Time-varying adaptive asymptotic temperature control method for fuel cell thermal management system

Abstract

The invention discloses a time-varying self-adaptive asymptotic temperature control method for a fuel cell thermal management system, and the method comprises the following steps: S1, building a control-oriented multiple-input multiple-output thermal management system model based on the inlet and outlet temperatures of an electric pile, the double-circulation temperature dynamics and the internal heat exchange process of the system; s2, designing a novel time-varying command filter and introducing the novel time-varying command filter into a backstepping control framework in order to achieve a target of presetting temperature tracking error convergence time; s3, environment and system parameter perturbation are considered, a time-varying error compensator based on a smoothing sign function is combined, and a dual-channel time-varying self-adaptive asymptotic temperature tracking controller is provided to process unknown perturbation and compensate filtering errors; s4, selecting a proper Lyapunov function to prove that a closed-loop system is stable, and the temperatures at the inlet and the outlet of the galvanic pile can be gradually tracked to a reference value; according to the method, the problems of non-uniform temperature distribution and severe fluctuation of the electric pile caused by dynamic load change, parameter uncertainty and the like are solved, the operation efficiency of the battery is improved, and the service life of the battery is prolonged.

Description

Technical Field

[0001] This invention relates to the field of fuel cell technology, and more specifically, to a time-varying adaptive asymptotic temperature control method for a fuel cell thermal management system. Background Technology

[0002] In recent years, with the increasingly severe energy crisis and environmental problems, proton exchange membrane fuel cells (PEMFCs), as a type of hydrogen fuel cell, have become one of the most promising clean energy technologies in transportation, distributed power generation, and the green hydrogen industry due to their advantages such as high energy density, zero emissions, and rapid start-up. PEMFCs can efficiently generate electricity by coordinating hydrogen and oxygen supply, hydrothermal management, and power management subsystems. The thermal management system plays a crucial role in regulating the stack temperature, directly affecting the battery's operating efficiency and lifespan. However, in actual operation, dynamic load variations, external disturbances, and parameter uncertainties often lead to unavoidable fluctuations in the stack temperature. When the temperature is too low or too high, electrode flooding or membrane dehydration can easily occur, resulting in system damage. Therefore, establishing an accurate thermal management system model and developing suitable temperature control methods to precisely and quickly regulate the stack operation within a suitable temperature range (60-80℃) is crucial.

[0003] Based on the above analysis, current literature on PEMFC thermal management system models mostly employs linear modeling methods, often neglecting the influence of external disturbances and parameter uncertainties, making it difficult to accurately characterize the nonlinear coupling characteristics between temperature and coolant flow rate. Regarding control algorithms, existing research is mainly applicable to single-loop structures, while applying them to dual-loop structures still faces limitations such as complex parameter tuning and control performance dependent on model accuracy. Therefore, the problem of how to construct a control-oriented multi-input multi-output thermal management system model under complex and variable operating conditions, and how to develop a simple and effective control method to achieve high-precision temperature tracking control, urgently needs to be solved. Summary of the Invention

[0004] The purpose of this invention is to provide a time-varying adaptive asymptotic temperature control method for a fuel cell thermal management system, which solves the problem of uneven and drastic temperature distribution in the fuel cell stack caused by dynamic load variations and parameter uncertainties, which seriously affects the battery's operating efficiency and service life.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] A time-varying adaptive asymptotic temperature control method for a fuel cell thermal management system includes the following steps:

[0007] S1. Based on the inlet and outlet temperatures of the fuel cell stack, the dynamic temperature of the dual-cycle system, and the internal heat exchange process of the system, construct a control-oriented multi-inlet multi-outlet thermal management system model.

[0008] S2. To achieve the pre-set target of temperature tracking error convergence time, a novel time-varying command filter is designed and introduced into the backstepping control framework.

