Active-disturbance-rejection control method for solid oxide battery

Abstract

The invention relates to an active-disturbance-rejection control method for a solid oxide battery, and belongs to the technical field of automatic control, and the method comprises the steps: randomly generating a plurality of target parameter combinations according to a candidate solution space of each target parameter of LADRC, and taking each target parameter combination as a firefly position, calculating the maximum brightness of the fireflies according to the positions of the fireflies; updating the firefly position of the target firefly with the highest brightness ranking, and then updating the firefly position of each firefly according to the inertia weight and the adaptive step length factor; then, control parameters of the SOC system are generated based on the firefly positions through LADRC, and when performance indexes of the SOC system running according to the control parameters meet index requirements, it is determined that LADRC parameter optimization is completed. According to the invention, the improved firefly algorithm is applied to the active-disturbance-rejection controller of the SOC system for parameter optimization, so that the anti-interference capability of the output voltage of the solid oxide battery is improved.

Description

Technical Field

[0001] This invention relates to the field of automatic control technology, and in particular to a method for self-disturbance rejection control of solid oxide batteries. Background Technology

[0002] Solid oxide cells (SOCs), as efficient and clean energy conversion devices, inherently possess highly coupled, nonlinear, and multivariable characteristics in their stacks. When integrated into complex SOC systems and applied in fields such as distributed generation, these systems are susceptible to external disturbances such as load variations and temperature fluctuations, leading to unstable output voltage. To improve the stability and reliability of SOC systems, an advanced control strategy needs to be designed to ensure stable output voltage under various operating conditions.

[0003] Proportional-Integral-Derivative (PID) control has poor adaptability, struggles to handle the nonlinear characteristics of SOC systems, has weak disturbance rejection capabilities, and its parameter tuning relies heavily on experience. While fuzzy control and Model Predictive Control (MPC) can address some nonlinear problems, fuzzy control relies on empirical rules, resulting in inaccurate disturbance estimation, and MPC requires an accurate model, making it difficult to meet the complexity requirements of SOC systems. Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) exhibit slow convergence speeds in high-dimensional parameter spaces, are prone to getting trapped in local optima, and are difficult to apply in real-time to complex systems. Summary of the Invention

[0004] In view of this, it is necessary to provide a method, device, electronic device and storage medium for solid oxide battery self-disturbance rejection control, so as to solve the problem that traditional control methods have insufficient disturbance rejection capability when facing the control requirements of SOC system.

[0005] To address the aforementioned problems, in a first aspect, the present invention provides a method for controlling the self-disturbance rejection of solid oxide batteries, comprising: Based on the candidate solution space of each target parameter of the linear active disturbance rejection controller, multiple combinations of target parameters are randomly generated, and each combination of target parameters is used as a firefly position. Calculate the maximum brightness of the fireflies based on their location; After updating the firefly position of the target firefly using a random generation method, the firefly position of each firefly is updated according to the inertia weight and the adaptive step size factor; wherein, the target firefly is the firefly with the maximum brightness sorted in the preset last interval among all fireflies. The linear active disturbance rejection controller generates control parameters for the solid oxide battery system based on the firefly's location. When the performance indicators of the solid oxide battery system meet the requirements during operation according to the control parameters, it is determined that the optimization of the linear active disturbance rejection controller parameters is complete, and the solid oxide battery system is controlled by the optimized linear active disturbance rejection controller.

[0006] In one possible implementation, the method further includes: The iteration count is updated when multiple combinations of target parameters are randomly generated and each combination of target parameters is used as a firefly position. When the performance indicators of the solid oxide battery system meet the requirements during operation according to the control parameters, the optimization of the linear active disturbance rejection controller parameters is determined to be complete, including: When the performance indicators of the solid oxide battery system meet the requirements when operating according to the control parameters, or when the number of iterations equals the threshold number, the optimization of the linear active disturbance rejection controller parameters is determined to be complete.

