PID (Proportion Integration Differentiation) control device and method of fuel cell system

Abstract

The invention discloses a PID control apparatus and method of a fuel cell system. The PID control device comprises a hydrogen pressure sensing unit which collects an actual hydrogen pressure value at an outlet of a hydrogen proportional valve arranged between the hydrogen supply device and the fuel cell stack and generates a collected value representing the actual hydrogen pressure value; the PID controller is used for carrying out a preset PID control algorithm on a hydrogen pressure deviation value between the acquisition value and target hydrogen pressure of the fuel cell system, the variable quantity of the hydrogen pressure deviation value and the cumulant of the hydrogen pressure deviation value so as to obtain a coefficient of the PID controller; and calculating a control amount for the opening degree of the hydrogen proportional valve according to the coefficient.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of power equipment control, and particularly relates to a PID control device and method for a fuel cell system. BACKGROUND

[0002] In the technical field of fuel cell power stations, especially in fixed fuel cell power stations, hydrogen supply system control and anode water and nitrogen discharge are the key to ensuring the efficient and stable operation of the system. At present, the industry generally adopts a PID control strategy to regulate the hydrogen proportional valve in the hydrogen supply system control method of a PEMFC proton exchange membrane fuel cell power generation system.

[0003] During the operation of a fuel cell system, the accumulation of anode water and nitrogen is a problem that cannot be ignored. At present, for anode nitrogen discharge, it is mainly dependent on the discharge of impurity gas at a fixed time by experiment calibration or observation of the numerical change of the voltage patrol device of the stack. SUMMARY

[0004] The hydrogen supply system control and anode water and nitrogen discharge device and method for a fuel cell system in the prior art still have obvious defects in ensuring the safety, reliability and operability of the system. The present application aims to at least solve one of the technical problems in the prior art to some extent.

[0005] According to an aspect of the present application, a PID control device for a fuel cell system is provided, the fuel cell system comprising a fuel cell stack, a hydrogen supply device for supplying hydrogen to the fuel cell stack via a hydrogen inlet pipeline, characterized in that the PID control device comprises: a hydrogen pressure sensing unit for collecting an actual hydrogen pressure value at the outlet of a hydrogen proportional valve and generating a collection value representing the actual hydrogen pressure value, wherein the hydrogen proportional valve is arranged between the hydrogen supply device and the fuel cell stack; a PID controller for performing a preset PID control algorithm on a hydrogen pressure deviation value between the collection value and a target hydrogen pressure of the fuel cell system, a change amount of the hydrogen pressure deviation value, and an accumulated amount of the hydrogen pressure deviation value to obtain a coefficient of the PID controller, and calculating a control amount for the opening degree of the hydrogen proportional valve according to the coefficient.

[0006] Through the above-mentioned PID control device, a fuzzy PID control method is provided for the control strategy of the fuel cell hydrogen supply valve, which directly controls the outlet pressure of the proportional valve (the inlet pressure of the stack) through ordinary PID parameter setting and fuzzy PID self-adaptive control, improves the dynamic response speed of the system, and reduces the steady-state time of the system.

[0007] Preferably, the coefficient of the PID controller comprises a proportional coefficient k associated with the hydrogen pressure deviation valuep The integral coefficient k associated with the accumulated amount i The differential coefficient k associated with the change d .

[0008] Using the aforementioned PID control equipment, a fuzzy PID control method is provided for the control strategy of the hydrogen supply valve in a fuel cell. This method directly and adaptively controls the proportional valve outlet pressure (stack inlet pressure), improving the system's dynamic response speed and reducing the system's steady-state time.

[0009] Preferably, the PID control device performs a preset PID control algorithm on the hydrogen pressure deviation between the acquired value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation, including: the PID control device performs a preset first PID control algorithm on the hydrogen pressure deviation between the acquired value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation according to Equation 1, to calculate the control quantity u(k) for the opening degree of the hydrogen proportional valve:

[0010]

[0011] Where e(k) is the hydrogen pressure deviation value collected in the kth sampling, where e(k) = r(k) - c(k), where r(k) is the target hydrogen pressure, c(k) is the actual hydrogen pressure measured by the hydrogen pressure sensing unit, and e(k-1) is the hydrogen pressure deviation value collected in the (k-1)th sampling. p k is the proportionality coefficient. i For the integral coefficient, k d Here, is the differential coefficient, k is the k-th sample, and j is the accumulation operator.

[0012] The PID control device calculates the increment value Δu(k) of the control quantity u(k) according to Equation 2:

[0013] △u(k)= k p ×[e(k)-e(k-1)]+k i ×e(k)+k d Equation 2: ×[e(k)-2×e(k-1)+e(k-2)]

[0014] The PID control device outputs a control command generated based on the incremental value Δu(k) to the hydrogen proportional valve. The hydrogen proportional valve adjusts its opening degree according to the control command. The hydrogen pressure sensing unit collects the actual hydrogen pressure value at the outlet of the hydrogen proportional valve after the opening degree adjustment. The PID control device adjusts k based on the collected actual hydrogen pressure value after the opening degree adjustment. p k i k d To calculate the initial scaling factor k p0 Initial integration coefficient k i0 Initial differential coefficients k d0 .

[0015] Using the aforementioned PID control equipment, a fuzzy PID control method is provided for the control strategy of the hydrogen supply valve in a fuel cell. The parameters are tuned using a conventional PID controller, and then the fuzzy PID controller is used to directly and adaptively control the proportional valve outlet pressure (stack inlet pressure), which improves the dynamic response speed of the system and reduces the steady-state time of the system.

[0016] Preferably, the PID control algorithm for the PID control device to preset the hydrogen pressure deviation between the acquired value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation further includes: a second PID control algorithm for the PID control device to preset the hydrogen pressure deviation between the acquired value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation, in order to determine the fuzzification proportional coefficient Δk. p fuzzy integral coefficient Δk i fuzzy differential coefficients Δk d .

[0017] Preferably, the PID control device maps the hydrogen pressure deviation between the collected value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation to elements in corresponding fuzzy sets according to a preset fuzzy control rule table. The PID control device then determines the fuzzification ratio coefficient Δk based on the mapped elements in the fuzzy sets and a preset database lookup table. p The fuzzification integral coefficient Δk i The fuzzy differential coefficient Δk d The proportional coefficient k of the PID controller is obtained according to Equation 3. p Integral coefficient k i Differential coefficient k d ,

[0018] k p =k p0 +k up ×Δk p

[0019] k i =k i0 +k ui ×Δk i Equation 3

[0020] k d =k d0 +k ud ×Δk d

[0021] Where, k up It is the fuzzification scaling factor Δk p The scaling factor is constant, k ui It is the fuzzification integral coefficient Δk i The scaling factor is constant, k ud It is the fuzzy differential coefficient Δk d The scaling factor is a constant.

