Air cooling PEMFC temperature control method and system based on ADRC

Abstract

The invention discloses an ADRC-based air cooling PEMFC temperature control method and system, and relates to the technical field of fuel cell control, and the method comprises the following steps: inputting the actual temperature at the current moment and the temperature control quantity at the previous moment into a linear expansion state observer, and obtaining the estimated temperature and estimated total disturbance at the next moment; the estimated temperature error is input into a linear state error feedback controller, and the initial control quantity of the next moment is obtained; performing feedforward compensation on the estimated total disturbance at the next moment to the initial control quantity at the next moment to obtain the temperature control quantity at the next moment; in the feed-forward compensation process, the temperature control quantity gain at the next moment is optimized through extremum search; and controlling the temperature of the air-cooled proton exchange membrane fuel cell through the temperature control quantity at the next moment. The ADRC controller provided by the invention has very strong anti-interference capability and a good control effect, and can solve the problem of model mismatch.

Description

Technical Field

[0001] The present invention relates to the technical field of fuel cell control, and particularly to a temperature control method and system for an air-cooled PEMFC based on ADRC. Background Art

[0002] With the increasing severity of environmental pollution and energy crisis, the development of clean energy is extremely urgent. Among them, the Proton Exchange Membrane Fuel Cell (PEMFC) is considered to be the most promising clean energy conversion device due to its high energy conversion efficiency, high specific power, fast startup, and pollution-free advantages. In small-power fuel cell application scenarios (such as drones and forklifts), air-cooled PEMFCs are widely used due to their simple and compact structure. However, since their fans need to supply air and cool the fuel cell stack at the same time, it increases the complexity of temperature control.

[0003] In the temperature control of air-cooled PEMFCs, the most widely used method is still PID (Proportional-Integral-Derivative) control. However, the air-cooled PEMFC temperature control system is a strongly nonlinear system. Applying PID control is prone to problems such as low adjustment accuracy, slow adjustment time, and large overshoot. To overcome the defects of PID control, some scholars have used advanced model-based control methods to achieve the temperature control of air-cooled PEMFCs, such as Model Predictive Control (MPC) and Linear Quadratic Regulator (LQR). Although these advanced control methods can achieve satisfactory control effects in specific scenarios, they rely too much on the accuracy of the model and are often difficult to handle external disturbances caused by environmental interference and measurement noise or internal disturbances caused by inaccurate modeling. Therefore, it is prone to model mismatch problems, and due to the complex calculation, it is difficult to implement and maintain in actual engineering, thus limiting its application scenarios. Summary of the Invention

[0004] Based on the above defects existing in the prior art, the present invention provides a temperature control method and system for an air-cooled PEMFC based on ADRC, which solves the problems that although the existing advanced control methods can achieve satisfactory control effects in specific scenarios, they rely too much on the accuracy of the model and are often difficult to handle external disturbances caused by environmental interference and measurement noise or internal disturbances caused by inaccurate modeling. Therefore, it is prone to model mismatch problems, and due to the complex calculation, it is difficult to implement and maintain in actual engineering, thus limiting its application scenarios.

[0005] The present invention adopts the following technical solutions: In the first aspect, the present invention provides a temperature control method for an air-cooled PEMFC based on ADRC, including the following steps: Collect the actual temperature of the air-cooled proton exchange membrane fuel cell at the current moment and the temperature control quantity at the previous moment; Construct an active disturbance rejection controller (ADRC), including a linear extended state observer and a linear state error feedback controller; Input the actual temperature at the current moment and the temperature control quantity at the previous moment into the linear extended state observer to obtain the estimated temperature and the estimated total disturbance at the next moment; subtract the estimated temperature at the next moment from the target temperature of the air-cooled proton exchange membrane fuel cell to obtain the estimated temperature error, and input the estimated temperature error into the linear state error feedback controller to obtain the preliminary control quantity at the next moment; Feed forward compensate the estimated total disturbance at the next moment to the preliminary control quantity at the next moment to obtain the temperature control quantity at the next moment; control the temperature of the air-cooled proton exchange membrane fuel cell through the temperature control quantity at the next moment.

