplary embodiment of the present application is shown. Figure 1 The flowchart of step S140 of the lithium-ion battery internal resistance calculation method shown in FIG. Figure 5 In the embodiment shown, step S140 in the method for calculating the internal resistance of a lithium-ion battery of this embodiment further includes the following steps:

[0147] Step 510: Calculate the full life cycle mass transfer internal resistance and the full life cycle ohmic internal resistance.

[0148] In one embodiment of the present application, the whole life cycle mass transfer internal resistance is calculated, including: obtaining the whole life cycle electrolyte concentration potential based on the second change relationship of lithium ion concentration over time and the initial electrolyte concentration potential.

[0149]

[0150] in, is the full life cycle electrolyte concentration potential, t0 is the battery aging time, T is the ambient temperature, x is the battery SOC, and I is the charge and discharge current. The positive electrode concentration potential, the negative electrode concentration potential, and the full life cycle electrolyte concentration potential are summed to obtain a second total concentration potential; the ratio of the second total concentration potential to the charge and discharge current is determined as the full life cycle mass transfer internal resistance. In one embodiment of the present application, the full life cycle mass transfer internal resistance is calculated by the following formula:

[0151]

[0152] The internal resistance of mass transfer throughout the entire life cycle, is the positive electrode concentration potential, is the negative electrode concentration potential, is the electrolyte concentration difference potential over the entire life cycle, and I is the charge and discharge current.

[0153] In this embodiment, R = 8.314, F = 96500, x1 = x2, and Equations (11), (12), and (25) are substituted into Equation (26) to calculate the full life cycle mass transfer internal resistance:

[0154]

[0155] in, is the mass transfer internal resistance over the entire life cycle, t0 is the battery aging time, T is the ambient temperature, I is the charge and discharge current, x1 is the negative electrode SOC, and x is the lithium-ion battery SOC.

[0156] In one embodiment of the present application, calculating the full life cycle mass transfer internal resistance includes: obtaining the initial ohmic internal resistance of the lithium-ion battery by calculating the functional relationship between the ohmic internal resistance and the state of charge and temperature of the lithium-ion battery. In one embodiment of the present application, the initial ohmic internal resistance of the lithium-ion battery is calculated using formula (23).

[0157] In one embodiment of the present application, the main factors affecting the battery life are: high temperature (accelerated internal side reactions); low temperature (metal ions are easily reduced, lithium is precipitated, and the crystal structure of the active material is easily destroyed); high SOC or overcharge of the battery (electrolyte decomposition, side reactions between the electrolyte and the positive electrode, lithium ion deposition); low SOC or overdischarge of the battery (the negative copper collector is easily corroded, and the crystal structure of the active material is easily peeled off); high charge and discharge rate (the crystal structure of the active material is easily fatigued and destroyed, and the high charge and discharge rate causes a large temperature rise that accelerates internal side reactions).

[0158] Therefore, as the battery ages, the thickness of the solid electrolyte membrane on the positive and negative electrode surfaces will increase over time, and the structure of the material will also degrade over time. The relationship between the thickness of the solid electrolyte membrane and the aging time can be approximately expressed as:

[0159] l=1+βln(1+θt0) Formula (28)

[0160] Where l is the thickness of the solid electrolyte membrane, β and θ are constants, and t0 is the battery aging time.

[0161] In this embodiment, since the ohmic resistance is approximately proportional to the thickness of the solid electrolyte membrane, the relationship between the thickness of the solid electrolyte membrane and the aging of the lithium-ion battery and the initial ohmic internal resistance is obtained as follows:

[0162]

[0163] in, represents the initial ohmic internal resistance of the battery in its initial state, β and θ are constants, and t0 is the battery aging time. By considering the impact of battery aging on the internal resistance of lithium-ion batteries and calculating the resistance of lithium-ion batteries throughout their life cycle, the internal resistance of lithium-ion batteries is made closer to the actual internal resistance of lithium-ion batteries, improving the accuracy of predicted battery internal resistance. In addition, by detecting changes in lithium-ion internal resistance, technicians can promptly understand the aging of lithium-ion batteries, thereby performing maintenance on lithium-ion batteries and, to a certain extent, extending the service life of lithium-ion batteries.

