All-vanadium redox flow battery control method and device, storage medium and electronic equipment

Abstract

The invention discloses an all-vanadium redox flow battery control method and device, a storage medium and electronic equipment. The method comprises the following steps: acquiring actual measurement data of the all-vanadium redox flow battery; performing parameter optimization on a fractional order state-space equation and a fractional order measurement equation constructed based on the all-vanadium redox flow battery according to actual measurement data; based on the fractional order state-space equation, the fractional order measurement equation and the actual measurement data, predicting the charge state and terminal voltage of the all-vanadium redox flow battery at the second moment; and when the deviation between the measured value at the first moment and the predicted value at the second moment is greater than a preset threshold value, adjusting the working current of the all-vanadium redox flow battery according to the measured value at the first moment and the predicted value at the second moment. According to the method, the dependence of the polarization voltage on the historical state and the non-uniform characteristic of ion diffusion are described by means of the fractional order state-space equation, and the charge state and the terminal voltage at the next moment can be predicted more accurately in combination with the actually measured data at the first moment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vanadium redox flow battery control, and particularly relates to a vanadium redox flow battery control method and device, a storage medium and an electronic device. BACKGROUND

[0002] Vanadium redox flow battery (VRFB) realizes energy storage and release through reversible oxidation and reduction of vanadium ions in positive and negative electrolytes, and has a wide application prospect in grid-level energy storage, renewable energy consumption and other scenarios.

[0003] At present, the control of the vanadium redox flow battery mostly depends on the traditional integer order model, and the polarization characteristics and dynamic response of the vanadium redox flow battery are described by integer order elements such as resistance and capacitance. The polarization characteristics refer to the voltage loss (polarization voltage) caused by the chemical reaction resistance and the difference in ion concentration during the charging and discharging process of the battery. The dynamic response refers to the real-time evolution characteristics of the battery state (such as the state of charge, the terminal voltage) with the change of the working current. However, there are complex electrochemical kinetic behaviors inside the vanadium redox flow battery, such as non-uniform mass transfer in porous electrodes, non-ideality of vanadium ion transmembrane diffusion and memory of polarization effect. The integer order element can only describe the linear and local instantaneous response, and cannot represent the kinetic characteristics of the vanadium redox flow battery, which leads to insufficient prediction accuracy of the battery state. Controlling the battery state is crucial under the working conditions such as charging and discharging of the vanadium redox flow battery, which needs to avoid excessive charging and discharging, maintain polarization stability to prevent safety risks, and meet the performance requirements of diversified scenarios. The accuracy of the control strategy is highly dependent on the accuracy of the battery state prediction. If the predicted state is not accurate, the control strategy will be difficult to adapt to the real-time state of the battery, which will eventually lead to poor control effect and unable to give the optimal instruction. SUMMARY

[0004] In view of the above problems, the present application provides a vanadium redox flow battery control method, device, storage medium and electronic device.

[0005] To solve the above technical problems, the present application proposes the following solutions:

[0006] In a first aspect, the application provides a method for controlling a vanadium redox flow battery, the method comprising: obtaining actual measurement data of the vanadium redox flow battery, the actual measurement data comprising an end voltage, an operating current and a discharge capacity of the vanadium redox flow battery at a first time point; performing parameter optimization on a fractional-order state space equation and a fractional-order measurement equation constructed based on the vanadium redox flow battery according to the actual measurement data, the fractional-order state space equation being used to describe a dependence relationship of a polarization voltage change on a historical state of the battery and a non-uniform distribution characteristic of ion diffusion in space, and the fractional-order measurement equation being used to convert the dependence relationship and the non-uniform distribution characteristic into an actually measurable end voltage signal; predicting a state of charge and an end voltage of the vanadium redox flow battery at a second time point based on the fractional-order state space equation, the fractional-order measurement equation and the actual measurement data, the second time point being a next time point of the first time point; and adjusting the operating current of the vanadium redox flow battery according to a measured value at the first time point and a predicted value at the second time point, so as to reduce an error between the measured value at the second time point and the predicted value at the second time point.

[0007] In combination with the first aspect, in a possible implementation manner, the fractional-order state space equation is: wherein U1 and U2 are voltages across the first polarization capacitance C1 and the second polarization capacitance C2 respectively, SOC is a state of charge of the battery, R1 and R2 are charge transfer polarization resistance and concentration polarization resistance respectively, a and β are fractional-order orders, Q n is a rated discharge capacity of the battery, T is a sampling time interval, I k is the operating current at the kth time point, is a memory kernel of fractional calculus.

[0008] In combination with the first aspect, in another possible implementation manner, the fractional-order measurement equation is: k+1 U OCV,k+1 -U 1,k+1 -U 2,k+1 -R0I k+1 wherein U k+1 is the end voltage of the vanadium redox flow battery at the k+1th time point, U OCV,k+1 is an open-circuit voltage of the vanadium redox flow battery at the k+1th time point, and R0 is an ohmic resistance.

[0009] In combination with the first aspect, in another possible implementation manner, the degree of deviation between the predicted value and the measured value of the vanadium redox flow battery is determined according to wherein is the measured value of the end voltage, is the predicted value of the end voltage; and when the degree of deviation is greater than a deviation threshold, the parameters in the fractional-order state space equation and the fractional-order measurement equation are updated according to wherein θ k is a parameter value of the kth iteration, and J'(θ k) is the partial derivative matrix of the objective function J(θ) with respect to the parameter θ, until the degree of deviation is less than or equal to the deviation threshold.

[0010] In combination with the first aspect, in another possible implementation method, the operating current of the all-vanadium liquid flow battery is adjusted according to the measured value at the first moment and the predicted value at the second moment, including: determining the working scenario of the all-vanadium liquid flow battery according to the direction of the working current at the first moment, wherein, when the direction of the working current at the first moment is flowing into the battery, it indicates that the all-vanadium liquid flow battery is in a charging scenario, and when the direction of the working current is flowing out of the battery, it indicates that the all-vanadium liquid flow battery is in a discharging scenario; determine the adjustment strategy of the working current of the all-vanadium liquid flow battery according to the working scenario.

[0011] In combination with the first aspect, in another possible implementation, when the all-vanadium redox flow battery is in a charging scenario, determining an adjustment strategy for the operating current of the all-vanadium redox flow battery includes: when the terminal voltage measurement value at the first moment is greater than the terminal voltage prediction value at the second moment, and the deviation is greater than the positive deviation safety threshold, according to I k+1 =I k (1-k1) adjusts the operating current of the all-vanadium liquid flow battery, where k1 is the current attenuation gain factor; when the terminal voltage measurement value at the first moment is less than the terminal voltage prediction value at the second moment, and the deviation is greater than the negative deviation safety threshold, according to I k+1 =I k (1+k2) adjusts the operating current of the all-vanadium redox flow battery, where k2 is the current compensation gain factor, and the current attenuation gain factor is greater than the current compensation gain factor; when the state of charge prediction value at the second moment is greater than the state of charge safety threshold, according to Adjust the working current of the all-vanadium redox flow battery, where λ is the attenuation coefficient, η is the threshold proportional factor, and SOC rated is the rated state of charge; when the difference between the discharge capacity measurement value at the first moment and the discharge capacity converted based on the state of charge prediction value exceeds the capacity threshold, Adjust the operating current of the all-vanadium redox flow battery, where γ is the capacity compensation coefficient, Q rated is the rated capacity, Δt is the sampling interval, Q k is the discharge capacity measurement value at the first moment, Q theory ·SOC k+1 The discharge capacity is calculated based on the predicted state of charge value.

[0012] In combination with the first aspect, in another possible implementation, when the all-vanadium redox flow battery is in a discharge scenario, determining an adjustment strategy for the operating current of the all-vanadium redox flow battery includes: when the terminal voltage prediction value at the second moment is less than the discharge termination voltage threshold, adjusting the operating current of the all-vanadium redox flow battery according to I k+1 =I safe-min Adjust the operating current of the all-vanadium redox flow battery, where Isafe-min is a lower limit of a safe discharge current; when a difference between the measured value of the terminal voltage at the first time and the predicted value of the terminal voltage at the second time is greater than an allowed difference threshold of the terminal voltage, the working current of the all-vanadium redox flow battery is adjusted according to I k+1 = I k · (1 + k3 · sign (U k - U k+1 )), wherein k3 is a discharge current adjustment gain factor; when the predicted value of the state of charge at the second time is less than a low state of charge threshold, the working current of the all-vanadium redox flow battery is adjusted according to I , wherein P target is a target output power of the all-vanadium redox flow battery.

