Method and system for determining lithium ion loss of battery

Abstract

The invention provides a battery lithium ion loss determination method and system, and the method comprises the steps: obtaining the electricity price information of each moment in a preset time period, inputting the electricity price information into a pre-established peak regulation instruction model, and obtaining the charging and discharging power of each moment in the preset time period; determining a peak regulation command sequence of the preset time length based on the charging and discharging power of each moment in the preset time length; determining a current regulation value of each energy storage battery in the lithium battery at each moment in the preset duration according to the peak regulation command sequence of the preset duration, and forming a current sequence; substituting the current sequence into a pre-established battery model to obtain the current intensity of the side reaction of the energy storage battery; and determining the lithium ion loss value of each energy storage battery in the preset duration according to the current intensity of the side reaction of the energy storage battery. According to the technical scheme provided by the invention, the lithium ion loss of the battery in the peak regulation process can be determined, and theoretical guidance is provided for a battery manager to formulate a scientific operation strategy.

Description

Technical Field

[0001] The present application relates to the technical field of battery energy storage and energy management, and in particular to a method and system for determining battery lithium ion loss. Background Art

[0002] In recent years, renewable energy has become increasingly important in power grids, placing increasing demands on the grid's load-side flexibility. Furthermore, increasing fluctuations and randomness in supply and demand are also constraining grid operations. Faced with this challenge, utilizing lithium-ion battery energy storage to coordinate the spatiotemporal mismatch between electricity supply and demand is a strategic choice for China and most other countries worldwide. Due to complexity and solvability limitations, water tank models are often used to describe battery characteristics when embedding lithium-ion battery models into grid operation scenarios. However, the limitations and imprecision of water tank models prevent decision makers from understanding the degradation trajectory and characteristics of lithium-ion batteries during peak-shaving service, resulting in poor energy management effectiveness for battery energy storage. Therefore, a solution is urgently needed to understand the degradation trajectory and characteristics of lithium-ion batteries during peak-shaving service. Summary of the Invention

[0003] The present application provides a method and system for determining battery lithium ion loss, so as to at least solve the technical problem of being unable to help decision makers understand the degradation trajectory and characteristics of lithium batteries during peak-shaving services.

[0004] The first embodiment of the present application provides a method for determining lithium ion loss in a battery, the method comprising:

[0005] Obtaining electricity price information at each moment within a preset duration, and inputting the electricity price information into a pre-established peak load instruction model to obtain the charge and discharge power at each moment within the preset duration;

[0006] Determining a peak shaving command sequence of the preset duration based on the charge and discharge power at each moment within the preset duration;

[0007] Determine the current adjustment value of each energy storage battery in the lithium battery at each moment within the preset time period according to the peak shaving command sequence of the preset time period, and form a current sequence;

[0008] Substituting the current sequence into a pre-established battery model to obtain the current intensity of the side reaction of the energy storage battery;

[0009] Determining the lithium ion loss value of each energy storage battery within the preset time period according to the current intensity of the side reaction of the energy storage battery;

[0010] The current intensity of the side reactions of the energy storage battery includes: the current intensity of the lithium precipitation side reaction, the current intensity of the solid electrolyte membrane growth side reaction, and the current intensity of the lithium ion fracture side reaction.

[0011] Preferably, the process of establishing the peak-shaving instruction model includes:

[0012] The objective function is constructed with the goal of minimizing the electricity purchase cost on the peak demand side;

[0013] The capacity constraint, charge and discharge power constraint, and state of charge constraint of the lithium battery are used as constraint conditions, and the peak load instruction model is constructed in combination with the objective function.

[0014] Furthermore, the calculation formula of the peak-shaving command sequence of the preset duration is as follows:

[0015]

[0016] Where r is the peak load command sequence with preset duration, The Nth time within the preset time r The charge and discharge power at each moment, N r The total number of moments within the preset duration.

