CN113779794B - Lithium ion battery SOP estimation method and system considering microscopic constraint - Google Patents
Lithium ion battery SOP estimation method and system considering microscopic constraint Download PDFInfo
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- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 title claims abstract description 128
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- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 claims abstract description 25
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- 238000004458 analytical method Methods 0.000 description 2
- 238000009831 deintercalation Methods 0.000 description 2
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- G06F2119/08—Thermal analysis or thermal optimisation
Abstract
The invention belongs to the field of lithium ion battery SOP estimation, and particularly relates to a lithium ion battery SOP estimation method and system considering microscopic constraints. The method comprises the steps of constructing an electrochemical-thermal coupling model of the lithium ion battery, and obtaining parameters of the electrochemical-thermal coupling model of the lithium ion battery; based on an electrochemical-thermal coupling model of the lithium ion battery, estimating the power state of the lithium ion battery under the condition of considering macroscopic constraint and microscopic constraint, and generating a power state characteristic diagram of the lithium ion battery; wherein the macroscopic constraints include current constraints, voltage constraints, state of charge constraints, and temperature constraints, and the microscopic constraints include liquid phase concentration constraints, solid phase concentration constraints, and lithium precipitation constraints.
Description
Technical Field
The invention belongs to the field of lithium ion battery SOP estimation, and particularly relates to a lithium ion battery SOP estimation method and system considering microscopic constraints.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
Lithium ion batteries are widely used in electric vehicles due to their advantages of high energy density, high power density, long cycle life, and the like. In order to ensure safe and efficient operation of lithium ion batteries, a battery management system is indispensable. Among them, state estimation is one of important functions of the battery management system, and real-time accurate estimation of State of Charge (SOC), power State of Power (SOP), state of Health (SOH), and the like is realized.
SOP refers to the maximum available input or output power of the battery in the next few seconds to tens of seconds, and is an important decision basis for battery charge and discharge control, which determines the performance of vehicle starting, acceleration, climbing, and the like, and the regenerative braking energy recovery capability. In the SOP estimation algorithm, multiple constraints of temperature, SOC, current and terminal voltage are typically imposed to ensure that the battery operates in a safe area.
The existing SOP estimation method is classified as follows: (1) interpolation. The method uses a set of incremental charge-discharge pulse tests to determine battery peak power capability. The SOP characteristic map can be manufactured by testing at different temperatures and SOCs to obtain the charge and discharge power values under different states. (2) modeling. And establishing a battery parameter model, and realizing the estimation of SOP by limiting the state or output of the battery parameter model. Based on the dynamic model, the model can be more accurate and the estimated SOP of the battery is more reliable by increasing the change of temperature and aging on the model parameters. (3) data driving method. The method regards the battery as a black box, does not consider the reaction mechanism and the characteristics in the battery, uses a data analysis and machine learning method, takes the SOP to be estimated as the output quantity of the model, takes influencing factors as the input quantity, tests a large amount of data, and uses the model to learn and train so as to realize the estimation of the SOP of the battery.
The inventors found that the existing SOP estimation method has the following disadvantages:
(1) The temperature ranges are conserved. Prior studies generally estimate battery SOP over a conservative temperature range (about 15 deg.c to 40 deg.c), even at a fixed temperature. For areas with large latitude and longitude spans, particularly at low temperature, the power performance of the battery can be obviously reduced, and the safety and durability of the battery can be ensured only by accurately estimating the SOP.
(2) Microscopic constraints are not considered. Currently, most of the current uses macroscopic physical quantities as constraints, such as current, voltage, temperature or SOC. However, the internal microscopic state of the battery can directly reflect the aging and fault state of the battery, and if microscopic constraint cannot be considered, the advanced SOP estimation result can be caused, so that the battery is damaged.
Disclosure of Invention
In order to solve the technical problems in the background art, the invention provides a lithium ion battery SOP estimation method and system considering microscopic constraints, which are suitable for lithium ion battery SOP estimation in a wide temperature range and can ensure safe and efficient operation of a lithium ion battery.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a first aspect of the present invention provides a lithium ion battery SOP estimation method taking microscopic constraints into account, comprising:
constructing an electrochemical-thermal coupling model of the lithium ion battery, and obtaining parameters of the electrochemical-thermal coupling model of the lithium ion battery;
based on an electrochemical-thermal coupling model of the lithium ion battery, estimating the power state of the lithium ion battery under the condition of considering macroscopic constraint and microscopic constraint, and generating a power state characteristic diagram of the lithium ion battery;
wherein the macroscopic constraints include current constraints, voltage constraints, state of charge constraints, and temperature constraints, and the microscopic constraints include liquid phase concentration constraints, solid phase concentration constraints, and lithium precipitation constraints.
