A high-temperature solid oxide battery multi-level bidirectional test control method and system

Abstract

The application provides a high-temperature solid oxide battery multilevel bidirectional test control method and system, relates to the solid oxide battery test technical field, and the method comprises the following steps: obtaining a measured object parameter; obtaining a test resource capability set; establishing a resource compatibility matrix, judging the matching relationship of interfaces, media, ranges, response times and safety boundaries, determining the matching state between each measured object port and test resource port; generating an initial resource control parameter set; generating a control instruction sequence; executing the control instruction sequence and synchronously collecting process data and safety states; calculating a risk level, online reconstructing the control instruction sequence, obtaining a corrected control instruction sequence and submitting the corrected control instruction sequence to a bottom layer for execution; forming an evaluation vector and feeding back a corrected subsequent test strategy. The closed-loop control architecture constructed by the application can upgrade the test from an artificial preset process to intelligent control of controller autonomous adaptation, arrangement, reconstruction and feedback, and improve universality and safety.

Description

Technical Field

[0001] This invention relates to the field of solid oxide battery testing technology, and specifically to a multi-level bidirectional testing and control method for high-temperature solid oxide batteries. Background Technology

[0002] High-temperature solid oxide batteries (SOFC / SOEC) can be tested for power generation in SOFC mode, electrolysis in SOEC mode, and reversible switching tests can be performed on the same stack or system. Existing testing systems mostly adopt a modular design approach, integrating multiple testing modules at the hardware level, such as gas supply modules, stack installation modules, electrical modules, exhaust gas treatment modules, and data acquisition modules, providing basic testing capabilities for test objects of specific levels or power ratings.

[0003] However, there are significant differences in the number of ports, gas medium, temperature and pressure boundaries, rated current and voltage, thermal inertia, response time and safety boundaries between different levels of the tested objects (single cell, stack, module and system). Existing test platforms are usually configured according to a single object or a single power level. The test process still relies on manual selection of pipelines, gas, temperature, power load and sampling scheme. The test control logic is mostly a preset fixed process.

[0004] Due to the lack of controller-oriented object adaptation models, resource capability models, task node models, safety reconfiguration models, and evaluation feedback models, existing technologies struggle to automatically transform test objects at different levels into resource control parameters and test objectives into dynamically adjustable control command sequences. Furthermore, the gas, heat, and electrical parameters in SOFC / SOEC bidirectional testing exhibit strong coupling characteristics, making it difficult for existing systems to achieve automatic coordinated control of these parameters. When safety risk states change, existing systems also struggle to proactively intervene by modifying test tasks in a timely manner. In addition, existing testing systems lack a closed-loop mechanism for real-time feedback of test data evaluation results to the test control process, hindering deep coupling between the testing process and evaluation results. Summary of the Invention

[0005] To address the problems in related technologies, this invention provides a multi-level bidirectional testing and control method for high-temperature solid oxide batteries.

[0006] To achieve the above objectives, the technical solution adopted by the present invention includes:

[0007] According to a first aspect of the present invention, a multi-level bidirectional test control method for high-temperature solid oxide batteries is provided, comprising the following steps:

[0008] Obtain the parameters of the object under test;

[0009] Acquire a set of test resource capabilities;

[0010] A resource compatibility matrix is ​​established based on the parameters of the object under test and the set of test resource capabilities. The matching relationship of interface, medium, range, response time and security boundary is determined, and the matching status between each port of the object under test and the port of the test resource is determined.

[0011] An initial resource control parameter set is generated based on the compatibility matrix;

[0012] Generate a sequence of control instructions based on the test objective and the initial resource control parameter set;

[0013] The control test resource layer executes the control command sequence and synchronously collects process data and security status.

[0014] The risk level is calculated based on the security status, and the control instruction sequence is reconstructed online based on the risk level, the current task node, the initial resource control parameter set, and the evaluation vector. The corrected control instruction sequence is then handed over to the underlying layer for execution.

[0015] The evaluation vector is formed based on the process data, and feedback is used to correct subsequent testing strategies.

[0016] Optionally, a resource compatibility matrix is ​​established based on the parameters of the object under test and the set of test resource capabilities, specifically including:

[0017] A compatibility matrix is ​​constructed by using each port or control requirement of the tested object in the parameters of the tested object as a row element of the matrix, and each test resource port or resource unit in the test resource capability set as a column element of the matrix. ;

[0018] When the The port or control requirements of the tested object are related to the first When each test resource port or resource unit meets the matching conditions in terms of interface type, media type, measurement range, response time, and security boundaries... Take the matchable state; otherwise, take the unmatchable state.

[0019] Optionally, an initial resource control parameter set is generated based on the compatibility matrix, specifically including:

[0020] Based on the compatibility matrix, available resources are selected, and an initial resource control parameter set is generated. The initial resource control parameter set It includes at least gas control parameters, steam control parameters, thermal control parameters, electrical control parameters, sampling control parameters, and safety threshold parameters;

[0021] When resources are insufficient, output downgraded test parameters or an unexecutable message.

[0022] Optionally, a sequence of control instructions is generated based on the test objective and the initial resource control parameter set, specifically including:

[0023] Test target and initial resource control parameter set Converted to multiple task nodes The constructed control command sequence ;

[0024] Each task node At least include control actions Setting parameters Sampling items Entry conditions Exit conditions Exception handling strategy and rating tags .

[0025] Optionally, a risk level is calculated based on the security status, and the control command sequence is reconstructed online based on the risk level, the current task node, the initial resource control parameter set, and the evaluation vector. Specifically, this includes:

[0026] Real-time collection of security status The security status This includes hydrogen concentration, oxygen content, combustible gas concentration, inlet and outlet pressure difference, dew point deviation, temperature gradient, electrical insulation, and exhaust gas treatment status.

[0027] According to the security status Risk level is determined by its rate of change. The risk levels include normal, warning, restricted, and dangerous.

[0028] When any safety status parameter reaches the warning threshold, the warning level is output and the set value is corrected or the ramp rate is reduced.

[0029] When any safety status parameter reaches the limit threshold, the limit level is output and a hold node or purge node is inserted;

[0030] When any safety status parameter reaches the interlocking threshold, the danger level is output and the interlocking shutdown is triggered;

[0031] Reconstruct the current task node and subsequent task nodes according to safety priority, and output the corrected control instruction sequence. .

[0032] Optionally, the evaluation vector is formed based on the process data, and feedback is used to correct subsequent testing strategies, specifically including:

[0033] Data collected during the testing process Time synchronization, steady-state identification, feature extraction, and comprehensive evaluation are performed to form an evaluation vector. The evaluation vector At a minimum, it includes voltage stability, current or power stability, electrical efficiency, steam utilization or fuel utilization, temperature gradient, impedance characteristics, attenuation rate, safety margin, and data reliability.