[0017] Furthermore, the current adjustment value of each energy storage battery in the lithium battery at each moment within the preset time period is determined according to the peak shaving command sequence of the preset time period, and a current sequence is formed, including:

[0018] Get the preset declared capacity value;

[0019] Determining the current regulation value of each energy storage battery in the lithium battery at each moment within a preset time period according to the preset declared capacity value and the peak shaving command sequence;

[0020] A current sequence is constructed based on the current regulation value of each energy storage cell in the lithium battery at each moment within the preset time period.

[0021] Furthermore, the calculation formula of the current regulation value of each energy storage battery in the lithium battery at each moment within the preset time period is as follows:

[0022] I l =C shave r l / N b U norm

[0023] Where, I l is the current regulation value of each energy storage cell in the lithium battery at the first moment within the preset time, C shave is the preset declared capacity value, r l is the charge and discharge power at the first moment within the preset time, N b is the total number of energy storage cells in the lithium battery, and U is the lithium battery voltage;

[0024] norm

[0025] The current sequence is calculated as follows:

[0026]

[0027] Where I is the current sequence.

[0028] Furthermore, the calculation formula of the pre-established battery model is as follows:

[0029]

[0030] Where V is N r ×1 voltage sequence, j tot is the main reaction rate of the energy storage battery, j SEI is the side reaction rate of the energy storage battery, is the average lithium insertion rate of the positive and negative electrode solid phase active particles, T amb is the ambient temperature of the battery, θ is the battery model parameter set, f bat is the expression of the battery model;

[0031] The calculation formula of the current intensity of the side reaction of the energy storage battery is as follows:

[0032]

[0033] Where, j LP is the current intensity of the lithium deposition side reaction, a s,SEI is the reaction area per unit volume of the side reaction of solid electrolyte membrane growth, i 0,SEI is the exchange current density of the side reaction of solid electrolyte film growth, α c,SEI is the reduction direction proportional coefficient of the side reaction of solid electrolyte membrane growth, a s,LP is the reaction area per unit volume of the lithium deposition side reaction, i 0,LP is the exchange current density of the lithium deposition side reaction, α c,LP is the reduction direction proportional coefficient of the lithium precipitation side reaction, U LP is the trigger voltage of the lithium deposition side reaction, F is the Faraday constant, R is the ideal gas constant, T is the battery temperature, φ se is the potential difference at the solid-liquid interface, U SEI is the trigger voltage of the side reaction of solid electrolyte film growth, is the current intensity of the lithium ion fracture side reaction, λ AM is the aging parameter of the lithium ion fracture side reaction, where j tot =j n +j SEI +j LP ,j n The reaction current intensity of the main reaction.

[0034] Furthermore, the calculation formula for the lithium ion loss value of each energy storage battery within the preset time period is as follows:

[0035]

[0036] Where, is the lithium ion loss value of each energy storage battery, Lithium ion loss caused by the side reaction of solid electrolyte film growth, The loss of lithium ions due to the side reaction of lithium deposition is Lithium ion loss due to lithium ion fracture;

[0037] in, Where A - is the cross-sectional area of the negative electrode separator, L - is the thickness of the separator area of the negative electrode, is the theoretical maximum lithium insertion rate of the negative electrode active particles, is the lithium insertion rate of the negative electrode solid active particles, ε s is the volume fraction of the negative electrode solid.

[0038] A second embodiment of the present application provides a system for determining battery lithium ion loss, comprising:

[0039] An acquisition module is used to obtain electricity price information at each moment within a preset duration, and input the electricity price information into a pre-established peak-shaving instruction model to obtain the charge and discharge power at each moment within the preset duration;

[0040] A first determining module is configured to determine a peak shaving command sequence of the preset duration based on the charge and discharge power at each moment within the preset duration;

[0041] A second determining module is used to determine the current adjustment value of each energy storage battery in the lithium battery at each moment within the preset time length according to the peak-shaving command sequence of the preset time length, and form a current sequence;

[0042] a third determination module, configured to bring the current sequence into a pre-established battery model to obtain the current intensity of the side reaction of the energy storage battery;

[0043] a fourth determining module, configured to determine a lithium ion loss value of each energy storage battery within the preset time period according to the current intensity of the side reaction of the energy storage battery;

[0044] The current intensity of the side reactions of the energy storage battery includes: the current intensity of the lithium precipitation side reaction, the current intensity of the solid electrolyte membrane growth side reaction, and the current intensity of the lithium ion fracture side reaction.