[0009] S3. Considering environmental and system parameter perturbations, a dual-channel time-varying adaptive asymptotic temperature tracking controller is proposed, which combines a time-varying error compensator based on a smoothed sign function, to handle unknown perturbations and compensate for filtering errors.

[0010] S4. Select a suitable Lyapunov function to prove that the closed-loop system is stable and that the inlet and outlet temperatures of the fuel cell stack can asymptotically track the reference value.

[0011] Furthermore, step S1 specifically includes:

[0012] Based on the dynamics of the fuel cell stack inlet and outlet temperatures, the dual-cycle temperature dynamics, and the internal heat exchange processes derived from the first law of thermodynamics, an understanding of the fuel cell stack temperature is established. Small circulation outlet coolant temperature Large circulation outlet coolant temperature and fuel cell inlet temperature The dynamic multi-input multi-output thermal management system model is as follows:

[0013] ,

[0014] in, Indicates the system status; Indicates control input, and These represent the water pump speed and the fan speed, respectively; smooth function , For the fuel cell stack current, The output voltage of a single battery cell is taken into account for voltage drop caused by operating losses; The model parameters are expressed as follows:

[0015] , , , ,

[0016] , , , , , , , , ,

[0017] in, This refers to the number of battery cells. This refers to the enthalpy of hydrogen. It is Faraday's constant. For the quality of the fuel cell stack, For the specific heat of the fuel cell stack, For ambient temperature, This refers to the pump displacement. For coolant density, Specific heat of coolant; volumetric flow rate of coolant through intercooler ,in This refers to the cooling power of the intercooler. This refers to the outlet temperature of the fuel cell stack. The binary variable representing the control of the thermostat, i.e., when At that time, the coolant flows through the small circulation or the large circulation; This refers to the volume of coolant in the small circulation loop. This refers to the volume of coolant inside the radiator. For the number of fans, For fan displacement, air density, For the specific heat of air, This refers to the volume of coolant stored in the water tank.

[0018] Due to coolant temperature, system pressure, and heat exchange with the environment, , , as well as Because the parameters are constantly changing, under the constraints of the physical boundaries of the coolant circulation piping and water tank system, the following parameters are assumed. and It is reasonable that time-varying and bounded.

[0019] Furthermore, step S2 includes the following sub-steps:

[0020] S2.1 To achieve the goal of pre-setting the convergence time of temperature tracking error, a novel time-varying command filter is proposed as follows:

[0021] ,

[0022] in, For the constants to be designed, virtual control For filter input, For the filter output, a bounded function Constructed as:

[0023] ,

[0024] in, , The convergence time to be preset and ;

[0025] S2.2 To facilitate stability analysis of the system within the actual specified time, based on The following theorem is given:

[0026] If a continuously differentiable function The following conditions must be met:

[0027] ,

[0028] in, It is a positive constant, and the function Meet the conditions ,in If it is a positive integer, then when hour, It is bounded and converges to a set. ,along with , It eventually converges to zero;

[0029] By introducing the time-varying command filter designed in step S2.1 into the backstepping control framework, the time required for the temperature tracking error to converge to the bounded set is preset.

[0030] Furthermore, step S3 includes the following sub-steps:

[0031] S3.1 To ensure that the stack temperature tracks its reference value under ambient temperature perturbation. Define the stack temperature tracking error as ,right Taking the derivative yields the following error dynamics:

[0032] ,

[0033] in, ;

[0034] Regarding time-varying ambient temperature, the definition is... ;

[0035] S3.2 Construct the Lyapunov function as follows: The estimation error , for The estimate, and For the parameters to be designed; Differentiate, to ensure A time-varying adaptive asymptotic temperature tracking control law is designed for the fuel cell stack outlet temperature channel. for:

[0036] ,

[0037] in, , The function to be designed is a positive constant and a strictly decreasing function. Meet the conditions , It is a positive number; The update law is:

[0038] ;