[0007] In one possible implementation, the method further includes: When the performance metric does not meet the metric requirements and the number of iterations is less than the number threshold, the process returns to the step of randomly generating multiple combinations of target parameters and using each combination of target parameters as a firefly position.

[0008] In one possible implementation, the inertia weight decreases in a stepwise manner as the number of iterations increases.

[0009] In one possible implementation, the target parameters include the observer bandwidth and the input gain estimate.

[0010] In one possible implementation, the method further includes: Calculate the relative brightness and attractiveness of fireflies based on their maximum brightness. The step of updating the firefly position of each firefly based on inertia weight and adaptive step size factor includes: Based on the relative brightness and attractiveness of each firefly, combined with inertial weights and adaptive step size factors, the firefly position of each firefly is updated.

[0011] In one possible implementation, the relative brightness of the firefly is calculated using the following formula:

[0012] In the formula, The maximum brightness of the firefly is determined by the objective function; γ The absorption coefficient is . Fireflies a With fireflies b Spatial distance between them and Fireflies a With fireflies b Location within the search space.

[0013] In a second aspect, the present invention also provides a solid oxide battery self-disturbance rejection control device, comprising: The first firefly position generation module is used to randomly generate multiple combinations of target parameters based on the candidate solution space of each target parameter of the linear active disturbance rejection controller, and to use each combination of target parameters as a firefly position. A brightness calculation module is used to calculate the maximum brightness of the firefly based on its location. The second firefly position generation module is used to update the firefly position of the target firefly using a random generation method, and then update the firefly position of each firefly according to the inertia weight and the adaptive step size factor; wherein, the target firefly is the firefly with the highest brightness in the preset last interval among all fireflies. A control parameter generation module is used to generate control parameters for the solid oxide battery system based on the firefly position using the linear active disturbance rejection controller. The optimization determination module is used to determine that the optimization of the linear active disturbance rejection controller parameters is complete when the performance indicators of the solid oxide battery system meet the requirements during operation according to the control parameters, and to control the solid oxide battery system through the optimized linear active disturbance rejection controller.

[0014] Thirdly, the present invention also provides an electronic device, including a memory and a processor, wherein the memory is used to store a program; the processor is coupled to the memory and is used to execute the program stored in the memory to implement the steps in the solid oxide battery active disturbance rejection control method described in any of the above claims.

[0015] Fourthly, the present invention also provides a computer-readable storage medium for storing a computer-readable program, wherein the program or instructions, when executed by a processor, are capable of implementing the steps in any of the above-described solid oxide battery active disturbance rejection control methods.

[0016] The beneficial effects of this invention are: This invention employs a Linear Active Disturbance Rejection Controller (LADRC) for adaptive control of the SOC system. Compared to traditional controllers, LADRC can effectively estimate and compensate for internal and external disturbances in the system, significantly improving the stability of the SOC system. Even under conditions of sudden load changes or temperature fluctuations, it can maintain stable output voltage and has stronger robustness to unknown disturbances.

[0017] This invention also applies an improved Firefly Algorithm (FA) to LADRC for parameter optimization. By introducing inertia weights and adaptive step size factors into the Firefly Algorithm, the global search capability and convergence speed of the algorithm are improved. A random generation method is used to update firefly individuals with low luminescence, enhancing population diversity and avoiding premature convergence. Optimizing LADRC parameters through the improved Firefly Algorithm enhances the control performance of LADRC, thereby improving the anti-interference capability of the solid oxide battery output voltage.