[0034] The evaluation vector As feedback variables, input to the task orchestration layer and / or security constraint layer;

[0035] According to the evaluation vector Output feedback commands to continue execution, extend steady state, supplement operating conditions, reduce load, limit boundaries, or terminate the test.

[0036] Optionally, in SOEC electrolysis mode, the high-temperature solid oxide battery multi-level bidirectional test control method further includes steam-electrolysis current linkage control:

[0037] According to the electrolysis current Number of battery cells Faraday constant and maximum allowable steam utilization rate Constraint steam molar flow rate setpoint satisfy: ,in, For safety margin coefficient and ;

[0038] When the steam flow rate, dew point, inlet temperature, or pressure conditions do not meet the boundaries, the electrolysis current ramp-up is limited, generating hold, limit, or purge reconfiguration commands.

[0039] Optionally, in SOFC power generation mode, the high-temperature solid oxide battery multi-level bidirectional test control method further includes fuel-load coordination control:

[0040] The lower limit of fuel supply is calculated based on current, number of solar cells, and upper limit of fuel utilization rate.

[0041] Fuel flow and electronic load are adjusted based on reactor temperature, anode pressure differential, and load change rate.

[0042] If an anomaly occurs, perform a load reduction or shutdown and refactoring.

[0043] Optionally, in the SOFC-SOEC reversible switching mode, the high-temperature solid oxide battery multi-level bidirectional test control method further includes reversible switching control:

[0044] The switching process is broken down into a sequence of task nodes: SOFC steady-state confirmation, load reduction and holding, atmosphere transition, thermal state holding, switching condition confirmation, electrical interface switching, SOEC steam initiation, and electrolysis current ramp-up.

[0045] Each task node is configured with corresponding entry and exit conditions;

[0046] Real-time monitoring of temperature gradients and the risk of hydrogen-oxygen crossover, and dynamic intervention.

[0047] According to a second aspect of the present invention, a multi-level bidirectional test and control system for high-temperature solid oxide batteries is also provided, for executing the multi-level bidirectional test and control method for high-temperature solid oxide batteries according to any one of the technical solutions in the first aspect of the present invention. The system includes a controller and a test resource layer connected to the controller; the controller includes an object adaptation layer, a task orchestration layer, a safety constraint layer, and a data evaluation layer.

[0048] The test resource layer is used to provide underlying physical execution and perception resources, and outputs a real-time set of resource capabilities to the outside world;

[0049] The object adaptation layer is used to establish a compatibility matrix based on the parameters of the object under test and the resource capability set, and to generate an initial resource control parameter set based on the compatibility matrix;

[0050] The task orchestration layer is used to generate a sequence of control instructions consisting of multiple task nodes based on the test objective and the initial resource control parameter set.

[0051] The security constraint layer is used to calculate the risk level based on the real-time collected security status, and to reconstruct the control command sequence online based on the risk level, and output the corrected control command sequence to the test resource layer for execution;

[0052] The data evaluation layer is used to generate an evaluation vector based on the data collected during the testing process, and to feed the evaluation vector back to the task orchestration layer and / or the security constraint layer.

[0053] Beneficial effects:

[0054] 1. First, this invention enables cross-level adaptive matching, improving the versatility of the testing system. Specifically, by establishing a resource compatibility matrix, this invention performs multi-dimensional structured matching of the parameters of the object under test with the capabilities of testing resources. This allows the same testing platform to automatically adapt to different levels of objects under test, such as single cells, stacks, modules, and systems, and automatically generate initial control parameters that include multi-domain coordination of gas, heat, electricity, sampling, and safety. This eliminates the tedium and uncertainty of manual configuration and effectively enhances the cross-level versatility of the testing platform.

[0055] Second, the testing process using the method of this invention is programmable, operable, and reconfigurable, offering excellent control flexibility. Specifically, this invention parses the test target into a sequence of instructions composed of standardized task nodes. Each node encapsulates entry conditions, exit conditions, and exception handling strategies, transforming the testing process from a fixed, preset script into a dynamic control object that can be identified, paused, jumped, inserted, or reconfigured in real time by the controller. This effectively improves the flexibility of process control in complex testing scenarios.

[0056] Third, this invention can upgrade the safety response from passive alarm to active reconfiguration, enhancing system security. Specifically, this invention quantifies the real-time safety status into four risk levels: normal, warning, restricted, and dangerous, and configures differentiated reconfiguration strategies for each level. This allows the system to autonomously correct set values, insert protection nodes, or trigger interlock shutdown when risks occur. In this way, it can achieve a leap from simple alarm prompts to active intervention control command sequences, effectively reducing the safety risks caused by delays in manual response.

[0057] Fourth, the deep closed-loop coupling of testing and evaluation in this invention ensures the quality of test data. Specifically, this invention transforms test data into an evaluation vector in real time, encompassing performance, stability, degradation, safety margin, and data reliability, and directly feeds it back to the task orchestration and safety constraint stages. This allows the system to autonomously extend steady-state time, retest operating conditions, or terminate invalid tests based on the evaluation results, fundamentally changing the traditional model where evaluation and testing are separated, and ensuring the reliability and validity of test results.

[0058] Fifth, this invention enables quantitative coordinated control through strongly coupled gas-heat-electric parameters. Specifically, this invention establishes a quantitative linkage constraint between steam flow and electrolysis current for SOEC electrolysis mode, a dynamic following relationship between fuel supply and load for SOFC power generation mode, and a condition-driven standardized node flow mechanism for reversible switching processes. This allows the control of strongly coupled parameters in bidirectional testing of high-temperature solid oxide batteries to be upgraded from relying on manual experience-based adjustment to automated coordinated control based on physical relationships, effectively reducing performance degradation and safety risks during operating condition switching and steady-state operation.

[0059] 2. Other beneficial effects or advantages of the present invention will be described in detail in the specific embodiments. Attached Figure Description

[0060] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the 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.

[0061] in:

[0062] Figure 1 This is a flowchart illustrating the steps of a multi-level bidirectional test control method for high-temperature solid oxide batteries provided in an exemplary embodiment of the present invention.

[0063] Figure 2 This is a schematic diagram of the overall structure of a high-temperature solid oxide battery multi-level bidirectional test and control system provided in an exemplary embodiment of the present invention;

[0064] Figure 3 This is a schematic diagram of the structure of the test resource layer provided in an exemplary embodiment of the present invention;

[0065] Figure 4 This is a schematic diagram of the process for generating a resource control parameter set for an object adaptation layer, provided in an exemplary embodiment of the present invention.

[0066] Figure 5 This is a schematic diagram of the task node structure and control instruction sequence generation provided in an exemplary embodiment of the present invention;

[0067] Figure 6 This is a schematic diagram of the dynamic reconfiguration control instruction sequence for the security constraint layer provided in an exemplary embodiment of the present invention;

[0068] Figure 7 This is a schematic diagram of the data evaluation layer feedback control process provided in an exemplary embodiment of the present invention;

[0069] Figure 8 This is a schematic diagram illustrating the implementation of SOEC steam-electrolysis current linkage control according to an exemplary embodiment of the present invention;

[0070] Figure 9 This is a schematic diagram illustrating an exemplary embodiment of the SOFC-SOEC reversible switching control provided by the present invention. Detailed Implementation

[0071] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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 some embodiments of the present invention, but not all embodiments.