[0022] Using the aforementioned PID control equipment, a fuzzy PID control method is provided for the control strategy of the hydrogen supply valve in a fuel cell. The parameters are tuned using a conventional PID controller, and then the fuzzy PID controller is used to directly and adaptively control the proportional valve outlet pressure (stack inlet pressure), which improves the dynamic response speed of the system and reduces the steady-state time of the system.

[0023] Preferably, the PID control device further includes: a hydrogen flow sensing unit installed in the hydrogen inlet pipe, wherein the hydrogen flow sensing unit measures the hydrogen flow rate in real time and generates a flow rate value representing the flow rate; and a current acquisition unit that measures the stack current of the fuel cell stack in real time and generates a current value representing the stack current.

[0024] Preferably, the PID controller calculates the actual hydrogen consumption of the fuel cell system based on the flow rate value, and the PID controller calculates the theoretical hydrogen consumption of the fuel cell system based on the current value. The PID controller compares the actual hydrogen consumption with the theoretical hydrogen consumption to control the opening / closing of the anode nitrogen venting valve of the fuel cell system based on the comparison result.

[0025] By using the aforementioned PID control equipment, a method for nitrogen emission from stationary fuel cell power plants is provided to address the problem of nitrogen accumulation at the anode of fuel cells. The stationary fuel cell power plant integrates a hydrogen flow meter to detect hydrogen flow and monitor hydrogen flow data online in real time.

[0026] Preferably, the PID control device further includes: a liquid level sensing unit installed in the water vapor separator of the fuel cell stack, and the liquid level sensing unit measures the liquid level in the water vapor separator in real time and generates a liquid level value representing the liquid level.

[0027] Preferably, the PID controller compares the liquid level value with a preset threshold to control the opening / closing of the drain valve of the fuel cell system based on the comparison result.

[0028] The aforementioned PID control device provides a method for discharging liquid water from fuel cell anodes in stationary fuel cell power plants. The stationary fuel cell power plant integrates a liquid level sensor to detect the liquid level in the water tank of the water vapor separator, thereby controlling the opening of the drain valve. The drain valve is then closed based on the pressure sensor and hydrogen flow meter integrated into the system.

[0029] According to another aspect of the present invention, a PID control method for a fuel cell system is provided. The fuel cell system includes a fuel cell stack, a hydrogen supply device that supplies hydrogen to the fuel cell stack via a hydrogen inlet pipe, and a hydrogen proportional valve disposed between the hydrogen supply device and the fuel cell stack. The PID control method comprises the following steps: a hydrogen pressure sensing step, acquiring the actual hydrogen pressure value at the outlet of the hydrogen proportional valve and generating a acquired value representing the actual hydrogen pressure value; and a PID control step, performing a preset PID control algorithm on the hydrogen pressure deviation value between the acquired value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation value, and the cumulative amount of the hydrogen pressure deviation value to obtain PID control coefficients, and calculating a control quantity for the opening degree of the hydrogen proportional valve based on the PID control coefficients.

[0030] Preferably, the PID control coefficient includes a proportional coefficient k associated with the hydrogen pressure deviation value. p The integral coefficient k associated with the accumulated amount i The differential coefficient k associated with the change d .

[0031] Preferably, the PID control step, which presets the hydrogen pressure deviation between the acquired value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation, includes: performing a preset first PID control algorithm based on Equation 1 on the hydrogen pressure deviation between the acquired value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation, to calculate the control quantity u(k) for the opening of the hydrogen proportional valve.

[0032]

[0033] Where e(k) is the hydrogen pressure deviation value collected in the kth sampling, where e(k) = r(k) - c(k), where r(k) is the target hydrogen pressure, c(k) is the actual hydrogen pressure measured by the hydrogen pressure sensing unit, and e(k-1) is the hydrogen pressure deviation value collected in the (k-1)th sampling. p k is the proportionality coefficient. i For the integral coefficient, k d Here, is the differential coefficient, k is the k-th sample, and j is the accumulation operator.

[0034] Calculate the increment value Δu(k) of the control quantity u(k) according to Equation 2:

[0035] △u(k)= k p ×[e(k)-e(k-1)]+k i ×e(k)+k d Equation 2: ×[e(k)-2×e(k-1)+e(k-2)]

[0036] The PID control device outputs a control command generated based on the incremental value Δu(k) to the hydrogen proportional valve. The hydrogen proportional valve adjusts its opening degree according to the control command. The hydrogen pressure sensing unit collects the actual hydrogen pressure value at the outlet of the hydrogen proportional valve after the opening degree adjustment. The PID control device adjusts k based on the collected actual hydrogen pressure value after the opening degree adjustment. p k i k d To calculate the initial scaling factor k p0 Initial integration coefficient k i0 Initial differential coefficients k d0 .

[0037] Preferably, the PID control step, which presets the hydrogen pressure deviation between the acquired value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation, further includes: a second PID control algorithm that presets the hydrogen pressure deviation between the acquired value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation, to determine the fuzzification proportional coefficient Δk. p fuzzy integral coefficient Δk i fuzzy differential coefficients Δk d .

[0038] Preferably, in the PID control step, according to a preset fuzzy control rule table, the hydrogen pressure deviation between the collected value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation are mapped to elements in corresponding fuzzy sets. Based on the elements in the mapped fuzzy sets and a preset database lookup table, the fuzzification proportional coefficient Δk is determined. p The fuzzification integral coefficient Δk i The fuzzy differential coefficient Δk d The proportionality constant k is obtained according to Equation 3. p Integral coefficient k i Differential coefficient k d ,

[0039]

[0040] Where, k up It is the fuzzification scaling factor Δk p The scaling factor is constant, k ui It is the fuzzification integral coefficient Δk i The scaling factor is constant, k ud It is the fuzzy differential coefficient Δk d The scaling factor is a constant.

[0041] Preferably, the PID control method further includes the following steps: a hydrogen flow sensing step, which measures the flow rate of hydrogen flowing through the hydrogen inlet pipe in real time and generates a flow rate value representing the flow rate; and a current acquisition step, which measures the stack current of the fuel cell stack in real time and generates a current value representing the stack current.

[0042] Preferably, in the PID control step, the actual hydrogen consumption of the fuel cell system is calculated based on the flow rate value, and the theoretical hydrogen consumption of the fuel cell system is calculated based on the current value. The actual hydrogen consumption is compared with the theoretical hydrogen consumption, and the opening / closing of the anode nitrogen venting valve of the fuel cell system is controlled according to the comparison result.

[0043] Preferably, the PID control method further includes the following steps: a liquid level sensing step, wherein the liquid level in the water vapor separator of the fuel cell stack is measured in real time, and a liquid level value representing the liquid level is generated.

[0044] Preferably, in the PID control step, the liquid level value is compared with a preset threshold to control the opening / closing of the drain valve of the fuel cell system based on the comparison result.