Further, in the electrochemical-thermal coupling model of the lithium ion battery, the temperature counter electrode open circuit potential U is considered i According to Nernst equation U i Characterized by:
wherein i=p, n represents the positive electrode or the negative electrode of the battery; t (T) ref Is the reference temperature;is the open circuit potential of the electrode at the reference temperature; t (T) b Is the battery temperature.
Further, in the electrochemical-thermal coupling model of the lithium ion battery, the ohmic effect, the charge transfer reaction and the lithium ion diffusion are also affected by temperature, and the variation relation of relevant parameters of the ohmic effect, the charge transfer reaction and the lithium ion diffusion with temperature is characterized by an Arrhenius equation:
wherein X represents parameters having Arrhenius characteristics, including a solid phase diffusion time constant, a liquid phase diffusion time constant, an electrode reaction constant, and an ohmic internal resistance; k (K) pre And E is a Respectively indicating the pre-finger factor and the activation energy; r is R g Is an ideal gas constant; t (T) b Is the battery temperature.
Further, the electrochemical-thermal coupling model parameters of the lithium ion battery are obtained through experiments.
Further, based on the electrochemical-thermal coupling model and the dichotomy of the lithium ion battery, the power state of the lithium ion battery is estimated under the condition of considering the macro constraint and the micro constraint.
Further, in the process of estimating the power state of the lithium ion battery, for a discharge scene, the discharge current is a positive value, the continuous discharge current is used as the input of an electrochemical-thermal coupling model, and the result in the prediction duration is obtained through simulation under the given initial temperature and charge state; and if the simulation result meets all macro constraints and micro constraints simultaneously, updating the lower limit of the search current in the dichotomy, otherwise, updating the upper limit of the search current until the difference between the upper limit and the lower limit of the search current in the dichotomy meets the tolerance requirement, and calculating the discharge peak power.
Further, in the process of estimating the power state of the lithium ion battery, for a charging scene, the charging current is a negative value, the continuous charging current is used as the input of an electrochemical-thermal coupling model, and the result in the prediction duration is obtained through simulation under the given initial temperature and charge state; and if the simulation result meets all macro constraints and micro constraints simultaneously, updating the upper limit of the search current in the dichotomy, otherwise, updating the lower limit of the search current until the difference between the upper limit and the lower limit of the search current in the dichotomy meets the tolerance requirement, and calculating the charging peak power.
A second aspect of the present invention provides a lithium ion battery SOP estimation system accounting for microscopic constraints, comprising:
the model building module is used for building an electrochemical-thermal coupling model of the lithium ion battery and obtaining parameters of the electrochemical-thermal coupling model of the lithium ion battery;
the power state estimation module is used for estimating the power state of the lithium ion battery based on the electrochemical-thermal coupling model of the lithium ion battery under the condition of considering macroscopic constraint and microscopic constraint, and generating a power state characteristic diagram of the lithium ion battery;
wherein the macroscopic constraints include current constraints, voltage constraints, state of charge constraints, and temperature constraints, and the microscopic constraints include liquid phase concentration constraints, solid phase concentration constraints, and lithium precipitation constraints.
A third aspect of the present invention provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps in a lithium ion battery SOP estimation method taking into account microscopic constraints as described above.
A fourth aspect of the invention provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps in a lithium ion battery SOP estimation method taking into account microscopic constraints as described above when executing the program.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a lithium ion battery SOP estimation method which takes microscopic constraint into account and is suitable for a wide temperature range, wherein an electrochemical-thermal coupling model of the lithium ion battery is established, and based on the model, the macroscopic constraint such as current, voltage and temperature and the microscopic constraint such as solid-liquid phase concentration and lithium precipitation are considered, so that SOP estimation in the wide temperature range is realized.
Additional aspects of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention.