[0013] In a second aspect, the present application provides an all-vanadium redox flow battery control device, comprising:

[0014] an acquisition module configured to acquire actual measurement data of the all-vanadium redox flow battery, the actual measurement data comprising a terminal voltage, a working current and a discharge capacity of the all-vanadium redox flow battery at a first time;

[0015] a parameter optimization module configured to perform parameter optimization on a fractional order state space equation and a fractional order measurement equation constructed based on the all-vanadium redox flow battery according to the actual measurement data, the fractional order state space equation being used to describe a dependence relationship of a polarization voltage change on a battery historical state and a non-uniform distribution characteristic of ion diffusion in space, and the fractional order measurement equation being used to convert the dependence relationship and the non-uniform distribution characteristic into an actually measurable terminal voltage signal;

[0016] a prediction module configured to predict a state of charge and a terminal voltage of the all-vanadium redox flow battery at a second time based on the fractional order state space equation, the fractional order measurement equation and the actual measurement data, the second time being a next time of the first time;

[0017] a control module configured to, when a difference between a measured value at the first time and a predicted value at the second time is greater than a preset threshold, adjust a working current of the all-vanadium redox flow battery according to the measured value at the first time and the predicted value at the second time, so as to reduce an error between a measured value at the second time and the predicted value at the second time.

[0018] In order to achieve the above-mentioned purpose, according to a third aspect of the present application, a storage medium is provided, the storage medium comprising a stored program, wherein when the program runs, the device where the storage medium is located performs the all-vanadium redox flow battery control method of the first aspect.

[0019] In order to achieve the above object, according to a fourth aspect of the present application, an electronic device is provided, the device comprising at least one processor, and at least one memory connected with the processor via a bus; wherein the processor and the memory complete mutual communication through the bus; the processor is used to invoke program instructions in the memory to execute the full vanadium redox flow battery control method of the first aspect.

[0020] By means of the above technical solution, the technical solution provided by the present application has at least the following advantages:

[0021] The present application uses a fractional order state space equation to depict the dependence of the polarization voltage on the historical state and the non-uniform characteristics of ion diffusion, and in combination with the measured data of the terminal voltage, working current and discharge capacity at the first time, the state of charge and the terminal voltage at the next time can be more accurately predicted, and the prediction deviation caused by the traditional integer order model due to neglecting the memory effect can be avoided.

[0022] The above description is only a summary of the technical solutions of the present application, in order to more clearly understand the technical means of the present application, the content of the specification can be implemented, and in order to make the above and other purposes, characteristics and advantages of the present application more obvious and easy to understand, the following specific embodiments of the present application are described. BRIEF DESCRIPTION OF DRAWINGS

[0023] By reading the detailed description of the preferred embodiments below, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of illustrating the preferred embodiments and are not considered to be limiting on the present application. Moreover, the same reference symbols are used to represent the same components throughout the drawings. In the drawings:

[0024] Figure 1 A flowchart of a full vanadium redox flow battery control method provided by an embodiment of the present application is shown;

[0025] Figure 2 A schematic diagram of an equivalent circuit model of a full vanadium redox flow battery provided by an embodiment of the present application is shown;

[0026] Figure 3 A schematic diagram of a parameter identification method provided by an embodiment of the present application is shown;

[0027] Figure 4 A structural schematic diagram of a full vanadium redox flow battery control device provided by an embodiment of the present application is shown;

[0028] Figure 5 A structural schematic diagram of an electronic device provided by an embodiment of the present application is shown. DETAILED DESCRIPTION

[0029] Exemplary embodiments of the present application will be described herein below with reference to the accompanying drawings. While exemplary embodiments of the present application are illustrated, it is to be understood that the present application can be carried out in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the present application to those skilled in the art.

[0030] The terms "first", "second", and the like, in the embodiments of the present application, do not have a logically or chronologically dependent relationship, and do not limit the quantity and execution order. It should also be understood that although the following description uses the terms first, second, and the like to describe various elements, these elements should not be limited by the terms. These terms are only used to distinguish one element from another.

[0031] In the embodiments of the present application, the term "at least one" means one or more, and the term "multiple" in the embodiments of the present application means two or more.

[0032] It should also be understood that the term "if" can be interpreted as "when" or "upon" or "in response to a determination" or "in response to detecting". Similarly, the phrase "if it is determined" or "if [a stated condition or event] is detected" can be interpreted as "upon determining" or "in response to determining" or "upon detecting [the stated condition or event]" or "in response to detecting [the stated condition or event]", depending on the context.

[0033] All-vanadium redox flow battery relies on the reversible oxidation-reduction reaction of vanadium ions between the positive and negative electrolytes to realize energy storage and release. Its core mechanism is to realize energy storage and release by different valence state vanadium ions (such as V 2+ / V 3+ , VO 2+ / VO2 +)In the process of charging and discharging, the energy conversion is completed by the electron transfer and ion diffusion. This feature makes it have broad application prospects in the field of long-term stable energy storage such as grid-level energy storage and renewable energy consumption. At present, the control of the all-vanadium redox flow battery is mostly based on the traditional integer order model, which describes the polarization characteristics and dynamic response through integer order elements such as resistance and capacitance. This kind of model has simple structure and low computational complexity, which is convenient for engineering implementation. However, there are complex electrochemical kinetic behaviors in the battery, such as non-uniform mass transfer in porous electrodes, non-ideal transmembrane diffusion of vanadium ions, and memory effect of polarization. These behaviors have non-locality and history dependence. The traditional integer order model cannot accurately capture the gradual attenuation process of the polarization effect and the concentration gradient change of ion diffusion because it uses idealized integer order capacitors and resistors. This leads to insufficient accuracy of state of charge prediction. For example, in the electrochemical impedance spectrum analysis of the equivalent circuit model, the Nyquist curve often deviates from the actual measured semicircular trajectory, which exposes the defect of describing the non-ideal capacitance characteristics of the battery (such as constant phase element behavior), and further makes the state of charge prediction based on the model unable to accurately reflect the real-time remaining power of the battery, affecting the effectiveness of the charging and discharging control strategy. Based on this, the application provides a control method for an all-vanadium redox flow battery.

[0034] Next, the control method for the all-vanadium redox flow battery will be described in detail in conjunction with the drawings. Figure 1 The flowchart of the control method for the all-vanadium redox flow battery provided by the application is shown. Specifically, the following steps are included:

[0035] Step 110, obtaining actual measurement data of the all-vanadium redox flow battery.

[0036] The actual measurement data of the all-vanadium redox flow battery is the core parameter reflecting the real-time operation state of the battery. The present application collects the terminal voltage, working current and discharge capacity of the all-vanadium redox flow battery at the first moment. Among them, the terminal voltage refers to the real-time voltage between the positive and negative electrodes of the battery, which is a comprehensive embodiment of the internal electrochemical reaction, polarization effect and ohmic loss of the battery, and its value is directly related to the state of charge and charging and discharging safety of the battery. For example, the terminal voltage is too high during charging, which may indicate the risk of overcharging, and the terminal voltage is too low during discharging, which may indicate over-discharging or battery performance degradation. The working current represents the current size and direction flowing through the battery, and the positive direction is flowing into the battery (corresponding to the charging scene), and the negative direction is flowing out of the battery (corresponding to the discharging scene). The working current is a direct incentive to drive the internal state change of the battery, and its size will affect the electrochemical reaction rate, heat generation characteristics and energy transmission efficiency. The discharge capacity refers to the actual released electric quantity of the battery in the discharging process, reflecting the actual energy output capability of the battery, which is closely related to the state of charge, electrolyte concentration, electrode active material and other factors. The deviation between the measured value and the predicted value can reveal the battery performance degradation or prediction model misalignment problem. The above measurement data at the first moment is the basis for subsequent state prediction and current control, and provides key input for initialization and deviation calculation of fractional order state space equation.

[0037] Step 120, parameter optimization of the fractional order state space equation and the fractional order measurement equation constructed based on the all-vanadium redox flow battery according to the actual measurement data.

[0038] First, an equivalent circuit model of the all-vanadium redox flow battery as shown in Figure 2 The equivalent circuit model of the all-vanadium redox flow battery includes: a voltage source, an ohmic internal resistance, a polarization resistance and a polarization capacitance. The circuit connection relationship is: the positive electrode of the voltage source is connected in series with the ohmic internal resistance, the first polarization branch composed of the charge transfer polarization resistance and the first polarization capacitance in parallel, and the second polarization branch composed of the concentration polarization resistance and the second polarization capacitance in parallel, and finally connected to the circuit output positive electrode. The negative electrode of the voltage source is directly connected to the circuit output negative electrode.

[0039] The functions of each element in the equivalent circuit model of the all-vanadium redox flow battery will be described below.