[0045] In summary, the present invention provides the following technical advantages:

[0046] By using ordinary PID for parameter tuning and then using fuzzy PID to directly adaptively control the proportional valve outlet pressure (fuel cell inlet pressure), the system's dynamic response speed is improved and the system's steady-state time is reduced.

[0047] When nitrogen accumulation is detected, causing pressure changes, the control system dynamically adjusts the proportional valve according to the rate of pressure change. If the pressure increase is caused by slow nitrogen accumulation, the proportional valve can be adjusted to a lesser extent to avoid excessive reduction of the valve opening, which could lead to insufficient hydrogen supply.

[0048] By comprehensively considering operating parameters, the actual needs of the system can be judged more accurately, avoiding hydrogen supply problems caused by adjusting based on a single parameter. When the pressure increases but the hydrogen flow rate is already close to the minimum requirement of the fuel cell, the control system can limit the proportional valve to further reduce its opening.

[0049] During the operation of a fuel cell system, complex operating conditions such as load changes and temperature fluctuations can affect hydrogen consumption. By integrating and comparing hydrogen consumption over a period of time, these complex operating conditions can be adapted to a certain extent. For example, during dynamic load changes, even if the current fluctuates instantaneously, integral calculations can more accurately determine whether the overall hydrogen consumption is affected by nitrogen accumulation. Attached Figure Description

[0050] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0051] Figure 1This is an example diagram of a hydrogen supply system according to an embodiment of this application.

[0052] Figure 2 This is a schematic diagram of a common PID control principle for a hydrogen proportional valve in a PID control device for a fuel cell system according to an embodiment of this application.

[0053] Figure 3 This is a schematic diagram of the fuzzy PID control principle of the PID control device for the hydrogen proportional valve in the fuel cell system according to an embodiment of this application.

[0054] Figure 4 This is a schematic diagram of the overall PID control principle of the hydrogen proportional valve for the PID control device of the fuel cell system according to an embodiment of this application.

[0055] Figure 5 This is a flowchart of PID parameter tuning for a PID control method for a fuel cell system according to an embodiment of this application.

[0056] Figure 6 This is a flowchart illustrating the operation of a PID control method for a fuel cell system according to an embodiment of this application.

[0057] Figure 7 This is a functional block diagram of a fuel cell system implementing a PID control method according to an embodiment of this application. Detailed Implementation

[0058] 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.

[0059] 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 steps is not necessarily limited to those steps or steps explicitly listed, but may include other steps or steps not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0060] In existing technologies, the hydrogen outlet pressure of the fuel cell stack is controlled through air inlet pressure feedback. However, this method has certain limitations when facing problems such as insufficient hydrogen flow or low hydrogen utilization efficiency. Specifically, when the concentration of impurity gases, such as nitrogen, inside the fuel cell stack is high, the inlet and outlet pressures of the stack may become close. In this case, the system may not be able to identify the risk of insufficient hydrogen flow, thus affecting the accuracy and timeliness of hydrogen supply. This method does not take into account the dynamic changes in nitrogen accumulation, which may lead to untimely discharge and excessive accumulation of nitrogen in the stack, affecting the stack's performance and efficiency. For anode liquid water discharge, the current main methods are timed drainage based on experimental calibration or periodic drainage based on current integration. However, these methods often cannot efficiently respond to actual liquid water accumulation, resulting in insufficient anode water discharge, affecting the stack's thermal management and long-term reliability. In addition, traditional control strategies often struggle to adapt quickly to complex operating conditions such as load changes and temperature fluctuations, resulting in poor performance of the hydrogen supply system in terms of dynamic response speed and steady-state time.

[0061] To address the shortcomings of traditional hydrogen supply system control and anode water and nitrogen emission devices and methods for fuel cell systems, this invention proposes a technical solution for hydrogen supply system control and anode water and nitrogen emission devices and methods for fuel cell systems, aiming to improve safety, accuracy and efficiency, while simplifying the operation process and increasing the level of automation.

[0062] To facilitate understanding, we will now briefly introduce the concepts, algorithms, and principles involved in the PID (proportional-integral-derivative) control device for the fuel cell system according to this invention:

[0063] Fuzzy PID Control Algorithm: Fuzzy PID control is an algorithm that combines fuzzy logic with traditional PID (Proportional-Integral-Derivative) control to improve the control performance of a system facing uncertainty and nonlinear characteristics. Based on traditional PID control, fuzzy PID dynamically adjusts PID parameters by introducing fuzzy logic rules to adapt to control requirements under different operating conditions, thereby improving the robustness and flexibility of control. The following is a detailed explanation of the fuzzy PID control algorithm: Steps of the Fuzzy PID Control Algorithm: 1. Error Calculation: First, calculate the system error (e), which is the difference between the target value and the actual value. In this invention, the error is the difference between the target hydrogen pressure and the actual hydrogen pressure. 2. Error Rate of Change Calculation: Calculate the rate of change of the error (ec), which is the difference between the current error and the error at the previous moment, reflecting the dynamic trend of the error. 3. Error Integral Calculation: Calculate the integral of the error (ei), which is the accumulation of the error over time, used to eliminate the steady-state error of the system. 4. Fuzzification: Map the error (e), the rate of change of the error (ec), and the integral of the error (ei) to a fuzzy set. This step transforms precise numerical values ​​into fuzzy semantic descriptions, such as "large positive" (PB), "zero" (ZO), and "large negative" (NB). 5. Rule Formulation: Based on the fuzzified error, a series of fuzzy control rules are formulated. For example, "If the error is large positive and the error rate of change is large positive, then the proportional gain increases." These rules reflect expert knowledge and experience. 6. Fuzzy Inference: Using these rules, fuzzy inference is performed on the current error and error rate of change to determine the corresponding fuzzy PID parameters. The inference process may involve various fuzzy logic operations, such as intersection, union, and complement. 7. Membership Functions: Membership functions are defined for each fuzzy set. These functions describe the degree to which a given value belongs to a specific fuzzy set. For example, Z-type or S-type functions are used to describe the "large negative" and "large positive" fuzzy sets, and trigonometric functions are used to describe the "zero" fuzzy set. 8. Quantization Factors: Quantization factors are determined for the error and error rate of change, used to map the actual numerical values ​​to the appropriate range of the fuzzy set. 9. Fuzzy Control Rule Table: A fuzzy control rule table is created that determines the adjustment amount (Δk) of the PID parameters based on the quantized error and error rate of change values. p Δk i Δk d 10. Defuzzification: The defuzzification process converts the fuzzy PID parameter adjustments derived from fuzzy rule reasoning into clear numerical values. Common defuzzification methods include the centroid method and the maximum membership method. 11. PID Parameter Adjustment: The defuzzified PID parameter adjustments are superimposed on the original PID parameters to form new PID parameters. For example, k p _{new}=k p _{old}+Δk p12. Execution Control: The adjusted PID parameters are used to execute control system operations, adjusting the opening of the hydrogen proportional valve, the state of the drain valve and nitrogen discharge valve, etc., to achieve the target control effect. 13. Periodic Repetition: The above steps are executed within one control cycle and then repeated to adapt to the dynamically changing control requirements of the system.