FIG. 1 (a) is a simplified electrochemical model of a lithium ion battery;
fig. 1 (b) is a lumped thermal model of a lithium ion battery;
FIG. 2 is a discharge/charge peak power estimation flow chart;
FIG. 3 (a) is the peak power of discharge taking into account macroscopic and microscopic constraints;
fig. 3 (b) is a graph of discharge peak power considering only macro constraints;
FIG. 3 (c) is the peak charge power taking into account macroscopic and microscopic constraints;
fig. 3 (d) is the charging peak power considering only macro constraints.
Detailed Description
The invention will be further described with reference to the drawings and examples.
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
Example 1
Referring to fig. 2, the present embodiment provides a lithium ion battery SOP estimation method considering microscopic constraints, which includes:
step 1: and constructing an electrochemical-thermal coupling model of the lithium ion battery, and obtaining parameters of the electrochemical-thermal coupling model of the lithium ion battery.
The electrochemical-thermal coupling model of the lithium ion battery of this embodiment describes the dynamic characteristics of the battery by using a simplified electrochemical model and a collective thermal model, and the electrochemical-thermal coupling model structure of the lithium ion battery and the coupling relationship between them are shown in fig. 1 (a) and fig. 1 (b).
The electrochemical model of the lithium ion battery can describe the physical and chemical processes of solid phase diffusion, liquid phase diffusion, charge transfer reaction, ohmic effect and the like which occur in the battery, and has higher precision. The conventional electrochemical model includes a plurality of coupled partial differential equations and nonlinear algebraic equations, which are computationally complex, and the present embodiment uses a simplified electrochemical model to characterize the cells.
Wherein:
open circuit voltage:
open circuit voltage is the potential difference between two electrodes in the steady state of the battery:
in U oc Open circuit voltage for the battery; u (U) p And U n The open circuit potentials of the positive electrode and the negative electrode of the battery are respectively, and the values of the open circuit potentials are the function of the solid-phase lithium intercalation amount of the electrode;and->The concentration of saturated lithium ions of the positive and negative electrode materials respectively; />And->The average lithium ion concentration in the positive and negative electrodes respectively has the following corresponding relation with the battery SOC:
wherein i=p, n represents the positive electrode or the negative electrode of the battery;and->The average lithium ion concentration in the electrode at battery SOC of 1 and 0, respectively.
Solid phase diffusion:
the charge and discharge of a battery depend on intercalation and deintercalation of lithium ions in an electrode material, i.e., a solid-phase diffusion process. This process can cause an uneven distribution of lithium ion concentration in the electrode particles. The relationship between the electrode particle surface and the average lithium ion concentration is expressed as:
wherein i=p, n represents the positive electrode or the negative electrode of the battery;lithium ion concentration at the surface of the electrode particles; />The difference between the lithium ion concentration on the surface of the electrode particles and the average value; i is battery load current, and the current is a positive value when discharging is set; τ s,i A time constant for solid phase diffusion of the electrode; c (C) s,i Is the equivalent polarization capacitance of electrode solid-phase diffusion.
The change in surface lithium ion concentration corresponds to the change in surface potential, thereby producing a solid phase diffusion overpotential. Solid phase diffusion overpotential eta for a single electrode s,i Expressed as:
total overpotential eta generated by solid phase diffusion of positive and negative electrodes s,tot Namely:
η s,tot ＝η s,p -η s,n (5)
liquid phase diffusion:
liquid phase diffusion refers to the phenomenon of diffusion of lithium ions in an electrolyte. This process may cause uneven distribution of lithium ion concentration in the thickness direction of the electrode. The change in liquid phase lithium ion concentration at the electrode and current collector is expressed as:
wherein i=p, n represents the positive electrode or the negative electrode of the battery; c e,i The lithium ion concentration is the liquid phase lithium ion concentration at the junction of the positive electrode and the negative electrode and the current collector;is the average lithium ion concentration in the electrolyte; τ e,i A time constant for liquid phase diffusion in the two electrode areas; c (C) e,i Is the equivalent polarization capacitance of liquid phase diffusion.
The change of the concentration of liquid-phase lithium ions at the junction of the two electrodes and the current collector generates liquid-phase diffusion overpotential, which is expressed as:
wherein eta is e Diffusion overpotential for the liquid phase; k (K) e The coefficients are converted for lumped.