[0164] In one embodiment of the present application, the full life cycle ohmic internal resistance is obtained based on the relationship between the ohmic internal resistance and the state of charge and ambient temperature of the lithium-ion battery and the relationship between the change of the ohmic internal resistance as the lithium-ion battery ages. In one embodiment of the present application, formula (23) is substituted into formula (29) to obtain the full life cycle ohmic internal resistance:

[0165]

[0166] in, The ohmic internal resistance over the entire life cycle is is the ohmic internal resistance at the reference temperature, T is the temperature, x is the battery state of charge, t0 is the battery aging time, a, b, c are the coefficients to be fitted, and β and θ are constants.

[0167] Step 520 , summing the charge transfer internal resistance, the full life cycle mass transfer internal resistance, and the full life cycle ohmic internal resistance to obtain the full life cycle internal resistance of the battery to be calculated.

[0168] In a real-time example of this application, R = 8.314, F = 96500, the charge transfer resistance is considered to be a constant throughout the entire life cycle, and the internal resistance of the battery to be calculated over the entire life cycle can be expressed as follows:

[0169]

[0170] in, is the internal resistance of the battery to be calculated throughout its life cycle, R ct Charge transfer internal resistance, Internal resistance to mass transfer throughout the entire life cycle Ohmic internal resistance throughout the entire life cycle.

[0171] In one embodiment of the present application, equations (6), (27), and (30) are substituted into equation 31, where R = 8.314, F = 96500, x1 = x2 = x, to obtain the full life cycle internal resistance of the battery to be calculated.

[0172]

[0173] in, is the internal resistance of the battery over its entire life cycle, T is the temperature, I is the charge and discharge current, t0 is the battery aging time, x1 is the negative electrode SOC, is the ohmic internal resistance at the reference temperature, x is the battery SOC, and a, b, and c are the ohmic internal resistance fitting coefficients.

[0174] exist Figure 5 In the technical solution shown, the full life cycle mass transfer internal resistance and the full life cycle ohmic internal resistance are calculated to obtain the full life cycle internal resistance of the battery to be calculated. This takes into account the change law of the battery's full life cycle internal resistance, making the predicted battery internal resistance closer to the battery internal resistance during actual use.

[0175] See also Figure 6 , Figure 6 An exemplary embodiment of the present application is shown. Figure 5 The lithium-ion battery internal resistance calculation method shown in the figure also includes the following steps before step S510:

[0176] Step S610, setting multiple groups of second test parameters, the second test parameters including ambient temperature, charge and discharge current, and battery state of charge, and selecting a preset number of battery cells for each group of test parameters;

[0177] Step S620, performing a cyclic voltammetry test and an AC impedance test on the battery under second test parameters at predetermined aging time intervals, repeating the predetermined cycle, wherein the cyclic voltammetry test is used to calibrate the diffusion coefficient of lithium ions, and the AC impedance test is used to calibrate the ohmic internal resistance;

[0178] In one embodiment of the present application, the preset number of battery cells is 6 battery cells, the preset aging time is 1 month, and the preset cycle is 6 cycles. The first group of second test parameters includes ambient temperature T1, charge and discharge current I1, and battery SOCx1. The second group of second test parameters includes ambient temperature T2, charge and discharge current I2, and battery SOCx2. The third group of second test parameters includes ambient temperature T3, charge and discharge current I3, and battery SOCx3. The battery is subjected to a cycle aging test and a calendar aging test under each group of second test parameters. In this embodiment, a cyclic voltammetry test and an AC impedance test are performed according to each group of second test parameters every 1 month of battery aging time, and the lithium ion diffusion coefficient and ohmic resistance under the corresponding aging conditions are calculated, and repeated for 6 cycles.

[0179] Step S630: compile the diffusion coefficients obtained from the test into a matrix table to obtain the diffusion coefficient D(t)=f D (I, T, x, t0), compile the ohmic resistance obtained from the test into a matrix table to obtain the ohmic internal resistance R throughout the life cycle Ω (t) = f Ω (t0,x,I,T). Where I is the charge and discharge current, T is the ambient temperature, x is the battery state of charge, and t0 is the aging time.