[0040] The voltage source is used to represent the open circuit voltage of the all-vanadium redox flow battery (the stable voltage between the positive and negative electrodes of the battery in the open circuit state (i.e. no load, no current through)), which is determined by the state of charge of the battery. The value reflects the thermodynamic equilibrium potential of the internal electrochemical reaction of the battery, which is the benchmark for the output voltage of the battery.

[0041] The ohmic internal resistance is used to reflect the ohmic loss of the battery conduction loop. When the current flows through the ohmic internal resistance, it will follow Ohm's law to generate a voltage drop proportional to the current. This phenomenon directly reflects the instantaneous energy loss characteristics of the battery.

[0042] The polarization resistance is used to describe the polarization effect in the electrochemical reaction, including charge transfer polarization and concentration polarization. In the electrochemical reaction, when the current passes through the electrode-electrolyte interface, due to the transfer of electric charge at the interface (i.e. the transfer of electrons between the electrode and the reactant), a certain resistance (such as an activation energy barrier) needs to be overcome, resulting in the phenomenon that the electrode potential deviates from its equilibrium potential, which is called charge transfer polarization. The ions of the reactant (or product) in the electrolyte near the electrode are insufficient due to the diffusion rate, resulting in a difference between the concentration and the bulk solution concentration, thereby causing the electrode potential to deviate from the equilibrium potential, which is called concentration polarization. Among them, the charge transfer polarization resistance reflects the resistance of the electrode surface electrochemical reaction, and the concentration polarization resistance reflects the resistance of the ion diffusion in the electrolyte, and the two polarization resistances are connected in parallel with the polarization capacitance, which together simulate the dynamic characteristics of the polarization process.

[0043] The polarization capacitance adopts a fractional order capacitor (i.e. a constant phase element CPE), which is different from the traditional integer order capacitor. By virtue of the fractional order characteristics, the non-ideal capacitor behavior inside the battery can be more accurately simulated, and by adjusting the fractional order, the non-semicircular trajectory in the electrochemical impedance spectrum can be fitted, reflecting the memory effect and non-local characteristics of the battery.

[0044] In the equivalent circuit model of the all-vanadium redox flow battery, the combination of the polarization resistance and the polarization capacitance is the core link, and the fractional calculus theory is used to characterize the nonlinear dynamic characteristics of the battery. The ohmic resistance and the voltage source respectively provide the basic resistance voltage division function and the potential reference, and together constitute a complete equivalent circuit model, which provides support for the terminal voltage estimation and parameter identification.

[0045] In order to accurately characterize the dynamic behavior of the equivalent circuit model and realize the quantitative description and prediction of the state of the all-vanadium redox flow battery, based on the topological structure and element characteristics of the above equivalent circuit model and combined with the fractional calculus theory, the fractional order state space equation and the fractional order measurement equation are derived and established, so as to mathematically associate the battery state, input and output, and support the subsequent state of charge estimation and charge and discharge control.

[0046] In the embodiments of the present application, the fractional order state space equation of the all-vanadium redox flow battery is constructed to describe the dynamic evolution law of the battery under discrete time sequence, which provides a mathematical foundation for the subsequent state of charge prediction and charge and discharge control strategy design, and its specific form is as follows:

[0047]

[0048] where U1, U2 are the voltages across the first and second polarization capacitances C1 and C2, respectively, which reflect the accumulated potentials in different polarization processes (e.g., charge transfer polarization, concentration polarization) inside the battery. SOC is the state of charge of the battery, which is a key indicator to measure the ratio of the remaining capacity to the rated capacity, and directly reflects the available energy level of the battery. R1, R2 are the charge transfer polarization resistance and the concentration polarization resistance, respectively, the former mainly corresponds to the resistance of the electrode surface electrochemical reaction, and the latter relates to the resistance of the ion diffusion process in the electrolyte, which collectively describes the impedance characteristics of the electrochemical reaction and mass transfer inside the battery. a, b are the fractional orders, which are different from the traditional integer order model. The fractional order characteristics enable the equation to accurately capture the memory and non-local dynamic behavior of the battery polarization effect, such as the continuous influence of the battery state at past time on the current time. n is the rated discharge capacity of the battery, which is the reference quantity for calculating the state of charge and determines the maximum amount of electricity that the battery can theoretically release. T is the sampling time interval, which is used to discretize the continuous battery dynamic process. k is the working current at time k, which is the input excitation of the battery charging and discharging process and directly drives the changes in the battery internal state. are the memory kernels of fractional calculus. In the fractional order model of battery state evolution, they play the role of "memory carriers". Unlike traditional integer order models that only focus on immediate state correlation, memory kernels use their unique weighted accumulation mechanism to continuously transfer the "past influence" caused by polarization, ion diffusion, and other processes at historical time (from the initial to the previous stage before the current time) to the current state calculation in the form of mathematical weights. For example, when describing the dynamic changes of polarization voltage over time, the memory kernel will adjust the contribution of polarization effects at different historical times according to the fractional order a, b, so that the model can accurately restore the "memory continuity" of non-local dynamic behaviors such as electrochemical reactions and mass transfer inside the battery. The hysteresis effect of charge transfer polarization and the historical accumulation effect of concentration polarization can be accurately represented in the fractional order equation through memory kernels, helping the model to more accurately capture the complex dynamic characteristics of the battery.

[0049] From the overall architecture, the left side of the equation represents the battery state at time k+1, which is the polarization voltage and state of charge at the next time. The right side of the equation can be divided into two parts: the state transition term and the input driving term which jointly describe how the battery state evolves from the current time (time k) to the next time (time k+1).

[0050] The state transition term reflects the inheritance and decay influence of the battery state at the current time on the battery state at the next time. For the transition of U1, the coefficient The fractional order α incorporates the dynamic characteristics of the first polarization branch, describing the memory decay of the charge transfer polarization process. That is, the polarization voltage accumulated at past time will gradually decay and be transmitted to the next time according to this coefficient. The transfer logic of U2 is the same, The second polarization branch describes the dynamic decay of the concentration polarization, reflecting the historical influence of ion diffusion and other processes. The transfer coefficient of SOC is 1, because the state of charge is essentially the accumulation of electric quantity, and the SOC at the current time will be directly transmitted to the next time, and then the change will be corrected by the current-related term.

[0051] The input driving term focuses on the excitation of the working current on the battery state and the persistent influence of the historical state of the battery. It is divided into current direct excitation and historical state memory and respectively describe the charge and discharge excitation of the working current flowing through the polarization branch to the voltages across the first polarization capacitor and the second polarization capacitor. The current injection will change the potential accumulation of the polarization capacitor, and then affect U1 and U2 at the next time. According to the current direction (the current is negative when charging and positive when discharging), combined with the rated capacity, the change of the state of charge is calculated. Simply put, it is the time integral of the current divided by the rated capacity to obtain the increase or decrease of the state of charge. The historical state memory introduces the memory kernel of fractional calculus and By weightedly accumulating the polarization voltage at historical time before k+1 time, the memory effect of the battery is embodied, that is, the polarization state at multiple past times will continuously affect the state evolution at the current time. This is also the key advantage of the fractional order model over the traditional integer order model, which can accurately capture the non-ideal capacitor characteristics and long-term dynamic dependence of the battery.

[0052] The fractional order state space equation of the present application ingeniously combines the physical mechanism of the equivalent circuit model (such as the polarization dynamics of the polarization branch) and the memory of fractional calculus, which not only retains the physical nature of the internal electrochemical reaction and ion transport of the battery, and has a solid mechanism support for the prediction model, but also accurately describes the historical dependence characteristics that the traditional model cannot describe through the fractional order and the memory kernel, solving the complex dynamic problem of the battery polarization process.

[0053] The above clearly shows the fractional order state space equation of the all-vanadium redox flow battery, which is used to describe the dynamic change rule of the internal state of the battery over time, and clearly presents the evolution process of the state variable at discrete time. On this basis, in order to establish the correlation between the external measurable physical quantity (such as the terminal voltage) and the internal state, a fractional order measurement equation needs to be constructed. The role of the fractional order measurement equation is to directly reflect the corresponding relationship between the state variable and the measurement output, and it together with the state space equation constitutes a complete state measurement model. This model ultimately provides a basis for subsequent state estimation (such as state of charge estimation) and charging and discharging control decision based on measurement data, realizing the closed-loop logic from physical signal acquisition to control strategy execution.