[0072] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0073] Furthermore, the terms "comprising" and "having," and any variations thereof, used in the description of this invention are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices. It should also be noted that in embodiments of this invention, the words "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in embodiments of this invention should not be construed as preferred or advantageous over other embodiments or designs. Specifically, the use of the words "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0074] To facilitate a clearer and more accurate understanding of the technical solution of this invention by those skilled in the art, the technical concept of this invention will be explained below.

[0075] The technical concept of this invention lies in upgrading the multi-level bidirectional testing process of high-temperature solid oxide batteries from a preset "human-operated machine" execution mode to a dynamic closed-loop control mode of "controller autonomous cognition and decision-making." Specifically, this invention establishes an object adaptation layer to automatically match the physical parameters of the tested object with the underlying resource capabilities, uniformly transforming the tested objects at each level into resource control parameters recognizable by the controller; it establishes a task orchestration layer to decompose diverse test objectives into standardized task node sequences with entry / exit conditions and anomaly handling strategies, enabling the test process to no longer rely on manually preset scripts but possess machine-executable, jumpable, and intervention-enabled capabilities; it establishes a safety constraint layer to quantify the safety status into risk levels in real time and reconstruct the control command sequence online, enabling the system to proactively correct, reduce load, or interlock in the face of risks rather than passively triggering alarms; and it establishes a data evaluation layer to convert test data into evaluation vectors in real time and feed them back to the task orchestration and safety constraint links in a closed loop, transforming the evaluation results from offline reports into real-time feedback variables in the control loop.

[0076] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings.

[0077] like Figure 1As shown, according to a first aspect of the present invention, a multi-level bidirectional test control method for high-temperature solid oxide batteries is provided, comprising the following steps:

[0078] Obtain the parameters of the object under test;

[0079] Acquire a set of test resource capabilities;

[0080] A resource compatibility matrix is ​​established based on the parameters of the object under test and the set of test resource capabilities. The matching relationship of interface, medium, range, response time and security boundary is determined, and the matching status between each port of the object under test and the port of the test resource is determined.

[0081] An initial resource control parameter set is generated based on the compatibility matrix;

[0082] Generate a sequence of control instructions based on the test objective and the initial resource control parameter set;

[0083] The control test resource layer executes the control command sequence and synchronously collects process data and security status.

[0084] The risk level is calculated based on the security status, and the control instruction sequence is reconstructed online based on the risk level, the current task node, the initial resource control parameter set, and the evaluation vector. The corrected control instruction sequence is then handed over to the underlying layer for execution.

[0085] The evaluation vector is formed based on the process data, and feedback is used to correct subsequent testing strategies.

[0086] Through the above technical solution, firstly, the method of this implementation can achieve automated cross-level adaptation between the object under test and test resources. Specifically, in this invention, through the technical path of "obtaining the parameters of the object under test—obtaining the set of test resource capabilities—establishing a compatibility matrix to determine the matching relationship—generating an initial set of resource control parameters," the differentiated port requirements of objects under test at different levels can be structurally matched with the multi-type resource capabilities of the test resource layer. This allows objects at different levels, such as single batteries, fuel cell stacks, modules, and systems, to be automatically identified and their resources configured on the same test platform. This eliminates the need for manual review of specifications and manual comparison of port compatibility, specifically addressing the problem of insufficient cross-level adaptation capabilities in existing technologies.

[0087] Second, this implementation method enables the automated conversion of test targets into executable instruction sequences. Specifically, in this invention, the step of "generating a control instruction sequence based on the test target and the initial resource control parameter set" automatically parses diverse test targets into instruction sequences composed of multiple task nodes. Compared to the existing technology where the test process is fixed in software code or operation manuals and changes to the test target require manual resetting of the process, this step enables the controller to autonomously convert high-level test targets into low-level execution instructions. The test process no longer relies on preset scripts and has the characteristics of being machine-executable and operable.

[0088] Third, this implementation method enables a leap from passive security alarms to proactive security reconfiguration. Specifically, in this invention, by "calculating the risk level based on the security status and reconfiguring the control command sequence online based on the risk level, the current task node, the initial resource control parameter set, and the evaluation vector," not only is a status alert provided when a security risk occurs, but the control commands that have not yet been executed are also dynamically adjusted. Compared to existing technologies where manual judgment and adjustment are required after a security alarm is triggered, this step enables direct intervention of security constraints in the testing process, allowing the system to autonomously correct the testing strategy within a timescale beyond human response, thereby effectively reducing the security risks caused by delays in manual intervention.

[0089] Fourth, this implementation method enables real-time closed-loop feedback of test data evaluation to the control process. Specifically, in this invention, through the step of "forming an evaluation vector based on process data and using it to correct subsequent test strategies," the data collected during the test is transformed into an evaluation vector in real time and directly used as an input variable in the control loop to adjust subsequent test tasks. Compared to the existing technology that treats data evaluation as an offline analysis method and separates the evaluation results from test control, this step allows "evaluation" to become part of the test process from the end point of the test. This enables deep closed-loop coupling between the test process and data evaluation, thereby allowing the test system to autonomously optimize test strategies based on data quality.

[0090] In one embodiment of the present invention, establishing a resource compatibility matrix based on the parameters of the object under test and the set of test resource capabilities may specifically include: using each port or control requirement of the object under test in the parameters of the object under test as a row element of the matrix, and using each test resource port or resource unit in the set of test resource capabilities as a column element of the matrix to construct the compatibility matrix. When the first The port or control requirements of the tested object are related to the first When each test resource port or resource unit meets the matching conditions in terms of interface type, media type, measurement range, response time, and security boundaries... Take the matchable state; otherwise, take the unmatchable state.

[0091] In existing related technologies, the matching judgment of interface form, media type, range, response time, and security boundary relies on manual comparison item by item, which is inefficient and prone to omissions. This implementation method, however, incorporates multi-dimensional matching conditions into matrix elements. The judgment rules upgrade the cross-level adaptation process from "manual one-by-one comparison" to "matrix structured operation", thereby eliminating the subjectivity and uncertainty of manual judgment and providing a reliable computational basis for the automated generation of subsequent control parameters.

[0092] In one embodiment of the present invention, generating an initial resource control parameter set based on a compatibility matrix may specifically include: selecting available resources based on the compatibility matrix and generating an initial resource control parameter set. Initial resource control parameter set It should include at least gas control parameters, steam control parameters, thermal control parameters, electrical control parameters, sampling control parameters, and safety threshold parameters; when resources are insufficient, it should output degraded test parameters or an unexecutable message.