[0180] exist Figure 6 In the technical solution shown, the diffusion coefficient and the ohmic internal resistance over the entire life cycle are obtained through experimental testing, and the internal resistance of the battery to be calculated over the entire life cycle is calculated based on the diffusion coefficient and the ohmic internal resistance over the entire life cycle. This takes into account the changing law of the internal resistance over the entire life cycle of the battery, making the predicted battery internal resistance closer to the battery internal resistance during actual use.

[0181] In one embodiment of the present application, the diffusion coefficient D(t) of the entire life cycle is set to f D Substitute (I, T, X, t) into formula (15) to calculate the activation energy Ea and pre-exponential factor D0. Substitute the values ​​of Ea and D0 into formula 16 and integrate formula 16 to obtain the second variation relationship of lithium ion concentration with time:

[0182] C(t)=f C (t0,T,x,I) Formula (33)

[0183] Where C is the concentration, I is the charge and discharge current, T is the ambient temperature, x is the battery charge value, and t0 is the aging time. Substituting formula (33) into formula (13) yields formula (25). In one embodiment of the present application, R Ω (t) = f ΩSubstitute (t0, x, I, T) into formula (27), obtain the values ​​of β and θ by fitting, substitute the values ​​of β and θ into formula (30), calculate the full life cycle ohmic internal resistance, and thus obtain the full life cycle resistance of the battery to be calculated according to formula (32).

[0184] In one embodiment of the present application, the lithium-ion battery is an LFP (lithium ferrous phosphate, LiFePO4) battery. FIG7 is a graph showing the changes in voltage, current, and resistance of an LFP (lithium ferrous phosphate, LiFePO4) battery under fast charging conditions. Figure 7a This is the curve of the change of LFP battery SOC and voltage under fast charging conditions. Figure 7b This is a curve diagram of the change of SOC and current of LFP battery under fast charging conditions; Figure 7c Figure 7 shows the change curve of the LFP battery SOC and resistance under fast charging conditions. In this embodiment, the aging time t0 is 0 and the temperature T is 25 degrees Celsius. As shown in Figure 7, under fast charging conditions, the voltage and current corresponding to the LFP battery SOC value of 0-100% are substituted into formula (24) to calculate the battery internal resistance corresponding to the LFP battery SOC value, forming the LFP battery SOC value-LFP battery internal resistance curve under fast charging conditions.

[0185] In one embodiment of the present application, the lithium-ion battery is an LFP (lithium ferrous phosphate, LiFePO4) battery. FIG8 is a diagram showing changes in voltage, current, and resistance of an LFP (lithium ferrous phosphate, LiFePO4) battery under driving conditions. Figure 8a The curve diagram of the change of LFP battery SOC and voltage under driving conditions is shown in Figure 2. Figure 8b This is a curve diagram of the change of LFP battery SOC and current under driving conditions; Figure 8c Figure 8 shows the variation of the LFP battery SOC and resistance under driving conditions. In this embodiment, the aging time t0 is 0 and the temperature T is 25 degrees Celsius. As shown in Figure 8, under driving conditions, the voltage and current corresponding to the LFP battery SOC values ​​of 0 to 100% are substituted into Equation (24) to calculate the battery internal resistance corresponding to the LFP battery SOC value, forming the LFP battery SOC value-LFP battery internal resistance curve under driving conditions.

[0186] In one embodiment of the present application, the lithium-ion battery is an NMC (lithium nickel manganese cobalt, LiNixMnyCozO2) battery. FIG9 shows the voltage, current, and resistance changes of the NMC (lithium nickel manganese cobalt, LiNixMnyCozO2) battery under driving conditions. Figure 9a This is the curve of NMC battery SOC and voltage changes under driving conditions. Figure 9b This is a curve diagram of the change of NMC battery SOC and current under driving conditions; Figure 9cFigure 9 shows the variation of the NMC battery SOC and resistance under driving conditions. In this embodiment, the aging time t0 is 0 and the temperature T is 25 degrees Celsius. As shown in Figure 9, the voltage and current corresponding to the NMC battery SOC values ​​of 0 to 100% are substituted into Equation (24) to calculate the battery internal resistance corresponding to the NMC battery SOC value, forming the NMC battery SOC value-LFP battery internal resistance curve under driving conditions.