[0039] S3.3 To ensure uniform temperature distribution inside the fuel cell stack, the temperature difference between the coolant inlet and outlet needs to be stabilized within 10°C. Simultaneously, the fuel cell stack inlet temperature must track its reference value under environmental and system parameter perturbations. Based on the proposed time-varying command filter, the stack inlet temperature tracking error is defined as follows: Introducing coordinate transformation ,right Taking the derivative yields the following error dynamics:

[0040] ,

[0041] Regarding time-varying parameters, the definition is... ,in ;

[0042] S3.4. To compensate for the effects of filtering errors, a compensation signal is defined. and Its dynamics are as follows:

[0043] ,

[0044] ,

[0045] in, and For the positive constants to be designed and , and For the positive constants to be designed and Construct the Lyapunov function as follows: The tracking error that was compensated estimation error , for The estimate, and For the parameters to be designed; Differentiate, to ensure Design virtual control laws for:

[0046] ,

[0047] in, and ; The update law is:

[0048] ;

[0049] S3.5, The tracking error to be compensated is further defined by the introduced coordinate transformation as follows: Taking its derivative, we can obtain the following error dynamics:

[0050] ,

[0051] Regarding time-varying parameters, the definition is... ,in ;

[0052] S3.6, Targeting Construct the Lyapunov function as The estimation error , for The estimate, and For the parameters to be designed; Differentiate, to ensure A time-varying adaptive asymptotic temperature tracking control law is designed for the fuel cell stack inlet temperature channel. for:

[0053] ,

[0054] in, and ; The update law is:

[0055] .

[0056] Furthermore, step S4 includes the following sub-steps:

[0057] S4.1, Regarding the temperature tracking error of the fuel cell stack Compensated tracking error and Construct the following Lyapunov candidate function and define a compact set:

[0058] ,

[0059] ,

[0060] in, For any given positive constant; Take the derivative if it satisfies Can be launched , and Bounded, meaning there exist positive constants. and Meet the conditions and Furthermore, according to Young's inequality after scaling, if satisfy , then when When you get:

[0061] ,

[0062] in, ,

[0063]

[0064] if According to Russell's invariant set principle, all closed-loop signals are eventually uniformly bounded, and when... hour, Converging to set Inside;

[0065] S4.2, in Inner inequality Integrating, we get:

[0066] ,

[0067] In summary, Consistent and continuous It exists, therefore, according to Barbara's lemma, it is known that... ,So , , and This means that the control objective of asymptotically tracking the inlet and outlet temperatures of the fuel cell stack to the reference value can be achieved.

[0068] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0069] 1. This invention establishes a control-oriented multi-input multi-output thermal management system model that comprehensively considers ambient temperature perturbations and parameter uncertainties. This model can fully characterize the dynamics of the inlet and outlet temperatures of the fuel cell stack, improve the modeling accuracy under actual operating conditions, and promote the design of collaborative control schemes for the inlet and outlet temperatures of the fuel cell stack.

[0070] 2. This invention designs a novel time-varying command filter and introduces it into the backstepping control framework to realize the pre-setting of the convergence time of temperature tracking error. This breaks through the limitation of the conservative assumption that the application of first-order filters in traditional dynamic surface control relies on the bounded derivative of the virtual control law, and lays the foundation for the analysis of the transient performance of thermal management systems within a specified time.

[0071] 3. This invention combines a time-varying error compensator based on a smoothed sign function and proposes a dual-channel time-varying adaptive asymptotic temperature tracking controller to quickly cancel filtering errors. The designed adaptive law can handle environmental and system parameter perturbations, and ultimately reduces control conservatism while achieving asymptotic tracking of the stack inlet and outlet temperatures. Attached Figure Description

[0072] Figure 1 The diagram shows the structural composition of the thermal management system for a proton exchange membrane fuel cell.

[0073] Figure 2 A flowchart is shown for the time-varying adaptive asymptotic temperature control method of the fuel cell thermal management system.

[0074] Figure 3 A schematic diagram showing the load current and stack voltage changes according to an embodiment of the present invention is shown.