[0064] Technical advantages of fuzzy PID control algorithm:

[0065] - Robustness: Fuzzy PID control can better cope with nonlinear systems and external disturbances, improving the stability and reliability of the control system.

[0066] - Flexibility: By dynamically adjusting the PID parameters, fuzzy PID control can adapt to different working conditions more flexibly, improving control response and performance.

[0067] - Easy to implement: Fuzzy logic rules are intuitive and easy to understand. They can be set based on expert knowledge and experience, making them suitable for the control design of complex systems.

[0068] The fuzzy PID control algorithm, through the above steps, combines the stability of traditional PID control with the flexibility and intelligence of fuzzy logic, effectively improving the control performance of fuel cell systems under complex operating conditions.

[0069] "Positive Big" (PB), "Zero" (ZO), and "Negative Big" (NB): In fuzzy logic control, "Positive Big" (PB), "Zero" (ZO), and "Negative Big" (NB) represent different members of a fuzzy set used to describe the fuzzy state of input variables. These fuzzy terms are mainly used to quantify system states or human intuition and experience that are difficult to express with precise numerical values. Here are their specific meanings: 1. "Positive Big" (PB): This term describes the situation when the input variable (e.g., error e or error change rate ec) is in the positive range and its value is relatively large. In fuzzy logic, "positive" does not mean a precise numerical value, but rather a fuzzy range where values ​​are all positive, but close to the upper limit. For example, in a hydrogen pressure control scenario, if the detected hydrogen pressure is much higher than the set target pressure, this state might be described as "positive." 2. "Zero" (ZO): "Zero" means that the input variable is close to zero or its influence is very small. It is also a fuzzy concept, describing a variable fluctuating within a very small range, neither too positive nor too negative. For example, when the error in hydrogen pressure is very small, almost zero, or the rate of change in hydrogen flow rate is very small, the word "zero" might be used to describe it. 3. "Large Negative" (NB): In contrast to "Large Positive," "Large Negative" is used to describe a variable in a large range of negative numbers. This usually indicates that the system state is far from the desired target and is below the target value. For example, if the hydrogen pressure is significantly lower than the target value, such a situation would be identified as "Large Negative" by the fuzzy logic controller.

[0070] The definitions of these fuzzy sets (PB, ZO, NB) need to be set according to the specific application scenario and system characteristics. For example, membership functions can be defined to map the precise values ​​of input variables to these fuzzy sets. Membership functions specify the degree to which a value belongs to a particular fuzzy set. For example, membership functions of Z-shaped or S-shaped distributions can be used to describe sets with "large negative" or "large positive" values, while membership functions of triangular distributions are suitable for sets with "zero" values.

[0071] In the example of hydrogen system control in the fuel cell power plant of the present invention, the use of fuzzy concepts such as "large positive", "zero" and "large negative" can help the controller better understand the real-time state of the system and dynamically adjust the PID parameters accordingly to achieve a more accurate and stable control effect.

[0072] u(k): In control theory, u(k) typically represents the control signal or output in discrete time. It is the core output of the controller in a control system, used to adjust the behavior of the controlled object (such as motor speed, temperature, pressure, etc.) to achieve the desired goal. Specifically, in the fuzzy PID control algorithm mentioned in this invention, u(k) is the control action output by the controller to the actuator (such as a hydrogen proportional valve) at time (k), that is, the kth sampling. It is calculated based on the error e(k) at the current moment, as well as the error changes and accumulated errors at previous moments. This control signal directly affects the action of the actuator. For example, in a fuel cell hydrogen supply system, u(k) determines the opening degree of the hydrogen proportional valve, thereby affecting the hydrogen flow rate and ultimately helping the system maintain the desired hydrogen pressure level. In the following formulas mentioned in this invention:

[0073] -k p It is the proportional coefficient, which determines the direct contribution of the error e(k) to the control signal;

[0074] -k i These are integral coefficients, used to calculate the cumulative effect of error over time, with the aim of eliminating steady-state error.

[0075] -k d It is the differential gain, which estimates the rate of change of error. It helps to predict future errors and react in advance, reducing overshoot.

[0076] In fuzzy PID control, u(k) is the result of conventional PID control plus fuzzy control adjustments. That is, u(k) not only includes the proportional, integral, and derivative terms based on the error, but also incorporates dynamic adjustments to the PID parameters under fuzzy logic rules to further optimize control performance and enhance the controller's intelligence and adaptability. In the context of fuzzy PID control, the calculation of u(k) also includes an additional step: superimposing the incremental value of the fuzzy adjustment onto the conventional PID control.

[0077]

[0078] These incremental values ​​are calculated based on the fuzzy control rules and the current error state, aiming to better adapt to complex and dynamic system environments. The initial proportional gain k is... p0 Initial integration coefficient k i0 Initial differential coefficients k d0 This is the gain value of a conventional PID controller, while the increment (fuzzy proportional coefficient Δk) is... p fuzzy integral coefficient Δk i fuzzy differential coefficients Δk dThe adjustment amounts are retrieved through the fuzzy control rule table, and they are related to the quantization factor (i.e., k). up It is the fuzzification scaling factor Δk p The scaling factor is constant, k ui It is the fuzzification integral coefficient Δk i The scaling factor is constant, k ud It is the fuzzy differential coefficient Δk d The signal is multiplied by the proportional factor (which is a constant) and then superimposed on the conventional PID output to generate the final control signal u(k). In this way, the controller can not only respond quickly according to the current error state of the system, but also take into account historical data and future predictions, thereby achieving more accurate and intelligent control.

[0079] The PID control device for a fuel cell system according to the present invention will be described in detail below with reference to the accompanying drawings.

[0080] Figure 1 This is an example diagram of a hydrogen supply system according to an embodiment of this application. Figure 1 As shown in the upper diagram, the hydrogen supply system according to an embodiment of this application includes: a hydrogen source 102, a hydrogen on / off valve 104, a hydrogen pressure regulating valve 106, a hydrogen flow meter 108, a hydrogen heat exchanger 110, a hydrogen proportional valve 112, a hydrogen ejector 114, an MFC (mass flow controller) 116, a nitrogen flow calibration valve 118, an atmosphere 120, a fuel cell stack 122, a pressure relief valve 124, a liquid level sensor 126, a hydrogen-water vapor separator 128, an anode nitrogen venting valve 130, and an anode drain valve 132. Furthermore, as... Figure 1 As shown in the lower part of the diagram, the hydrogen supply system according to an embodiment of this application further includes a hydrogen flow / pressure intelligent controller 134. Specifically, data collected by the current acquisition device 136, the hydrogen flow meter 108, and the hydrogen pressure sensor 138 are input to the hydrogen flow / pressure intelligent controller 134. The hydrogen flow / pressure intelligent controller 134 generates control commands based on the input data, which are output to the MFC (mass flow controller) 116, the hydrogen proportional valve 112, the anode nitrogen purging valve 130, and the anode drain valve 132, respectively. The PID control device of the fuel cell system according to an embodiment of this application includes a hydrogen flow meter 108, a liquid level sensor 126, a current acquisition device 136, a hydrogen flow / pressure intelligent controller 134, and a hydrogen pressure sensing unit (not shown). Specifically, the hydrogen pressure sensing unit can acquire the actual hydrogen pressure value at the outlet of the hydrogen proportional valve 112 and generate a acquired value representing the actual hydrogen pressure value.