[0006] 7. Preferably, the construction of the active disturbance rejection controller (ADRC) includes the following steps: Obtain the disturbance rejection paradigm of the ADRC, and the disturbance rejection paradigm is as follows: ; In the formula, is the controlled variable, is the derivative of the controlled variable, is the temperature control quantity, is the temperature control quantity gain, is the total disturbance composed of internal disturbance and external disturbance; Convert the disturbance rejection paradigm of the ADRC into the state space equation of the ADRC, and estimate the total disturbance through the linear extended state observer. The specific form of the linear extended state observer is as follows: ; In the formula, and are the estimated parameters, is used to estimate , is used to estimate , is the estimated temperature, is the derivative of, is the derivative of, and are the adjustable parameters of the observer; Input the linear extended state observer into the state space equation of the ADRC to obtain the control equation, and the control equation is as follows: ; ; In the formula, is the preliminary control quantity generated by the linear state error feedback controller; The control of the single integral link is realized through proportional control: ; In the formula, is the proportional coefficient, r is the target temperature.

[0007] Preferably, the active disturbance rejection controller (ADRC) includes multiple adjustable parameters, and the bandwidths corresponding to the multiple adjustable parameters are specifically as follows: ; In the formula, is the bandwidth of the linear state error feedback controller, is the bandwidth of the linear extended state observer.

[0008] Preferably, the step of feeding forward and compensating the estimated total disturbance at the next moment to the preliminary control quantity at the next moment to obtain the temperature control quantity at the next moment includes the following steps: During the feedforward compensation process, optimize the gain of the temperature control quantity at the next moment through extremum search; Combine the optimized gain of the temperature control quantity at the next moment with the compensated preliminary control quantity at the next moment to obtain the temperature control quantity at the next moment.

[0009] Preferably, the step of optimizing the gain of the temperature control quantity at the next moment through extremum search includes the following steps: Obtain the actual temperature error between the actual temperature at the current moment and the target temperature, and define the objective function based on the actual temperature error. The objective function is as follows: ; In the formula, is t the objective function at time T is the control process time, is the actual temperature error; Apply a sine disturbance to the gain of the temperature control quantity at the current moment to obtain the objective function at the current moment; Obtain the gradient of the objective function at the current moment, and optimize the gain of the temperature control quantity along the gradient direction, specifically as follows: ; In the formula, is the derivative of the temperature control quantity gain at the current moment, k is the adjustment step size, is the gradient information.

[0010] Preferably, the temperature of the air-cooled proton exchange membrane fuel cell is controlled by the temperature control quantity at the next moment, which specifically includes the following steps: Construct a thermal management system model of the air-cooled proton exchange membrane fuel cell, including a fuel cell stack model and a thermal analysis module; The thermal analysis module is used to calculate the temperature change rate of the fuel cell stack model, as specifically shown below: ; In the formula, represents the total input energy, represents the output electrical energy, represents the heat taken away by the cooling air, represents the heat dissipated by radiation and natural convection, represents the heat capacity, t is the time; The temperature control quantity is the fan duty ratio; the temperature control quantity at the next moment is input into the thermal analysis module to change the air flow rate and the surface heat transfer coefficient of the cathode flow channel, so as to control the temperature of the fuel cell stack.

[0011] In a second aspect, the present invention provides an air-cooled PEMFC temperature control system based on ADRC, including: An acquisition module, which is used to acquire the actual temperature of the air-cooled proton exchange membrane fuel cell at the current moment and the temperature control quantity at the previous moment; A construction module, which is used to construct an active disturbance rejection controller (ADRC), including a linear extended state observer and a linear state error feedback controller; An input module, which is used to input the actual temperature at the current moment and the temperature control quantity at the previous moment into the linear extended state observer to obtain the estimated temperature and the estimated total disturbance at the next moment; the target temperature is subtracted from the estimated temperature at the next moment to obtain the estimated temperature error, and the estimated temperature error is input into the linear state error feedback controller to obtain the preliminary control quantity at the next moment; A control module, which is used to feed forward compensate the estimated total disturbance at the next moment to the preliminary control quantity at the next moment to obtain the temperature control quantity at the next moment; the temperature of the air-cooled proton exchange membrane fuel cell is controlled by the temperature control quantity at the next moment.