[0187] Figure 10 The figure schematically shows a device for calculating the internal resistance of a lithium-ion battery according to an exemplary embodiment of the present invention. Figure 10 As shown, a lithium-ion battery internal resistance calculation device 1000 according to an embodiment of the present invention includes: an acquisition module 1010, a decomposition module 1020, a calculation module 1030, and a combination module 1040.

[0188] The acquisition module 1010 is used to obtain the relationship between the change of lithium ion concentration and time, and obtain the ohmic internal resistance of the entire life cycle; the decomposition module 1020 is used to decompose the battery internal resistance to be calculated into charge transfer internal resistance, mass transfer internal resistance and ohmic internal resistance; the calculation module 1030 is used to calculate the charge transfer internal resistance based on temperature and charge and discharge current, calculate the mass transfer internal resistance based on the relationship between the change of lithium ion concentration and time, charge and discharge current and concentration potential, and calculate the ohmic internal resistance based on the relationship between temperature and ohmic internal resistance as the lithium ion battery ages; the combination module 1040 combines the mass transfer internal resistance, charge transfer internal resistance and ohmic internal resistance to obtain the battery internal resistance to be calculated.

[0189] In an exemplary embodiment of the present invention, the calculation module 1030 is configured to obtain the charge transfer internal resistance through the gas constant, the Faraday constant, the temperature, and the charge and discharge current.

[0190] In an exemplary embodiment of the present invention, the calculation module 1030 is used to obtain the negative electrode concentration potential through the temperature and the state of charge of the negative electrode of the lithium-ion battery; obtain the positive electrode concentration potential through the temperature and the state of charge of the positive electrode of the lithium-ion battery; obtain the electrolyte concentration potential through the migration number of lithium ions, the concentration of lithium ions in the electrolyte layer on the surface of the positive electrode of the battery, the concentration of lithium ions in the electrolyte layer on the surface of the negative electrode of the battery, the temperature and the first change relationship of the lithium ion concentration with time; and obtain the mass transfer internal resistance based on the positive electrode concentration potential, the negative electrode concentration potential, the electrolyte concentration potential and the charge and discharge current.

[0191] In an exemplary embodiment of the present invention, the calculation module 1030 is configured to obtain the negative electrode concentration potential using the following formula:

[0192]

[0193] in, is the concentration potential of the lithium ion transfer process in the negative electrode, F is the Faraday constant, R is the gas constant, T is the temperature, and x1 is the charge state of the negative electrode.

[0194] In an exemplary embodiment of the present invention, the calculation module 1030 is configured to obtain the positive electrode concentration potential using the following formula:

[0195]

[0196] in, is the concentration potential of the lithium ion transfer process in the positive electrode, F is the Faraday constant, R is the gas constant, T is the ambient temperature, and x2 is the positive electrode charge state.

[0197] In an exemplary embodiment of the present invention, the calculation module 1030 is used to obtain the initial electrolyte concentration potential through the migration number of lithium ions, the concentration of lithium ions in the electrolyte layer on the surface of the battery positive electrode, the concentration of lithium ions in the electrolyte layer on the surface of the battery negative electrode, the Faraday constant, the gas constant, and the temperature:

[0198]

[0199] in, is the initial concentration potential of the electrolyte, t + is the migration number of lithium ions, is the concentration of lithium ions in the electrolyte layer on the positive electrode surface, is the concentration of lithium ions in the electrolyte layer on the negative electrode surface, F is the Faraday constant, R is the gas constant, and T is the temperature; the electrolyte concentration potential is obtained based on the first change relationship of lithium ion concentration over time and the initial electrolyte concentration potential.

[0200]

[0201] in, is the electrolyte concentration potential, T is the temperature, and t0 is the battery aging time.