[0018] Finally, evaluating the parameter optimization effect of LADRC through the performance indicators of the SOC system can ensure the effectiveness and superiority of the LADRC control strategy after parameter optimization. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating an embodiment of the active disturbance rejection control method for solid oxide batteries provided by the present invention. Figure 2 This is a schematic diagram of a second-order LADRC structure provided by the present invention; Figure 3 A schematic diagram of a SOC system structure is provided by the present invention; Figure 4 This is a schematic diagram of the overall process of the solid oxide battery active disturbance rejection control method provided by the present invention. Figure 5 A schematic diagram of an embodiment of the solid oxide battery self-disturbance rejection control device provided by the present invention; Figure 6 A schematic diagram of an embodiment of the electronic device provided by the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0022] In the description of the embodiments of this invention, unless otherwise stated, "a plurality of" means two or more. The terms "first," "second," etc., used in the embodiments of this invention are used to distinguish similar objects, and are not used to describe a specific order or sequence, nor to indicate or imply their relative importance or implicitly specify the number of indicated technical features. It should be understood that such data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class, and the number of objects is not limited; for example, a first object can be one or more.

[0023] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0024] Reference Figure 1 The diagram illustrates a flowchart of an embodiment of the active disturbance rejection control method for solid oxide batteries provided by the present invention. The method includes: S101, based on the candidate solution space of each objective parameter of the linear active disturbance rejection controller, randomly generate multiple combinations of objective parameters, and use each combination of objective parameters as a firefly position.

[0025] The target parameter is the predetermined parameter to be optimized in LADRC, such as the input gain estimate ( b 0) and observer bandwidth ( ω c ).

[0026] LADRC connects to the SOC system and is used for linear active disturbance rejection control of the SOC system. (Refer to...) Figure 2 This illustrates a schematic diagram of a second-order LADRC structure, which addresses uncertainties in a SOC system such as output voltage. V fcThis is treated as an unknown disturbance and estimated and compensated for using a Linear Extended State Observer (LESO). LADRC effectively handles internal and external disturbances in the SOC system, improving its control performance. The LADRC setpoint (…) r This means that the output of the SOC system should eventually reach and stabilize at the target value; key internal parameters of LADRC include: input gain estimate ( b 0) and observer bandwidth ( ω c ), and the location of LESO's poles ω 0 can take the value 4 ω c The LADRC control output is the hydrogen flow rate ( q f The input to the SOC system is the hydrogen flow rate ( q f ), output quantity is y ( V fc ).

[0027] Reference Figure 3 This diagram illustrates a SOC system structure provided by the present invention. The SOC system generates electricity, water, and heat through the electrochemical reaction of hydrogen at the anode and oxygen at the cathode. The main controlled variable for the reaction is the hydrogen flow rate (…). q f The controlled variable is the output voltage. V fc ), external load current ( I fc ) is a disturbance variable. The SOC system also includes temperature output ( T out Other parameters, used as auxiliary variables, include the valve molar constants for hydrogen, oxygen, and water vapor. , , ); reaction constant ( K r ); reaction time for each gas flow rate ( , , Fuel processor response time ( ); initial temperature ( T int ) and constant temperature ( T 0); thermal conductivity ( λ ) and effective thickness ( h eff ).

[0028] Multiple combinations of objective parameters can be randomly generated based on the candidate solution space of each objective parameter in LADRC using a uniform or normal distribution to cover possible optimization regions. Then, each combination of objective parameters is treated as a firefly position.

[0029] S102, calculate the maximum brightness of the firefly based on its location.

[0030] Maximum brightness characterizes the fitness of the target parameter combination (firefly position), which is obtained by calculation through the target fitness function and reflects the quality of LADRC control.

[0031] S103, after updating the firefly position of the target firefly using a random generation method, the firefly position of each firefly is updated according to the inertia weight and the adaptive step size factor; wherein, the target firefly is the firefly with the maximum brightness in the preset last interval among all fireflies.

[0032] Inertia weights are used to retain historical position information and can achieve a dynamic balance of search capabilities through exponential decay. The adaptive step size factor adjusts the movement amplitude according to the iteration process, dynamically calculated using the current optimal solution and the individual spacing, avoiding oscillations caused by a fixed step size. The target firefly selection mechanism focuses on updating the positions of low-brightness individuals, preventing premature convergence by strengthening the search capabilities of inferior individuals.