[0054] The measurement equation is as follows: U k+1 = U OCV,k+1 - U 1,k+1 - U 2,k+1 - R0I k+1 , wherein U k+1 is the terminal voltage of the all-vanadium redox flow battery at k+1 time, which is the external voltage signal that can be directly measured when the battery outputs or inputs electric energy, reflecting the overall electrical characteristics of the battery. U OCV,k+1 is the open-circuit voltage of the all-vanadium redox flow battery at k+1 time. R0 is the ohmic resistance, which represents the ohmic loss characteristics of the battery conduction loop (such as electrolyte, electrode, separator, etc.), and a voltage drop proportional to the current will be generated when the current passes through.

[0055] The core value of the measurement equation is to correlate the internal state variables U1, U2 described in the fractional order state space equation with the external directly measurable terminal voltage U k+1 .

[0056] In the embodiments of the present application, when the state variables U 1,k , U 2,k , SOC k at k time are known, the internal states U 1,k+1 , U 2,k+1 at k+1 time are predicted by the fractional order state space equation, and then substituted into the measurement equation, the predicted value of the terminal voltage at k+1 time can be calculated. Comparing it with the actually measured terminal voltage can be used as the basis for model parameter identification and state estimation accuracy verification, realizing the closed loop from internal state description to external characteristic verification, supporting the fine management and control of the all-vanadium redox flow battery.

[0057] After obtaining the comparison results of the predicted value and the actually measured value of the terminal voltage through the above process, the deviation information needs to be further converted into the driving force for model optimization. Specifically, based on the difference between the predicted value and the measured value, the objective function for parameter identification can be constructed as follows: wherein U is the measured value of the terminal voltage, is a predicted value of the terminal voltage. When the deviation degree of the measured value of the terminal voltage from the predicted value is greater than a deviation threshold, the terminal voltage is predicted according to the parameters in the fractional order state space equation and the fractional order measurement equation are updated, wherein θ k is a parameter value of the kth iteration, J'(θ k ) is a partial derivative matrix of the objective function J(θ) with respect to the parameter θ, until the deviation degree is less than or equal to the deviation threshold.

[0058] As shown in Figure 3 , the parameters to be identified (Ohmic resistance R0, charge transfer polarization resistance R1, concentration polarization resistance R2, first polarization capacitance C1, second polarization capacitance C2, fractional order orders α, β) are first initialized. Then the actual measurement data (working current I k , terminal voltage U k ) are obtained, the terminal voltage U k+1 at the next time is predicted based on the fractional order state space equation, the fractional order measurement equation and the actual measurement data of the all-vanadium redox flow battery, and the residual error u k -u k+1 is calculated, and then the objective function value J is obtained. Then the convergence is judged, and if |J k+1 -J k | < ε (ε is a convergence threshold value), the optimal parameters are output. If it does not converge, the parameters are updated according to the optimization algorithm, the model output, the residual error and the objective function value are calculated again, and the convergence is judged, and the iteration is repeated until the convergence condition is met, and finally the optimal parameters are obtained.

[0059] This process reversely injects the results of external characteristic verification into the model internal parameter adjustment link, forms a complete closed loop of prediction verification and correction, realizes dynamic mapping from the internal state of the battery to the external characteristics, continuously improves the description accuracy of the model to the actual physical process through data feedback, and provides a key technical path for parameter adaptive update and state accurate estimation of the all-vanadium redox flow battery.

[0060] Step 130, based on the fractional order state space equation, the fractional order measurement equation and the actual measurement data, the state of charge and the terminal voltage of the all-vanadium redox flow battery at the second time are predicted.

[0061] After obtaining the actual measurement data of the terminal voltage, working current and discharge capacity at the first time, the internal state variables of the battery are first calculated by using the fractional order state space equation. The equation introduces the memory kernel of fractional calculus (such as α-order and β-order memory terms), and the historical polarization voltage (U1, U2) before the kth time is included in the current state evolution calculation in the form of weighted accumulation, which reflects the historical dependence of the polarization effect and the non-uniformity of ion diffusion. For example, the polarization voltage U 1，k+1 at the k+1th time is not only related to U1，k and working current I k related, also through the memory core accumulates all historical times before k time U 1，j (j = 1 to k), so as to capture the long-term memory effect of the internal electrochemical reaction of the battery.

[0062] After completing the prediction of the internal state variables (U 1,k+1 , U 2,k+1 , SOC k+1 ), the abstract internal state is further converted into a physically observable terminal voltage signal through the fractional order measurement equation. The measurement equation takes the open circuit voltage U OCV,k+1 as the reference, deducts the polarization voltage (U 1,k+1 , U 2,k+1 ) and Ohmic internal resistance voltage drop (R0I k+1 ), and finally obtains the terminal voltage prediction value U k+1 at k+1 time.

[0063] The present application decouples the thermodynamic properties (open circuit voltage) of the battery from the kinetic properties (polarization process, ohmic loss), both retains the clarity of physical meaning, and through the adjustment ability of fractional order (α, β) to adapt the non-ideal capacitance behavior under different working conditions, such as fitting the constant phase element characteristics of the non-semicircular trajectory in the electrochemical impedance spectrum.

[0064] The whole prediction process forms a closed loop feedback mechanism: the measured data provides the initial boundary conditions for the model, the fractional order equation iteratively updates the state variables through historical data, the measurement equation maps the internal state to the external measurable parameters, and the final output of the state of charge and the terminal voltage prediction value can be directly used for the charge and discharge control decision of the second time (the next time of the first time). Compared with the prediction lag caused by the traditional integer order model ignoring the memory effect, this method significantly improves the timeliness and accuracy of state prediction through the fine description of the battery dynamic characteristics by the fractional order term, especially suitable for complex scenarios with rapid changes in polarization voltage or uneven ion diffusion during charging and discharging.

[0065] Step 140, when the deviation between the measurement value at the first time and the prediction value at the second time is greater than a preset threshold, adjusting the working current of the all-vanadium redox flow battery according to the measurement value at the first time and the prediction value at the second time.

[0066] Since the all-vanadium redox flow battery is affected by complex physical factors such as temperature changes, electrolyte concentration fluctuations, electrode aging, etc. during actual operation, and the fractional order state space equation and the fractional order measurement equation describe the dynamic characteristics based on the ideal conditions of mathematical abstraction, there is inevitably a deviation between the predicted value and the measured value. This deviation not only reflects the battery state estimation error or model parameter misalignment, but also reveals potential operating risks such as overcharging and over-discharging. Therefore, after obtaining the measured value at the first time and the predicted value at the second time according to steps 110 and 130, the measured value at the first time and the predicted value at the second time are compared and analyzed. This cross-time deviation comparison is the core mechanism of discrete control systems. By comparing the measured value at time k with the predicted value at time k+1, the control system can adjust the current at time k+1 in advance to offset the prediction error, achieve dynamic tracking and accurate control of the battery state, and ultimately improve the prediction accuracy of the terminal voltage and state of charge.

[0067] When the deviation between the measured value at the first time and the predicted value at the second time is greater than a preset threshold, the working current of the all-vanadium redox flow battery is adjusted based on the measured value at the first time and the predicted value at the second time, in combination with the working scenario of the all-vanadium redox flow battery.

[0068] The working scenario of the all-vanadium redox flow battery can be determined by the direction of the working current at the first time. Specifically, when the direction of the working current at the first time is flowing into the battery, it indicates that external energy (such as a charger or a power grid) is inputting electrical energy into the battery, and at this time, the electrochemical reaction inside the battery is dominated by the energy storage process, corresponding to the charging scenario. For example, during the valley electricity period of the power grid, the battery is charged through an external power source, and the current flows from the positive electrode of the external power source into the positive electrode of the battery, flows to the negative electrode through the internal electrolyte and electrode, and then returns to the negative electrode of the power source through the external circuit, forming a charging loop. At this time, the physical representation of the current direction is completely consistent with the charging scenario.

[0069] Conversely, when the direction of the working current at the first time is flowing out of the battery, it means that the electrical energy stored inside the battery is being released to the external load, and the electrochemical reaction is dominated by the energy release process, corresponding to the discharging scenario. For example, during the peak electricity period of the power grid, the battery supplies power to the user load, and the current flows out of the positive electrode of the battery, consumes energy through the load, and then returns to the negative electrode of the battery, forming a discharging loop. At this time, the direction of the current flowing out of the battery directly reflects the working state of the battery as an energy source outputting power to the outside.

[0070] The adjustment strategy when the all-vanadium redox flow battery is in the charging scenario is described below.