[0045] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the method described in the first aspect is implemented.

[0046] A fourth embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first embodiment.

[0047] The technical solutions provided by the embodiments of this application bring at least the following beneficial effects:

[0048] This application proposes a method and system for determining battery lithium ion loss, the method comprising: obtaining electricity price information at each moment within a preset duration, and inputting the electricity price information into a pre-established peak-shaving instruction model to obtain the charge and discharge power at each moment within the preset duration; determining a peak-shaving command sequence for the preset duration based on the charge and discharge power at each moment within the preset duration; determining the current adjustment value of each energy storage cell in the lithium battery at each moment within the preset duration according to the peak-shaving command sequence of the preset duration, and forming a current sequence; bringing the current sequence into a pre-established battery model to obtain the current intensity of the energy storage cell side reaction; determining the lithium ion loss value of each energy storage cell in the lithium battery within the preset duration according to the current intensity of the energy storage cell side reaction; wherein the current intensity of the energy storage cell side reaction includes: the current intensity of the lithium precipitation side reaction, the current intensity of the solid electrolyte membrane growth side reaction, and the current intensity of the lithium ion fracture side reaction. The technical solution proposed in this application can clearly define the lithium ion loss of the battery during the peak-shaving process and provide theoretical guidance for battery managers to formulate scientific operation strategies.

[0049] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0051] Figure 1 A flowchart of a method for determining battery lithium ion loss according to one embodiment of the present application;

[0052] Figure 2 The present invention is a structural diagram of a system for determining lithium ion loss in a battery according to an embodiment of the present application. DETAILED DESCRIPTION

[0053] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0054] The present application proposes a method and system for determining battery lithium ion loss, the method comprising: obtaining electricity price information at each moment within a preset duration, and inputting the electricity price information into a pre-established peak-shaving instruction model to obtain the charge and discharge power at each moment within the preset duration; determining a peak-shaving command sequence for the preset duration based on the charge and discharge power at each moment within the preset duration; determining the current adjustment value of each energy storage cell in the lithium battery at each moment within the preset duration according to the peak-shaving command sequence for the preset duration, and forming a current sequence; bringing the current sequence into a pre-established battery model to obtain the current intensity of the energy storage cell side reaction; determining the lithium ion loss value of each energy storage cell in the lithium battery within the preset duration according to the current intensity of the energy storage cell side reaction; wherein the current intensity of the energy storage cell side reaction includes: the current intensity of the lithium precipitation side reaction, the current intensity of the solid electrolyte membrane growth side reaction, and the current intensity of the lithium ion fracture side reaction. The technical solution proposed in the present application can clearly define the lithium ion loss of the battery during the peak-shaving process and provide theoretical guidance for battery managers to formulate scientific operation strategies.

[0055] The following describes a method and system for determining battery lithium ion loss according to an embodiment of the present application with reference to the accompanying drawings.

[0056] Example 1

[0057] Figure 1 This is a flow chart of a method for determining battery lithium ion loss according to one embodiment of the present application, as shown in FIG. Figure 1 As shown, the method includes:

[0058] Step 1: Obtain electricity price information at each moment within a preset duration, and input the electricity price information into a pre-established peak load instruction model to obtain the charge and discharge power at each moment within the preset duration.

[0059] In the embodiment of the present disclosure, the process of establishing the peak load instruction model includes:

[0060] The objective function is constructed with the goal of minimizing the electricity purchase cost on the peak demand side;

[0061] The capacity constraint, charge and discharge power constraint, and state of charge constraint of the lithium battery are used as constraint conditions, and the peak load instruction model is constructed in combination with the objective function.

[0062] It should be noted that the calculation formula of the objective function is as follows:

[0063]

[0064] Where F is the electricity purchase cost on the peak demand side, π h is the electricity price at time h, is the charging power at time h, is the discharge power at time h, and H is the total number of moments.