[0033] Specifically, firstly, multiple firefly locations are generated in the parameter space, each corresponding to a set of parameters to be optimized in LARDC. The SOC system response characteristics under various combinations of objective parameters can be evaluated using a simulation model, and the corresponding fitness value is calculated as the maximum brightness. Then, position perturbations are applied to individuals with lower maximum brightness, and the positions of each firefly are updated by combining inertia weights and an adaptive step size factor. In one example, the firefly positions can be updated according to the following formula: X_i = w X_i + β ( X_j - X_i ) + α (rand - 0.5) In the formula, X_i For the first i The location of the fireflies X_j For the first j The location of the fireflies For inertial weights, firefly j The attraction of fireflies i The step size factor is an adaptive step size factor that decreases adaptively as the number of iterations increases, and rand is a random number.

[0034] S104, the control parameters of the solid oxide battery system are generated based on the firefly position by a linear active disturbance rejection controller; After the locations of each firefly are updated, the locations of each firefly can be sequentially assigned to the target parameters of LADRC. Each assignment will generate a set of control parameters for the SOC system. The control parameters can be hydrogen flow rate (…). q f ).

[0035] S105, when the performance indicators of the solid oxide battery system meet the requirements during operation according to the control parameters, it is determined that the optimization of the linear active disturbance rejection controller parameters is completed, and the solid oxide battery system is controlled by the optimized linear active disturbance rejection controller.

[0036] If any target parameter combination (firefly position) is assigned to LADRC, and LADRC can control the SOC system to meet the performance requirements during operation, then the target parameter combination with the optimal performance will be imported into LADRC to adjust the SOC's operating state in real time. For example, when key indicators such as the SOC system's output voltage fluctuation amplitude, adjustment time, or deviation performance indicators such as integral absolute error (IAE) reach a preset threshold, parameter optimization is determined to be complete, and the control parameters are locked.

[0037] The solid oxide battery active disturbance rejection control method provided in this embodiment can be applied to a solid oxide battery active disturbance rejection control system, which can be a software system running on a terminal device. The terminal device can be a tablet computer, in-vehicle device, augmented reality (AR) / virtual reality (VR) device, laptop computer, ultra-mobile personal computer (UMPC), netbook, personal digital assistant (PDA), mobile phone, etc. This embodiment does not impose any restrictions on the specific type of terminal device.

[0038] In summary, this embodiment employs LADRC for adaptive control of the SOC system, which can significantly improve the stability of the SOC system. Simultaneously, applying the improved FA algorithm to LADRC for parameter optimization can enhance the control performance of LADRC, thereby improving the anti-interference capability of the solid oxide battery output voltage. Finally, evaluating the parameter optimization effect of LADRC through the performance indicators of the SOC system ensures the effectiveness and superiority of the optimized LADRC control strategy.

[0039] In some embodiments of the present invention, the method further includes: The number of iterations is updated when multiple combinations of target parameters are randomly generated and each combination of target parameters is used as a firefly position. When the performance indicators of the solid oxide battery system meet the requirements during operation according to the control parameters, the steps for completing the optimization of the linear active disturbance rejection controller parameters include: When the performance indicators of the solid oxide battery system meet the requirements during operation according to the control parameters, or when the number of iterations equals the threshold number, the optimization of the linear active disturbance rejection controller parameters is considered complete.

[0040] The iteration count refers to the number of times the algorithm iterates during execution. This can be achieved by accumulating the value of each iteration using a counter to track the progress of the optimization process. The iteration threshold is the preset maximum allowed number of iterations, which can be set using a fixed value or a dynamic adjustment strategy.

[0041] Specifically, each time a firefly location is randomly generated, the iteration count is automatically updated to record the current optimization stage. When the performance metric meets the requirements, the controller parameters are considered optimized; if the performance metric fails to meet the requirements but the iteration count has reached the threshold, the optimization process is also terminated, and the current optimal combination of objective parameters is selected as the final result. This mechanism ensures that the algorithm outputs a feasible solution within a finite time, avoiding the waste of computational resources caused by prolonged failure to meet performance metrics.