[0071] When the first time terminal voltage measurement value is greater than the second time terminal voltage prediction value, and the deviation is greater than the positive deviation safety threshold, it indicates that the actual performance of the current terminal voltage of the battery exceeds the model expectation, and there may be overcharge risk or abnormal enhancement of polarization effect. This difference may be caused by the rapid rise of the battery state of charge (SOC) near full charge, the sudden decrease of the internal ohmic resistance, or the failure of the fractional order model to accurately capture the dynamic changes of the polarization process (such as the decrease of the charge transfer polarization resistance). At this time, the running state of the battery needs to be intervened by adjusting the working current to avoid the safety problems such as electrolyte decomposition and electrode side reaction caused by continuous voltage out-of-limit, and to trigger the model parameter identification process to optimize the prediction accuracy. At this time, the current working current is adjusted by introducing a current attenuation gain factor k1. That is, according to I k+1 = I k ·(1-k1) to adjust the working current of the all-vanadium redox flow battery. In other words, when the measured terminal voltage value is significantly higher than the predicted value, it reflects that the polarization voltage rising speed of the battery under the current current exceeds the expectation, or the state of charge is close to the full charge state. By reducing the charging current, the electrochemical reaction rate can be slowed down, and the polarization effect can be further inhibited.

[0072] When the first time terminal voltage measurement value is less than the second time terminal voltage prediction value, and the deviation is greater than the negative deviation safety threshold, it indicates that the actual output capability of the battery is weaker than the model expectation, and there may be over-discharge risk, internal performance degradation or underestimation of the model to the polarization effect. This difference may be caused by the rapid drop of the battery state of charge (SOC) near empty, the significant increase of the ohmic resistance (such as the decrease of the electrolyte concentration or the electrode aging), or the failure of the fractional order model to accurately reflect the dynamic changes of the concentration polarization (such as the increase of the ion diffusion resistance). At this time, the working current is dynamically adjusted by introducing a current compensation gain factor k2, that is, according to I k+1 = I k ·(1+k2) to adjust the working current of the all-vanadium redox flow battery, so as to prevent the continuous deviation of the voltage from the safety interval and cause irreversible damage, and at the same time, to improve the tracking ability of the model parameters to the true state of the battery. In other words, when the measured terminal voltage value is significantly lower than the predicted value, it reflects that the internal ohmic resistance of the battery increases, the ion diffusion rate decreases, or the active material concentration is insufficient. By reducing the charging current, the polarization effect and ohmic loss in the battery can be reduced, the available time of the battery under the current working condition can be prolonged, and irreversible damage caused by over-discharge can be avoided.

[0073] In the embodiments of the present application, positive bias (measured value greater than predicted value) is generally related to overcharge risk, which requires a rapid response to protect the battery. Negative bias (measured value less than predicted value) reflects the performance degradation or energy depletion trend of the battery, which needs to balance system efficiency and safety while avoiding over-discharge. Therefore, to achieve differentiated risk response, the current attenuation gain factor set in the present application is greater than the current compensation gain factor, ensuring that the current can be attenuated more quickly in the overcharge scenario, while adjusting the current in a more moderate manner in the negative bias scenario, taking into account safety protection and energy utilization efficiency.

[0074] When the state of charge predicted value at the second time is greater than the state of charge safety threshold, it indicates that the remaining capacity of the all-vanadium redox flow battery has approached or exceeded the allowed maximum energy storage upper limit, and there is an overcharge risk. This situation can cause imbalance of vanadium ion concentration in the electrolyte, side reactions (such as water decomposition) of the electrode, or an increase in internal pressure of the battery, thereby affecting the battery life and even causing safety hazards. At this time, the state of charge needs to be further inhibited from rising by dynamically adjusting the working current, that is, according to Adjusting the working current of the all-vanadium redox flow battery, wherein λ is an attenuation coefficient, η is a threshold proportion factor, SOC rated is the rated state of charge. Since SOC k+1 / SOC rated -η relates the actual state of charge to the safety boundary and quantifies the degree of overcharge risk. The exponential attenuation form flexibly controls the current adjustment rate through the attenuation coefficient, and can adjust the working current in a flexible manner that adapts to the electrochemical characteristics of the all-vanadium redox flow battery, thereby intervening from the source of the current input, slowing down the imbalance of vanadium ion concentration in the electrolyte, inhibiting electrode side reactions (such as water decomposition), protecting the safety of the battery, prolonging the service life, and making the regulation of overcharge risk both effective and consistent with the operation rules of the battery.

[0075] When the difference between the discharge capacity measured value at the first time and the discharge capacity converted based on the state of charge predicted value exceeds the capacity threshold, it indicates that performance degradation occurs inside the battery, such as loss of electrode active material, abnormal vanadium ion concentration in the electrolyte (due to leakage or side reactions), causing the actual output capacity to deviate from the prediction. Since Q theory ·SOC k+1 is the discharge capacity converted based on the state of charge predicted value, Q k is the discharge capacity measured value Q rated at the first time, Q The difference between the discharge capacity measured value at the first time and the discharge capacity converted based on the state of charge predicted value can be quantified, combined with the capacity compensation coefficient γ. According to Adjust the operating current of the all-vanadium liquid flow battery to compensate for the capacity output differences caused by battery performance fluctuations, adapt the current to the actual state of the battery, maintain stable battery energy output, and at the same time suppress risks such as over-discharge caused by deviations, ensuring battery safety and efficient operation.

[0076] The following describes the adjustment strategy for the all-vanadium redox flow battery in a discharge scenario.

[0077] When the terminal voltage prediction value at the second moment is less than the discharge termination voltage threshold, it indicates that the terminal voltage of the all-vanadium liquid flow battery is about to fall outside the safe operating range under the current discharge condition, and there is a risk of over-discharge. This phenomenon may be due to the battery state of charge (SOC) being close to the discharge limit, insufficient electrolyte concentration resulting in a decrease in ion conductivity, or electrode aging causing a significant increase in internal resistance, resulting in rapid voltage decay. Over-discharge can cause irreversible electrode damage (such as active material shedding), degradation of electrolyte components (such as excessive concentration of low-valent vanadium ions), and even cause a sharp deterioration in battery polarization characteristics, affecting cycle life. At this time, according to I k+1 =I safe-min Adjust the operating current of the all-vanadium redox flow battery, where I safe-min is the lower limit of safe discharge current. By forcibly limiting the current working current to I safe-min , can directly reduce the polarization effect and ohmic loss inside the battery, slowing down the terminal voltage drop rate. Specifically, the larger the discharge current, the faster the active material is consumed per unit time, and the superposition of the ohmic internal resistance voltage drop and the polarization voltage will accelerate the voltage drop. safe-min As a pre-set safety threshold, it can not only ensure that the battery maintains basic discharge function in the low-risk range (such as meeting the system's short-term emergency power supply needs), but also buy time for state of charge estimation correction and electrolyte circulation system adjustment. For example, if the battery's predicted voltage hits the bottom due to state of charge estimation error, it switches to I safe-min After the actual depth of discharge slows down, the model can be corrected using real-time measurement data to avoid actual over-discharge caused by misjudgment. If electrode aging or electrolyte degradation causes increased internal resistance, low current operation can reduce the yield of side reactions, slow the loss rate of active materials, and extend the battery's usable time in critical states. This adjustment essentially cuts off the risk conduction path through hard current limiting, controlling the discharge process within the safety boundaries allowed by the battery's physical properties, achieving emergency blocking of over-discharge risks and maintaining system stability.

[0078] When the terminal voltage measurement value at the first time deviates from the terminal voltage prediction value at the second time by more than the terminal voltage allowable deviation threshold, it indicates that the physical and chemical processes inside the battery have changed significantly, for example, when the state of charge is close to the full charge or empty extreme value, the polarization voltage will produce a nonlinear jump due to the sudden change of the electrochemical reaction rate; the sudden rise or drop of the electrolyte temperature will change the ion diffusion coefficient and the charge transfer rate, causing the deviation of the concentration polarization and the activation polarization voltage from the model expectation; the electrode interface aging may suddenly increase (such as electrode surface passivation) or decrease (such as active material shedding leading to contact area change), thereby causing a significant difference between the measured value and the predicted value of the terminal voltage. At this time, the working current of the all-vanadium redox flow battery is adjusted according to I k+1 =I k ·(1+k3·sign(U k -U k+1 )) where sign(U k -U k+1 ) can quickly identify the deviation direction (positive deviation corresponds to overcharge risk, negative deviation corresponds to overdischarge risk), and the discharge current adjustment gain factor k3 drives the current to be dynamically adjusted in proportion according to the deviation direction: if it is an overcharge trend (the measured value is greater than the predicted value), the sign function outputs positive, and the current is adjusted by 1+k3 to achieve attenuation, thereby inhibiting the continuous rise of the voltage; if it is an overdischarge trend (the measured value is less than the predicted value), the sign function outputs negative, and the current is adjusted by 1-k3 (such as attenuating the discharge current), thereby avoiding the continuous drop of the voltage. This adjustment method does not require complex calculation and can quickly respond to changes in the internal state of the battery. By directly intervening in the size of the current, it can suppress the overcharge and overdischarge risks from the source of energy input / output, adapt to the voltage deviation caused by the physical and chemical process changes, and maintain the basic stability of the system energy interaction while ensuring the safety of the terminal voltage.