[0012] Compared with the prior art, at least one of the above technical solutions adopted by the present invention can achieve the following beneficial effects: The present invention provides a temperature control method for an air-cooled PEMFC based on ADRC. Facing the complex non-linear system of the air-cooled PEMFC, the PID control is prone to disadvantages such as large overshoot and long adjustment time. The present invention uses an active disturbance rejection controller (ADRC) to control the temperature of the PEMFC. First, an ADRC is constructed, including a linear extended state observer and a linear state error feedback controller. In the specific control process, the total disturbance and temperature can be estimated by the linear extended state observer, and the linear state error feedback controller can output a preliminary control quantity according to the estimated temperature error. At the same time, the estimated total disturbance is fed forward and compensated to the preliminary control quantity, and finally the temperature control quantity is obtained. The ADRC controller can handle internal and external disturbances through the total disturbance term, has strong anti-disturbance ability and good control effect, can solve the problem of model mismatch, and has a simpler structure compared with advanced control methods, which is easy to implement and maintain in practical engineering and has a wide range of application scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0014] Figure 1 Schematic diagram of the air-cooled PEMFC thermal analysis module of the present invention; Figure 2 Structural diagram of the first-order linear ADRC controller of the present invention; Figure 3 Applied current disturbance diagram of the present invention; Figure 4 Comparison diagram of the temperature control effects of PID and ADRC on the fuel cell stack in the embodiment of the present invention; Figure 5 Extremum search structural diagram of the present invention; Figure 6 Structural diagram of the ES-ADRC controller of the present invention; Figure 7 Comparison diagram of the temperature control effects of ADRC and ES-ADRC on the fuel cell stack in the embodiment of the present invention; Figure 8 Control action gain of the present invention Change situation; Figure 9 Comparison diagram of the objective function in the ES optimization of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0015] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0016] I. Explanation and illustration of the embodiments. This part is an explanatory embodiment that expands and explains the technical solutions of the claims in order to enable those skilled in the art to fully understand how the present invention is specifically implemented.

[0017] The present invention provides an air-cooled PEMFC temperature control method based on adaptive ADRC (Active Disturbance Rejection Controller), including the following steps: S1: Based on the physical characteristics of the air-cooled PEMFC thermal management system, build its dynamic model on the Matlab / Simulink simulation platform.

[0018] The dynamic model of the air-cooled PEMFC thermal management system mainly consists of two parts: the PEMFC stack and the thermal analysis module. The PEMFC stack uses a semi-empirical equation to model and calculate the output voltage. The semi-empirical PEMFC model is often used in the simulation research at the PEMFC system level because of its fast calculation speed and high accuracy:

[0019] (1); Among them, (2); (3); (4); (5); (6); (7); (8); In the formula, , , , , , , λ , b and are 9 coefficients that can be calibrated through experimental data. is the reaction entropy, is the number of electrons transferred in the reaction, is the Faraday constant, is the standard temperature, is the gas constant, is the battery temperature, is the partial pressure of hydrogen, is the partial pressure of oxygen, is the partial pressure of water vapor, is the oxygen concentration, is the working current, is the total current, is the reaction active area, is the total internal resistance, is the ohmic internal resistance, is the resistivity, is the concentration loss coefficient, is the thickness of the exchange membrane, is the current density.

[0020] The thermal analysis module calculates the temperature change rate of the PEMFC stack using the energy conservation equation, and its main input and output energy forms are as Figure 1 shown. The PEMFC temperature change rate is as follows: (9); In the formula, represents the total input energy of the PEMFC, represents the electrical energy output by the PEMFC, represents the heat carried away by the cooling air, represents the heat dissipated by radiation and natural convection, represents the heat capacity of the PEMFC, t is the time.

[0021] The total input energy of the fuel cell is the total energy obtained from the combustion of hydrogen, and the consumption of hydrogen is related to the current and the number of single cells, The calculation of is as follows: (10); In the formula, represents the consumption of hydrogen, F represents the Faraday constant, is the enthalpy of combustion of hydrogen, represents the number of single cells.

[0022] The output electrical energy is the product of the stack voltage and the current, The calculation of is as follows: (11); In the formula, represents the stack voltage.

[0023] Define the forced convection term of air as the heat carried away by the cooling air: (12); Wherein, is the surface heat transfer coefficient, is the ambient temperature, is the total area of the cathode flow channel.