[0093] In existing related technologies, parameter configuration for different control domains (gas, steam, heat, electricity, sampling, and safety) is independent and completed step by step, and only simple error reports are given when resources are mismatched. This implementation method, however, generates and packages multi-domain control parameters together during the adaptation phase, thereby achieving integrated resource configuration. Furthermore, when resources are insufficient, it outputs degraded test parameters instead of simply rejecting the system, allowing it to provide feasible solutions even under resource-constrained conditions. This effectively improves the resource utilization flexibility and availability of the testing platform.

[0094] In one embodiment of the present invention, generating a control instruction sequence based on a test target and an initial resource control parameter set may specifically include: setting the test target... and initial resource control parameter set Converted to multiple task nodes The constructed control command sequence Each task node At least include control actions Setting parameters Sampling items Entry conditions Exit conditions Exception handling strategy and rating tags .

[0095] In existing technologies, test processes are mostly fixed in the form of preset scripts or sequential instructions, lacking a fine-grained structure that can be dynamically intervened by the controller. This implementation encapsulates each task node as a complete information unit containing control actions, setting parameters, sampling items, entry conditions, exit conditions, exception handling strategies, and evaluation labels. This transforms the test process from an "uninterrupted continuous flow of instructions" into a "recognizable, jumpable, insertable, and reconfigurable sequence of nodes," thus providing an operable instruction structure foundation for online reconfiguration steps.

[0096] In one embodiment of the present invention, a risk level is calculated based on the security status, and the control command sequence is reconstructed online based on the risk level, the current task node, the initial resource control parameter set, and the evaluation vector. Specifically, this may include: real-time acquisition of the security status. ;Safe status This includes hydrogen concentration, oxygen content, combustible gas concentration, inlet and outlet pressure difference, dew point deviation, temperature gradient, electrical insulation, and exhaust gas treatment status; based on safety status... Risk level is determined by its rate of change. Risk levels include normal, warning, restricted, and dangerous.

[0097] When any safety status parameter reaches the warning threshold, output the warning level and correct the set value or reduce the ramp rate; when any safety status parameter reaches the limit threshold, output the limit level and insert a holding node or purging node; when any safety status parameter reaches the interlock threshold, output the danger level and trigger interlock shutdown.

[0098] Reconstruct the current task node and subsequent task nodes according to safety priority, and output the corrected control instruction sequence. .

[0099] In existing related technologies, safety protection is mostly based on a single threshold triggering alarm. This implementation quantifies safety risks into four levels: normal, warning, restriction, and danger, and sets differentiated reconfiguration actions for each level (e.g., correcting set values, inserting holding nodes, triggering interlock shutdown). In this way, it is possible to achieve a leap from "single-point alarm" to "tiered active intervention", and establish a precise mapping relationship between safety protection measures and control command sequences.

[0100] In one embodiment of the present invention, an evaluation vector is formed based on process data, and feedback is used to correct subsequent testing strategies. Specifically, this may include: processing data collected during the testing process. Time synchronization, steady-state identification, feature extraction, and comprehensive evaluation are performed to form an evaluation vector. Evaluation vector At a minimum, the evaluation vectors should include voltage stability, current or power stability, electrical efficiency, steam or fuel utilization rate, temperature gradient, impedance characteristics, attenuation rate, safety margin, and data reliability. As a feedback variable, input to the task orchestration layer and / or safety constraint layer; based on the evaluation vector Output feedback commands to continue execution, extend steady state, supplement operating conditions, reduce load, limit boundaries, or terminate the test.

[0101] In existing related technologies, data evaluation is mostly used as an offline analysis method, and there is no direct correlation between evaluation indicators and test control. This implementation method unifies and quantifies multiple evaluation indicators such as voltage stability, efficiency, attenuation rate, safety margin, and data reliability into an evaluation vector. And directly input as feedback variables into the task orchestration layer and / or safety constraint layer, so that "evaluation" can be transformed from a data report at the test endpoint into a real-time feedback signal in the control loop, fundamentally changing the logical relationship between evaluation and testing.

[0102] In one embodiment of the present invention, under SOEC electrolysis mode, the high-temperature solid oxide battery multi-level bidirectional test control method of the present invention may further include steam-electrolysis current linkage control:

[0103] According to the electrolysis current Number of battery cells Faraday constant and maximum allowable steam utilization rate Constraint steam molar flow rate setpoint satisfy: ,in, For safety margin coefficient and (Preferably 1.05-1.50, which can be determined based on at least one of the following: steam flow control error, dew point measurement error, steam generator response time, electrolysis current ramp-up rate, inlet pipeline condensation risk, level of the object under test, and test safety level); when the steam flow, dew point, inlet temperature, or pressure state does not meet the boundary, the electrolysis current ramp-up is restricted, and a hold, limit, or purge reconfiguration command is generated.

[0104] In this implementation, the safety margin factor Used to compensate for dynamic lag and errors in the processes of steam generation, transportation, measurement and control. The value of is greater than 1, preferably 1.05-1.50, and more preferably 1.10-1.30. It can be determined based on at least one of the following: steam flow control error, dew point measurement error, steam generator response time, electrolysis current ramp rate, inlet pipeline condensation risk, level of the object being tested, and test safety level.

[0105] For example, when the object under test is a single cell or a short stack, and vapor generation and dew point control are stable, A value of 1.05-1.15 is acceptable; however, when the object under test is a fuel cell stack or module, or when the electrolytic current ramp-up rate is high, A value of 1.10-1.30 is acceptable; however, when the object under test is a system-level test, has a long steam pipeline, a high risk of inlet condensation, or is under a safety warning state, A value of 1.30-1.50 is acceptable.

[0106] For example, It can also be dynamically adjusted based on real-time operating status, for example:

[0107]

[0108] in, Based on the basic margin factor, For steam flow tracking error, For dew point deviation, This is the normalized value of the electrolysis current ramp-up rate. For safety status correction items, to These are the weighting coefficients.

[0109] In this way, the lower limit of steam supply can be adjusted according to the test object level, steam supply capacity and safety status, thereby reducing the risk of under-steam and fuel cell stack damage.

[0110] In existing related technologies, steam supply and electrolysis current are usually controlled by separate circuits, which can easily lead to performance degradation or damage to the electrolytic cell due to gas-electricity imbalance. This embodiment establishes a steam molar flow rate setpoint. With electrolysis current The quantitative constraint inequality between them allows the upper limit of steam utilization rate to be incorporated into the control logic as a hard boundary. This enables the gas-electric coordination to be upgraded from relying on manual experience to quantitative linkage control based on physical relationships, thereby effectively solving the coupling risk of steam shortage and current overload in the electrolysis mode.

[0111] In one embodiment of the present invention, under SOFC power generation mode, the high-temperature solid oxide battery multi-level bidirectional test control method of the present invention may further include fuel-load coordination control:

[0112] The lower limit of fuel supply is calculated based on the current, number of cells, and upper limit of fuel utilization; the fuel flow rate and electronic load are adjusted based on the stack temperature, anode pressure difference, and load change rate; and load reduction or shutdown reconfiguration is performed in case of anomalies.