Charge transfer:
the charge transfer reaction occurs at the interface of the solid phase electrode particles and the electrolyte, and the resulting overpotential can be expressed by the redefined Butler-Volmer equation:
wherein i=p, n represents the positive electrode or the negative electrode of the battery; η (eta) ct,i An over-potential for charge transfer to an electrode; k (K) i Is a lumped electrode reaction constant. R is R g Representing an ideal gas constant; f represents a faraday constant.
The total overpotential generated by the charge transfer of the positive electrode and the negative electrode is as follows:
η ct,tot ＝η ct,p -η ct,n (9)
ohmic overpotential:
the ohmic overpotential inside the cell is expressed as:
wherein R is ohm Is the total ohmic internal resistance and mainly composed of the internal resistance R of electrolyte e And SEI film internal resistance R sei Composition is prepared.
In connection with the above analysis, the cell terminal voltage is expressed as:
V b ＝U oc +η s,tot +η e +η ct,tot +η ohm (11)
the heat generation power of the battery is mainly composed of reversible heat and irreversible heat, and can be calculated by the Bernardi heat generation power formula as follows:
in which Q gen Generating heat power for the battery; q (Q) r And Q ir Respectively represents reversible heat and irreversible heat power; t (T) b Is the battery temperature;and->The entropy heat coefficient of the anode and the cathode of the battery is respectively expressed, and the value of the entropy heat coefficient is a function of the solid-phase lithium intercalation amount in the electrode.
This embodiment uses a lumped parameter thermal model to describe its thermal characteristics. According to the law of conservation of energy, the rate of change of the temperature of the battery cell is expressed as:
wherein R is th And C th Respectively the thermal resistance and the thermal capacity of the battery; t (T) ∞ Is ambient temperature.
Considering the effect of temperature on the open circuit voltage, the electrode open circuit potential in equation (1) is expressed according to the Nernst equation:
wherein i=p, n represents the positive electrode or the negative electrode of the battery; t (T) ref Is the reference temperature;is the open circuit potential of the electrode at the reference temperature.
In addition, ohmic effects, charge transfer reactions, and lithium ion diffusion are also affected by temperature. The relation of the related parameters with temperature is expressed as an Arrhenius equation:
wherein X represents a parameter having Arrhenius characteristics, including a solid phase diffusion time constant τ s,i Time constant τ of liquid phase diffusion e,i Electrode reaction constant K i And ohmic internal resistance R ohm ；K pre And E is a Respectively indicating the pre-finger factor and the activation energy; r is R g Is an ideal gas constant.
Step 2: based on an electrochemical-thermal coupling model of the lithium ion battery, estimating the power state of the lithium ion battery under the condition of considering macroscopic constraint and microscopic constraint, and generating a power state characteristic diagram of the lithium ion battery;
wherein the macroscopic constraints include current constraints, voltage constraints, state of charge constraints, and temperature constraints, and the microscopic constraints include liquid phase concentration constraints, solid phase concentration constraints, and lithium precipitation constraints.
Generally, to ensure safe and efficient operation of the battery, the battery is operated in the prediction time domain (i.e., t k ∈[t 0 ,t 0 +Δt]) A plurality of macroscopic constraints such as current, voltage, SOC, temperature, etc. need to be satisfied, expressed as:
in the method, in the process of the invention,and->The lower and upper limits of the designed terminal voltage, commonly referred to as discharge and charge cut-off voltages, respectively; i min And I max The lower limit and the upper limit of the designed current are respectively; SOC (State of Charge) min And SOC (System on chip) max The lower limit and the upper limit of the SOC are respectively designed; />Is the upper limit of the designed battery temperature. Since a large amount of heat is generated when the battery is charged and discharged at peak power, the battery temperature is increased, and therefore, a lower temperature limit is not required.