[0024] Define the natural convection and radiative heat transfer of air as the surface heat dissipation of the fuel cell stack: (13); Wherein, is the equivalent thermal resistance.

[0025] S2: According to the dynamic model of the air-cooled PEMFC thermal management system established in S1, design a temperature control strategy and initially implement temperature control using PID.

[0026] The temperature control strategy of the air-cooled PEMFC is to change the air flow rate by adjusting the fan PWM (Pulse Width Modulation) signal, thereby changing the surface heat transfer coefficient of the cathode flow channel, and finally achieving precise control of the fuel cell stack temperature. From the general structure and working conditions of the fuel cell, it can be determined that the air flow is within the laminar flow range. Therefore, the relationship between the air flow rate and the surface heat transfer coefficient of the cathode flow channel is determined by the Dittus-Boelter equation:

[0027] (14); Wherein, represents the Nusselt number of the cathode flow channel, represents the Reynolds number, represents the Prandtl number, represents the characteristic dimension, represents the pipe diameter, represents the dynamic viscosity of air, represents the dynamic viscosity of the wall surface.

[0028] PID is the most widely used controller in practical engineering, with the characteristics of simple structure, easy implementation and strong robustness. The present invention first uses a PID controller to achieve temperature control of the air-cooled PEMFC. The PID controller will calculate the control quantity according to the temperature error to adjust the fan PWM according to the following formula:

[0029] (15); Wherein, is the proportional coefficient, is the integral coefficient, is the differential coefficient, is the control action, is the temperature error between the given value and the actual value. In the stack temperature control of the air-cooled PEMFC thermal management system, is the fan PWM signal, is the difference between the given value and the actual value of the stack temperature. The PID controller will generate a control action continuously according to the error until the stack temperature is controlled to the given value.

[0030] S3: Design an ADRC controller to achieve the temperature control of the air-cooled PEMFC thermal management system and compare the temperature control effect of the PID controller in S2.

[0031] The temperature control strategy in S3 is the same as that in S2, that is, the stack temperature is controlled by adjusting the PWM signal of the fan. Since the PID controller in S2 only generates a control action according to the temperature error, it is difficult to achieve a good control effect, and problems such as large overshoot and long adjustment time often occur. Although the advanced controller designed based on model information has a very prominent control effect in specific scenarios, it is too dependent on the accuracy of the model, and it is often difficult to handle external disturbances such as environmental interference and measurement noise or internal disturbances caused by inaccurate modeling. Moreover, the advanced controller has a huge computational load and is often difficult to implement and maintain in actual engineering. In order to overcome the defects of PID control and MPC control, the present invention uses active disturbance rejection control (ADRC) to achieve the temperature control of the air-cooled PEMFC thermal management system.

[0032] ADRC is an improved version of PID control, which has the advantages of simple structure and small computational load. At the same time, ADRC can handle internal and external disturbances and compensate through the final control action, so it has a good control effect and anti-disturbance ability. The first-order linear ADRC adopted in the present invention is mainly composed of linear state error feedback (LSEF) and linear extended state observer (Land Earth Station Operator, LESO), and its controller structure diagram is as Figure 2 shown.

[0033] The anti-disturbance paradigm of the first-order linear ADRC is: (16); In the formula, represents the controlled quantity, is the derivative of the controlled quantity, represents the control action, represents the gain of the control action, represents the total disturbance composed of internal and external disturbances. In the present invention, is the stack temperature, It is the PWM signal of the fan. To facilitate the design of the LESO, the above equation needs to be converted into the form of a state-space equation:

[0034] (17); The meanings of the terms in the equation are as follows: (18); In the equation, is the derivative of the state variable , is the derivative of the state variable , is the temperature of the battery stack, is the total disturbance f 's derivative.

[0035] Since the total disturbance term cannot be directly measured and needs to be estimated through a state observer, an LESO is introduced, and its structure is as follows: (19); In the equation, , is used to estimate , is used to estimate , is the estimated temperature, is the derivative of z, is the output matrix, The matrix and The matrix are the same as those in Equation (18), is the observer design parameter. After expanding Equation (19), we can get: (20); In the equation, and are the estimated parameters, is 's derivative, is 's derivative, and are the adjustable parameters of the observer.