[0081] The following is for reference. Figure 2 The present application describes in detail the PID control device of the fuel cell system according to the embodiment of the present application, which is based on the ordinary PID control principle of the hydrogen proportional valve.Figure 2 This is a schematic diagram of a standard PID control principle for a hydrogen proportional valve in a fuel cell system according to an embodiment of this application. During the control of the hydrogen proportional valve, the hydrogen flow / pressure intelligent controller 134 first follows the standard PID control principle for the hydrogen proportional valve, and then employs... Figure 3 The diagram illustrates the principle of fuzzy PID control. In other words, the control of the hydrogen proportional valve primarily involves calibrating the proportional coefficient Kp0, integral coefficient Ki0, and derivative coefficient Kd0 using ordinary PID control. Then, fuzzy PID control is employed. Figure 2 In the schematic diagram of a typical PID control, p1 represents the "actual hydrogen pressure," 202 indicates "collecting the actual hydrogen pressure p1, unit pressure kPa," p represents the "target hydrogen pressure," 204 represents the "PID controller," 206 represents the "hydrogen proportional valve opening coefficient c," and 208 represents the "hydrogen proportional valve opening control command R." Furthermore, in... Figure 2 In the schematic diagram of a typical PID control, e(k) represents the hydrogen pressure deviation sampled for the kth time, where e(k) = r(k) - c(k); r(k) is the input of the target hydrogen pressure; c(k) is the output of the actual hydrogen pressure; e(k-1) is the hydrogen pressure deviation sampled for the (k-1)th time; k p k i k d These are the proportional coefficient, integral coefficient, and derivative coefficient, respectively; T is the sampling period; k is the kth sampling; and j is the calculation accumulation operator. The PID controller uses a preset first PID control algorithm based on Equation 1 to calculate the control quantity u(k) for the opening degree of the hydrogen proportional valve, considering the hydrogen pressure deviation between the collected values ​​and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation.

[0082]

[0083] The PID controller performs two PID increment calculations based on Equation 2, resulting in:

[0084] △u(k)= k p ×[e(k)-e(k-1)]+k i ×e(k)+k d Equation 2: ×[e(k)-2×e(k-1)+e(k-2)]

[0085] In practical applications, after the system starts operating, a fixed initial opening value R0 is given to the hydrogen proportional valve, and the initial hydrogen pressure value P0 is collected. The ordinary PID control method described above is then executed to tune the initial k. p0 k i0 and k d0value.

[0086] The above tuning yields the initial k p0 k i0 and k d0 The value processing flow is as follows Figure 5 As shown, Figure 5 A flowchart illustrating the PID parameter tuning process of a PID control method for a fuel cell system according to an embodiment of this application is shown. Figure 5 As shown, the PID parameter tuning process begins at step 602 and continues with the following steps: Step 604, input the target hydrogen pressure P0 (kPa), then proceed to step 606, acquire the actual hydrogen pressure P1 (kPa), then proceed to step 608, perform PID deviation calculation e = u0 - u1, and provide it to the PID controller for incremental calculation, sending the pressure increment to the input of the hydrogen proportional valve. The hydrogen pressure sensor acquires the hydrogen pressure value, then proceed to step 610, determine whether the hydrogen pressure value obtained from the current PID tuning parameters meets the requirements. If the hydrogen pressure value obtained from the current PID tuning parameters meets the requirements, then proceed to step 614, perform debugging and tuning for the next target hydrogen pressure data, then proceed to step 616, determine whether all parameter tuning is complete. If it is determined that all parameter tuning is complete, proceed to step 618 to end the PID parameter tuning process. Furthermore, if it is determined in step 610 that the hydrogen pressure value obtained from the current PID tuning parameters does not meet the requirements, proceed to step 612, and continue to modify k... p k i k d The parameters are adjusted and readjusted, and the hydrogen pressure overshoot, response time, and steady-state error are recorded. Then, proceed to step 606. Alternatively, if it is determined in step 616 that not all parameters have been adjusted, proceed to step 604.

[0087] Next, refer to Figure 3 The fuzzy PID control of the PID control device for the hydrogen proportional valve is further described. Figure 3 This is a schematic diagram of the fuzzy PID control principle for the hydrogen proportional valve in a PID control device for a fuel cell system according to an embodiment of this application. Figure 3 In the fuzzy PID control schematic diagram shown, P1 represents "actual hydrogen pressure", P represents "target hydrogen pressure", 302 represents "PID controller", 304 represents "proportional valve opening coefficient c", 306 represents "hydrogen proportional valve", 308 represents "hydrogen pressure sensor", 310 represents "differentiator", 312 represents "integrator", 314 represents "fuzzy controller", 314-1 represents "fuzzification module", and 314-2 represents "lookup table". In other words, as... Figure 3As shown, the input P of the PID controller is the target hydrogen control pressure of the fuel cell system, and the output P1 is the actual hydrogen pressure, which serves as the feedback value; e(t), ec(t), and ei(t) represent the hydrogen pressure deviation, the change in deviation, and the cumulative deviation, respectively; Ke and Kec are the deviation quantization factor and the deviation change quantization factor, respectively, both of which are constants; △Kp, △Ki, and △Kd are the lookup values ​​of the proportional coefficient change, integral coefficient change, and derivative coefficient change in the fuzzy controller's lookup table 314-2 database, respectively; c represents the hydrogen proportional valve opening coefficient, that is, the percentage opening corresponding to the unit pressure value of the hydrogen proportional valve.