[0075] Figure 4 A schematic diagram showing the reactor inlet / outlet temperature regulation performance results of an embodiment of the present invention is provided.

[0076] Figure 5 This diagram illustrates the comparison of reactor outlet temperature regulation performance under different methods according to embodiments of the present invention.

[0077] Figure 6 This diagram illustrates a comparison of reactor infeed temperature regulation performance under different methods according to embodiments of the present invention.

[0078] Figure 7 The diagram illustrates the changes in pump speed under different methods according to embodiments of the present invention. Detailed Implementation

[0079] To more clearly illustrate the present invention, the following description, in conjunction with preferred embodiments and accompanying drawings, further clarifies the invention. Those skilled in the art should understand that the specific description below is illustrative rather than restrictive and should not be construed as limiting the scope of protection of the present invention.

[0080] like Figure 1As shown, the thermal management system of a proton exchange membrane fuel cell includes: a water pump, a radiator, a thermostat, a water tank, an intercooler, a heater, and a temperature sensor. The water pump provides circulation power, driving the coolant to flow in the loop; the radiator transfers heat absorbed by the coolant from the fuel cell stack to the metal fins, preparing for heat dissipation into the air; a fan is installed on the radiator, and the fan controls the airflow through the radiator by rotating blades, thus quickly removing heat from the fins; the thermostat adjusts the flow rate into the large and small loops according to the coolant temperature, thereby controlling the battery's operating temperature; the water tank holds the coolant as its volume changes due to thermal expansion and contraction; the intercooler cools the compressed air from the air compressor, ensuring the air entering the fuel cell stack is within a reasonable temperature range; the heater provides auxiliary heating to the coolant during cold starts at low temperatures, helping the fuel cell stack quickly reach its operating temperature; and the temperature sensor monitors the coolant temperature at the fuel cell stack inlet / outlet and other critical points in real time.

[0081] Small and large circulation are the two core coolant flow paths in the thermal management system. The system switches between them via a thermostat and adjusts the circulation path in real time according to the fuel cell stack temperature to ensure that the fuel cell stack is maintained within the optimal operating temperature range (usually 60-80℃). Small circulation is used during the initial system startup or under low-temperature conditions. The thermostat closes the radiator channel, and the coolant flows through the water pump, heater, and thermostat before entering the fuel cell stack. This circulation can prevent fuel cell stack performance degradation and membrane electrode damage caused by low-temperature operation. Large circulation plays a role when the fuel cell stack temperature is too high. The thermostat closes the heater channel, and the coolant flows through the radiator driven by the water pump. Through heat exchange with the outside air, the heat generated by the fuel cell stack is quickly dissipated into the environment, and then returns to the fuel cell stack via the thermostat. This circulation effectively prevents the fuel cell stack from overheating, which can lead to membrane electrode dehydration and catalyst sintering.

[0082] The time-varying adaptive asymptotic temperature control method for a fuel cell thermal management system provided in this embodiment can achieve high-performance temperature control of the thermal management system under complex operating conditions, effectively improving battery operating efficiency. Figure 2 As shown, the control method includes the following steps:

[0083] S1. Based on the inlet and outlet temperatures of the fuel cell stack, the dynamic temperature of the dual-cycle system, and the internal heat exchange process of the system, construct a control-oriented multi-inlet multi-outlet thermal management system model.

[0084] S2. To achieve the pre-set target of temperature tracking error convergence time, a novel time-varying command filter is designed and introduced into the backstepping control framework.

[0085] S3. Considering environmental and system parameter perturbations, a dual-channel time-varying adaptive asymptotic temperature tracking controller is proposed, which combines a time-varying error compensator based on a smoothed sign function, to handle unknown perturbations and compensate for filtering errors.

[0086] S4. Select a suitable Lyapunov function to prove that the closed-loop system is stable and that the inlet and outlet temperatures of the fuel cell stack can asymptotically track the reference value.