[0113] In existing related technologies, the adjustment of fuel flow and electronic load is independent, which can easily lead to insufficient fuel supply or thermal management malfunction. In this embodiment, the lower limit of fuel supply is calculated with the upper limit of fuel utilization rate as a constraint, and the reactor temperature, anode pressure difference and load change rate are introduced as correction factors. In this way, a dynamic following relationship can be formed between fuel supply and load, realizing the coordinated control of heat-gas-electricity in the power generation mode.

[0114] In this embodiment, "abnormality" can include any one or more of the following: actual fuel flow rate is lower than the fuel supply lower limit, stack temperature or temperature gradient exceeds the preset temperature boundary, anode pressure difference or pressure difference change rate exceeds the preset pressure difference boundary, load change rate exceeds the preset ramp rate boundary, stack voltage is lower than the voltage lower limit or voltage drop rate exceeds the preset threshold, and exhaust gas temperature or exhaust gas combustible component concentration exceeds the preset range. When an abnormality occurs, corresponding load reduction, holding, purging, or shutdown reconfiguration can be performed.

[0115] In one embodiment of the present invention, under the SOFC-SOEC reversible switching mode, the high-temperature solid oxide battery multi-level bidirectional test control method of the present invention may further include reversible switching control:

[0116] The switching process is broken down into a sequence of task nodes: SOFC steady-state confirmation, load reduction and maintenance, atmosphere transition, thermal state maintenance, switching condition confirmation, electrical interface switching, SOEC steam initiation, and electrolysis current ramp-up. Each task node is configured with corresponding entry and exit conditions. Temperature gradient and hydrogen-oxygen crossover risks are monitored in real time and dynamic interventions are implemented.

[0117] In existing related technologies, reversible switching is mostly performed manually in sequence. The accuracy and safety of the switching sequence are highly dependent on the operator's experience, and the risks of thermal shock and atmosphere crossover are difficult to control effectively. This implementation breaks down the entire switching process into a standardized sequence of task nodes with strict entry / exit conditions, transforming bidirectional switching from "manual sequential operation" to "condition-driven automated node flow." Combined with real-time monitoring of temperature gradients and hydrogen-oxygen crossover risks, the safety and repeatability of the bidirectional switching process can be guaranteed from the control architecture level.

[0118] According to a second aspect of the present invention, a multi-level bidirectional test and control system for high-temperature solid oxide batteries is also provided, for executing the multi-level bidirectional test and control method for high-temperature solid oxide batteries according to any one of the technical solutions in the first aspect of the present invention. The system includes a controller and a test resource layer connected to the controller (wherein the test resource layer and the controller can be connected through an execution interface and a data acquisition interface); the controller includes an object adaptation layer, a task orchestration layer, a safety constraint layer and a data evaluation layer.

[0119] The test resource layer provides underlying physical execution and sensing resources and outputs a real-time set of resource capabilities. For example, the test resource layer can function as an underlying physical execution and sensing unit, which may include resource units such as gas supply, steam generation, heating and insulation, power load, measurement and acquisition, safety execution, and exhaust gas treatment. Each type of resource is abstracted as a resource capability object. The resource capability object should at least include resource type, range, control accuracy, response time, interface type, media compatibility, current occupancy status, and security boundaries, and output a real-time set of resource capabilities. .

[0120] The object adaptation layer is used to establish a compatibility matrix based on the parameters and resource capability set of the object under test, and to generate an initial set of resource control parameters based on the compatibility matrix. For example, the object adaptation layer can be deployed in the controller to obtain parameters of different objects under test. Establish a compatibility matrix between the port of the object under test and the port of the test resource. and based on and Generate initial resource control parameter set The It includes at least gas control parameters, steam control parameters, thermal control parameters, electrical control parameters, sampling control parameters, and safety threshold parameters.

[0121] The task orchestration layer is used to generate a sequence of control instructions consisting of multiple task nodes based on the test objective and the initial resource control parameter set; for example, the task orchestration layer can be used to set the test objective... and Converted to multiple task nodes The constructed control command sequence Each task node At least include control actions Setting parameters Sampling items Entry conditions Exit conditions Exception handling strategy and rating tags .

[0122] The safety constraint layer is used to calculate the risk level based on the real-time collected safety status, and to reconstruct the control command sequence online based on the risk level, outputting the corrected control command sequence to the test resource layer for execution. For example, the safety constraint layer can collect real-time safety status data including hydrogen concentration, oxygen content, pressure difference, dew point, temperature gradient, electrical insulation, and exhaust gas status. Calculate the risk level and based on Current task node , and evaluation vector For control command sequence Perform online reconstruction and output the corrected control command sequence. Execute at the test resource layer.

[0123] The data evaluation layer generates evaluation vectors based on data collected during the testing process and feeds these vectors back to the task orchestration layer and / or the safety constraint layer. For example, the data evaluation layer can evaluate the data collected during the testing process. Time synchronization, steady-state identification, feature extraction, and comprehensive evaluation are performed to form an evaluation vector that includes performance, stability, efficiency, degradation, safety margin, and data reliability. and will As feedback variables, input to the task orchestration layer and / or security constraint layer.

[0124] In this embodiment, it should also be noted that the present invention has the following core technical logic:

[0125] First, cross-level object adaptive adaptation based on capability matrix.

[0126] The object adaptation layer receives parameters such as the level of the object under test, rated power, number of ports, and temperature and pressure boundaries. Then, through the compatibility matrix Determine its compatibility with the current test resource layer capabilities. The system automatically calculates and distributes an initial set of resource control parameters, including those related to gas, steam, heat, electricity, sampling, and safety thresholds, based on the matching relationships between interfaces, media, measurement ranges, and safety boundaries. When resources are insufficient, it outputs downgraded test parameters or an unexecutable message, enabling automatic adaptation across object levels.

[0127] Second, dynamic orchestration of test instructions based on the node model.

[0128] The system transforms the manual testing process into a series of task nodes that can be identified and executed by the controller. Each node contains control actions, setting parameters, sampling items, entry conditions, exit conditions, and exception handling strategies, enabling the test process to be executed, paused, jumped, or reconstructed by the lower-level machine.

[0129] Third, a two-way coordinated control mechanism oriented towards strong coupling of gas, heat, and electricity.

[0130] To address the deep physical coupling characteristics of SOFC / SOEC modes, the system of this invention can incorporate strict coordination control boundaries:

[0131] 1. SOEC steam-electrolysis current linkage. Based on the electrolysis current... Number of battery cells Faraday constant and maximum allowable steam utilization rate Calculate the lower limit of steam molar flow rate When the steam flow rate, dew point, inlet temperature, or pressure conditions do not meet the boundary requirements, the system limits the rise of the electrolysis current.