[0065] The calculation formula of the capacity constraint of the lithium battery is as follows:

[0066]

[0067] E h =SOC(h)×E n

[0068] Where, E h+1 is the capacity of the battery at time h+1, E h is the capacity of the battery at time h, η is the conversion efficiency during charge and discharge, and SOC(h) is the state of charge at time h;

[0069] The calculation formula of the charge and discharge power constraint is as follows:

[0070]

[0071] Where, P min is the minimum charge and discharge power of the battery;

[0072] The calculation formula of the state of charge constraint is as follows:

[0073] SOC(0)=0.1

[0074] Where SOC(0) is the state of charge at the initial moment.

[0075] It should be noted that the peak-shaving instruction is modeled using a water tank model to obtain a peak-shaving instruction model.

[0076] Step 2: Determine a peak load regulation command sequence of the preset duration based on the charge and discharge power at each moment within the preset duration.

[0077] In the embodiment of the present disclosure, the calculation formula of the peak-shaving command sequence of the preset duration is as follows:

[0078]

[0079] Where r is the peak load command sequence with preset duration, The Nth time within the preset time r The charge and discharge power at each moment, N ris the total number of moments within the preset duration, where N r =H.

[0080] Step 3: Determine the current adjustment value of each energy storage battery in the lithium battery at each moment within the preset time period according to the peak-shaving command sequence of the preset time period, and form a current sequence.

[0081] In the embodiment of the present disclosure, step 3 specifically includes:

[0082] Get the preset declared capacity value;

[0083] Determining the current regulation value of each energy storage battery in the lithium battery at each moment within a preset time period according to the preset declared capacity value and the peak shaving command sequence;

[0084] A current sequence is constructed based on the current regulation value of each energy storage cell in the lithium battery at each moment within the preset time period.

[0085] The calculation formula for the current regulation value of each energy storage battery in the lithium battery at each moment within the preset time period is as follows:

[0086] I l =C shave r l / N b U norm

[0087] Where, I l is the current regulation value of each energy storage cell in the lithium battery at the first moment within the preset time, C shave is the preset declared capacity value, r l is the charge and discharge power at the first moment within the preset time, N b is the total number of energy storage cells in the lithium battery, U norm is the lithium battery voltage; wherein the preset declared capacity value may be the maximum declared capacity.

[0088] The current sequence is calculated as follows:

[0089]

[0090] Where I is the current sequence.

[0091] It should be noted that the power signal, i.e. the charge and discharge power obtained in step 1, is converted into a current signal and used as the input of the battery model to realize the battery operation simulation. r =1800, so the peak shaving command sequence is Normalize the value to the range of [-1,1]. The final output power of the lithium battery energy storage should be equal to the response signal amplitude and the declared capacity C shave The product of

[0092] The number of energy storage cells in a lithium battery is N b To simplify the problem, this method assumes that the performance and parameters of each battery in the energy storage system are the same. Under this assumption, the peak power of each battery is P / N b Studies have shown that whether it is a lithium iron phosphate battery or a ternary lithium battery, when the state of charge is around 0.5, the battery voltage can be approximately considered to be U norm Therefore, the current sequence of the battery is:

[0093]

[0094] Step 4: Substitute the current sequence into a pre-established battery model to obtain the current intensity of the side reaction of the energy storage battery; wherein the current intensity of the side reaction of the energy storage battery includes: the current intensity of the lithium precipitation side reaction, the current intensity of the solid electrolyte membrane growth side reaction, and the current intensity of the lithium ion fracture side reaction.

[0095] In the embodiment of the present disclosure, the calculation formula of the pre-established battery model is as follows:

[0096]

[0097] Where V is N r ×1 voltage sequence, j tot is the main reaction rate of the energy storage battery, j SEI is the side reaction rate of the energy storage battery, is the average lithium insertion rate of the positive and negative electrode solid phase active particles, T amb is the ambient temperature of the battery, θ is the battery model parameter set, f bat is the expression of the battery model; where j tot and j SEI All are N r ×5 matrix, Then N r × 6 matrix (the negative electrode is divided into 5 regions, and the positive electrode is not divided into regions because aging does not need to be considered), and θ is determined by the health status of the battery.