[0087] The following section provides a detailed explanation of each step.

[0088] Step S1 includes:

[0089] Based on the dynamics of the fuel cell stack inlet and outlet temperatures, the dual-cycle temperature dynamics, and the internal heat exchange processes derived from the first law of thermodynamics, an understanding of the fuel cell stack temperature is established. Small circulation outlet coolant temperature Large circulation outlet coolant temperature and fuel cell inlet temperature The dynamic multi-input multi-output thermal management system model is as follows:

[0090] ,

[0091] in, Indicates the system status; Indicates control input, and These represent the water pump speed and the fan speed, respectively; smooth function , For the fuel cell stack current, The output voltage of a single battery cell is taken into account for voltage drop caused by operating losses; The model parameters are expressed as follows:

[0092] , , , ,

[0093] , , , , , , , , ,

[0094] in, This refers to the number of battery cells. This refers to the enthalpy of hydrogen. It is Faraday's constant. For the quality of the fuel cell stack, For the specific heat of the fuel cell stack, For ambient temperature, This refers to the pump displacement. For coolant density, Specific heat of coolant; volumetric flow rate of coolant through intercooler ,in This refers to the cooling power of the intercooler. This refers to the outlet temperature of the fuel cell stack. The binary variable representing the control of the thermostat, i.e., when At that time, the coolant flows through the small circulation or the large circulation; This refers to the volume of coolant in the small circulation loop. This refers to the volume of coolant inside the radiator. For the number of fans, For fan displacement, air density, For the specific heat of air, This refers to the volume of coolant stored in the water tank.

[0095] Due to coolant temperature, system pressure, and heat exchange with the environment, , , as well as Because the parameters are constantly changing, under the constraints of the physical boundaries of the coolant circulation piping and water tank system, the following parameters are assumed. and It is reasonable that time-varying and bounded.

[0096] Step S2 further includes the following sub-steps.

[0097] S2.1 To achieve the goal of pre-setting the convergence time of temperature tracking error, a novel time-varying command filter is proposed as follows:

[0098] ,

[0099] in, For the constants to be designed, virtual control For filter input, For the filter output, a bounded function Constructed as:

[0100] ,

[0101] in, , The convergence time to be preset and ;

[0102] S2.2 To facilitate stability analysis of the system within the actual specified time, based on The following theorem is given:

[0103] If a continuously differentiable function The following conditions must be met:

[0104] ,

[0105] in, It is a positive constant, and the function Meet the conditions ,in If it is a positive integer, then when hour, It is bounded and converges to a set. ,along with , It eventually converges to zero;

[0106] By introducing the time-varying command filter designed in step S2.1 into the backstepping control framework, the time required for the temperature tracking error to converge to the bounded set is preset.

[0107] Step S3 further includes the following sub-steps:

[0108] S3.1 To ensure that the stack temperature tracks its reference value under ambient temperature perturbation. Define the stack temperature tracking error as ,right Taking the derivative yields the following error dynamics:

[0109] ,

[0110] in, ;

[0111] Regarding time-varying ambient temperature, it can be defined ;

[0112] S3.2 Construct the Lyapunov function as follows: The estimation error , for The estimate, and For the parameters to be designed; Differentiate, to ensure A time-varying adaptive asymptotic temperature tracking control law is designed for the fuel cell stack outlet temperature channel. for:

[0113] ,

[0114] in, , The function to be designed is a positive constant and a strictly decreasing function. Meet the conditions , It is a positive number; The update law is:

[0115] ;

[0116] S3.3 To ensure uniform temperature distribution inside the fuel cell stack, the temperature difference between the coolant inlet and outlet needs to be stabilized within 10°C. Simultaneously, the fuel cell stack inlet temperature must track its reference value under environmental and system parameter perturbations. Based on the proposed time-varying command filter, the stack inlet temperature tracking error is defined as follows: Introducing coordinate transformation ,right Taking the derivative yields the following error dynamics:

