A multi-stack solid oxide fuel cell system equalization control method based on operating expenditure function

Abstract

The application provides a kind of based on operating expenditure function's multiple stack solid oxide fuel cell system equalization control method, belongs to fuel cell system control and energy management technical field.According to the load demand in combination with the operation observation information of multiple stack solid oxide fuel cell system, with the stack operating expenditure minimization of multiple stack solid oxide fuel cell system as optimization goal, the total gas amount entering multiple stack solid oxide fuel cell system is determined by iterative solution;The power adjustment direction of each stack is determined based on the operation observation information of multiple stack solid oxide fuel cell system through preset fuzzy rule, and the power distribution ratio of each stack is corrected by combining multiple factor comprehensive score function, to determine the final power distribution ratio of each stack.This method solves the power distribution of each stack by fuzzy control combined with stack operating expenditure optimization, significantly reduces the stack temperature deviation, fuel utilization deviation and TPB degradation deviation, and reduces the inconsistency.

Description

Technical Field

[0001] This invention relates to the field of fuel cell system control and energy management technology, and in particular to a method for equalization control of multi-stack solid oxide fuel cell systems based on operating expenditure functions. Background Technology

[0002] As marine propulsion systems evolve towards low-carbon and hydrogen-based technologies, high-temperature solid oxide fuel cells (SOFCs) are considered a crucial next-generation marine energy solution due to their high efficiency, fuel flexibility, and suitability for megawatt-scale expansion. However, limited by single-stack power ratings and engineering manufacturing constraints, marine SOFC systems typically employ parallel or modular integration of multiple stacks to achieve high power output. Nevertheless, during long-term operation, multi-stack systems inevitably encounter the following problems: manufacturing variations lead to deviations in the initial microstructure and material properties of each stack; uneven gas distribution results in different reaction environments for each stack; and thermal coupling causes alternating periods of localized overheating and cold. These factors cause continuous differences in temperature, fuel utilization, electrochemical performance, and degradation rates among the stacks, resulting in multi-stack inconsistencies. These inconsistencies have a cumulative amplification characteristic, ultimately leading to premature failure of some stacks and limiting the overall system lifespan and economic viability.

[0003] In existing technologies, multi-stack systems commonly employ power sharing or simple state feedback allocation strategies. These methods fail to consider the inherent coupling between efficiency, lifetime, and operating costs, and cannot effectively suppress inconsistency evolution during long-term operation.

[0004] Therefore, there is an urgent need to propose a multi-stacking equalization control method that takes into account economy, efficiency and degradation suppression. Summary of the Invention

[0005] In view of this, the present invention provides a balanced control method for a multi-stack solid oxide fuel cell system based on an operating expenditure function. By constructing an optimal operating domain under operating cost constraints and combining fuzzy decision-making and cost correction mechanisms, the method achieves the following: transforming the strong coupling relationship between multivariable inputs and system performance into a controllable operating domain of temperature and fuel utilization; dynamically adjusting the direction and amplitude of power transfer between stacks based on stack degradation state and gas supply differences; effectively suppressing the accumulation of inconsistencies in the temperature field, reaction zone, and degradation process of multiple stacks; improving the overall system efficiency, extending lifespan, and reducing unit power generation costs.

[0006] Therefore, the present invention provides the following technical solution:

[0007] A method for equalization control of a multi-stack solid oxide fuel cell system based on an operating expenditure function includes: Based on the load demand and the operational observation information of the multi-stack solid oxide fuel cell system, with the optimization objective of minimizing the stack operating expenditure of the multi-stack solid oxide fuel cell system, the total gas volume entering the multi-stack solid oxide fuel cell system is determined by iterative solution. Based on the operational observation information of the multi-stack solid oxide fuel cell system, the power adjustment direction of each stack is determined by a preset fuzzy rule, and the power allocation ratio of each stack is corrected by a multi-factor comprehensive scoring function to determine the final power allocation ratio of each stack.

[0008] Furthermore, the operational observation information includes: Temperature of each fuel cell stack, fuel flow rate of each fuel cell stack, and degradation status of each fuel cell stack.

[0009] Furthermore, the stack operating expenses of the multi-stack solid oxide fuel cell system include:

[0010] in, For multi-stack solid oxide fuel cell systems Operating expenses; This refers to the unit price of a hydrogen SOFC fuel cell stack. This refers to the hydrogen flow rate; This indicates the unit price of a flat-plate SOFC stack; Indicates the effective three-phase interface of the hydrogen electrode initial value, express The derivative with respect to time; This refers to the stack power.