[0132] 2. SOFC Fuel-Load Coordination. The lower limit of fuel supply is set based on the upper limit of current and fuel utilization, and the flow rate and load are adjusted in real time in conjunction with temperature and pressure differences.

[0133] 3. Smooth SOFC-SOEC reversible switching. The switching process is broken down into task nodes such as load reduction and holding, atmosphere transition, thermal state holding, and steam priority. The risks of thermal shock, pressure shock, and atmosphere crossover during the switching process are reduced by entry and exit conditions.

[0134] Fourth, online reconstruction of control sequences based on multidimensional state observation.

[0135] The security constraint layer is based on real-time collected security status. Assess risk level The risk levels include normal, warning, restricted, and dangerous. The safety constraint layer refactors the current task node and subsequent task nodes according to safety priority; for example, in the warning state, it corrects the set value or reduces the ramp rate, in the restricted state, it inserts a hold or purge node, and in the dangerous state, it triggers an interlock shutdown.

[0136] Fifth, a comprehensive data evaluation mechanism based on multi-source closed-loop feedback.

[0137] The data evaluation layer is not only responsible for recording data It performs steady-state identification and comprehensive performance calculation in real time, and generates evaluation vectors. The evaluation vector is directly used as a feedback variable input to the task orchestration and safety constraint layer. If the evaluation finds that the steady-state performance is not up to standard, the data reliability is insufficient, or there is a risk of degradation, the system will automatically trigger instructions to adjust, such as extending the test time, supplementing the test conditions, or reducing the load, to achieve a deep closed loop between the test process and the evaluation results.

[0138] Sixth, the specific construction of compatibility matrix, risk level and evaluation vector.

[0139] Compatibility Matrix It can be represented as ,in, This indicates the port or control requirements of the object under test. This indicates a test resource port or resource unit; when the interface type, media type, measurement range, response time, and security boundaries all meet the matching conditions... Use the matchable state; otherwise, use the unmatchable state. The object adaptation layer is based on... Select available resources and generate an initial resource control parameter set. .

[0140] Risk level According to the security status Its rate of change is determined. Safety status. This includes hydrogen concentration, oxygen content, combustible gas concentration, inlet and outlet pressure difference, dew point deviation, temperature gradient, electrical insulation, and exhaust gas treatment status. When any parameter reaches the warning threshold, limit threshold, or interlock threshold, the safety constraint layer outputs a warning, limit, or hazard level respectively, and reconstructs the control command sequence accordingly. .

[0141] Evaluation Vector At a minimum, this includes voltage stability, current or power stability, electrical efficiency, steam or fuel utilization rate, temperature gradient, impedance characteristics, attenuation rate, safety margin, and data reliability. The data evaluation layer is based on... Output feedback commands to continue execution, extend steady state, supplement operating conditions, reduce load, limit boundaries, or terminate the test.

[0142] The technical solution of the present invention will be further described below with reference to an exemplary embodiment.

[0143] In this exemplary implementation, please refer to Figures 2 to 7 The high-temperature solid oxide battery multi-level bidirectional test and control system provided by the present invention may include a test resource layer, an object adaptation layer, a task orchestration layer, a safety constraint layer, and a data evaluation layer.

[0144] in, Figure 2 This diagram illustrates the overall system architecture of an exemplary embodiment of the present invention. The system constructs a five-layer core closed-loop architecture: "test resources - object adaptation - task orchestration - security constraints - data evaluation". Specifically, the object adaptation layer stores the parameters of the object under test. With underlying resource capabilities Initial control parameters are generated through fusion. The task orchestration layer will With the test target Transform into an executable sequence of control instructions ; Execution at the underlying resources During the process, the security constraint layer is based on real-time state The sequence is reconstructed online; the data evaluation layer then processes the data. Transform into evaluation vector It also features closed-loop feedback, enabling the transformation of physical testing into a computable and reconfigurable control object.

[0145] Specifically,

[0146] 1. Test the resource layer. Please refer to [link / reference]. Figure 3 This layer can include gas supply resources, steam generation resources, heating and insulation resources, power load resources, measurement and acquisition resources, exhaust gas treatment resources, and safety execution resources. Each type of resource is abstracted as a resource capability object. This includes at least the resource type, measurement range, accuracy, response speed, interface type, media compatibility, current occupancy status, and security boundaries. The test resource layer outputs a set of resource capabilities. It also receives control commands from the upper layer, including control quantities such as gas / steam flow rate, furnace temperature, current and voltage, sampling frequency, and interlocking thresholds.

[0147] exist Figure 3 middle, Figure 3 This diagram illustrates a test resource layer structure according to an exemplary embodiment of the present invention. The diagram reflects the abstraction process from the underlying physical hardware (including actual resource units such as gas, steam, heat, and electricity) to the digital control layer. Each type of physical resource is transformed into a computable resource capability object containing range, accuracy, response, and safety boundaries. Unified output of resource capabilities to external parties It provides a physical constraint base for the adaptive adaptation of upper-layer objects and the issuance of instructions.

[0148] 2. Object Adaptor Layer. Please refer to [link / reference]. Figure 4 It is used to obtain the parameters of the object under test. (At least including object level, number / area of ​​solar cells, rated power / current / voltage, temperature and pressure range, dielectric and safety boundaries), and according to Establish a compatibility matrix between the port of the object under test and the port of the test resource. Based on this matrix, an initial set of resource control parameters is calculated and generated. When resources cannot meet the demand, output resource gap or degradation test parameters.

[0149] exist Figure 4 middle, Figure 4 This document illustrates a flowchart of an exemplary embodiment of the present invention for generating a resource control parameter set in the object adaptation layer. This logic addresses the "island" problem in cross-layer adaptation by establishing a compatibility matrix between object ports and resource ports. This involves combining the customized requirements (level, area, medium, etc.) of multi-level tested objects with currently available resources. Perform automatic verification. If the verification passes, generate a control parameter set. If resources are limited, a downgrade solution is output, avoiding the blindness of manual allocation.

[0150] 3. Task orchestration layer. Please refer to [link / reference]. Figure 5 It is used to test the target (Covering SOFC power generation, SOEC electrolysis, reversible switching, polarization / impedance testing, and durability testing, etc.) Convert to control command sequence .sequence Composed of multiple task nodes Each node consists of at least a control action, setting parameters, sampling items, entry conditions, exit conditions, exception handling strategies, and evaluation labels.

[0151] exist Figure 5 middle, Figure 5 This diagram illustrates the task node structure and control instruction sequence generation of an exemplary embodiment of the present invention. The diagram also clarifies the test objective. How can it be decoupled into a machine-recognizable sequence of instructions? .sequence Composed of multiple independent task nodes The system is composed of interconnected components, with each node strictly encapsulated with control actions, setting parameters, entry conditions, exit conditions, and exception handling strategies. This transforms rigid manual testing procedures into dynamic objects that can be intervened, paused, or skipped by the controller in real time.