[0117] ,

[0118] Regarding time-varying parameters, they can be defined. ,in ;

[0119] S3.4. To compensate for the effects of filtering errors, a compensation signal is defined. and Its dynamics are as follows:

[0120] ,

[0121] ,

[0122] in, and For the positive constants to be designed and , and For the positive constants to be designed and Construct the Lyapunov function as follows: The tracking error that was compensated estimation error , for The estimate, and For the parameters to be designed; Differentiate, to ensure Design virtual control laws for:

[0123] ,

[0124] in, and ; The update law is:

[0125] ;

[0126] S3.5, The tracking error to be compensated is further defined by the introduced coordinate transformation as follows: Taking its derivative, we can obtain the following error dynamics:

[0127] ,

[0128] Regarding time-varying parameters, they can be defined. ,in ;

[0129] S3.6, Targeting Construct the Lyapunov function as The estimation error , for The estimate, and For the parameters to be designed; Differentiate, to ensure A time-varying adaptive asymptotic temperature tracking control law is designed for the fuel cell stack inlet temperature channel. for:

[0130] ,

[0131] in, and ; The update law is:

[0132] .

[0133] Step S4 further includes the following sub-steps:

[0134] S4.1, Regarding the temperature tracking error of the fuel cell stack Compensated tracking error and Construct the following Lyapunov candidate function and define a compact set:

[0135] ,

[0136] ,

[0137] in, For any given positive constant; Take the derivative if it satisfies Can be launched , and Bounded, meaning there exist positive constants. and Meet the conditions and Furthermore, according to Young's inequality after scaling, if satisfy , then when When you get:

[0138] ,

[0139] in, ,

[0140]

[0141] if According to Russell's invariant set principle, all closed-loop signals are eventually uniformly bounded, and when... hour, Converging to set Inside;

[0142] S4.2, in Inner inequality Integrating, we get:

[0143] ,

[0144] In summary, Consistent and continuous It exists, therefore, according to Barbara's lemma, it is known that... ,So , , and This means that the control objective of asymptotically tracking the inlet and outlet temperatures of the fuel cell stack to the reference value can be achieved.

[0145] Example:

[0146] To verify the effectiveness of the time-varying adaptive asymptotic temperature control method for the fuel cell thermal management system in this embodiment, MATLAB simulation experiments were conducted, detailed as follows:

[0147] The parameters selected for the thermal management system model are: , , , , , , , , , , , ;

[0148] The parameters for selecting the time-varying command filter are: , , ;

[0149] Selection and control law and The parameters and functions related to the update law are: , , ;

[0150] Selection and compensation signals Dynamic, virtual control law and The parameters and functions related to the update law are: , , , ;

[0151] Selection and compensation signals Dynamics, control law and The parameters and functions related to the update law are: , , , ;

[0152] nominal parameters , and The 10% perturbation, along with room temperature perturbation and time-varying load current, are introduced into the system, specifically set as follows: Case 1 only considers the case of constant room temperature, i.e., when hour, Scenario 2 considers a step fluctuation in room temperature, i.e., when hour, ,when hour, ,when hour, ,when hour, Scenario 3 considers sinusoidal fluctuations in room temperature, i.e., when hour, ; Figure 3 The diagram shows the load current and stack voltage variations of a hydrogen fuel cell, demonstrating that the stack model constructed within the allowable error range can accurately reflect the output characteristics of a hydrogen fuel cell.