[0011] Furthermore, the iterative solution is performed under constraints; the constraints include: The fuel cell stack temperature is less than or equal to the preset fuel cell stack temperature threshold. The combustion chamber temperature is less than or equal to the preset combustion chamber temperature threshold. The temperature difference between the fuel and air inlet of the fuel stack is less than or equal to a preset temperature threshold. The fuel utilization rate is within a preset range.

[0012] Furthermore, the total gas volume entering the multi-stack solid oxide fuel cell system is determined through iterative solution, including: The solution space is represented as:

[0013] in, Represent the solution space; This refers to the temperature of the fuel cell stack. For fuel utilization rate; The amount of air entering the multi-stack solid oxide fuel cell system is determined based on the stack temperature using proportional-integral control. The opening degree of the bypass valve is determined based on the temperature of the fuel cell stack using proportional-integral control. The amount of hydrogen entering the multi-stack solid oxide fuel cell system is determined based on the fuel utilization rate.

[0014] Furthermore, based on the operational observation information of the multi-stack solid oxide fuel cell system, the power adjustment direction of each stack is determined through preset fuzzy rules, including: Using the relative degradation degree of each fuel cell stack and the proportion of fuel flow as input variables, the fuzzy controller outputs the power adjustment direction of each fuel cell stack based on preset fuzzy rules; The relative degradation degree of the target stack is the ratio of the degradation state of the target stack to the degradation state of all stacks in the multi-stack solid oxide fuel cell system; The target stack's fuel flow rate ratio is the ratio of the target stack's fuel flow rate to the total fuel flow rate of the multi-stack solid oxide fuel cell system.

[0015] Furthermore, the step of combining a multi-factor comprehensive scoring function to correct the power allocation ratio of each stack and determine the final power allocation ratio of each stack includes: The numerical difference method is used to calculate the fuel cell stack. The marginal cost is expressed by the formula:

[0016] in, This represents the marginal cost of the fuel cell stack. This refers to the stack of a multi-stack solid oxide fuel cell system. Operating expenses; For fuel cell stack The power; Construct a multi-factor comprehensive scoring function, the formula of which is:

[0017] in, For fuel cell stack Corrected rating; Marginal cost; Positive constants to avoid numerical singularity; Indicates fuel cell stack Degenerate state; Indicates the percentage of fuel flow; For cost weighting, For degenerate weights, Fuel weight; The initial power allocation ratio is corrected based on a multi-factor comprehensive scoring function, and the power allocation for each stack is determined by the following formula:

[0018] in, To correct the power distribution ratio of the fuel cell stack, To correct the previous stack power allocation ratio; The corrected power allocation ratio of the fuel cell stack is normalized to determine the final power allocation ratio, expressed by the following formula:

[0019] in, For fuel cell stack Final power allocation ratio; This represents the total number of fuel cells.

[0020] Furthermore, the weight parameters of the multi-factor comprehensive scoring function are adjusted through a dynamic weight adjustment mechanism based on a preset reference support, including:

[0021] in, Operating expenses for multi-stack solid oxide fuel cell systems, For preset reference expenditures, Update the weighting factor. To adjust the gain.

[0022] Advantages and positive effects of the present invention: This method allocates power to each fuel cell stack through fuzzy control and optimization, significantly reducing stack temperature deviation, fuel utilization deviation, and TPB degradation deviation, resulting in an overall inconsistency reduction of approximately 78%–87%. This, in turn, improves overall system performance, achieving an overall increase of approximately 15%–30% in system efficiency, cumulative power generation, and equivalent lifetime. Furthermore, this method makes decisions while minimizing operating costs, resulting in significant optimization of system operating costs.

[0023] This method employs progressive fuzzy-cost collaborative control, which does not rely on complex model predictive control. It features a clear control structure, low computational burden, and strong engineering feasibility. Furthermore, this method exhibits good robustness to manufacturing variations and operational disturbances, making it suitable for ships and large-scale distributed hydrogen energy systems. Attached Figure Description