The power performance of the battery is limited by the internal microscopic reaction, and SOP is estimated only based on macroscopic constraints, so that the safe and efficient management of the battery is not facilitated. Therefore, on the basis of the macroscopic constraints, microscopic constraints related to battery aging and safety states are also considered, including liquid phase concentration constraints, solid phase concentration constraints and lithium precipitation constraints. The concrete introduction is as follows:
liquid phase concentration constraints: liquid phase diffusion can lead to uneven distribution of lithium ion concentration in the electrolyte inside the battery. When the concentration is too low, the deintercalation rate of lithium ions in the electrode particles is affected, so that the battery performance is suddenly reduced; when the concentration is too high, corrosion is caused to metal elements such as current collectors inside the battery. Therefore, in order to protect lithium ions in the electrolyte from over-exhaustion and supersaturation phenomena, the following constraints should be imposed on the lithium ion concentration in the electrolyte during charge and discharge:
wherein i=p, n represents the positive electrode or the negative electrode of the battery;and->The lower and upper limits of the ratio between the electrolyte concentration and the initial concentration, respectively.
Solid phase concentration constraints: the solid phase diffusion process is driven by a lithium ion concentration gradient within the electrode active particles. At the same time, due to the elastoplastic nature of the active particles, the non-uniform concentration distribution undoubtedly leads to a radially non-uniform volume expansion of the particles, thereby inducing internal mechanical stresses. Such stresses increase the likelihood of breakage of the active particles, which can lead to loss of electrode material over time. To suppress such adverse phenomena, the difference between the surface of the counter electrode particle and the average lithium ion concentration is constrained as follows:
wherein i=p, n represents the positive electrode or the negative electrode of the battery;is the upper limit of the ratio between the concentration difference and the saturation concentration.
Lithium separation constraint: lithium separation refers to a phenomenon that lithium ions cannot be inserted into a negative electrode during charging of a battery and form metallic lithium on the surface of the negative electrode. If the lithium precipitation phenomenon continuously occurs, lithium dendrites can be formed on the surfaces of the negative electrode particles, and when the lithium precipitation phenomenon is serious, the lithium dendrites penetrate through a diaphragm to cause an internal short circuit thermal runaway accident. Thus, the following lithium analysis constraints are contemplated in the present invention:
wherein U is LiP The equilibrium potential for lithium evolution reactions is typically 0.
In view of the above macroscopic and microscopic constraints, a battery SOP profile is generated based on an electrochemical-thermal coupling model and dichotomy principles, as shown in fig. 2.
(1) For discharge scenes
(1) Since the discharge current is positive, I lower ＝0,I upper ＝I max ；I lower And I upper Respectively representing the lower limit and the upper limit of the search current in the dichotomy;
(2) to sustain discharge currentAs input of an electrochemical-thermal coupling model, simulation obtains a result within a predicted duration Δt given an initial temperature and state of charge;
(3) if the simulation result meets all macro-micro constraints, updating I lower The value of (2) is such thatOtherwise update I upper The value of>
(4) Repeating steps (2) and (3) until the current meets the tolerance requirement, i.e. I upper -I lower ≤ε I The method comprises the steps of carrying out a first treatment on the surface of the Wherein ε I Is the current tolerance;
(5) calculating the discharge peak power:wherein V is b Is the battery terminal voltage.
(2) For charging scenarios
(1) Since the charging current is negative, I lower ＝I min ,I upper ＝0；
(2) To continue charging currentAs input of an electrochemical-thermal coupling model, simulation obtains a result within a predicted duration Δt given an initial temperature and state of charge;
(3) if the simulation result meets all macro-micro constraints, updating I upper The value of (2) is such thatOtherwise update I lower The value of>
(4) Repeating steps (2) and (3) until the current meets the tolerance requirement, i.e. I upper -I lower ≤ε I ；
(5) Calculating charging peak power:
taking lithium cobaltate 18650 battery produced by a certain company as an example, electrochemical-thermal model parameters are obtained through experiments, and a peak power characteristic diagram of the battery when the predicted time length is 30s is given based on the proposed SOP estimation method. The relevant macroscopic and microscopic constraints are shown in table 1:
TABLE 1 SOP estimation macroscopic and microscopic constraint settings
Fig. 3 (a) -3 (d) present discharge/charge peak power profiles that consider both macroscopic and microscopic constraints and only macroscopic constraints. Since the battery has good lithium ion diffusion, electrochemical reaction and conductivity at high temperature, it can be seen that the battery exhibits better discharge and charge capabilities as the temperature increases. At the same temperature, the discharge peak power increases with the increase of the SOC, and the charge peak power is opposite. The results taking both macroscopic and microscopic constraints into account exhibit an overall decreasing trend, in contrast to the results taking only macroscopic constraints into account. This also illustrates that existing SOP estimation methods that impose only macroscopic constraints are relatively aggressive. Further, the information in the profile may be stored by the vehicle controller in the form of a multi-dimensional look-up table to guide optimal control and energy management of the vehicle.