[0153] To facilitate the evaluation of the advantages of the proposed method in terms of temperature control accuracy, robustness, and environmental adaptability, command filtering control, finite-time command filtering control, and traditional preset-time command filtering control were selected as comparative algorithms for simulation testing. The results are as follows: Figures 4-7 As shown;

[0154] in, Figure 4 The diagram shows the performance results of the thermal management system for regulating reactor inlet and outlet temperatures under the proposed method. Figure 5 This diagram illustrates the comparison of the reactor outlet temperature regulation performance of the thermal management system under different methods. Figure 6 This diagram illustrates the comparison of reactor infeed temperature regulation performance under different methods. Figure 7The diagram illustrates the changes in pump speed in the thermal management system under different methods. (Based on simulation diagrams) Figures 4-7 It can be seen that the proposed time-varying adaptive asymptotic temperature control method of fuel cell thermal management system achieves precise regulation of stack inlet and outlet temperatures within a preset time under dynamic load and parameter uncertainty. The water pump speed can quickly respond to environmental changes and adjust the stack temperature in a timely manner. Furthermore, by designing an adaptive law, it can effectively overcome load current changes and parameter perturbations to control the stack inlet and outlet temperatures, avoid local overheating, ensure uniform temperature distribution inside the stack, improve battery operating efficiency, and extend service life.

[0155] The above analysis demonstrates the effectiveness of the time-varying adaptive asymptotic temperature control method for fuel cell thermal management systems provided in this embodiment.

[0156] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. For those skilled in the art, other variations or modifications can be made based on the above description. It is impossible to exhaustively list all the implementation methods here. All obvious variations or modifications derived from the technical solutions of the present invention are still within the protection scope of the present invention.

Claims

1. A time-varying adaptive asymptotic temperature control method for a fuel cell thermal management system, characterized in that, Includes the following steps: S1. Based on the inlet and outlet temperatures of the fuel cell stack, the dynamic temperature of the dual-cycle system, and the internal heat exchange process of the system, construct a control-oriented multi-inlet multi-outlet thermal management system model. S2. To achieve the pre-set target of temperature tracking error convergence time, a novel time-varying command filter is designed and introduced into the backstepping control framework. S3. Considering environmental and system parameter perturbations, a dual-channel time-varying adaptive asymptotic temperature tracking controller is proposed, which combines a time-varying error compensator based on a smoothed sign function, to handle unknown perturbations and compensate for filtering errors. S4. Select a suitable Lyapunov function to prove that the closed-loop system is stable and that the inlet and outlet temperatures of the fuel cell stack can asymptotically track the reference value.

2. The time-varying adaptive asymptotic temperature control method for a fuel cell thermal management system according to claim 1, characterized in that, Step S1 specifically includes: Based on the dynamics of the fuel cell stack inlet and outlet temperatures, the dual-cycle temperature dynamics, and the internal heat exchange processes derived from the first law of thermodynamics, an understanding of the fuel cell stack temperature is established. Small circulation outlet coolant temperature Large circulation outlet coolant temperature and fuel cell inlet temperature The dynamic multi-input multi-output thermal management system model is as follows: ， in, Indicates the system status; Indicates control input, and These represent the water pump speed and the fan speed, respectively; smooth function , For the fuel cell stack current, The output voltage of a single battery cell is taken into account for voltage drop caused by operating losses; The model parameters are expressed as follows: ， ， ， ， ， ， ， ， ， ， ， ， ， in, This refers to the number of battery cells. This refers to the enthalpy of hydrogen. It is Faraday's constant. For the quality of the fuel cell stack, For the specific heat of the fuel cell stack, For ambient temperature, This refers to the pump displacement. For coolant density, Specific heat of coolant; volumetric flow rate of coolant through intercooler ,in This refers to the cooling power of the intercooler. This refers to the outlet temperature of the fuel cell stack. The binary variable representing the control of the thermostat, i.e., when At that time, the coolant flows through the small circulation or the large circulation; This refers to the volume of coolant in the small circulation loop. This refers to the volume of coolant inside the radiator. For the number of fans, For fan displacement, air density, For the specific heat of air, This refers to the volume of coolant stored in the water tank. Due to coolant temperature, system pressure, and heat exchange with the environment, , , as well as Because the parameters are constantly changing, under the constraints of the physical boundaries of the coolant circulation piping and water tank system, the following parameters are assumed. and It is reasonable that time-varying and bounded.