[0024] 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 or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a framework diagram of a balanced control method for multi-stack solid oxide fuel cell systems based on operating expenditure functions; Figure 2 This is a process flow diagram for a solid oxide fuel cell system. Figure 3 A diagram of a large-scale integrated energy system for ships based on solid oxide fuel cells; Figure 4 This diagram illustrates the power allocation of the fuel cell stack under different allocation strategies; EPA represents equal power distribution, FPA represents fuzzy power allocation only, and FCC represents the fuzzy-cost coordinating strategy proposed in the scheme. Figure 5 A schematic diagram illustrating the dynamic response of PEN temperature and its inconsistent characteristics under different allocation strategies; Figure 6 A schematic diagram illustrating the dynamic response of fuel utilization rate (FU) and its inconsistent characteristics under different allocation strategies; Figure 7 Dynamic response to the three-phase interface TPB and its inconsistency characteristics under different allocation strategies; Figure 8 A diagram showing the comparison of normalized system performance indicators under different control strategies; Figure 9 This is a diagram illustrating the relative system performance improvements under the EPA strategy. Figure 10 This diagram illustrates the comprehensive evaluation of system performance improvement under three strategies for different operating conditions. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] This invention provides a method for equalization control of a multi-stack solid oxide fuel cell system based on an operating expenditure function, comprising: Based on load demand and operational observation information of multi-stack solid oxide fuel cell system, with minimizing stack operating expenses of multi-stack solid oxide fuel cell system as optimization objective, the total gas volume entering multi-stack solid oxide fuel cell system is determined by iterative solution. Based on the operational observation information of the multi-stack solid oxide fuel cell system, the power adjustment direction of each stack is determined by a preset fuzzy rule, and the power allocation ratio of each stack is corrected by a multi-factor comprehensive scoring function to determine the final power allocation ratio of each stack.

[0029] Combination Figure 1 As shown, a method for equalization control of a multi-stack solid oxide fuel cell system based on an operating expenditure function includes: 1. Collect operational observation information, including: temperature of each fuel cell stack, fuel flow rate of each fuel cell stack, and degradation status of each fuel cell stack.

[0030] 2. Based on the load demand and the operational observation information of the multi-stack solid oxide fuel cell system, with the optimization objective of minimizing the stack operating expenses of the multi-stack solid oxide fuel cell system, the total gas volume entering the multi-stack solid oxide fuel cell system is determined through iterative solution. 1) Stack operating expenses of multi-stack solid oxide fuel cell systems:

[0031] in, For multi-stack solid oxide fuel cell systems Operating expenses; This refers to the unit price of a hydrogen SOFC fuel cell stack. This refers to the hydrogen flow rate; This indicates the unit price of a flat-plate SOFC stack; Indicates the effective three-phase interface of the hydrogen electrode initial value, express The derivative with respect to time; This refers to the stack power.

[0032] The iterative solution is performed under constraints; the constraints include: The fuel cell stack temperature is less than or equal to the preset fuel cell stack temperature threshold. The combustion chamber temperature is less than or equal to the preset combustion chamber temperature threshold. The temperature difference between the fuel and air inlet of the fuel stack is less than or equal to a preset temperature threshold. The fuel utilization rate is within a preset range.

[0033] The solution space obtained by iterative solution is represented as:

[0034] in, Represent the solution space; This refers to the temperature of the fuel cell stack. Fuel utilization rate.

[0035] The amount of air entering the multi-stack solid oxide fuel cell system is determined based on the stack temperature using proportional-integral control; the opening degree of the bypass valve is determined based on the stack temperature using proportional-integral control; and the amount of hydrogen entering the multi-stack solid oxide fuel cell system is determined based on fuel utilization rate.

[0036] 3. Based on the operational observation information of the multi-stack solid oxide fuel cell system, the power adjustment direction of each stack is determined by pre-set fuzzy rules.

[0037] Using relative degradation and fuel flow rate as input variables, the fuzzy controller outputs the adjustment direction of each fuel cell stack.

[0038] Relative degree of degradation:

[0039] in, Indicates fuel cell stack Degenerate state, with the denominator being the sum of the total number of degenerate states across multiple clusters; For fuel cell stack The relative degree of degradation; Fuel flow percentage:

[0040] in, Indicates fuel cell stack fuel flow rate, This represents the total fuel flow rate of the system. For fuel cell stack The percentage of fuel flow.

[0041] Power allocation ratio:

[0042] in, For fuel cell stack The power allocation ratio; Heap power, This represents the total power of the system.

[0043] Relative degree of degradation , set as Fuel flow rate percentage Set as Power allocation ratio The fuzzy rules are shown in Table 1: Table 1

[0044] 4. The power allocation ratio of each fuel cell stack is adjusted by combining a multi-factor comprehensive scoring function to determine the final power allocation ratio of each fuel cell stack: 1) The numerical difference method is used to calculate the fuel cell stack. The marginal cost, reflecting the increase in operating expenses resulting from the additional power provided by the fuel cell stack, is expressed by the formula:

[0045] in, This represents the marginal cost of the fuel cell stack. This indicates the power generation cost of a multi-stack solid oxide fuel cell system; For fuel cell stack The power.