[0042] In some embodiments of the present invention, the method further includes: If the performance metrics do not meet the requirements and the number of iterations is less than the threshold, return to step S101.

[0043] In some embodiments of the present invention, the inertia weight decreases in a stepwise manner as the number of iterations increases.

[0044] Inertia weights can be implemented by adjusting weight values ​​in stages, for example, by dividing the total number of iterations into multiple stages and setting different fixed weight values ​​in each stage. Step-like decreasing refers to the weight value decreasing discontinuously with the number of iterations. This can be achieved using a discrete decreasing strategy, for example, by reducing the weight value by a fixed amount after each preset number of iterations.

[0045] Specifically, during the optimization process, the inertia weight is initially set to a large value to enhance global search capabilities. As the number of iterations increases, the weight value is gradually reduced in a step-like manner to improve local search accuracy. For example, the total number of iterations is divided into three stages: the initial stage weight is set to 0.9, the intermediate stage weight is reduced to 0.6, and the later stage weight is reduced to 0.3. Each weight adjustment occurs when the number of iterations reaches a preset threshold, such as triggering a weight update every one-third of the total number of iterations. By using a discretized step-like reduction method, the premature convergence problem that may be caused by linear reduction is avoided, while balancing the exploration and development capabilities of the algorithm at different search stages is achieved.

[0046] In some embodiments of the present invention, the method further includes: Calculate the relative brightness and attractiveness of fireflies based on their maximum brightness. The steps for updating the firefly position of each firefly based on inertia weights and adaptive step size factors include: The firefly position of each firefly is updated based on its relative brightness and attractiveness, combined with inertia weights and adaptive step size factors.

[0047] The relative brightness and attractiveness of each firefly are used to determine its direction of movement. Based on this, the firefly position can be updated by combining inertial weights and adaptive step size factors.

[0048] In some embodiments of the present invention, the relative brightness of fireflies is calculated using the following formula:

[0049] In the formula, The maximum brightness of the firefly is determined by the objective function; γ The absorption coefficient is . Fireflies a With fireflies b Spatial distance between them and Fireflies a With fireflies b Location within the search space.

[0050] Reference Figure 4This is a schematic diagram of the overall process of the solid oxide battery active disturbance rejection control method provided by the present invention. The process includes: Step 1: Initialize FA parameters, such as the number of fireflies, step size factor, maximum number of iterations, etc.

[0051] Step 2: Randomly generate firefly locations.

[0052] Step 3: Calculate the maximum brightness of each firefly. Relative brightness and attractiveness .

[0053] Step 4: Automatically update the 30% of fireflies with the weakest maximum brightness using a random generation method.

[0054] Step 5: Update the firefly position by adaptively expanding the search range based on the stepped inertia weight and step size factor.

[0055] Step 6: If the termination condition is met, stop the algorithm; otherwise, proceed to step 2.

[0056] This embodiment optimizes LADRC using FA. The optimized LADRC can quickly respond to external disturbances and ensure the stability of the output voltage.

[0057] Reference Figure 5 The diagram shows a structural schematic of an embodiment of the solid oxide battery self-disturbance rejection control device provided by the present invention. The device 500 includes: The first firefly position generation module 501 is used to randomly generate multiple combinations of target parameters based on the candidate solution space of each target parameter of the linear active disturbance rejection controller, and to use each combination of target parameters as a firefly position. Brightness calculation module 502 is used to calculate the maximum brightness of the firefly based on its location. The second firefly position generation module 503 is used to update the firefly position of the target firefly using a random generation method, and then update the firefly position of each firefly according to the inertia weight and the adaptive step size factor; wherein, the target firefly is the firefly with the highest brightness in the preset last interval among all fireflies. The control parameter generation module 504 is used to generate control parameters for the solid oxide battery system based on the firefly position using a linear active disturbance rejection controller. The optimization determination module 505 is used to determine that the linear active disturbance rejection controller parameters have been optimized when the performance indicators of the solid oxide battery system meet the requirements during operation according to the control parameters, and then control the solid oxide battery system through the optimized linear active disturbance rejection controller.