[0202] In an exemplary embodiment of the present invention, the calculation module 1030 is used to sum the positive electrode concentration difference potential, the negative electrode concentration difference potential and the electrolyte concentration difference potential to obtain a first total concentration difference potential; and determine the ratio of the first total concentration difference potential to the charge and discharge currents as the mass transfer internal resistance.

[0203] In an exemplary embodiment of the present invention, the calculation module 1030 is used to set a first test parameter, the first test parameter including the state of charge of the lithium-ion battery, the reference ambient temperature, and a preset frequency range, and the first test parameter includes multiple groups; the AC impedance under the first test parameter is tested to obtain multiple groups of AC impedance test results; the AC impedance test results are recorded as Nyquist diagrams to obtain multiple Nyquist diagrams, and the intercept of the horizontal axis of the high-frequency band in the Nyquist diagram is obtained by a linear difference method; the intercept of the Nyquist diagram is recorded as the ohmic internal resistance under the corresponding test parameter to obtain multiple reference ohmic internal resistances, and a two-dimensional numerical table of reference ohmic internal resistances is output; the reference ohmic internal resistance in the two-dimensional numerical table of reference ohmic internal resistance is fitted based on the functional relationship between the ohmic internal resistance, temperature, and the state of charge of the lithium-ion battery to obtain an ohmic internal resistance fitting coefficient; the ohmic internal resistance fitting coefficient is substituted into the functional relationship between the ohmic internal resistance, temperature, and the state of charge of the lithium-ion battery to obtain the ohmic internal resistance.

[0204] In an exemplary embodiment of the present invention, the lithium-ion battery internal resistance calculation device also includes a battery full life cycle internal resistance calculation module 1050, which is used to calculate the full life cycle mass transfer internal resistance and the full life cycle ohmic internal resistance; the charge transfer internal resistance, the full life cycle mass transfer internal resistance and the full life cycle ohmic internal resistance are summed to obtain the full life cycle internal resistance of the battery to be calculated.

[0205] In an exemplary embodiment of the present invention, the battery life cycle internal resistance calculation module 1050 is used to obtain the full life cycle electrolyte concentration potential based on the second change relationship of lithium ion concentration over time and the initial electrolyte concentration potential.

[0206]

[0207] in, is the electrolyte concentration potential, t0 is the battery aging time, T is the ambient temperature, x is the battery state of charge, and I is the charge and discharge current; the positive electrode concentration potential, the negative electrode concentration potential and the full life cycle electrolyte concentration potential are summed to obtain the second total concentration potential; the ratio of the second total concentration potential to the charge and discharge current is determined as the full life cycle mass transfer internal resistance.

[0208] In an exemplary embodiment of the present invention, the battery life cycle internal resistance calculation module 1050 is used to obtain the initial ohmic internal resistance of the lithium-ion battery through the functional relationship between the ohmic internal resistance and the state of charge and temperature of the lithium-ion battery; based on the relationship between the thickness of the solid electrolyte membrane and the aging of the lithium-ion battery and the initial ohmic internal resistance, the relationship between the change of the ohmic internal resistance with the aging of the lithium-ion battery is obtained as follows:

[0209]

[0210] in, represents the initial ohmic internal resistance of the battery in its initial state, β and θ are constants, and t0 is the battery aging time. Based on the relationship between the ohmic internal resistance and the state of charge and ambient temperature of the lithium-ion battery and the change in the ohmic internal resistance with the aging of the lithium-ion battery, the full life cycle ohmic internal resistance is obtained:

[0211]

[0212] in, The ohmic internal resistance over the entire life cycle is is the ohmic internal resistance at the reference temperature, T is the temperature, x is the battery state of charge, t0 is the battery aging time, a, b, c are the coefficients to be fitted, and β and θ are constants.

[0213] It should be noted that the apparatus provided in the above embodiments and the methods provided in the above embodiments are based on the same concept. The specific manner in which the various modules and units perform their operations has been described in detail in the method embodiments and will not be repeated here. In actual applications, the apparatus provided in the above embodiments can, as needed, allocate the above functions to different functional modules, i.e., divide the internal structure of the apparatus into different functional modules to perform all or part of the functions described above. This is not a limitation herein.