[0046] 2) A multi-factor comprehensive scoring function is constructed based on the stack degradation state and fuel ratio to suppress the inconsistent evolution of multiple stacks. The formula is expressed as:

[0047] in, For fuel cell stack Corrected rating; Marginal cost; Positive constants to avoid numerical singularity; Indicates the degraded state of the fuel cell stack, i.e. ; Indicates the percentage of fuel flow; For cost weighting, For degenerate weights, Fuel weight.

[0048] 3) Based on the multi-factor comprehensive scoring function, the power allocation ratio of the fuzzy layer output is corrected to determine the power allocation of each stack. The formula is as follows:

[0049] in, To correct the power distribution ratio of the fuel cell stack, To correct the previous stack power distribution ratio; 4) Normalize the corrected power allocation ratio of the fuel cell stack to determine the final power allocation ratio, expressed by the formula:

[0050] in, For fuel cell stack Final power allocation ratio; This represents the total number of fuel cells.

[0051] 5) By using a dynamic weight adjustment mechanism, the adaptability of the control strategy under different operating conditions is enhanced. The formula is expressed as:

[0052] in, For the current operating expenses of the system, For preset reference expenditures, This is a weight update factor used to limit the rate of weight change to avoid frequent switching of power allocation. To adjust the gain.

[0053] Example like Figure 2 and Figure 3 As shown, the equalization control method for multi-stack solid oxide fuel cell systems based on operating expenditure functions is applied to the realization process of integrated ship energy, including: 1. In this embodiment, the specific constraints are as follows:

[0054]

[0055]

[0056]

[0057] in, Indicates the combustion chamber temperature. This refers to the temperature difference between the fuel in the fuel cell stack and the air inlet. This refers to the temperature of the fuel cell stack. Fuel utilization rate.

[0058] The solution space obtained by iterative solution is represented as:

[0059] in, Represent the solution space; This refers to the temperature of the fuel cell stack. Fuel utilization rate.

[0060] 2. In this embodiment, the relative degradation degree of each fuel cell stack and the proportion of fuel flow rate are used as input variables. A fuzzy controller outputs the power adjustment direction of each fuel cell stack based on preset fuzzy rules, including: Relative degree of degradation , set as Fuel flow rate percentage Set as Power allocation ratio ;in, ND represents negative, ZD represents zero, and PD represents positive. L2 indicates negative large (very low), L1 indicates low, EQ indicates equal, H1 indicates high, and H2 indicates very high. The meanings of LM, LP, ZO, HP, and HM are the same as above, except that they have different symbols to distinguish them: negative middle, negative small, hold, positive small, and positive middle, respectively. Fuzzy control uses a Gaussian membership function, and the parameter settings are shown in Table 2. Table 2

[0061] 3. In this embodiment, the preset reference expenditure is: , Calculated under rated load and slight degradation conditions.

[0062] Experiments were conducted to demonstrate the effectiveness of this method in suppressing inconsistencies between fuel cells and improving overall system performance. This paper compares and analyzes equal power allocation (EPA), fuzzy power allocation (FPA), and the proposed method (FCC). EPA and FPA are limited to controlling power allocation only. Figures 4-7 Starting from key internal states such as power distribution status, PEN temperature, fuel utilization rate, and TPB degradation, this study reveals the effect of different strategies on the regulation and balancing of inconsistencies between fuel cells.

[0063] Figure 4As shown: Under the EPA strategy, the two fuel cell stacks always bear approximately the same power output, and the system lacks the ability to perceive and adjust for differences in stack status. The FPA strategy begins to redistribute power based on the stack operating status, allowing the stack in better condition to bear a higher load, while the stack with a faster degradation trend receives some power mitigation. This method introduces marginal cost to perform a secondary correction for the inconsistency between stacks, so that power allocation not only responds to the state of a single stack, but also coordinates and regulates the distribution. The method employs FU (Power Activation) to suppress the widening of inter-reactor differences. Power trajectories reveal that this approach achieves smoother and more consistent power adjustments while avoiding drastic power fluctuations, providing a fundamental guarantee for subsequent state evolution.