[0058] It should be noted that the implementation principles or processes of the above modules can be referred to the aforementioned embodiments of the solid oxide battery self-disturbance rejection control method, and will not be elaborated here.

[0059] Reference Figure 6 The present invention illustrates an electronic device 600. The electronic device 600 includes a processor 601, a memory 602, and a display 603. Figure 6 Only some components of the electronic device 600 are shown, but it should be understood that it is not required to implement all the components shown, and more or fewer components may be implemented instead.

[0060] In some embodiments, processor 601 may be a central processing unit (CPU), microprocessor, or other data processing chip, used to run program code stored in memory 602 or process data, such as the solid oxide battery self-disturbance control method of the present invention.

[0061] In some embodiments, processor 601 may be a single server or a group of servers. The server group may be centralized or distributed. In some embodiments, processor 601 may be local or remote. In some embodiments, processor 601 may be implemented on a cloud platform. In one embodiment, the cloud platform may include a private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, internal cloud, multi-cloud, etc., or any combination thereof.

[0062] In some embodiments, memory 602 may be an internal storage unit of electronic device 600, such as a hard disk or memory of electronic device 600. In other embodiments, memory 602 may also be an external storage device of electronic device 600, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. equipped on electronic device 600.

[0063] Furthermore, the memory 602 may include both internal storage units of the electronic device 600 and external storage devices. The memory 602 is used to store application software and various types of data installed on the electronic device 600.

[0064] In some embodiments, display 603 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. Display 603 is used to display information from electronic device 600 and to display a visual user interface. Components 601-603 of electronic device 600 communicate with each other via a system bus.

[0065] In one embodiment, when processor 601 executes the solid oxide battery self-disturbance rejection control program in memory 602, the following steps can be implemented: Based on the candidate solution space of each objective parameter of the linear active disturbance rejection controller, multiple combinations of objective parameters are randomly generated, and each combination of objective parameters is used as a firefly position. Calculate the maximum brightness of the fireflies based on their location; After updating the firefly position of the target firefly using a random generation method, the firefly position of each firefly is updated according to the inertia weight and the adaptive step size factor; where the target firefly is the firefly with the highest brightness in the preset last interval among all fireflies. The control parameters of the solid oxide battery system are generated based on the firefly location using a linear active disturbance rejection controller. When the performance indicators of the solid oxide battery system meet the requirements during operation according to the control parameters, the optimization of the linear active disturbance rejection controller parameters is completed, and the solid oxide battery system is controlled by the optimized linear active disturbance rejection controller.

[0066] It should be understood that when the processor 601 executes the solid oxide battery self-disturbance rejection control program in the memory 602, in addition to the functions mentioned above, it can also perform other functions, as can be found in the description of the corresponding method embodiments above.

[0067] Furthermore, this embodiment of the invention does not specifically limit the type of electronic device 600 mentioned. Electronic device 600 can be a mobile phone, tablet computer, personal digital assistant (PDA), wearable device, laptop computer, or other portable electronic device. Exemplary embodiments of portable electronic devices include, but are not limited to, portable electronic devices running iOS, Android, Microsoft, or other operating systems. The aforementioned portable electronic device can also be other portable electronic devices, such as a laptop computer with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in some other embodiments of the invention, electronic device 600 may not be a portable electronic device, but rather a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0068] In one embodiment, the present invention also provides a computer-readable storage medium storing a computer program that, when executed by the processor, implements the steps of any of the above-described solid oxide battery active disturbance rejection control methods.