[0214] Figure 11 The following is a schematic diagram showing the structure of a computer system suitable for implementing an electronic device according to an embodiment of the present application. Figure 11 The computer system 1100 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0215] like Figure 11 As shown, the computer system 1100 includes a central processing unit (CPU) 1101, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 1102 or the program loaded from the storage part 1108 into the random access memory (RAM) 1103, such as executing the method described in the above embodiment. Various programs and data required for system operation are also stored in the RAM 1103. The CPU 1101, ROM 1102 and RAM 1103 are connected to each other via a bus 1104. An input / output (I / O) interface 1105 is also connected to the bus 1104.

[0216] The following components are connected to the I / O interface 1105: an input section 1106 including a keyboard, a mouse, and the like; an output section 1107 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 1108 including a hard disk and the like; and a communication section 1109 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 1109 performs communication processing via a network such as the Internet. A drive 1110 is also connected to the I / O interface 1105 as needed. Removable media 1111, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 1110 as needed, so that computer programs read therefrom can be installed into the storage section 1108 as needed.

[0217] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 1109, and / or installed from a removable medium 1111. When the computer program is executed by the central processing unit (CPU) 1101, the various functions defined in the system of the present application are executed.

[0218] It should be noted that the computer-readable medium shown in the embodiments of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable computer program. This propagated data signal can take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0219] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0220] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. In some cases, the names of these units do not constitute limitations on the units themselves.

[0221] Another aspect of the present application provides a computer-readable storage medium having a computer program stored thereon. When executed by a computer processor, the computer program causes the computer to perform the aforementioned method for calculating the internal resistance of a lithium-ion battery. The computer-readable storage medium may be included in the electronic device described in the above embodiments, or may exist independently and not be incorporated into the electronic device.

[0222] Another aspect of the present application provides a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the lithium-ion battery internal resistance calculation method provided in each of the above embodiments.

[0223] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the present invention. Anyone skilled in the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, any equivalent modifications or alterations made by one of ordinary skill in the art without departing from the spirit and technical principles disclosed herein are intended to be covered by the claims of the present invention.

Claims

1. A method for calculating the internal resistance of a lithium-ion battery, characterized in that: The lithium-ion battery internal resistance calculation method includes: Obtaining battery operating parameters, including temperature, charge and discharge current, concentration potential, the relationship between lithium ion concentration and time, and the relationship between the state of charge and temperature of the lithium ion battery and the ohmic internal resistance; Decompose the battery internal resistance to be calculated into charge transfer resistance, mass transfer resistance and ohmic resistance; Calculating the charge transfer internal resistance based on the temperature and the charge and discharge current, calculating the mass transfer internal resistance based on the first change relationship between the lithium ion concentration and time, the charge and discharge current, and the concentration potential, and calculating the ohmic internal resistance based on the change relationship between the state of charge and temperature of the lithium ion battery and the ohmic internal resistance; The battery internal resistance to be calculated is obtained by combining the mass transfer internal resistance, the charge transfer internal resistance and the ohmic internal resistance.

2. The method for calculating the internal resistance of a lithium-ion battery according to claim 1, wherein: Calculating the charge transfer internal resistance based on the temperature and the charge and discharge current includes: The charge transfer internal resistance is obtained by the gas constant, the Faraday constant, the temperature and the charge and discharge current.

3. The method for calculating the internal resistance of a lithium-ion battery according to claim 1, wherein: The mass transfer internal resistance is calculated based on the relationship between the change of lithium ion concentration and time and the concentration potential, where the concentration potential includes the negative electrode concentration potential, the positive electrode concentration potential and the electrolyte concentration potential, including: The negative electrode concentration potential is obtained by temperature and the state of charge of the negative electrode of the lithium ion battery; The positive electrode concentration potential is obtained by temperature and the state of charge of the positive electrode of the lithium ion battery; The electrolyte concentration potential is obtained by the first variation relationship between the migration number of lithium ions, the concentration of lithium ions in the electrolyte layer on the surface of the positive electrode of the battery, the concentration of lithium ions in the electrolyte layer on the surface of the negative electrode of the battery, temperature, and lithium ion concentration over time; The mass transfer internal resistance is obtained according to the positive electrode concentration difference potential, the negative electrode concentration difference potential, the electrolyte concentration difference potential and the charge and discharge current.