[0064] Figure 5 As shown: Under the EPA strategy, the temperature trajectories of the two fuel cell stacks gradually diverged. As operating time continues to increase, the temperature inconsistency reaches the 20–30 K range during long-term operation, indicating that the EPA strategy cannot suppress thermal state differentiation. The FPA strategy significantly improves this problem, limiting temperature inconsistency to approximately 5–8 K, demonstrating that state-aware power allocation can effectively mitigate the accumulation of thermal deviations. However, this strategy still does not fundamentally prevent the evolution of inconsistency. In contrast, this method will […]. The temperature was compressed to below 2–3 K and exhibited significant convergence characteristics. This result demonstrates that by explicitly introducing uniformity constraints in power allocation, the long-term amplification effect of thermal inconsistencies can be significantly mitigated.

[0065] Figure 6 As shown: Under the FPA strategy, the fuel utilization rates of the two reactors gradually deviate over time, resulting in inconsistency. FU In the later stages, this can reach 15–20%, indicating that even with power distribution, a significant imbalance in reaction load still occurs among the stacks. The FPA strategy, through adaptive power adjustment, will... FU This reduces the fuel utilization rate to approximately 5–8%, demonstrating an initial ability to mitigate the problem of uneven fuel distribution. This method brings the fuel utilization rates of the two reactors almost identical. FU Maintaining the concentration within 2–3% for an extended period significantly improves reaction load consistency, creating favorable conditions for the long-term stable operation of the fuel cell stack.

[0066] Figure 7 As shown: TPB inconsistency under EPA strategy The effect increases over time, reaching 10 at the end of its lifespan. 4The inconsistency is on the order of m² / m³, reflecting significant degradation and differentiation. The FPA strategy has slowed this trend to some extent, keeping the TPB inconsistency within the range of (4–6) × 10³ m² / m³, but a significant long-term cumulative effect still exists. In contrast, this method will... The stability is maintained at approximately 2–3 × 10³ m² / m³, and it exhibits slow evolution characteristics, indicating that it has achieved a fundamental suppression of inconsistency at the degradation level.

[0067] To comprehensively evaluate system performance under different strategies, a performance evaluation and relative gain analysis were conducted using six indicators: Cumulative Power Generation (CPG), lifetime, sub-repositories (repository 1 and repositories 2), system energy weighted average efficiency (EWAE), and cost-performance (C / P). The results are as follows: Figure 8 and Figure 9 As shown.

[0068] The system performance gains of FPA and our proposed method were quantified using the EPA strategy as a benchmark. The results show that, compared to the equal-distribution strategy, the EPA strategy can improve CPG and system lifetime by approximately 15–18%; our proposed method further expands the improvement to 20–25%, demonstrating optimal energy output over the entire lifecycle. Regarding energy efficiency indicators, the EPA strategy achieves better single-reactor energy efficiency (…). It has a slight advantage in terms of energy efficiency, but at the system level... This method is not optimal. Although it sacrifices some instantaneous energy efficiency per unit, it improves the overall system energy efficiency by about 3-5%, demonstrating the system optimization characteristic of prioritizing balance. In terms of economics, the normalization rule maps low cost to high score, and performs a reverse mapping on unit cost (1 The norm, or Cost-Performance ratio, shows that the pump method achieves approximately 20% improvement in unit power generation cost compared to the EPA strategy, significantly outperforming the simple FPA strategy. This result indicates that inconsistency mitigation is not only a reliability issue but also directly determines the long-term economics of the system.

[0069] Figure 10 As shown: In the three sets of working conditions: Figure 10 (a) is inconsistent regardless of the single structure (CTRL Group-0); Figure 10 (b) Inconsistent for a single run (CTRL Group-1); Figure 10 (c) is a composite inconsistency (Exp Group-2).

[0070] The EPA strategy exhibits significant limitations when structural or operational inconsistencies exist. It struggles to balance performance and economy under multiple inconsistencies. The FPA strategy can adaptively adjust power based on system operating conditions, effectively reducing single-reactor efficiency differences across all operating conditions, but still requires trade-offs in unit cost and lifetime.

[0071] This method exhibits optimal overall performance under all three operating conditions. This method can simultaneously improve... The study considers CPG and lifetime while maintaining a minimum radius in the unit cost dimension. This indicates that by introducing a correction mechanism to further constrain fuzzy decision-making, synergistic optimization among multiple objectives can be effectively achieved.

[0072] This method increases the cost weight to enhance economic efficiency when system operating costs are high; and increases the degradation weight to prioritize suppressing inter-stall differences when inconsistencies between stacks increase. Through this fuzzy-cost progressive collaborative control mechanism, adaptive adjustment of power allocation direction and intensity is achieved, thereby supporting the long-term coordinated operation of multiple stacks.