[0036] Through the LESO, the total disturbance term can be accurately estimated. Substituting it into Equation (17) can be reduced to a single-integral link: (21); (22); That is, through the ADRC controller, the complex air-cooled PEMFC thermal management system can finally be reduced to a simple single-integral link ,​ The control action generated for LSEF (Linear State Error Feedback).

[0037] That is Figure 2 The total process from the middle part to the output, so that the difficulty of controller design can be greatly reduced and satisfactory control effects can be achieved. The present invention realizes the control of a single integral link only through proportional control: (23); In the formula, is the target temperature.

[0038] It can be seen that the first-order linear ADRC has 3 adjustable parameters: , and , and the present invention uses the bandwidth method for adjustment. To achieve the convergence of LESO, it is necessary to make the eigenvalues of the matrix in formula (20) all less than 0, and then we can get:

[0039] (24); (25); In the formula, is the eigenvalue of the matrix.

[0040] By using pole placement, that is, making , the following relational expressions can be solved: (26); In the formula, and are two specific solutions of the eigenvalue of the matrix.

[0041] To ensure that LESO has a faster convergence speed than LSEF, generally let: (27); In the formula, is the bandwidth of LSEF, is the bandwidth of LESO.

[0042] Apply the current perturbation shown in Figure 3 , and compare the temperature control effects of the PID controller and the ADRC controller. As shown in Figure 4 , except for the initial perturbation stage, the amplitude of the temperature fluctuation caused by the remaining current perturbations of the ADRC controller is smaller than that of the PID controller. Thus, the superiority of ADRC control can be highlighted. At the initial stage of the control process, since in the LESO of ADRC needs to track y from 0, LESO fails to converge in time, resulting in a large temperature fluctuation during the first current perturbation.

[0043] S4: Optimize the ADRC controller in S3 using Extreme Search (Elastic Search, ES) to enable its control parameters to adaptively change with the system state.

[0044] To further improve the control effect of ADRC, the gain of its control action can be optimized , and this coefficient affects the total disturbance . If the value is appropriate, the total disturbance can be reduced, thus achieving a better control effect.

[0045] To achieve adaptive change with the system state, the present invention uses the Extreme Search (ES) method to optimize the value online. The structural diagram of the ES optimization method is as shown in Figure 5 . ES is a model-free online optimization method applicable to dynamic system optimization. A target function needs to be specified in advance. The target function of the present invention is selected as follows:

[0046] (28); In the formula, is the t target function at time T is the control process time, is the actual temperature error.

[0047] It can be seen that the target function of ES optimization is the integral of the square of the temperature error, and the temperature error is closely related to the value. Therefore, it can be considered that is related to by a non-linear function relationship: (29); In the formula, is the non-linear function, is the temperature control gain at time t.

[0048] Since the air-cooled PEMFC thermal management system after combining with the ADRC controller is very complex and it is difficult to obtain the exact expression, the model-free optimization method of ES is more applicable. Figure 6 shows the structural diagram of ES optimizing ADRC in the present invention. The core of ES lies in applying high-frequency perturbations to the variable to be optimized. In the present invention, a high-frequency sine signal perturbation is applied to , so that the gradient of the target function can be calculated according to the oscillation of the target function output by the system, and finally is optimized along the gradient direction.The objective function can be minimized to improve the temperature control effect. The ES optimization process in the present invention is shown in detail below. First, the control action gain at is perturbed by a high-frequency sine wave to obtain the high-frequency gain :

[0049] (30); In the formula, is the amplitude of the perturbation signal, is the frequency of the perturbation signal. Substitute into Equation (17) to design an ADRC controller to obtain the corresponding objective function , and perform a Taylor expansion on it:

[0050] (31); In the formula, is the derivative of the non-linear function.

[0051] To obtain the gradient information, multiply the objective function by the same sine signal: (32); In the formula, is an intermediate variable containing gradient information.

[0052] Substitute into Equation (31) to get: (33); Simplify through the double-angle formula of trigonometric functions to get: (34); Filter through a low-pass filter to obtain the gradient information : (35); Finally, let be adjusted along the gradient direction at the current t moment to optimize the objective function: (36); In the formula, is the derivative of the temperature control gain at the current moment, k is the adjustment step size, is the gradient information.