[0098] The calculation formula of the current intensity of the side reaction of the energy storage battery is as follows:

[0099]

[0100] Where, j LP is the current intensity of the lithium deposition side reaction, a s,SEI is the reaction area per unit volume of the side reaction of solid electrolyte membrane growth, i 0,SEI is the exchange current density of the side reaction of solid electrolyte film growth, α c,SEIis the reduction direction proportional coefficient of the side reaction of solid electrolyte membrane growth, a s,LP is the reaction area per unit volume of the lithium deposition side reaction, i 0,LP is the exchange current density of the lithium deposition side reaction, α c,LP is the reduction direction proportional coefficient of the lithium precipitation side reaction, U LP is the trigger voltage of the lithium deposition side reaction, F is the Faraday constant, R is the ideal gas constant, T is the battery temperature, φ se is the potential difference at the solid-liquid interface, U SEI is the trigger voltage of the side reaction of solid electrolyte film growth, is the current intensity of the lithium ion fracture side reaction, λ AM is the aging parameter of the lithium ion fracture side reaction, where j tot =j n +j SEI +j LP ,j n The reaction current intensity of the main reaction.

[0101] It should be noted that after obtaining the current sequence, substituting it into the battery model embedded with the side reaction rate, the battery voltage and internal state response sequence can be obtained. The battery model is expressed in the form of a function, denoted as f bat , the expression is as follows:

[0102]

[0103] This example proposes a new battery model that embeds the side reaction rate. Without increasing the computational complexity, it is possible to obtain an analytical expression for the non-uniform distribution of the main reaction rate and the side reaction rate, as follows:

[0104] Side reactions and main reactions in lithium-ion batteries will continuously affect battery parameters and cause changes in the overall performance of the battery.

[0105] First, the three main side reactions of lithium batteries are modeled from the perspective of battery reaction mechanism:

[0106]

[0107] Analyze the degradation mechanism of battery parameters, including:

[0108]

[0109] Where, is the volume of the reaction product per unit volume per unit time, is the change in the reaction product. s is the equivalent radius of the active particle, M and ρ are the relative molar mass and relative density, respectively. The subscripts LP and SEI represent lithium precipitation and solid electrolyte film growth, respectively. εs is the volume fraction of the current effective active particles, which will decrease as the battery ages. s,0 is the volume fraction of effective active particles in a new battery, which is a constant value.

[0110] The growth of deposits on the surface of active particles will cause the surface resistance of the active particles R f This method considers the lithium precipitation layer as a good conductor and only considers the resistance of the solid electrolyte membrane. SEI is the conductivity of the solid electrolyte membrane, is the volume fraction of the liquid phase reduced per unit volume. c is the concentration of various reaction products.

[0111] The loss of cyclable lithium ions caused by various side reactions can be obtained from the following formula:

[0112]

[0113] Step 5: Determine the lithium ion loss value of each energy storage battery within the preset time period according to the current intensity of the side reaction of the energy storage battery.

[0114] In the embodiment of the present disclosure, the calculation formula of the lithium ion loss value of each energy storage battery within the preset time period is as follows:

[0115]

[0116] Where, is the lithium ion loss value of each energy storage battery, Lithium ion loss caused by the side reaction of solid electrolyte film growth, The loss of lithium ions due to the side reaction of lithium deposition is Lithium ion loss due to lithium ion fracture;

[0117] in, Where A - is the cross-sectional area of the negative electrode separator, L - is the thickness of the separator area of the negative electrode, is the theoretical maximum lithium insertion rate of the negative electrode active particles, is the lithium insertion rate of the negative electrode solid active particles, ε s is the volume fraction of the negative electrode solid.

[0118] It should be noted that the solution proposed in this embodiment studies and analyzes the degradation patterns of lithium energy storage composed of lithium iron phosphate batteries and ternary lithium batteries in peak load shaving service scenarios, thereby helping battery managers formulate reasonable operation strategies:

[0119] 5-1) Select battery instance parameters;

[0120] 5-2) Substitute the selected battery instance parameters into the battery aging model, perform simulation analysis to determine the maximum declared capacity limit considering the load management requirements of the peak-shaving market, and propose a reasonable declared capacity strategy;

[0121] 5-3) Through simulation analysis, the battery operating cost is solved considering the load management demand of the peak-shaving market, and a reasonable battery operation strategy is proposed.