[0088] As previously stated, the PID control in this disclosure is an algorithm that combines fuzzy logic with traditional PID (proportional-integral-derivative) control. The following references... Figure 4 The present application describes in detail the overall PID control principle of the PID control device for the hydrogen proportional valve in the fuel cell system according to the embodiments of the present application. Figure 4 This is a schematic diagram of the overall PID control principle for the hydrogen proportional valve of the PID control device for a fuel cell system according to an embodiment of this application. Figure 4 As shown, 402 represents "hydrogen pressure deviation", 404 represents "integrator", 406 represents "differentiator", 408 represents "PID controller", and Pk represents "hydrogen pressure calculated by the PID controller". Figure 4 As shown in the diagram, in the PID controller, Kp0, Ki0, and Kd0 are the proportional, integral, and derivative coefficients of a typical PID controller, respectively, all of which are constants; Kup, Kui, and Kud are the proportional factors of ΔKp, ΔKi, and ΔKd, respectively, all of which are constants; Kp, Ki, and Kd are the proportional, integral, and derivative coefficients of the PID controller. The determination of fuzzy PID coefficients in the PID controller, specifically the method for determining the fuzzy PID proportional coefficient ΔKp, integral coefficient ΔKi, and derivative coefficient ΔKd, is as follows:

[0089] 1. Blurring process:

[0090] ① Define the basic universe of discourse as {-1,0,1};

[0091] ②e Hydrogen pressure deviation range [-180, 180] kPa, corresponding quantization factor Ke = 1 / 180;

[0092] ③The range of hydrogen pressure deviation variation is [-360, 360] kPa, and the corresponding quantification factor Kec = 1 / 360;

[0093] ④ The ranges of △Kp are given as [-0.2, 0.2], △Ki as [-0.5, 0.5], and △Kd as [-0.2, 0.2], and the corresponding proportionality coefficients are Kup = 0.2, Kui = 0.5, and Kud = 0.2, respectively.

[0094] ⑤ The parameters are fuzzified, and the corresponding fuzzy set is {NB,ZO,PB}, where each value has the meaning of (negative large, zero, positive large).

[0095] ⑥ The membership function of fuzzy sets NB and PB adopts Z distribution and S distribution respectively, and the membership function of fuzzy set ZO adopts triangular distribution.

[0096] ⑦ The fuzzy control rule table for △Kp, △Ki, and △Kd obtained according to actual engineering applications is as follows:

[0097]

[0098] In the fuzzy control rule table above, the fuzzy linguistic variables are defined as a 7-segment fuzzy universe of discourse {NB, NM, NS, ZO, PS, PM, PB}, with the corresponding universe of discourse being {large negative, medium negative, small negative, zero, small positive, medium positive, large positive}.

[0099] 2. Defuzzy computation:

[0100] Using the centroid method, the following fuzzy control lookup table is obtained:

[0101]

[0102] 3. Calculation of PID controller coefficients after superposition

[0103] Kp = Kp0 + Kup × △Kp

[0104] Ki = Ki0 + Kui × △Ki

[0105] Kd=Ki0+Kud×△Kd

[0106] Wherein, Kp0, Ki0, and Kd0 are ordinary PID tuning coefficients; △Kp, △Ki, and △Kd are fuzzy control 169 matrix database lookup table values; and Kup, Kui, and Kud are fuzzy coefficient tuning values.

[0107] Figure 6 This is a flowchart illustrating the operation of a PID control method for a fuel cell system according to an embodiment of this application. Figure 6As shown, the control flow begins at step 502, and then at step 504, the proportional valve opening interval [M, N] is defined to correspond to the opening percentage [a, b]; the opening percentage of the hydrogen proportional valve per unit hydrogen pressure is c, in units of % / kPa; after the fuel cell system starts, the opening percentage is given as R0, and the hydrogen pressure is P0. Next, proceeding to step 506, the target hydrogen pressure P is input, the initial hydrogen pressure deviation e(0) = P - P0, the PID controller calculates the hydrogen pressure u(1) = Kp × e(0) + KiΣe(j) + Kd[e(0)], and the PID controller issues the first opening command R1 = R0 + [u(1) - P0] × c to the hydrogen proportional valve. Next, proceed to step 508. Sample 1: actual hydrogen pressure sample value P1, hydrogen pressure deviation is e(1) = P - P1, the PID controller calculates hydrogen pressure u(2) = Kp × e(1) + KiΣe(j) + Kd[e(1) - e(0)], the PID controller issues the second opening command R2 = R1 + [u(2) - P1] × c to the hydrogen proportional valve. Next, proceed to step 510. Sample 2: actual hydrogen pressure sample value P2, hydrogen pressure deviation is e(2) = P - P2, the PID controller calculates hydrogen pressure u(3) = Kp × e(2) + KiΣe(j) + Kd[e(2) - e(1)], the PID controller issues the third opening command R3 = R2 + [u(3) - P2] × c to the hydrogen proportional valve. Next, proceed to step 512, and perform n-1 samplings again. Next, proceed to step 514, sampling n: the actual hydrogen pressure sampling value Pn, the hydrogen pressure deviation is e(n) = P - Pn, the PID controller calculates the hydrogen pressure u(n+1) = Kp × e(n) + KiΣe(j) + Kd[e(n) - e(n-1)], and the PID controller issues the (n+1)th opening command Rn+1 = Rn + [u(n+1) - Pn] × c to the hydrogen proportional valve. Next, proceed to step 516, determining whether Pn is within the interval Px < Pn < P+x, where x is the set error range. If it is determined in step 516 that Pn is within the interval Px < Pn < P+x, then proceed to step 518, the proportional valve maintains the opening setpoint Rn. Next, proceed to step 520, ending the control flow. Alternatively, if it is determined in step 516 that Pn is not within the interval Px < Pn < P+x, then proceed to step 514.

[0108] Figure 7This is a functional block diagram of a PID control method for a fuel cell system according to an embodiment of this application. The program storage module 702 stores a program for use by the PID controller in the PID control method. The data sampling module 704 samples the actual hydrogen pressure. The control parameter calculation module 706 calculates the control parameters used by the PID controller in the PID control method. The instruction issuing module 708 issues an instruction generated by the PID controller based on the control parameters calculated by the control parameter calculation module 706 and the actual hydrogen pressure sampled by the data sampling module 704 to the opening control execution module 710. The opening control execution module 710 adjusts the opening of the hydrogen proportional valve based on this instruction.

[0109] Next, the anode water and nitrogen emission control method executed by the PID control device of the fuel cell system according to the present invention will be described. The nitrogen emission and anode water control method executed by the PID control device of the fuel cell system according to the present invention is as follows:

[0110] 1. Stable operating conditions

[0111] Under stable operating condition A1, pressure control takes priority. The opening of the hydrogen proportional valve is adjusted so that the hydrogen inlet pressure P1 reaches the required value.

[0112] 2. Open the anode nitrogen venting valve.

[0113] Under steady-state condition A1, calculate the difference ΔQ = Q_actual hydrogen consumption integral and the theoretical hydrogen consumption integral. actual -Q theory Set a reasonable threshold Q. th When △Q < △Q th1 (where △Q < △Q) th1 When the hydrogen flow rate is 3% of the design value, it indicates that there is a certain accumulation of impurity gases such as nitrogen and water vapor in the anode. Keeping the current proportional valve opening unchanged, the MFC is controlled to increase the hydrogen flow rate M1. At this time, ΔQ th1 <△Q<△Q th2 (where, △Q) th2 When the hydrogen flow rate is 6% of the design value, and the hydrogen inlet pressure P1 increases by m% or the hydrogen-air pressure difference ΔP1 increases by n%, the nitrogen venting valve is opened.