[0053] Apply the same current perturbation as in S3, and the temperature control effect is as shown in Figure 7 . ES-ADRC has a smaller overshoot and a shorter adjustment time compared to ADRC. As shown in Figure 8As shown, the improvement of the temperature control effect benefits from the ES realizing the adaptive optimization of in the ADRC controller, thereby reducing the total disturbance term f , and improving the convergence speed of the LESO. Figure 9 shows the objective function before and after the ES optimization during the entire control process. It can be seen that the objective function after the ES optimization is significantly smaller. As can be seen from Equation (28), the smaller the , the better the control effect.

[0054] Based on the same concept, the present invention also provides an ADRC-based air-cooled PEMFC temperature control system, including a collection module, a construction module, an input module, and a control module.

[0055] The collection module is used to collect the actual temperature of the air-cooled proton exchange membrane fuel cell at the current moment and the temperature control amount at the previous moment.

[0056] The construction module is used to construct an active disturbance rejection controller (ADRC), including a linear extended state observer and a linear state error feedback controller.

[0057] The input module is used to input the actual temperature at the current moment and the temperature control amount at the previous moment into the linear extended state observer to obtain the estimated temperature and the estimated total disturbance at the next moment; subtract the target temperature from the estimated temperature at the next moment to obtain the estimated temperature error, and input the estimated temperature error into the linear state error feedback controller to obtain the preliminary control amount at the next moment.

[0058] The control module is used to feed forward compensate the estimated total disturbance at the next moment to the preliminary control amount at the next moment to obtain the temperature control amount at the next moment; control the temperature of the air-cooled proton exchange membrane fuel cell through the temperature control amount at the next moment.

[0059] The present invention provides a method for controlling the temperature of an air-cooled PEMFC thermal management system using an ADRC controller. Facing a complex non-linear system such as an air-cooled PEMFC thermal management system, PID control is prone to disadvantages such as large overshoot and long adjustment time, while model-based advanced control methods rely too much on the accuracy of the model, often difficult to handle external and internal disturbances, and due to their huge computational amount, often difficult to implement and maintain in actual engineering. The ADRC controller is inherited from PID, has the advantages of flexible structure and small computational amount, is easy to implement in actual engineering, and the ADRC controller can handle internal and external disturbances through the total disturbance term, has strong anti-disturbance ability and good control effect, and overcomes the defects of PID control and advanced control.

[0060] The present invention also provides a method for adopting an ES self-adaptive optimized ADRC controller. The control action gain in the ADRC controller affects the final control effect, but it is difficult to accurately describe its functional relationship with the final control effect. Therefore, adopting the model-free optimization method ES applicable to dynamic systems is a good choice, which can realize online adjustment to optimize the control effect.

[0061] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications to these embodiments once they know the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present invention.

[0062] Obviously, those skilled in the art can make various changes and deformations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and deformations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these modifications and deformations.

Claims

1. An ADRC-based temperature control method for air-cooled PEMFC, characterized in that, It includes the following steps: Collect the actual temperature of the air-cooled proton exchange membrane fuel cell at the current moment and the temperature control quantity at the previous moment; Construct an active disturbance rejection controller (ADRC), including a linear extended state observer and a linear state error feedback controller; Input the actual temperature at the current moment and the temperature control quantity at the previous moment into the linear extended state observer to obtain the estimated temperature and the estimated total disturbance at the next moment; Subtract the estimated temperature at the next moment from the target temperature of the air-cooled proton exchange membrane fuel cell to obtain the estimated temperature error, and input the estimated temperature error into the linear state error feedback controller to obtain the preliminary control quantity at the next moment; Feed forward compensate the estimated total disturbance at the next moment to the preliminary control quantity at the next moment to obtain the temperature control quantity at the next moment; control the temperature of the air-cooled proton exchange membrane fuel cell through the temperature control quantity at the next moment.