[0079] When the state of charge prediction value at the second time is less than the low state of charge threshold, it indicates that the remaining releasable electric quantity of the all-vanadium redox flow battery has approached the lower limit of safe discharge, and if the current high-power output is continued, it is easy to cause overdischarge risk and damage the electrode structure and accelerate the electrolyte degradation. At this time, the working current of the all-vanadium redox flow battery is adjusted according to I where P target is the target output power of the all-vanadium redox flow battery. The principle is that the target output power is a reasonable power reference under the system demand and the battery safety constraint, and by combining the terminal voltage prediction value at the second time, the working current that adapts to the current low state of charge is calculated through the correlation between power and voltage, which not only guarantees the basic demand of the system for power, but also limits the overdischarge caused by excessive current, so that the battery can output energy in a safer and more stable way in the low state of charge interval, delay the further drop of the state of charge, and at the same time reserve a buffer space for charging or system energy dispatching adjustment, thereby maintaining the performance of the battery throughout the life cycle and the reliability of the system operation.

[0080] In summary, the application builds a dynamic model of the all-vanadium redox flow battery through a fractional order state space equation and a measurement equation, realizes accurate prediction of the state of charge and the terminal voltage in combination with multi-dimensional measured data, and forms a closed-loop control through a differentiated current adjustment strategy of the charging and discharging scene. The method not only solves the deficiency of the traditional integer order model in describing the polarization effect and ion diffusion through the memory and non-local characteristics of fractional calculus, but also improves the adaptability of the model to battery aging, working condition fluctuations and other actual scenes through a parameter iterative optimization mechanism.

[0081] It can be understood that, in order to realize the functions in the above-mentioned embodiments, the computer device comprises corresponding hardware structures and / or software modules for executing various functions. Those skilled in the art should easily realize that, in combination with the units and method steps of the examples described in the embodiments disclosed in the present application, the present application can be realized in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the form of hardware or computer software driven hardware depends on the specific application scenario and design constraints of the technical solution.

[0082] Further, as an implementation of the method embodiment described above Figure 1 As an implementation of the method embodiment described above Figure 4 As an implementation of the method embodiment described above

[0083] The acquisition module 410 is configured to acquire actual measurement data of the all-vanadium redox flow battery, and the actual measurement data comprises a terminal voltage, a working current and a discharging capacity of the all-vanadium redox flow battery at a first time point.

[0084] The parameter optimization module 420 is configured to perform parameter optimization on a fractional order state space equation and a fractional order measurement equation constructed based on the all-vanadium redox flow battery according to the actual measurement data. The fractional order state space equation is used to describe a dependence relationship of a polarization voltage change on a historical state of the battery and a non-uniform distribution characteristic of ion diffusion in space, and the fractional order measurement equation is used to convert the dependence relationship and the non-uniform distribution characteristic into an actually measurable terminal voltage signal.

[0085] The prediction module 430 is configured to predict a state of charge and a terminal voltage of the all-vanadium redox flow battery at a second time point based on the fractional order state space equation, the fractional order measurement equation and the actual measurement data. The second time point is a next time point of the first time point.

[0086] The control module 440 is configured to adjust the working current of the all-vanadium redox flow battery according to the measurement value at the first time and the prediction value at the second time when the deviation between the measurement value at the first time and the prediction value at the second time is greater than the preset threshold, so as to reduce the error between the measurement value at the second time and the prediction value at the second time.

[0087] Further, as shown in Figure 4 , the fractional order state space equation is: Wherein, U1 and U2 are voltages across the first polarization capacitor C1 and the second polarization capacitor C2 respectively, SOC is the battery state of charge, R1 and R2 are charge transfer polarization resistance and concentration polarization resistance respectively, α and β are fractional order degrees, Q n is the rated discharge capacity of the battery, T is a sampling time interval, I k is the working current at the kth time, is the memory kernel of the fractional order calculus.

[0088] Further, as shown in Figure 4 , the fractional order measurement equation is: U k+1 = U OCV,k+1 -U 1,k+1 -U 2,k+1 -R0I k+1 , wherein, U k+1 is the terminal voltage of the all-vanadium redox flow battery at the k+1th time, U OCV,k+1 is the open circuit voltage of the all-vanadium redox flow battery at the k+1th time, and R0 is the ohmic resistance.

[0089] Further, as shown in Figure 4 , the parameter optimization module 420 is specifically configured to determine the deviation degree between the prediction value and the measurement value of the all-vanadium redox flow battery according to , wherein, is the measurement value of the terminal voltage, is the prediction value of the terminal voltage; when the deviation degree is greater than the deviation threshold, update the parameters in the fractional order state space equation and the fractional order measurement equation according to , wherein, θ k is the parameter value of the kth iteration, J'(θ k ) is the partial derivative matrix of the objective function J(θ) with respect to the parameter θ, until the deviation degree is less than or equal to the deviation threshold.

[0090] Further, as shown in Figure 4 , the control module 440 is specifically configured to determine the working scenario of the all-vanadium redox flow battery according to the direction of the working current at the first time, wherein when the direction of the working current at the first time is flowing into the battery, it indicates that the all-vanadium redox flow battery is in the charging scenario, and when the direction of the working current is flowing out of the battery, it indicates that the all-vanadium redox flow battery is in the discharging scenario; determine the adjustment strategy of the working current of the all-vanadium redox flow battery according to the working scenario.

[0091] Further, such as Figure 4 As shown, the control module 440 is specifically used for, when the all-vanadium liquid flow battery is in a charging scenario, when the terminal voltage measurement value at the first moment is greater than the terminal voltage prediction value at the second moment, and the deviation is greater than the positive deviation safety threshold, according to I k+1 =I k (1-k1) adjusts the operating current of the all-vanadium liquid flow battery, where k1 is the current attenuation gain factor; when the terminal voltage measurement value at the first moment is less than the terminal voltage prediction value at the second moment, and the deviation is greater than the negative deviation safety threshold, according to I k+1 =I k (1+k2) adjusts the operating current of the all-vanadium redox flow battery, where k2 is the current compensation gain factor, and the current attenuation gain factor is greater than the current compensation gain factor; when the state of charge prediction value at the second moment is greater than the state of charge safety threshold, according to Adjust the working current of the all-vanadium redox flow battery, where λ is the attenuation coefficient, η is the threshold proportional factor, and SOC rated is the rated state of charge; when the difference between the discharge capacity measurement value at the first moment and the discharge capacity converted based on the state of charge prediction value exceeds the capacity threshold, Adjust the operating current of the all-vanadium redox flow battery, where γ is the capacity compensation coefficient, Q rated is the rated capacity, Δt is the sampling interval, Q k is the discharge capacity measurement value at the first moment, Q theory ·SOC k+1 The discharge capacity is calculated based on the predicted state of charge value.

[0092] Further, such as Figure 4 As shown, the control module 440 is specifically used to, when the all-vanadium liquid flow battery is in a discharge scenario, when the terminal voltage prediction value at the second moment is less than the discharge termination voltage threshold, according to I k+1 =I safe-min Adjust the operating current of the all-vanadium redox flow battery, where I safe-min is the lower limit of the safe discharge current; when the difference between the terminal voltage measurement value at the first moment and the terminal voltage prediction value at the second moment is greater than the terminal voltage allowable deviation threshold, according to I k+1 =I k ·(1+k3·sign(U k -U k+1 )) adjust the working current of the all-vanadium liquid flow battery, wherein k3 is the discharge current adjustment gain factor; when the state of charge prediction value at the second moment is less than the low state of charge threshold, according to Adjust the working current of the all-vanadium redox flow battery, where P target is the target output power of the all-vanadium redox flow battery.

[0093] Optionally, the all-vanadium redox flow battery control device can be an electronic device with data processing capability, or a functional module in the electronic device, which is not limited.

[0094] For example, the electronic device can be a server, which can be a single server, or a server cluster composed of multiple servers. For another example, the electronic device can be a terminal device such as a mobile phone, a tablet computer, a desktop computer, a laptop computer, a handheld computer, a notebook computer, an Ultra-mobile Personal Computer (UMPC), a netbook, a cellular phone, a Personal Digital Assistant (PDA), an Augmented Reality (AR) device, a Virtual Reality (VR) device, and the like. For another example, the electronic device can also be a video recording device, a video monitoring device, and the like. The specific form of the electronic device is not specially limited in the present application.