[0114] 3. Anode nitrogen vent valve closed.

[0115] Under stable operating condition A1, after the nitrogen vent valve opens, the hydrogen inlet pressure P1 of the fuel cell stack will decrease by m%, or the hydrogen-air pressure difference ΔP1 will decrease by n%, or the hydrogen flow meter will display a hydrogen flow rate ΔQ > ΔQ (the design value). th2 When the nitrogen purging valve and MFC are closed, the opening of the hydrogen proportional valve is adjusted according to the pressure requirements of the A1 working condition to complete one cycle of nitrogen purging.

[0116] 4. Open the anode drain valve.

[0117] During stable operation, the drain valve opens based on the anode signal indication. When the controller receives the signal from the water vapor separator level sensor, the drain valve opens.

[0118] 5. Anode drain valve closed.

[0119] The hydrogen inlet pressure P1 of the fuel cell stack will decrease by m%, or the hydrogen-air pressure difference ΔP1 will decrease by n%, or the hydrogen flow meter will display a hydrogen flow rate ΔQ > ΔQ (design value). th2 When necessary, close the drain valve.

[0120] Specifically, the calculation principles for the integral of actual hydrogen consumption and the integral of theoretical hydrogen consumption are as follows:

[0121] 1. Integral of actual hydrogen consumption

[0122] A high-precision flow sensor is installed in the hydrogen inlet pipeline to measure the hydrogen flow rate in real time. By integrating these flow rate data over a period of time, the actual amount of hydrogen used can be obtained. For example, if the flow sensor measures the hydrogen flow rate q1, q2, q3, ..., qn (unit: g / s) once per second, the actual amount of hydrogen used within the time interval [0, t] is... (where Δt is the sampling time interval).

[0123] 2. Theoretical hydrogen quantity integral

[0124] Based on the working principle of fuel cells, there is a definite relationship between the stack current and hydrogen consumption. For proton exchange membrane fuel cells (PEMFCs), according to Faraday's law, one hydrogen molecule is consumed for every two electrons produced (corresponding to a certain current I). The theoretical hydrogen consumption is calculated by integrating the stack current. Assuming the stack current changes with time as I(t), the theoretical hydrogen consumption over the time interval [0,t] is... (where F is the Faraday constant, approximately 96485 C / mol).

[0125] The technical solution of this invention achieves the following technical effects:

[0126] 1) The technical solution of the present invention is to perform parameter tuning by ordinary PID, and then to directly perform adaptive control of the proportional valve outlet pressure (fuel cell inlet pressure) by fuzzy PID, which improves the dynamic response speed of the system and reduces the steady state time of the system.

[0127] 2) When nitrogen accumulation is detected, causing pressure changes, the control system dynamically adjusts the proportional valve according to the rate of pressure change. If the pressure increase is caused by slow nitrogen accumulation, the proportional valve can be adjusted to a lesser extent to avoid excessive reduction of the valve opening, which could lead to insufficient hydrogen supply.

[0128] 3) By comprehensively considering operating parameters, the actual needs of the system can be judged more accurately, avoiding hydrogen supply problems caused by adjusting only a single parameter. When the pressure increases but the hydrogen flow rate is close to the minimum requirement of the fuel cell, the control system can limit the proportional valve to further reduce its opening.

[0129] 4) During the operation of a fuel cell system, complex operating conditions such as load changes and temperature fluctuations can affect hydrogen consumption. By integrating and comparing hydrogen consumption over a period of time, these complex operating conditions can be adapted to a certain extent. For example, during dynamic load changes, even if the current fluctuates instantaneously, integral calculations can more accurately determine whether the overall hydrogen consumption is affected by nitrogen accumulation.

[0130] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A PID control device for a fuel cell system, the fuel cell system comprising a fuel cell stack and a hydrogen supply device for supplying hydrogen to the fuel cell stack via a hydrogen inlet pipe, characterized in that, The PID control device includes: A hydrogen pressure sensing unit collects the actual hydrogen pressure value at the outlet of the hydrogen proportional valve and generates a collected value representing the actual hydrogen pressure value. The hydrogen proportional valve is located between the hydrogen supply device and the fuel cell stack to regulate the flow rate of hydrogen supplied by the hydrogen supply device to the fuel cell stack. The PID controller performs a preset PID control algorithm on the hydrogen pressure deviation between the collected value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation to obtain the coefficients of the PID controller, and calculates the control quantity for the opening degree of the hydrogen proportional valve based on the coefficients.

2. The PID control device for a fuel cell system according to claim 1, characterized in that, The coefficients of the PID controller include a proportionality coefficient k associated with the hydrogen pressure deviation value. p The integral coefficient k associated with the accumulated amount i The differential coefficient k associated with the change d .

3. The PID control device for a fuel cell system according to claim 1, characterized in that, The PID control device performs a preset PID control algorithm for the hydrogen pressure deviation between the collected value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation. The PID control device performs a preset first PID control algorithm based on Equation 1 on the hydrogen pressure deviation between the collected value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation, to calculate the control quantity u(k) for the opening of the hydrogen proportional valve: Where e(k) is the hydrogen pressure deviation value collected in the kth sampling, where e(k) = r(k) - c(k), where r(k) is the target hydrogen pressure, c(k) is the actual hydrogen pressure measured by the hydrogen pressure sensing unit, and e(k-1) is the hydrogen pressure deviation value collected in the (k-1)th sampling. p k is the proportionality coefficient. i For the integral coefficient, k d Here, is the differential coefficient, k is the k-th sample, and j is the accumulation operator. The PID control device calculates the increment value Δu(k) of the control quantity u(k) according to Equation 2: △u(k)= k p ×[e(k)-e(k-1)]+k i ×e(k)+k d Equation 2: ×[e(k)-2×e(k-1)+e(k-2)] The PID control device outputs a control command generated based on the incremental value Δu(k) to the hydrogen proportional valve. The hydrogen proportional valve adjusts its opening degree according to the control command. The hydrogen pressure sensing unit collects the actual hydrogen pressure value at the outlet of the hydrogen proportional valve after the opening degree adjustment. The PID control device adjusts k based on the collected actual hydrogen pressure value after the opening degree adjustment. p k i k d To calculate the initial scaling factor k p0 Initial integration coefficient k i0 Initial differential coefficients k d0 .

4. The PID control device for a fuel cell system according to claim 3, characterized in that, The PID control device further includes a preset PID control algorithm for the hydrogen pressure deviation between the collected value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation: The PID control device performs a preset second PID control algorithm on the hydrogen pressure deviation between the collected value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation, to determine the fuzzification proportional coefficient Δk. p fuzzy integral coefficient Δk i fuzzy differential coefficients Δk d .