4. The method for calculating the internal resistance of a lithium-ion battery according to claim 3, wherein: The negative electrode concentration potential is obtained by the gas constant, the Faraday constant, the temperature and the state of charge of the negative electrode of the lithium ion battery, including: The negative electrode concentration potential is obtained by the following formula: in, is the concentration potential of the lithium ion transfer process in the negative electrode, F is the Faraday constant, R is the gas constant, T is the temperature, and x1 is the charge state of the negative electrode.

5. The method for calculating the internal resistance of a lithium-ion battery according to claim 3, wherein: The positive electrode concentration potential is obtained by the gas constant, the Faraday constant, the temperature and the state of charge of the positive electrode of the lithium ion battery, including: The positive electrode concentration potential is obtained by the following formula: in, is the concentration potential of the lithium ion transfer process in the positive electrode, F is the Faraday constant, R is the gas constant, T is the ambient temperature, and x2 is the state of charge of the positive electrode.

6. The method for calculating the internal resistance of a lithium-ion battery according to claim 3, wherein: The electrolyte concentration potential is obtained by the migration number of lithium ions, the concentration of lithium ions in the electrolyte layer on the surface of the positive electrode of the battery, the concentration of lithium ions in the electrolyte layer on the surface of the negative electrode of the battery, the temperature, and the first change relationship between the lithium ion concentration and time, including: The initial electrolyte concentration potential is obtained by the migration number of lithium ions, the concentration of lithium ions in the electrolyte layer on the surface of the battery positive electrode, the concentration of lithium ions in the electrolyte layer on the surface of the battery negative electrode, the Faraday constant, the gas constant, and the temperature: in, is the initial electrolyte concentration potential, t + is the migration number of lithium ions, is the concentration of lithium ions in the electrolyte layer on the positive electrode surface, is the concentration of lithium ions in the electrolyte layer on the negative electrode surface, F is the Faraday constant, R is the gas constant, and T is the temperature; The electrolyte concentration potential is obtained according to the first change relationship between the lithium ion concentration and time and the initial electrolyte concentration potential. in, is the electrolyte concentration potential, T is the temperature, and t0 is the battery aging time.

7. The method for calculating the internal resistance of a lithium-ion battery according to claim 4, 5 or 6, wherein: The mass transfer internal resistance is obtained according to the positive electrode concentration potential, the negative electrode concentration potential, the electrolyte concentration potential and the charge and discharge current, including: Summing the positive electrode concentration difference potential, the negative electrode concentration difference potential, and the electrolyte concentration difference potential to obtain a first total concentration difference potential; The ratio of the first total concentration difference potential to the charge and discharge current is determined as the mass transfer internal resistance.

8. The method for calculating the internal resistance of a lithium-ion battery according to claim 1, wherein: Calculating the ohmic internal resistance according to a relationship between the state of charge and temperature of the lithium-ion battery and the ohmic internal resistance includes: Setting first test parameters, the first test parameters including the state of charge, temperature, and preset frequency range of the lithium-ion battery, the first test parameters including multiple groups; Testing the AC impedance under the first test parameters to obtain multiple sets of AC impedance test results; Recording the AC impedance test results as Nyquist plots, obtaining multiple Nyquist plots, and obtaining the intercept of the high-frequency horizontal axis of the Nyquist plots by a linear interpolation method; Recording the intercept of the Nyquist plot as the ohmic internal resistance under the corresponding test parameters, obtaining multiple reference ohmic internal resistances, and outputting a two-dimensional numerical table of the reference ohmic internal resistances; Fitting the reference ohmic internal resistance in the two-dimensional numerical table of the reference ohmic internal resistance based on the functional relationship between the ohmic internal resistance and the temperature and the state of charge of the lithium-ion battery to obtain an ohmic internal resistance fitting coefficient; The ohmic internal resistance fitting coefficient is substituted into the functional relationship between the ohmic internal resistance, the temperature and the state of charge of the lithium-ion battery to obtain the ohmic internal resistance.