[0122] This proposed method studies the aging patterns of load-side lithium-ion battery energy storage systems when providing peak-shaving services under different operating conditions. Furthermore, it proposes the concept of maximum declared capacity and derives battery declaration strategies under different operating conditions. This helps battery energy storage managers understand the degradation trajectory and characteristics of lithium-ion batteries during peak-shaving services, providing theoretical guidance for developing scientific operational strategies.

[0123] In summary, the method for determining battery lithium ion loss proposed in this embodiment can clearly identify the lithium ion loss of the battery during peak load regulation, and provide theoretical guidance for battery managers to formulate scientific operation strategies.

[0124] Example 2

[0125] Figure 2 This is a structural diagram of a system for determining battery lithium ion loss according to one embodiment of the present application, such as Figure 2 As shown, the system includes:

[0126] The acquisition module 100 is used to obtain electricity price information at each moment within a preset duration, and input the electricity price information into a pre-established peak load instruction model to obtain the charge and discharge power at each moment within the preset duration;

[0127] A first determining module 200 is configured to determine a peak shaving command sequence of a preset duration based on the charge and discharge power at each moment within the preset duration;

[0128] The second determining module 300 is configured to determine the current adjustment value of each energy storage battery in the lithium battery at each moment within the preset duration according to the peak shaving command sequence of the preset duration, and form a current sequence;

[0129] The third determination module 400 is configured to bring the current sequence into a pre-established battery model to obtain the current intensity of the energy storage battery side reaction; wherein the current intensity of the energy storage battery side reaction includes: the current intensity of the lithium precipitation side reaction, the current intensity of the solid electrolyte film growth side reaction, and the current intensity of the lithium ion fracture side reaction;

[0130] The fourth determining module 500 is configured to determine the lithium ion loss value of each energy storage cell within the preset time period according to the current intensity of the side reaction of the energy storage cell.

[0131] It should be noted that the process of establishing the peak load instruction model includes:

[0132] The objective function is constructed with the goal of minimizing the electricity purchase cost on the peak demand side;

[0133] The capacity constraint, charge and discharge power constraint, and state of charge constraint of the lithium battery are used as constraint conditions, and the peak load instruction model is constructed in combination with the objective function.

[0134] It should be noted that the calculation formula of the peak-shaving command sequence of the preset duration is as follows:

[0135]

[0136] Where r is the peak load command sequence with preset duration, The Nth time within the preset time r The charge and discharge power at each moment, N r The total number of moments within the preset duration.

[0137] In the embodiment of the present disclosure, the second determining module 300 is further configured to:

[0138] Get the preset declared capacity value;

[0139] Determining the current regulation value of each energy storage battery in the lithium battery at each moment within a preset time period according to the preset declared capacity value and the peak shaving command sequence;

[0140] A current sequence is constructed based on the current regulation value of each energy storage cell in the lithium battery at each moment within the preset time period.

[0141] The calculation formula for the current regulation value of each energy storage battery in the lithium battery at each moment within the preset time period is as follows:

[0142] I l =C shave r l / N b U norm

[0143] Where, I l is the current regulation value of each energy storage cell in the lithium battery at the first moment within the preset time, C shave is the preset declared capacity value, r l is the charge and discharge power at the first moment within the preset time, N b is the total number of energy storage cells in the lithium battery, and U is the lithium battery voltage;

[0144] norm

[0145] The current sequence is calculated as follows:

[0146]

[0147] Where I is the current sequence.