[0095] The following takes an example that the all-vanadium redox flow battery control device is an electronic device, as shown in Figure 5 , which is a hardware structure of an electronic device 500 provided by the present application. Figure 5

[0096] As shown in Figure 5 , the electronic device 500 includes a processor 510, a communication line 520, and a communication interface 530.

[0097] Optionally, the electronic device 500 can further include a memory 540. The processor 510, the memory 540, and the communication interface 530 can be connected through the communication line 520.

[0098] The processor 510 can be a Central Processing Unit (CPU), a general-purpose processor, a Network Processor (NP), a Digital Signal Processing (DSP), a microprocessor, a microcontroller, a Programmable Logic Device (PLD), or any combination thereof. The processor 510 can also be any other device with processing function, such as a circuit, a device, or a software module, which is not limited.

[0099] In an example, the processor 510 can include one or more CPUs, such as the CPU0 and the CPU1 in Figure 5 . ​

[0100] As an optional implementation, the electronic device 500 includes multiple processors, for example, in addition to the processor 510, the processor 570 can also be included. The communication line 520 is used to transmit information between the components included in the electronic device 500.

[0101] The communication interface 530 is used to communicate with other devices or other communication networks. The other communication network can be an Ethernet, a Radio Access Network (RAN), a Wireless Local Area Networks (WLAN), etc. The communication interface 530 can be a module, a circuit, a transceiver or any device capable of realizing communication.

[0102] The memory 540 is used to store instructions. The instructions can be a computer program.

[0103] The memory 540 can be a Read-only Memory (ROM) or other types of static storage devices that can store static information and / or instructions, or can be a Random Access Memory (RAM) or other types of dynamic storage device that can store information and / or instructions, or can be an Electrically Erasable Programmable Read-Only Memory (EEPROM), a Compact Disc Read-Only Memory (CD-ROM) or other optical disk storage, a magnetic disk storage medium or other magnetic storage device, etc., without limitation.

[0104] It should be noted that the memory 540 can exist independently of the processor 510, or can be integrated with the processor 510. The memory 540 can be used to store instructions or program codes or some data, etc. The memory 540 can be located in the electronic device 500 or outside the electronic device 500, without limitation.

[0105] The processor 510 is used to execute the instructions stored in the memory 540 to realize the communication method provided by the embodiments described below. For example, when the electronic device 500 is a terminal or a chip in the terminal, the processor 510 can execute the instructions stored in the memory 540 to realize the steps performed by the sending end in the embodiments described below.

[0106] As an optional implementation, the electronic device 500 further includes an output device 530 and an input device 560. The output device 530 can be a display screen, a speaker, or the like, which can output data of the electronic device 500 to a user. The input device 560 can be a keyboard, a mouse, a microphone, or the like, which can input data to the electronic device 500.

[0107] It should be noted that, Figure 5 The structure shown in the figure does not constitute a limitation on the electronic device, except Figure 5 In addition to the components shown, the electronic device can include more or fewer components than shown, or combine some components, or different arrangement of components.

[0108] The all-vanadium redox flow battery control device and application scenarios described in the embodiments of the present application are used to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art can know that, with the evolution of the all-vanadium redox flow battery control device and the appearance of new service scenarios, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0109] The embodiments of the present application provide a storage medium having a program stored thereon, which is executed by a processor to implement the all-vanadium redox flow battery control method.

[0110] The present application also provides a computer program product adapted to execute a program that initializes the following method steps when executed on a data processing device: obtaining actual measurement data of the all-vanadium redox flow battery, the actual measurement data including the terminal voltage, the working current and the discharge capacity of the all-vanadium redox flow battery at a first time; performing parameter optimization on the fractional order state space equation and the fractional order measurement equation constructed based on the all-vanadium redox flow battery according to the actual measurement data, the fractional order state space equation being used to describe the dependence relationship of the polarization voltage change on the battery historical state and the non-uniform distribution characteristics of ion diffusion in space, and the fractional order measurement equation being used to convert the dependence relationship and the non-uniform distribution characteristics into the terminal voltage signal that can be actually measured; predicting the state of charge and the terminal voltage of the all-vanadium redox flow battery at a second time based on the fractional order state space equation, the fractional order measurement equation and the actual measurement data, the second time being the next time of the first time; and adjusting the working current of the all-vanadium redox flow battery when the measurement value at the first time and the prediction value at the second time to reduce the error between the measurement value at the second time and the prediction value at the second time.

[0111] Further, the fractional order state space equation is: wherein U1 and U2 are the voltages across the first polarization capacitor C1 and the second polarization capacitor C2 respectively, SOC is the state of charge of the battery, R1 and R2 are the charge transfer polarization resistance and the concentration polarization resistance respectively, and α and β are the fractional order orders, and Q is the charge.n is the rated discharge capacity of the battery, T is the sampling time interval, I k is the operating current at time k, is the memory kernel of the fractional calculus.

[0112] Further, the fractional measurement equation is: U k+1 = U OCV,k+1 - U 1,k+1 - U 2,k+1 - R0I k+1 , wherein, U k+1 is the terminal voltage of the all-vanadium redox flow battery at time k+1, U OCV,k+1 is the open circuit voltage of the all-vanadium redox flow battery at time k+1, and R0 is the ohmic resistance.

[0113] Further, the deviation degree between the predicted value and the measured value of the all-vanadium redox flow battery is determined according to , wherein, is the measured value of the terminal voltage, is the predicted value of the terminal voltage; when the deviation degree is greater than a deviation threshold, the parameters in the fractional state space equation and the fractional measurement equation are updated according to , wherein, θ k is the parameter value of the kth iteration, and J'(θ k ) is the partial derivative matrix of the objective function J(θ) with respect to the parameter θ, until the deviation degree is less than or equal to the deviation threshold.

[0114] Further, the working scenario of the all-vanadium redox flow battery is determined according to the direction of the operating current at the first time, wherein when the direction of the operating current at the first time is flowing into the battery, it indicates that the all-vanadium redox flow battery is in a charging scenario, and when the direction of the operating current is flowing out of the battery, it indicates that the all-vanadium redox flow battery is in a discharging scenario; the adjustment strategy of the operating current of the all-vanadium redox flow battery is determined according to the working scenario.

[0115] Further, when the all-vanadium redox flow battery is in the charging scenario, the adjustment strategy of the operating current of the all-vanadium redox flow battery is determined, including: when the measured value of the terminal voltage at the first time is greater than the predicted value of the terminal voltage at the second time, and the deviation is greater than a positive deviation safety threshold, the operating current of the all-vanadium redox flow battery is adjusted according to I k+1 = I k ·(1-k1), wherein k1 is a current attenuation gain factor; when the measured value of the terminal voltage at the first time is less than the predicted value of the terminal voltage at the second time, and the deviation is greater than a negative deviation safety threshold, the operating current of the all-vanadium redox flow battery is adjusted according to I k+1 = I k ·(1+k2), wherein k2 is a current compensation gain factor, and the current attenuation gain factor is greater than the current compensation gain factor; when the predicted value of the state of charge at the second time is greater than a state of charge safety threshold, the operating current of the all-vanadium redox flow battery is adjusted according to adjusting the operating current of the all-vanadium redox flow battery, wherein λ is an attenuation coefficient, η is a threshold proportion factor, SOC rated is a rated capacity, Δt is a sampling interval, Q adjusting the operating current of the all-vanadium redox flow battery, wherein γ is a capacity compensation coefficient, Q rated is a rated capacity, Δt is a sampling interval, Q k is a discharge capacity measurement value at a first time, Q theory · SOC k+1 is a discharge capacity converted based on the state of charge prediction value.

[0116] Further, when the all-vanadium redox flow battery is in a discharge scenario, a strategy for adjusting the operating current of the all-vanadium redox flow battery is determined, including: when a terminal voltage prediction value at a second time is less than a discharge termination voltage threshold, adjusting the operating current of the all-vanadium redox flow battery according to I k+1 = I safe-min adjusting the operating current of the all-vanadium redox flow battery, wherein I safe-min is a safe discharge current lower limit; when a terminal voltage measurement value at a first time and a terminal voltage prediction value at a second time deviate by more than a terminal voltage allowable deviation threshold, adjusting the operating current of the all-vanadium redox flow battery according to I k+1 = I k · (1+k3·sign(U k -U k+1 )) adjusting the operating current of the all-vanadium redox flow battery, wherein k3 is a discharge current adjustment gain factor; when a state of charge prediction value at a second time is less than a low state of charge threshold, adjusting the operating current of the all-vanadium redox flow battery according to I adjusting the operating current of the all-vanadium redox flow battery, wherein P target is a target output power of the all-vanadium redox flow battery.