[0069] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware, and the program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0070] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for controlling disturbance rejection in solid oxide batteries, characterized in that, include: Based on the candidate solution space of each target parameter of the linear active disturbance rejection controller, multiple combinations of target parameters are randomly generated, and each combination of target parameters is used as a firefly position. Calculate the maximum brightness of the fireflies based on their location; After updating the firefly position of the target firefly using a random generation method, the firefly position of each firefly is updated according to the inertia weight and the adaptive step size factor; wherein, the target firefly is the firefly with the maximum brightness sorted in the preset last interval among all fireflies. The linear active disturbance rejection controller generates control parameters for the solid oxide battery system based on the firefly's location. When the performance indicators of the solid oxide battery system meet the requirements during operation according to the control parameters, it is determined that the optimization of the linear active disturbance rejection controller parameters is complete, and the solid oxide battery system is controlled by the optimized linear active disturbance rejection controller.

2. The method for controlling disturbance rejection in solid oxide batteries according to claim 1, characterized in that, The method further includes: The iteration count is updated when multiple combinations of target parameters are randomly generated and each combination of target parameters is used as a firefly position. When the performance indicators of the solid oxide battery system meet the requirements during operation according to the control parameters, the optimization of the linear active disturbance rejection controller parameters is determined to be complete, including: When the performance indicators of the solid oxide battery system meet the requirements when operating according to the control parameters, or when the number of iterations equals the threshold number, the optimization of the linear active disturbance rejection controller parameters is determined to be complete.

3. The method for controlling disturbance rejection in solid oxide batteries according to claim 2, characterized in that, The method further includes: When the performance metric does not meet the metric requirements and the number of iterations is less than the number threshold, the process returns to the step of randomly generating multiple combinations of target parameters and using each combination of target parameters as a firefly position.

4. The method for controlling disturbance rejection in solid oxide batteries according to claim 2, characterized in that, The inertia weight decreases in a stepwise manner as the number of iterations increases.

5. The method for controlling the active disturbance rejection of solid oxide batteries according to claim 1, characterized in that, The target parameters include observer bandwidth and input gain estimates.

6. The method for controlling disturbance rejection in solid oxide batteries according to claim 1, characterized in that, The method further includes: Calculate the relative brightness and attractiveness of fireflies based on their maximum brightness. The step of updating the firefly position of each firefly based on inertia weight and adaptive step size factor includes: Based on the relative brightness and attractiveness of each firefly, combined with inertial weights and adaptive step size factors, the firefly position of each firefly is updated.

7. The method for controlling the active disturbance rejection of solid oxide batteries according to claim 6, characterized in that, The relative brightness of the fireflies is calculated using the following formula: In the formula, The maximum brightness of the firefly is determined by the objective function; γ The absorption coefficient is . Fireflies a With fireflies b Spatial distance between them and Fireflies a With fireflies b Location within the search space.

8. A solid oxide battery self-disturbance rejection control device, characterized in that, include: The first firefly position generation module is used to randomly generate multiple combinations of target parameters based on the candidate solution space of each target parameter of the linear active disturbance rejection controller, and to use each combination of target parameters as a firefly position. A brightness calculation module is used to calculate the maximum brightness of the firefly based on its location. The second firefly position generation module is used to update the firefly position of the target firefly using a random generation method, and then update the firefly position of each firefly according to the inertia weight and the adaptive step size factor; wherein, the target firefly is the firefly with the highest brightness in the preset last interval among all fireflies. A control parameter generation module is used to generate control parameters for the solid oxide battery system based on the firefly position using the linear active disturbance rejection controller. The optimization determination module is used to determine that the optimization of the linear active disturbance rejection controller parameters is complete when the performance indicators of the solid oxide battery system meet the requirements during operation according to the control parameters, and to control the solid oxide battery system through the optimized linear active disturbance rejection controller.

9. An electronic device, characterized in that, Including memory and processor, among which, The memory is used to store programs; The processor, coupled to the memory, is used to execute the program stored in the memory to implement the steps in the solid oxide battery active disturbance rejection control method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps of the solid oxide battery active disturbance rejection control method according to any one of claims 1 to 7.

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