[0148] It should be noted that the calculation formula of the pre-established battery model is as follows:

[0149]

[0150] Where V is N r ×1 voltage sequence, j tot is the main reaction rate of the energy storage battery, j SEI is the side reaction rate of the energy storage battery, is the average lithium insertion rate of the positive and negative electrode solid phase active particles, T amb is the ambient temperature of the battery, θ is the battery model parameter set, f bat is the expression of the battery model;

[0151] The calculation formula of the current intensity of the side reaction of the energy storage battery is as follows:

[0152]

[0153]

[0154] Where, j LP is the current intensity of the lithium deposition side reaction, a s,SEI is the reaction area per unit volume of the side reaction of solid electrolyte membrane growth, i 0,SEI is the exchange current density of the side reaction of solid electrolyte film growth, α c,SEI is the reduction direction proportional coefficient of the side reaction of solid electrolyte membrane growth, a s,LP is the reaction area per unit volume of the lithium deposition side reaction, i 0,LP is the exchange current density of the lithium deposition side reaction, α c,LP is the reduction direction proportional coefficient of the lithium precipitation side reaction, U LP is the trigger voltage of the lithium deposition side reaction, F is the Faraday constant, R is the ideal gas constant, T is the battery temperature, φ se is the potential difference at the solid-liquid interface, U SEI is the trigger voltage of the side reaction of solid electrolyte film growth, is the current intensity of the lithium ion fracture side reaction, λ AM is the aging parameter of the lithium ion fracture side reaction, where j tot =j n +j SEI +j LP ,j n The reaction current intensity of the main reaction.

[0155] It should be noted that the calculation formula for the lithium ion loss value of each energy storage battery within the preset time period is as follows:

[0156]

[0157] Where, is the lithium ion loss value of each energy storage battery, Lithium ion loss caused by the side reaction of solid electrolyte film growth, The loss of lithium ions due to the side reaction of lithium deposition is Lithium ion loss due to lithium ion fracture;

[0158] in, Where A - is the cross-sectional area of the negative electrode separator, L - is the thickness of the separator area of the negative electrode, is the theoretical maximum lithium insertion rate of the negative electrode active particles, is the lithium insertion rate of the negative electrode solid active particles, ε s is the volume fraction of the negative electrode solid.

[0159] In summary, the system for determining battery lithium ion loss proposed in this embodiment can clearly identify the lithium ion loss of batteries during peak load regulation, and provide theoretical guidance for battery managers to formulate scientific operation strategies.

[0160] Example 3

[0161] To implement the above embodiments, the present disclosure further proposes an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method described in the first embodiment is implemented.

[0162] Example 4

[0163] In order to implement the above embodiments, the present disclosure further proposes a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method described in the first embodiment is implemented.

[0164] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0165] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0166] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for determining lithium ion loss in a battery, characterized in that: The method comprises: Obtaining electricity price information at each moment within a preset duration, and inputting the electricity price information into a pre-established peak load instruction model to obtain the charge and discharge power at each moment within the preset duration; Determining a peak shaving command sequence of the preset duration based on the charge and discharge power at each moment within the preset duration; Determine the current adjustment value of each energy storage battery in the lithium battery at each moment within the preset time period according to the peak shaving command sequence of the preset time period, and form a current sequence; Substituting the current sequence into a pre-established battery model to obtain the current intensity of the side reaction of the energy storage battery; Determining the lithium ion loss value of each energy storage battery within the preset time period according to the current intensity of the side reaction of the energy storage battery; The current intensity of the side reactions of the energy storage battery includes: the current intensity of the lithium precipitation side reaction, the current intensity of the solid electrolyte membrane growth side reaction, and the current intensity of the lithium ion fracture side reaction.

2. The method according to claim 1, wherein The process of establishing the peak-shaving instruction model includes: The objective function is constructed with the goal of minimizing the electricity purchase cost on the peak demand side; The capacity constraint, charge and discharge power constraint, and state of charge constraint of the lithium battery are used as constraint conditions, and the peak load instruction model is constructed in combination with the objective function.

3. The method according to claim 2, wherein The calculation formula of the peak-shaving command sequence of the preset duration is as follows: Where r is the peak load command sequence with preset duration, The Nth time within the preset time r The charge and discharge power at each moment, N r The total number of moments within the preset duration.