Example two
The embodiment provides a lithium ion battery SOP estimation system considering microscopic constraints, which comprises the following modules:
the model building module is used for building an electrochemical-thermal coupling model of the lithium ion battery and obtaining parameters of the electrochemical-thermal coupling model of the lithium ion battery;
the power state estimation module is used for estimating the power state of the lithium ion battery based on the electrochemical-thermal coupling model of the lithium ion battery under the condition of considering macroscopic constraint and microscopic constraint, and generating a power state characteristic diagram of the lithium ion battery;
wherein the macroscopic constraints include current constraints, voltage constraints, state of charge constraints, and temperature constraints, and the microscopic constraints include liquid phase concentration constraints, solid phase concentration constraints, and lithium precipitation constraints.
It should be noted that, each module in the embodiment corresponds to each step in the first embodiment one to one, and the implementation process is the same, which is not described here.
Example III
The present embodiment provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps in a lithium ion battery SOP estimation method taking into account microscopic constraints as described above.
The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), or the like.
Example IV
The present embodiment provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, which when executed implements the steps in a lithium ion battery SOP estimation method taking into account microscopic constraints as described above.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. The lithium ion battery SOP estimation method considering microscopic constraint is characterized by comprising the following steps of:
constructing an electrochemical-thermal coupling model of the lithium ion battery, and obtaining parameters of the electrochemical-thermal coupling model of the lithium ion battery;
based on an electrochemical-thermal coupling model of the lithium ion battery, estimating the power state of the lithium ion battery under the condition of considering macroscopic constraint and microscopic constraint, and generating a power state characteristic diagram of the lithium ion battery;
wherein the macroscopic constraints include current constraints, voltage constraints, state of charge constraints, and temperature constraints, and the microscopic constraints include liquid phase concentration constraints, solid phase concentration constraints, and lithium precipitation constraints;
the liquid phase concentration constraint is:
where i=p, n represents the positive or negative electrode of the battery;and->A lower limit and an upper limit of the ratio between the electrolyte concentration and the initial concentration, respectively; />Is the average lithium ion concentration in the electrolyte; c e，i (t k ) At t k At moment, the concentration of liquid-phase lithium ions at the junction of the positive electrode and the negative electrode and the current collector;
the solid phase concentration constraint is:
where i=p, n represents the positive or negative electrode of the battery;an upper limit for the ratio between the concentration difference and the saturation concentration;at t k At the moment, the lithium ion concentration on the surface of the electrode particles; />At t k At time, the average lithium ion concentration in the electrode; />Saturated lithium ion concentration as electrode material;
the lithium separation constraint is as follows:
wherein U is LiP Balancing the potential for lithium evolution reactions; r is R sei Is SEI film internal resistance; u (U) n Open circuit potential for the battery negative electrode;at t k At the moment, the lithium ion concentration on the surface of the anode particles; />A saturated lithium ion concentration that is the negative electrode material; />At t k At the moment, the charge of the negative electrode passes through the potential; />At t k At this time, the battery load current, the current at the time of discharging is set to a positive value.
2. The method for estimating SOP of a lithium-ion battery taking into account microscopic constraints according to claim 1, wherein in the electrochemical-thermal coupling model of the lithium-ion battery, a temperature versus electrode open-circuit potential U is considered i According to Nernst equation U i Characterized by:
wherein i=p, n represents the positive electrode or the negative electrode of the battery; t (T) ref Is the reference temperature;at a reference temperature ofIs a potential of an open electrode; t (T) b Is the battery temperature.
3. The method for estimating SOP of a lithium-ion battery taking microscopic constraints into account according to claim 1, wherein in the electrochemical-thermal coupling model of the lithium-ion battery, ohmic effects, charge transfer reactions and lithium ion diffusion are also affected by temperature, and the relationship between the ohmic effects, charge transfer reactions and lithium ion diffusion parameters with respect to temperature is characterized by Arrhenius equation:
wherein X represents parameters having Arrhenius characteristics, including a solid phase diffusion time constant, a liquid phase diffusion time constant, an electrode reaction constant, and an ohmic internal resistance; k (K) pre And E is a Respectively indicating the pre-finger factor and the activation energy; r is R g Is an ideal gas constant; t (T) b Is the battery temperature.