[0117] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as combinations of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus generate a means for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 The flow or multiple flows and / or blocks Figure 1 The device that implements the functions specified in the flow or multiple flows and / or blocks.

[0118] In one typical configuration, the device includes one or more processors (CPUs), memory, and a bus. The device can also include input / output interfaces, network interfaces, and the like.

[0119] The memory can include non-persistent memory, Random Access Memory (RAM), and / or non-volatile memory, such as Read Only Memory (ROM) or flash memory, among others, embodied in computer-readable media. The memory includes at least one memory chip.

[0120] Computer-readable media includes permanent and non-permanent, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital versatile disc (DVD), or other optical storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer-readable media does not include transitory media, such as modulated data signals and carrier waves.

[0121] It should also be noted that the terms "comprising," "including," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements in the list, but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without limitation, an element preceded by "comprises a" does not, without more constraints, foreclose the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0122] Those skilled in the art will appreciate that embodiments of the present application can be devised for use with various computer system configurations, including hand-held devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers and the like. Embodiments of the present application can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules can be located in both local and remote memory storage devices.

[0123] The above merely provides an example of the present application, and is not intended to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall fall into the scope of claims of the present application.

Claims

1. A method for controlling an all-vanadium redox flow battery, characterized in that: The method comprises: Acquiring actual measurement data of the all-vanadium redox flow battery, wherein the actual measurement data includes a terminal voltage, an operating current, and a discharge capacity of the all-vanadium redox flow battery at a first moment; Optimizing parameters of a fractional-order state-space equation and a fractional-order measurement equation constructed based on the all-vanadium redox flow battery according to the actual measurement data, wherein the fractional-order state-space equation is used to describe the dependence of the polarization voltage change on the battery's historical state and the spatially non-uniform distribution characteristics of ion diffusion, and the fractional-order measurement equation is used to convert the dependence and the non-uniform distribution characteristics into a terminal voltage signal that can be actually measured; Predicting the state of charge and terminal voltage of the all-vanadium redox flow battery at a second moment based on the fractional-order state-space equation, the fractional-order measurement equation, and the actual measurement data, where the second moment is a moment subsequent to the first moment; When the deviation between the measured value at the first moment and the predicted value at the second moment is greater than a preset threshold, the operating current of the all-vanadium liquid flow battery is adjusted according to the measured value at the first moment and the predicted value at the second moment to reduce the error between the measured value at the second moment and the predicted value at the second moment.

2. The method according to claim 1, characterized in that The fractional-order state-space equation is: Among them, U1 and U2 are the voltages across the first polarized capacitor C1 and the second polarized capacitor C2, SOC is the battery state of charge, R1 and R2 are the charge transfer polarization resistor and concentration polarization resistor, α and β are fractional orders, and Q n is the rated discharge capacity of the battery, T is the sampling time interval, I k is the working current at time k, is the memory kernel of fractional calculus.

3. The method according to claim 2, characterized in that The fractional-order measurement equation is: U k+1 =U OCV,k+1 -U 1,k+1 -U 2,k+1 -ROI k+1 Among them, U k+1 is the terminal voltage of the all-vanadium redox flow battery at time k+1, U OCV,k+1 is the open circuit voltage of the all-vanadium redox flow battery at time k+1, and R0 is the ohmic internal resistance.

4. The method according to claim 1, wherein Parameter optimization is performed on a fractional-order state space equation and a fractional-order measurement equation constructed based on the all-vanadium redox flow battery according to the actual measurement data, including: according to Determine the degree of deviation between the predicted and measured values ​​of the all-vanadium redox flow battery, where is the measured value of the terminal voltage, is the predicted value of the terminal voltage; When the deviation degree is greater than the deviation threshold, Update the parameters in the fractional-order state space equation and the fractional-order measurement equation, where θ k is the parameter value of the kth iteration, J′(θ k ) is the partial derivative matrix of the objective function J(θ) with respect to the parameter θ, until the degree of deviation is less than or equal to the deviation threshold.

5. The method according to claim 1, wherein Adjusting the operating current of the all-vanadium redox flow battery according to the measured value at the first moment and the predicted value at the second moment includes: Determining an operating scenario of the all-vanadium redox flow battery according to the direction of the operating current at the first moment, wherein when the direction of the operating current at the first moment is flowing into the battery, it indicates that the all-vanadium redox flow battery is in a charging scenario, and when the direction of the operating current is flowing out of the battery, it indicates that the all-vanadium redox flow battery is in a discharging scenario; An adjustment strategy for the operating current of the all-vanadium redox flow battery is determined according to the operating scenario.

6. The method according to claim 5, characterized in that When the all-vanadium redox flow battery is in a charging scenario, determining an adjustment strategy for the operating current of the all-vanadium redox flow battery includes: When the terminal voltage measurement value at the first moment is greater than the terminal voltage prediction value at the second moment, and the deviation is greater than the positive deviation safety threshold, according to I k+1 =I k (1-k1) adjusting the operating current of the all-vanadium redox flow battery, wherein k1 is the current attenuation gain factor; When the terminal voltage measurement value at the first moment is less than the terminal voltage prediction value at the second moment, and the deviation is greater than the negative deviation safety threshold, according to I k+1 =I k (1+k2) adjusting the operating current of the all-vanadium redox flow battery, wherein k2 is a current compensation gain factor, and the current attenuation gain factor is greater than the current compensation gain factor; When the state of charge prediction value at the second moment is greater than the state of charge safety threshold, Adjust the working current of the all-vanadium redox flow battery, where λ is the attenuation coefficient, η is the threshold proportional factor, and SOC rated is the rated state of charge; When the difference between the discharge capacity measurement value at the first moment and the discharge capacity calculated based on the state of charge prediction value exceeds the capacity threshold, Adjust the operating current of the all-vanadium redox flow battery, where γ is the capacity compensation coefficient, Q rated is the rated capacity, Δt is the sampling interval, Q k is the discharge capacity measurement value at the first moment, Q theory ·SOC k+1 The discharge capacity is calculated based on the predicted state of charge value.

7. The method according to claim 5, characterized in that When the all-vanadium redox flow battery is in a discharge scenario, determining an adjustment strategy for the operating current of the all-vanadium redox flow battery includes: When the terminal voltage prediction value at the second moment is less than the discharge termination voltage threshold, according to I k+1 =I safe-min Adjust the operating current of the all-vanadium redox flow battery, wherein I safe-min It is the lower limit of safe discharge current; When the difference between the terminal voltage measurement value at the first moment and the terminal voltage prediction value at the second moment is greater than the terminal voltage allowable deviation threshold, according to I k+1 =I k ·(1+k3·sign(U k -U k+1 )) adjusting the operating current of the all-vanadium redox flow battery, wherein k3 is a discharge current adjustment gain factor; When the state of charge prediction value at the second moment is less than the low state of charge threshold, Adjust the operating current of the all-vanadium redox flow battery, wherein P target is the target output power of the all-vanadium redox flow battery.

8. A vanadium redox flow battery control device, characterized in that: The device comprises: an acquisition module, configured to acquire actual measurement data of the all-vanadium redox flow battery, wherein the actual measurement data includes a terminal voltage, an operating current, and a discharge capacity of the all-vanadium redox flow battery at a first moment; a parameter optimization module for performing parameter optimization on a fractional-order state-space equation and a fractional-order measurement equation constructed based on the all-vanadium redox flow battery according to the actual measurement data, wherein the fractional-order state-space equation is used to describe the dependence of the polarization voltage change on the battery's historical state and the spatially non-uniform distribution characteristics of ion diffusion, and the fractional-order measurement equation is used to convert the dependence and the non-uniform distribution characteristics into a terminal voltage signal that can be actually measured; a prediction module, configured to predict the state of charge and terminal voltage of the all-vanadium redox flow battery at a second moment based on the fractional-order state-space equation, the fractional-order measurement equation, and the actual measurement data, where the second moment is a moment subsequent to the first moment; A control module is configured to adjust the operating current of the all-vanadium liquid flow battery according to the measured value at the first moment and the predicted value at the second moment when the deviation between the measured value at the first moment and the predicted value at the second moment is greater than a preset threshold, so as to reduce the error between the measured value at the second moment and the predicted value at the second moment.

9. A storage medium, characterized in that: The storage medium includes a stored program, wherein when the program is executed, the device where the storage medium is located is controlled to execute the all-vanadium redox flow battery control method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: The device includes at least one processor, and at least one memory and a bus connected to the processor; wherein the processor and the memory communicate with each other through the bus; the processor is used to call program instructions in the memory to execute the all-vanadium liquid flow battery control method according to any one of claims 1 to 7.

Images