5. The PID control device for a fuel cell system according to claim 4, characterized in that, The PID control device, according to a preset fuzzy control rule table, maps the hydrogen pressure deviation between the collected value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation to elements in corresponding fuzzy sets. Based on the elements in the mapped fuzzy sets, and using a preset database lookup table, the PID control device determines the fuzzification ratio coefficient Δk. p The fuzzification integral coefficient Δk i The fuzzy differential coefficient Δk d The proportional coefficient k of the PID controller is obtained according to Equation 3. p Integral coefficient k i Differential coefficient k d , Where, k up It is the fuzzification scaling factor Δk p The scaling factor is constant, k ui It is the fuzzification integral coefficient Δk i The scaling factor is constant, k ud It is the fuzzy differential coefficient Δk d The scaling factor is a constant.

6. The PID control device for a fuel cell system according to claim 1, characterized in that, The PID control device also includes: A hydrogen flow sensing unit is installed in the hydrogen inlet pipe, and the hydrogen flow sensing unit measures the flow rate of hydrogen in real time and generates a flow rate value representing the flow rate. The current acquisition unit measures the stack current of the fuel cell stack in real time and generates a current value representing the stack current.

7. The PID control device for a fuel cell system according to claim 6, characterized in that, The PID controller calculates the actual hydrogen consumption of the fuel cell system based on the flow rate value, and calculates the theoretical hydrogen consumption of the fuel cell system based on the current value. The PID controller compares the actual hydrogen consumption with the theoretical hydrogen consumption to control the opening / closing of the anode nitrogen venting valve of the fuel cell system based on the comparison result.

8. The PID control device for a fuel cell system according to claim 1, characterized in that, The PID control device also includes: A liquid level sensing unit is installed inside the water vapor separator of the fuel cell stack, and the liquid level sensing unit measures the liquid level inside the water vapor separator in real time and generates a liquid level value representing the liquid level.

9. The PID control device for a fuel cell system according to claim 8, characterized in that, The PID controller compares the liquid level value with a preset threshold to control the opening / closing of the drain valve of the fuel cell system based on the comparison result.

10. A PID control method for a fuel cell system, the fuel cell system comprising a fuel cell stack, a hydrogen supply device supplying hydrogen to the fuel cell stack via a hydrogen inlet pipe, and a hydrogen proportional valve disposed between the hydrogen supply device and the fuel cell stack, characterized in that, The PID control method includes the following steps: The hydrogen pressure sensing step involves acquiring the actual hydrogen pressure value at the outlet of the hydrogen proportional valve and generating a acquired value representing the actual hydrogen pressure value. The PID control step involves applying a preset PID control algorithm to the hydrogen pressure deviation between the acquired value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation to obtain PID control coefficients. Based on the PID control coefficients, the control quantity for the opening degree of the hydrogen proportional valve is calculated.

11. The PID control method for a fuel cell system according to claim 10, characterized in that, The PID control coefficient includes a proportionality coefficient k associated with the hydrogen pressure deviation value. p The integral coefficient k associated with the accumulated amount i The differential coefficient k associated with the change d .

12. The PID control method for a fuel cell system according to claim 10, characterized in that, The PID control step includes a preset PID control algorithm for the hydrogen pressure deviation between the collected value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation. Based on Equation 1, a preset first PID control algorithm is applied to the hydrogen pressure deviation between the collected value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation, to calculate the control quantity u(k) for the opening degree of the hydrogen proportional valve: Where e(k) is the hydrogen pressure deviation value collected in the kth sampling, where e(k) = r(k) - c(k), where r(k) is the target hydrogen pressure, c(k) is the actual hydrogen pressure measured by the hydrogen pressure sensing unit, and e(k-1) is the hydrogen pressure deviation value collected in the (k-1)th sampling. p k is the proportionality coefficient. i For the integral coefficient, k d Here, is the differential coefficient, k is the k-th sample, and j is the accumulation operator. Calculate the increment value Δu(k) of the control quantity u(k) according to Equation 2: △u(k)= k p ×[e(k)-e(k-1)]+k i ×e(k)+k d Equation 2: ×[e(k)-2×e(k-1)+e(k-2)] The PID control step outputs a control command generated based on the incremental value Δu(k) to the hydrogen proportional valve. The hydrogen proportional valve adjusts its opening degree according to the control command, and the actual hydrogen pressure value at the outlet of the hydrogen proportional valve after the opening degree adjustment is collected. k is then adjusted based on the collected actual hydrogen pressure value after the opening degree adjustment. p k i k d To calculate the initial scaling factor k p0 Initial integration coefficient k i0 Initial differential coefficients k d0 .

13. The PID control method for a fuel cell system according to claim 12, characterized in that, The PID control step further includes pre-setting the hydrogen pressure deviation between the acquired value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation. A pre-set second PID control algorithm is applied to the hydrogen pressure deviation between the collected value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation, in order to determine the fuzzification proportional coefficient Δk. p fuzzy integral coefficient Δk i fuzzy differential coefficients Δk d .

14. The PID control method for a fuel cell system according to claim 13, characterized in that, In the PID control step, according to a preset fuzzy control rule table, the hydrogen pressure deviation between the collected value and the target hydrogen pressure of the fuel cell system, the change in the hydrogen pressure deviation, and the cumulative amount of the hydrogen pressure deviation are mapped to elements in the corresponding fuzzy sets. Based on the elements in the mapped fuzzy sets and a preset database lookup table, the fuzzification scaling factor Δk is determined. p The fuzzification integral coefficient Δk i The fuzzy differential coefficient Δk d The proportionality constant k is obtained according to Equation 3. p Integral coefficient k i Differential coefficient k d , Where, k up It is the fuzzification scaling factor Δk p The scaling factor is constant, k ui It is the fuzzification integral coefficient Δk i The scaling factor is constant, k ud It is the fuzzy differential coefficient Δk d The scaling factor is a constant.

15. The PID control method for a fuel cell system according to claim 10, characterized in that, The PID control method further includes the following steps: The hydrogen flow sensing step measures the flow rate of hydrogen flowing through the hydrogen inlet pipe in real time and generates a flow rate value representing the flow rate. The current acquisition step involves measuring the stack current of the fuel cell stack in real time and generating a current value representing the stack current.

16. The PID control method for a fuel cell system according to claim 15, characterized in that, In the PID control step, the actual hydrogen consumption of the fuel cell system is calculated based on the flow rate value, and the theoretical hydrogen consumption of the fuel cell system is calculated based on the current value. The actual hydrogen consumption is compared with the theoretical hydrogen consumption, and the opening / closing of the anode nitrogen venting valve of the fuel cell system is controlled according to the comparison result.

17. The PID control method for a fuel cell system according to claim 10, characterized in that, The PID control method further includes the following steps: The liquid level sensing step measures the liquid level in the water vapor separator of the fuel cell stack in real time and generates a liquid level value representing the liquid level.

18. The PID control method for a fuel cell system according to claim 17, characterized in that, In the PID control step, the liquid level value is compared with a preset threshold, and the opening / closing of the drain valve of the fuel cell system is controlled according to the comparison result.

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