4. The method for estimating SOP of a lithium-ion battery in consideration of microscopic constraints according to claim 1, wherein the parameters of the electrochemical-thermal coupling model of the lithium-ion battery are obtained through experiments.
5. The method for estimating SOP of a lithium-ion battery taking into account microscopic constraints according to claim 1, wherein the power state of the lithium-ion battery is estimated based on an electrochemical-thermal coupling model of the lithium-ion battery and a dichotomy under consideration of macroscopic constraints and microscopic constraints.
6. The method for estimating SOP of a lithium-ion battery taking microscopic constraints into account according to claim 1, wherein in estimating the power state of the lithium-ion battery, for a discharge scenario, the discharge current is positive, the continuous discharge current is used as an input of an electrochemical-thermal coupling model, and the simulation obtains a result within a predicted period of time given an initial temperature and a state of charge; and if the simulation result meets all macro constraints and micro constraints simultaneously, updating the lower limit of the search current in the dichotomy, otherwise, updating the upper limit of the search current until the difference between the upper limit and the lower limit of the search current in the dichotomy meets the tolerance requirement, and calculating the discharge peak power.
7. The method for estimating SOP of a lithium-ion battery taking microscopic constraints into account according to claim 1, wherein in estimating the power state of the lithium-ion battery, for a charging scenario, the charging current is negative, the continuous charging current is used as an input of an electrochemical-thermal coupling model, and the simulation obtains a result within a predicted period of time given an initial temperature and a state of charge; and if the simulation result meets all macro constraints and micro constraints simultaneously, updating the upper limit of the search current in the dichotomy, otherwise, updating the lower limit of the search current until the difference between the upper limit and the lower limit of the search current in the dichotomy meets the tolerance requirement, and calculating the charging peak power.
8. A lithium ion battery SOP estimation system that accounts for microscopic constraints, comprising:
the model building module is used for building an electrochemical-thermal coupling model of the lithium ion battery and obtaining parameters of the electrochemical-thermal coupling model of the lithium ion battery;
the power state estimation module is used for estimating the power state of the lithium ion battery based on the electrochemical-thermal coupling model of the lithium ion battery under the condition of considering macroscopic constraint and microscopic constraint, and generating a power state characteristic diagram of the lithium ion battery;
wherein the macroscopic constraints include current constraints, voltage constraints, state of charge constraints, and temperature constraints, and the microscopic constraints include liquid phase concentration constraints, solid phase concentration constraints, and lithium precipitation constraints;
the liquid phase concentration constraint is:
where i=p, n represents the positive or negative electrode of the batteryA pole;and->A lower limit and an upper limit of the ratio between the electrolyte concentration and the initial concentration, respectively; />Is the average lithium ion concentration in the electrolyte; c e，i (t k ) At t k At moment, the concentration of liquid-phase lithium ions at the junction of the positive electrode and the negative electrode and the current collector;
the solid phase concentration constraint is:
where i=p, n represents the positive or negative electrode of the battery;an upper limit for the ratio between the concentration difference and the saturation concentration;at t k At the moment, the lithium ion concentration on the surface of the electrode particles; />At t k At time, the average lithium ion concentration in the electrode; />Saturated lithium ion concentration as electrode material;
the lithium separation constraint is as follows:
wherein U is LiP Balancing the potential for lithium evolution reactions; r is R sei Is SEI film internal resistance; u (U) n Open circuit potential for the battery negative electrode;at t k At the moment, the lithium ion concentration on the surface of the anode particles; />A saturated lithium ion concentration that is the negative electrode material; η (eta) ct，n (t k ) At t k At the moment, the charge of the negative electrode passes through the potential; i (t) k ) At t k At this time, the battery load current, the current at the time of discharging is set to a positive value.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the steps of the lithium ion battery SOP estimation method taking into account microscopic constraints according to any of claims 1-7.
10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor performs the steps in the lithium ion battery SOP estimation method taking into account microscopic constraints according to any of claims 1-7 when executing the program.
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