[0152] 4. Security Constraint Layer. Please refer to [link / reference]. Figure 6 It is used to collect real-time security status. (Including hydrogen and oxygen concentration, pressure difference, dew point, temperature gradient, and insulation condition, etc.), and calculate the risk level. Based on risk level Online reconstruction generation Normally press Execution; when a warning is issued, the set value is corrected or the ramp rate is reduced; when a limit is imposed, the current node is paused and the node is entered into a hold / purge state; when a danger occurs, the interlock is triggered and emergency cooling is initiated.

[0153] exist Figure 6 middle, Figure 6 A flowchart illustrating the dynamic reconfiguration control instruction sequence for the security constraint layer according to an exemplary embodiment of the present invention is provided. This diagram reveals the system's online defense mechanism against multi-dimensional risks: real-time security status. The risk level is quantified into four levels: normal, warning, restriction, and danger. Based on this level and according to safety priority, the controller performs online reconstruction calculations on the current control command sequence and outputs the corrected command sequence. It achieves multi-level closed-loop protection, from passive alarm to active correction, load reduction or interlocking.

[0154] 5. Data Evaluation Layer. Please refer to [link / reference]. Figure 7 Its collected data Synchronization, cleaning, and feature extraction are performed to form an evaluation vector. (Including performance, stability, degradation and safety margin indicators), and feed them back to the task orchestration layer and safety constraint layer to determine whether to extend the steady state, adjust the operating conditions or terminate the test.

[0155] exist Figure 7 middle, Figure 7 A flowchart illustrating the data evaluation layer feedback control process of an exemplary embodiment of the present invention is shown. (Test data) After time synchronization, steady-state identification, and feature extraction, a comprehensive evaluation vector containing performance and degradation indicators is generated. This vector is not used as an offline report, but is directly injected into the task orchestration and safety constraint module as a control feedback variable, giving the system the ability to autonomously adjust the subsequent test load or duration when the data reliability is insufficient or the steady state is not met.

[0156] Based on the above system, the high-temperature solid oxide battery multi-level bidirectional test control method of the present invention can include the following specific steps:

[0157] Step 1: Obtain the parameters of the object under test .

[0158] Step 2: Obtain the set of test resource capabilities .

[0159] Step 3: According to and Establish a resource compatibility matrix It determines the matching relationship between interface, medium, range, response time, and security boundary, and determines the matching status between each port of the tested object and the port of the test resource.

[0160] Step 4: Based on the compatibility matrix Generate initial resource control parameter set .

[0161] Step 5: Based on the test objective and Generate control command sequence .

[0162] Step 6: Control the execution of the test resource layer And collect process data simultaneously. With safety status .

[0163] Step 7: The security constraint layer is based on Calculate risk level And based on risk level Current task node , and evaluation vector right Online reconstruction was performed to obtain Then it is handed over to the lower level for execution.

[0164] Step 8: Data evaluation layer based on Forming evaluation vectors They will provide feedback and correct subsequent testing strategies.

[0165] In this exemplary embodiment, it should be noted that, for the strongly coupled gas-heat-electricity operating condition, strict coordination control logic can be built in:

[0166] 1. SOEC steam-electrolysis current linkage control (see also) Figure 8 The system is based on the electrolysis current. Number of battery cells Faraday constant and maximum allowable steam utilization rate Constraint steam molar flow rate setpoint satisfy ( (This is the safety margin factor). When the steam flow rate, dew point, inlet temperature, or pressure condition does not meet the boundary conditions, the safety constraint layer limits the current ramp-up and generates hold, limit, or purge reconfiguration commands.

[0167] exist Figure 8 middle, Figure 8 This diagram illustrates an exemplary embodiment of the SOEC steam-electrolysis current linkage control system according to the present invention. Addressing the strong gas-electric coupling characteristics in electrolysis mode, the system establishes a constraint relationship between steam flow rate and electrolysis current, ensuring that the steam molar flow rate setpoint... satisfy When steam supply is limited, dew point deviates, inlet temperature is insufficient, or pressure is abnormal, the safety constraint layer limits or reduces the electrolysis current setpoint and can insert a hold or purge node.

[0168] 2. SOFC Fuel-Load Coordination Control: The system calculates the lower limit of fuel supply based on current, number of cells, and upper limit of fuel utilization, and adjusts flow rate and electronic load according to reactor temperature, anode pressure difference, and load change rate. In case of anomalies, the safety layer performs load reduction or shutdown reconfiguration.

[0169] 3. SOFC-SOEC reversible switching control (see also) Figure 9 The task orchestration layer breaks down the switching process into task nodes with strict entry / exit conditions, such as SOFC steady-state confirmation, load reduction and maintenance, atmosphere transition, thermal state maintenance, switching condition confirmation, electrical interface switching, SOEC steam first, and electrolysis current ramp-up; while the safety constraint layer monitors the temperature gradient and hydrogen-oxygen crossover risk in real time and intervenes dynamically.

[0170] exist Figure 9 middle, Figure 9 This diagram illustrates an exemplary embodiment of the SOFC-SOEC reversible switching control system of the present invention. The system discretizes the bidirectional switching process into a sequence of time nodes, including steady-state confirmation, load reduction, atmosphere transition, and electrical switching. During the transition, the controller calculates the temperature gradient, pressure difference, dew point deviation, and hydrogen-oxygen crossover risk, and uses these safety indicators as entry or exit conditions for node transition, thereby reducing thermal shock and safety risks during switching operations.

[0171] The following are examples of several typical test scenarios.

[0172] Example 1: Electrolytic testing of SOEC stack-level cells.

[0173] The object adaptation layer reads the number of fuel cell stack plates, effective area, and differential pressure boundary to generate initial parameters. The task orchestration layer generates nodes for preheating, purging, steam introduction, and current step. During execution, if the dew point falls below the set lower limit, the safety constraint layer will automatically limit the current and force the system to enter a holding node.

[0174] Example 2: Module-level SOFC power generation test.

[0175] The object adaptation layer generates fuel / air flow and exhaust gas treatment parameters based on module power, fuel type, and thermal management method. The task orchestration layer generates open-circuit stable, step-by-step loading, and dynamic response nodes. The data evaluation layer evaluates the test based on electrical efficiency and temperature gradient, and feeds back abnormal results to subsequent step nodes.

[0176] Example 3: Bidirectional switching test of the same object.

[0177] The system first completes SOFC steady-state verification, then reduces the load and transitions to a different atmosphere according to the temperature gradient conditions; after fully meeting the dew point, differential pressure, and electrical interface conditions, it switches to SOEC mode. Throughout the switching process, the safety constraint layer monitors for temperature shocks and reverse current risks and can dynamically insert purge nodes.