3. The time-varying adaptive asymptotic temperature control method for a fuel cell thermal management system according to claim 2, characterized in that, Step S2 includes the following sub-steps: S2.1 To achieve the goal of pre-setting the convergence time of temperature tracking error, a novel time-varying command filter is proposed as follows: ， in, For the constants to be designed, virtual control For filter input, For the filter output, a bounded function Constructed as: ， in, , The convergence time is to be preset and ; S2.2 To facilitate stability analysis of the system within the actual specified time, based on The following theorem is given: If a continuously differentiable function The following conditions must be met: ， in, It is a positive constant, and the function Meet the conditions ,in If it is a positive integer, then when hour, It is bounded and converges to a set. ,along with , It eventually converges to zero; By introducing the time-varying command filter designed in step S2.1 into the backstepping control framework, the time required for the temperature tracking error to converge to the bounded set is preset.

4. The time-varying adaptive asymptotic temperature control method for a fuel cell thermal management system according to claim 3, characterized in that, Step S3 includes the following sub-steps: S3.1 To ensure that the stack temperature tracks its reference value under ambient temperature perturbation. Define the stack temperature tracking error as ,right Taking the derivative yields the following error dynamics: ， in, ; Regarding time-varying ambient temperature, the definition is... ; S3.2 Construct the Lyapunov function as follows: The estimation error , for The estimate, and For the parameters to be designed; Differentiate, to ensure A time-varying adaptive asymptotic temperature tracking control law is designed for the fuel cell stack outlet temperature channel. for: ， in, , The function to be designed is a positive constant and a strictly decreasing function. Meet the conditions , It is a positive number; The update law is: ； S3.3 To ensure uniform temperature distribution inside the fuel cell stack, the temperature difference between the coolant inlet and outlet needs to be stabilized within 10°C. Simultaneously, the fuel cell stack inlet temperature must track its reference value under environmental and system parameter perturbations. Based on the proposed time-varying command filter, the stack inlet temperature tracking error is defined as follows: Introducing coordinate transformation ,right Taking the derivative yields the following error dynamics: ， Regarding time-varying parameters, the definition is... ,in ; S3.

4. To compensate for the effects of filtering errors, a compensation signal is defined. and Its dynamics are as follows: ， ， in, and For the positive constants to be designed and , and For the positive constants to be designed and Construct the Lyapunov function as follows: The tracking error that was compensated estimation error , for The estimate, and For the parameters to be designed; Differentiate, to ensure Design virtual control laws for: ， in, and ; The update law is: ； S3.5, The tracking error to be compensated is further defined by the introduced coordinate transformation as follows: Taking its derivative, we can obtain the following error dynamics: ， Regarding time-varying parameters, the definition is... ,in ; S3.6, Targeting Construct the Lyapunov function as The estimation error , for The estimate, and For the parameters to be designed; Differentiate, to ensure A time-varying adaptive asymptotic temperature tracking control law is designed for the fuel cell stack inlet temperature channel. for: ， in, and ; The update law is: 。 5. The time-varying adaptive asymptotic temperature control method for a fuel cell thermal management system according to claim 4, characterized in that, Step S4 includes the following sub-steps: S4.1, Regarding the temperature tracking error of the fuel cell stack Compensated tracking error and Construct the following Lyapunov candidate function and define a compact set: ， ， in, For any given positive constant; Take the derivative if it satisfies Can be launched , and Bounded, meaning there exist positive constants. and Meet the conditions and Furthermore, according to Young's inequality after scaling, if satisfy , then when When you get: ， in, , if According to Russell's invariant set principle, all closed-loop signals are eventually uniformly bounded, and when... hour, Converging to set Inside; S4.2, in Inner inequality Integrating, we get: ， In summary, Consistent and continuous It exists, therefore, according to Barbara's lemma, it is known that... ,So , , and This means that the control objective of asymptotically tracking the inlet and outlet temperatures of the fuel cell stack to the reference value can be achieved.

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