4. The method according to claim 3, wherein The step of determining the current adjustment value of each energy storage battery in the lithium battery at each moment within the preset time period according to the peak shaving command sequence of the preset time period and forming a current sequence includes: Get the preset declared capacity value; Determining the current regulation value of each energy storage battery in the lithium battery at each moment within a preset time period according to the preset declared capacity value and the peak shaving command sequence; A current sequence is constructed based on the current regulation value of each energy storage cell in the lithium battery at each moment within the preset time period.

5. The method according to claim 4, wherein The calculation formula for the current regulation value of each energy storage battery in the lithium battery at each moment within the preset time period is as follows: I l =C shave r l / N b U norm Where, I l is the current regulation value of each energy storage cell in the lithium battery at the first moment within the preset time, C shave is the preset declared capacity value, r l is the charge and discharge power at the first moment within the preset time, N b is the total number of energy storage cells in the lithium battery, and U is the lithium battery voltage; norm The current sequence is calculated as follows: Where I is the current sequence.

6. The method according to claim 5, wherein The calculation formula of the pre-established battery model is as follows: Where V is N r ×1 voltage sequence, j tot is the main reaction rate of the energy storage battery, j SEI is the side reaction rate of the energy storage battery, is the average lithium insertion rate of the positive and negative electrode solid phase active particles, T amb is the ambient temperature of the battery, θ is the battery model parameter set, f bat is the expression of the battery model; The calculation formula of the current intensity of the side reaction of the energy storage battery is as follows: Where, j LP is the current intensity of the lithium deposition side reaction, a s,SEI is the reaction area per unit volume of the side reaction of solid electrolyte membrane growth, i 0,SEI is the exchange current density of the side reaction of solid electrolyte film growth, α c,SEI is the reduction direction proportional coefficient of the side reaction of solid electrolyte membrane growth, a s,LP is the reaction area per unit volume of the lithium deposition side reaction, i 0,LP is the exchange current density of the lithium deposition side reaction, α c,LP is the reduction direction proportional coefficient of the lithium precipitation side reaction, U LP is the trigger voltage of the lithium deposition side reaction, F is the Faraday constant, R is the ideal gas constant, T is the battery temperature, φ se is the potential difference at the solid-liquid interface, U SEI is the trigger voltage of the side reaction of solid electrolyte film growth, is the current intensity of the lithium ion fracture side reaction, λ AM is the aging parameter of the lithium ion fracture side reaction, where j tot =j n +j SEI +j LP ,j n The reaction current intensity of the main reaction.

7. The method according to claim 6, wherein The calculation formula for the lithium ion loss value of each energy storage battery within the preset time period is as follows: Where, is the lithium ion loss value of each energy storage battery, Lithium ion loss caused by the side reaction of solid electrolyte film growth, The loss of lithium ions due to the side reaction of lithium deposition is Lithium ion loss due to lithium ion fracture; in, Where A - is the cross-sectional area of the negative electrode separator, L - is the thickness of the separator area of the negative electrode, is the theoretical maximum lithium insertion rate of the negative electrode active particles, is the lithium insertion rate of the negative electrode solid active particles, ε s is the volume fraction of the negative electrode solid.

8. A system for determining lithium ion loss in a battery, characterized in that: The system comprises: An acquisition module is used to obtain electricity price information at each moment within a preset duration, and input the electricity price information into a pre-established peak-shaving instruction model to obtain the charge and discharge power at each moment within the preset duration; A first determining module is configured to determine a peak shaving command sequence of the preset duration based on the charge and discharge power at each moment within the preset duration; A second determining module is used to determine the current adjustment value of each energy storage battery in the lithium battery at each moment within the preset time length according to the peak-shaving command sequence of the preset time length, and form a current sequence; a third determination module, configured to bring the current sequence into a pre-established battery model to obtain the current intensity of the side reaction of the energy storage battery; a fourth determining module, configured to determine a lithium ion loss value of each energy storage battery within the preset time period according to the current intensity of the side reaction of the energy storage battery; The current intensity of the side reactions of the energy storage battery includes: the current intensity of the lithium precipitation side reaction, the current intensity of the solid electrolyte membrane growth side reaction, and the current intensity of the lithium ion fracture side reaction.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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