[0073] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for equalization control of a multi-stack solid oxide fuel cell system based on an operating expenditure function, characterized in that, include: Based on the load demand and the operational observation information of the multi-stack solid oxide fuel cell system, with the optimization objective of minimizing the stack operating expenditure of the multi-stack solid oxide fuel cell system, the total gas volume entering the multi-stack solid oxide fuel cell system is determined by iterative solution. Based on the operational observation information of the multi-stack solid oxide fuel cell system, the power adjustment direction of each stack is determined by a preset fuzzy rule, and the power allocation ratio of each stack is corrected by a multi-factor comprehensive scoring function to determine the final power allocation ratio of each stack.

2. The method according to claim 1, characterized in that, The operational observation information includes: Temperature of each fuel cell stack, fuel flow rate of each fuel cell stack, and degradation status of each fuel cell stack.

3. The method according to claim 1, characterized in that, The stack operating expenses of the multi-stack solid oxide fuel cell system include: in, For multi-stack solid oxide fuel cell systems Operating expenses; This refers to the unit price of a hydrogen SOFC fuel cell stack. This refers to the hydrogen flow rate; This indicates the unit price of a flat-plate SOFC stack; Indicates the effective three-phase interface of the hydrogen electrode initial value, express The derivative with respect to time; This refers to the stack power.

4. The method according to claim 3, characterized in that, The iterative solution is performed under constraints; the constraints include: The fuel cell stack temperature is less than or equal to the preset fuel cell stack temperature threshold. The combustion chamber temperature is less than or equal to the preset combustion chamber temperature threshold. The temperature difference between the fuel and air inlet of the fuel stack is less than or equal to a preset temperature threshold. The fuel utilization rate is within a preset range.

5. The method according to claim 1, characterized in that, The total gas volume entering the multi-stack solid oxide fuel cell system is determined through iterative solution, including: The solution space is represented as: in, Represent the solution space; This refers to the temperature of the fuel cell stack. For fuel utilization rate; The amount of air entering the multi-stack solid oxide fuel cell system is determined based on the stack temperature using proportional-integral control. The opening degree of the bypass valve is determined based on the temperature of the fuel cell stack using proportional-integral control. The amount of hydrogen entering the multi-stack solid oxide fuel cell system is determined based on the fuel utilization rate.

6. The method according to claim 1, characterized in that, Based on the operational observation information of the multi-stack solid oxide fuel cell system, the power adjustment direction of each stack is determined through preset fuzzy rules, including: Using the relative degradation degree of each fuel cell stack and the proportion of fuel flow as input variables, the fuzzy controller outputs the power adjustment direction of each fuel cell stack based on preset fuzzy rules; The relative degradation degree of the target stack is the ratio of the degradation state of the target stack to the degradation state of all stacks in the multi-stack solid oxide fuel cell system; The target stack's fuel flow rate ratio is the ratio of the target stack's fuel flow rate to the total fuel flow rate of the multi-stack solid oxide fuel cell system.

7. The method according to claim 2, characterized in that, The process of adjusting the power allocation ratio of each fuel cell stack using a multi-factor comprehensive scoring function to determine the final power allocation ratio of each stack includes: The numerical difference method is used to calculate the fuel cell stack. The marginal cost is expressed by the formula: in, This represents the marginal cost of the fuel cell stack. This refers to the stack of a multi-stack solid oxide fuel cell system. Operating expenses; For fuel cell stack The power; Construct a multi-factor comprehensive scoring function, the formula of which is: in, For fuel cell stack Corrected rating; Marginal cost; Positive constants to avoid numerical singularity; Indicates fuel cell stack Degenerate state; Indicates the percentage of fuel flow; For cost weighting, For degenerate weights, Fuel weight; The initial power allocation ratio is corrected based on a multi-factor comprehensive scoring function, and the power allocation for each stack is determined by the following formula: in, To correct the power distribution ratio of the fuel cell stack, To correct the previous stack power allocation ratio; The corrected power allocation ratio of the fuel cell stack is normalized to determine the final power allocation ratio, expressed by the following formula: in, For fuel cell stack Final power allocation ratio; This represents the total number of fuel cells.

8. The method according to claim 7, characterized in that, The weight parameters of the multi-factor comprehensive scoring function are adjusted according to a preset reference support through a dynamic weight adjustment mechanism, including: in, Operating expenses for multi-stack solid oxide fuel cell systems, For preset reference expenditures, Update the weighting factor. To adjust the gain.

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