[0178] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A multi-level bidirectional test and control method for high-temperature solid oxide batteries, characterized in that, Includes the following steps: Obtain the parameters of the object under test; Acquire a set of test resource capabilities; A resource compatibility matrix is ​​established based on the parameters of the object under test and the set of test resource capabilities. The matching relationship of interface, medium, range, response time and security boundary is determined, and the matching status between each port of the object under test and the port of the test resource is determined. An initial resource control parameter set is generated based on the compatibility matrix; Generate a sequence of control instructions based on the test objective and the initial resource control parameter set; The control test resource layer executes the control command sequence and synchronously collects process data and security status. The risk level is calculated based on the security status, and the control instruction sequence is reconstructed online based on the risk level, the current task node, the initial resource control parameter set, and the evaluation vector. The corrected control instruction sequence is then handed over to the underlying layer for execution. The evaluation vector is formed based on the process data, and feedback is used to correct subsequent testing strategies.

2. The high-temperature solid oxide battery multi-level bidirectional test and control method according to claim 1, characterized in that, A resource compatibility matrix is ​​established based on the parameters of the object under test and the set of test resource capabilities, specifically including: A compatibility matrix is ​​constructed by using each port or control requirement of the tested object in the parameters of the tested object as a row element of the matrix, and each test resource port or resource unit in the test resource capability set as a column element of the matrix. ; When the The port or control requirements of the tested object are related to the first When each test resource port or resource unit meets the matching conditions in terms of interface type, media type, measurement range, response time, and security boundaries... Take the matchable state; otherwise, take the unmatchable state.

3. The high-temperature solid oxide battery multi-level bidirectional test and control method according to claim 1, characterized in that, An initial resource control parameter set is generated based on the compatibility matrix, specifically including: Based on the compatibility matrix, available resources are selected, and an initial resource control parameter set is generated. The initial resource control parameter set It includes at least gas control parameters, steam control parameters, thermal control parameters, electrical control parameters, sampling control parameters, and safety threshold parameters; When resources are insufficient, output downgraded test parameters or an unexecutable message.

4. The high-temperature solid oxide battery multi-level bidirectional test control method according to claim 1, characterized in that, Based on the test objective and the initial resource control parameter set, a sequence of control instructions is generated, specifically including: Test target and initial resource control parameter set Converted to multiple task nodes The constructed control command sequence ; Each task node At least include control actions Setting parameters Sampling items Entry conditions Exit conditions Exception handling strategy and rating tags .

5. The high-temperature solid oxide battery multi-level bidirectional test and control method according to claim 1, characterized in that, The risk level is calculated based on the security status, and the control command sequence is reconstructed online based on the risk level, the current task node, the initial resource control parameter set, and the evaluation vector. Specifically, this includes: Real-time collection of security status The security status This includes hydrogen concentration, oxygen content, combustible gas concentration, inlet and outlet pressure difference, dew point deviation, temperature gradient, electrical insulation, and exhaust gas treatment status. According to the security status Risk level is determined by its rate of change. The risk levels include normal, warning, restricted, and dangerous. When any safety status parameter reaches the warning threshold, the warning level is output and the set value is corrected or the ramp rate is reduced. When any safety status parameter reaches the limit threshold, the limit level is output and a hold node or purge node is inserted; When any safety status parameter reaches the interlocking threshold, the danger level is output and the interlocking shutdown is triggered; Reconstruct the current task node and subsequent task nodes according to safety priority, and output the corrected control instruction sequence. .

6. The high-temperature solid oxide battery multi-level bidirectional test and control method according to claim 1, characterized in that, The evaluation vector is formed based on the process data, and feedback is used to correct subsequent testing strategies, specifically including: Data collected during the testing process Time synchronization, steady-state identification, feature extraction, and comprehensive evaluation are performed to form an evaluation vector. The evaluation vector At a minimum, it includes voltage stability, current or power stability, electrical efficiency, steam utilization or fuel utilization, temperature gradient, impedance characteristics, attenuation rate, safety margin, and data reliability. The evaluation vector As feedback variables, input to the task orchestration layer and / or security constraint layer; According to the evaluation vector Output feedback commands to continue execution, extend steady state, supplement operating conditions, reduce load, limit boundaries, or terminate the test.

7. The high-temperature solid oxide battery multi-level bidirectional test control method according to claim 1, characterized in that, In SOEC electrolysis mode, the multi-level bidirectional test control method for high-temperature solid oxide batteries also includes steam-electrolysis current linkage control: According to the electrolysis current Number of battery cells Faraday constant and maximum allowable steam utilization rate Constraint steam molar flow rate setpoint satisfy: ,in, For safety margin coefficient and ; When the steam flow rate, dew point, inlet temperature, or pressure conditions do not meet the boundaries, the electrolysis current ramp-up is limited, generating hold, limit, or purge reconfiguration commands.

8. The high-temperature solid oxide battery multi-level bidirectional test control method according to claim 1, characterized in that, In SOFC power generation mode, the high-temperature solid oxide battery multi-level bidirectional test control method also includes fuel-load coordination control: The lower limit of fuel supply is calculated based on current, number of solar cells, and upper limit of fuel utilization rate. Fuel flow and electronic load are adjusted based on reactor temperature, anode pressure differential, and load change rate. If an anomaly occurs, perform a load reduction or shutdown and refactoring.

9. The high-temperature solid oxide battery multi-level bidirectional test control method according to claim 1, characterized in that, In the SOFC-SOEC reversible switching mode, the high-temperature solid oxide battery multi-level bidirectional test control method also includes reversible switching control: The switching process is broken down into a sequence of task nodes: SOFC steady-state confirmation, load reduction and holding, atmosphere transition, thermal state holding, switching condition confirmation, electrical interface switching, SOEC steam initiation, and electrolysis current ramp-up. Each task node is configured with corresponding entry and exit conditions; Real-time monitoring of temperature gradients and the risk of hydrogen-oxygen crossover, and dynamic intervention.

10. A multi-level bidirectional test and control system for high-temperature solid oxide batteries, characterized in that, The system is used to perform the multi-level bidirectional test control method for high-temperature solid oxide batteries according to any one of claims 1-9, the system comprising a controller and a test resource layer connected to the controller; the controller comprises an object adaptation layer, a task orchestration layer, a safety constraint layer and a data evaluation layer; The test resource layer is used to provide underlying physical execution and perception resources, and outputs a real-time set of resource capabilities to the outside world; The object adaptation layer is used to establish a compatibility matrix based on the parameters of the object under test and the resource capability set, and to generate an initial resource control parameter set based on the compatibility matrix; The task orchestration layer is used to generate a sequence of control instructions consisting of multiple task nodes based on the test objective and the initial resource control parameter set. The security constraint layer is used to calculate the risk level based on the real-time collected security status, and to reconstruct the control command sequence online based on the risk level, and output the corrected control command sequence to the test resource layer for execution; The data evaluation layer is used to generate an evaluation vector based on the data collected during the testing process, and to feed the evaluation vector back to the task orchestration layer and / or the security constraint layer.

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