2. The air-cooled PEMFC temperature control method based on ADRC according to claim 1, characterized in that The construction of the active disturbance rejection controller (ADRC) includes the following steps: Obtain the disturbance rejection paradigm of the ADRC, and the disturbance rejection paradigm is as follows: ； In the formula, is the controlled variable, is the derivative of the controlled variable, is the temperature control variable, is the temperature control variable gain, is the total disturbance composed of internal disturbance and external disturbance; Convert the disturbance rejection paradigm of the ADRC into the state space equation of the ADRC, and estimate the total disturbance through the linear extended state observer. The specific form of the linear extended state observer is as follows: ； Wherein, and are estimated parameters, for estimating , for estimating , is the estimated temperature, is the derivative of, is the derivative of, and are the adjustable parameters of the observer; Input the linear extended state observer into the state space equation of the ADRC to obtain the control equation, and the control equation is as follows: ； ； In the formula, is the preliminary control quantity generated by the linear state error feedback controller; Realize the control of the single integral link through proportional control: ； In the formula, is the proportionality coefficient, r is the target temperature.

3. The temperature control method of an air-cooled PEMFC based on ADRC according to claim 2, characterized in that The active disturbance rejection controller (ADRC) includes multiple adjustable parameters, and the bandwidths corresponding to the multiple adjustable parameters are as follows: ； wherein, is the bandwidth of the linear state error feedback controller, is the bandwidth of the linear extended state observer.

4. The temperature control method of an air-cooled PEMFC based on ADRC according to claim 1, wherein, The step of feeding forward compensating the estimated total disturbance at the next moment to the preliminary control quantity at the next moment to obtain the temperature control quantity at the next moment includes the following steps: During the feed forward compensation process, optimize the gain of the temperature control quantity at the next moment through extremum search; Combine the optimized gain of the temperature control quantity at the next moment with the preliminary control quantity at the next moment after compensation to obtain the temperature control quantity at the next moment.

5. The temperature control method of an air-cooled PEMFC based on ADRC according to claim 4, characterized in that The step of optimizing the gain of the temperature control quantity at the next moment through extremum search includes the following steps: Obtain the actual temperature error between the actual temperature and the target temperature at the current moment, and define the objective function based on the actual temperature error. The objective function is as follows: ； In the formula, is t the objective function at time T is the control process time, is the actual temperature error; Apply a sine disturbance to the gain of the temperature control quantity at the current moment to obtain the objective function at the current moment; Obtain the gradient of the objective function at the current moment, and optimize the gain of the temperature control quantity along the gradient direction, specifically as follows: ； wherein, is the derivative of the temperature control quantity gain at the current moment, k is the adjustment step size, is the gradient information.

6. The temperature control method of an air-cooled PEMFC based on ADRC according to claim 1, characterized in that, The step of controlling the temperature of the air-cooled proton exchange membrane fuel cell through the temperature control quantity at the next moment specifically includes the following steps: Construct a thermal management system model of the air-cooled proton exchange membrane fuel cell, including a fuel cell stack model and a thermal analysis module; The thermal analysis module is used to calculate the temperature change rate of the fuel cell stack model, specifically as follows: ； Wherein, represents the total input energy, represents the output electric energy, represents the heat carried away by the cooling air, represents the heat dissipated by radiation and natural convection, represents the heat capacity, t is the time; The temperature control quantity is the fan duty ratio; input the temperature control quantity at the next moment into the thermal analysis module to change the air flow rate and the surface heat transfer coefficient of the cathode flow channel, and control the temperature of the fuel cell stack.

7. An air-cooled PEMFC temperature control system based on ADRC, characterized in that, It includes: A collection module for collecting the actual temperature of the air-cooled proton exchange membrane fuel cell at the current moment and the temperature control quantity at the previous moment; A building block for constructing an Active Disturbance Rejection Controller (ADRC), including a linear Extended State Observer (ESO) and a linear State Error Feedback Controller (SEFC). An input module for inputting the actual temperature at the current moment and the temperature control quantity at the previous moment into the linear Extended State Observer (ESO) to obtain the estimated temperature and the estimated total disturbance at the next moment. Subtract the target temperature from the estimated temperature at the next moment to obtain the estimated temperature error, and input the estimated temperature error into the linear State Error Feedback Controller (SEFC) to obtain the preliminary control quantity at the next moment. A control module for feedforward compensating the estimated total disturbance at the next moment to the preliminary control quantity at the next moment to obtain the temperature control quantity at the next moment; controlling the temperature of the air-cooled proton exchange membrane fuel cell with the temperature control quantity at the next moment.

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