9. The method for calculating the internal resistance of a lithium-ion battery according to claim 6, wherein: Combining the mass transfer internal resistance, the charge transfer internal resistance and the ohmic internal resistance to obtain the battery internal resistance to be calculated further includes: Calculate the whole life cycle mass transfer internal resistance and the whole life cycle ohmic internal resistance; The charge transfer internal resistance, the full life cycle mass transfer internal resistance and the full life cycle ohmic internal resistance are summed to obtain the full life cycle internal resistance of the battery to be calculated.

10. The method for calculating the internal resistance of a lithium-ion battery according to claim 9, wherein: Calculate the internal resistance to mass transfer over the entire life cycle, including: The full life cycle electrolyte concentration potential is obtained based on the second variation relationship of the lithium ion concentration over time and the initial electrolyte concentration potential. in, is the electrolyte concentration difference potential over the entire life cycle, t0 is the battery aging time, T is the ambient temperature, x is the state of charge of the lithium-ion battery, and I is the charge and discharge current; Summing the positive electrode concentration difference potential, the negative electrode concentration difference potential, and the full life cycle electrolyte concentration difference potential to obtain a second total concentration difference potential; The ratio of the second total concentration difference potential to the charge and discharge current is determined as the full life cycle mass transfer internal resistance.

11. The method for calculating the internal resistance of a lithium-ion battery according to claim 9, wherein: Calculate the full life cycle ohmic internal resistance, including: The initial ohmic internal resistance of the lithium-ion battery is obtained through the functional relationship between the ohmic internal resistance and the state of charge and temperature of the lithium-ion battery; According to the relationship between the thickness of the solid electrolyte membrane and the aging of the lithium-ion battery and the initial ohmic internal resistance, the relationship between the change of the ohmic internal resistance and the aging of the lithium-ion battery is obtained as follows: in, Represents the initial ohmic internal resistance of the lithium-ion battery in its initial state, β and θ are constants, and t0 is the battery aging time; The full life cycle ohmic internal resistance is obtained based on the functional relationship between the ohmic internal resistance and the state of charge and ambient temperature of the lithium-ion battery and the relationship between the change of the ohmic internal resistance as the lithium-ion battery ages: in, The ohmic internal resistance over the entire life cycle is is the ohmic internal resistance at the reference temperature, T is the temperature, x is the battery state of charge, t0 is the battery aging time, a, b, c are the coefficients to be fitted, and β and θ are constants.

12. A lithium-ion battery internal resistance calculation device, characterized in that: The lithium-ion battery internal resistance calculation device comprises: An acquisition module is used to obtain the ohmic internal resistance over the entire life cycle and obtain battery operating parameters, wherein the battery operating parameters include temperature, charge and discharge current, concentration potential, the relationship between lithium ion concentration and time, and the relationship between the state of charge and temperature of the lithium ion battery and the ohmic internal resistance; A decomposition module is used to decompose the battery internal resistance to be calculated into charge transfer resistance, mass transfer resistance and ohmic resistance; a calculation module for calculating the charge transfer internal resistance based on the temperature and the charge and discharge current, calculating the mass transfer internal resistance based on a relationship between the change in lithium ion concentration over time, the charge and discharge currents, and the concentration potential, and calculating the ohmic internal resistance based on a relationship between the state of charge and temperature of the lithium ion battery and the change in ohmic internal resistance; The combination module combines the mass transfer internal resistance, the charge transfer internal resistance and the ohmic internal resistance to obtain the battery internal resistance to be calculated.

13. An electronic device, characterized in that: The electronic device comprises: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the electronic device to implement the lithium-ion battery internal resistance calculation method according to any one of claims 1 to 11.

14. A computer-readable storage medium, characterized in that A computer program is stored thereon, and when the computer program is executed by a processor of a computer, the computer is caused to execute the method for calculating the internal resistance of a lithium-ion battery according to any one of claims 1 to 11.

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