# PID control method of fuel cell system

## A technology of a fuel cell system and control method, which is applied in the direction of fuel cells, circuits, electrical components, etc., and can solve the problems of slow response speed and large error of PID controllers

Active Publication Date: 2020-05-08

深圳国氢新能源科技有限公司

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## AI-Extracted Technical Summary

### Problems solved by technology

[0004] The main purpose of the present invention is to provide a PID control method for a fuel cell system...

### Method used

As in PID control algorithm design, adopt integral separation control algorithm in the large deviation range, carry out PD control, improve system response speed and reduce overshoot; Adopt variable speed integral control algorithm in the small deviation range, improve control precision, At the same time, the anti-integral saturation algorithm is used to prevent the maximum value of the controlled air flow, hydrogen flow and coolant temperature from being super high during integral accumulation.

In the present embodiment, by obtaining the deviation value between the theoretical input parameter value of fuel cell and the actual input parameter value, thus help to utilize the deviation value that obtains to calculate this time to the control quantity of fuel cell, to compensate this time The difference between the theoretical input parameter value and the actual input parameter value, so as to realize the control of the parameter value of the fuel cell to be input this time by collecting the last input parameter value of the fuel cell, thereby improving the operation control of the fuel cell system Accuracy and improved response speed of the control fuel cell system.

PID control method in the present invention adopts integr...

## Abstract

The invention discloses a PID control method of a fuel cell system. The PID control method comprises: constructing a theoretical database of a fuel cell, the theoretical database comprising power parameters and cooling liquid temperature parameters, hydrogen flow parameters and air flow parameters corresponding to the power parameters; obtaining a theoretical parameter value of the fuel cell and an actual parameter value corresponding to the theoretical parameter value, and calculating a deviation value between the actual parameter value and the theoretical parameter value, the theoretical parameter value being any one of a cooling liquid temperature value, a hydrogen flow value and an air flow value; inputting the deviation value into a preset PID control algorithm to calculate the control quantity of the fuel cell; and controlling a corresponding execution mechanism to adjust the temperature, the hydrogen flow or the air flow of the cooling liquid input into the fuel cell according to the control quantity, wherein the execution mechanism is a cooling system, a hydrogen supply system or a gas supply system. The invention is beneficial to improving the control precision of controlling the operation of the fuel cell system and improving the response speed of controlling the fuel cell system.

Application Domain

Fuel cells

Technology Topic

Process engineeringHydrogen supply +10

## Image

## Examples

- Experimental program(1)

### Example Embodiment

[0033] The embodiments of the present invention are described in detail below. Examples of the embodiments are shown in the accompanying drawings, in which the same or similar reference numerals indicate the same or similar elements or elements with the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present invention, but should not be understood as a limitation of the present invention. Based on the embodiments of the present invention, those of ordinary skill in the art have not made creative work All other embodiments obtained under the premise belong to the protection scope of the present invention.

[0034] The present invention provides a PID control method for a fuel cell system, wherein the fuel cell system includes a fuel cell stack, a hydrogen supply system for supplying hydrogen to the fuel cell stack, a gas supply system for supplying air to the fuel cell stack, and Cooling system for cooling the fuel cell stack, such as figure 1 As shown, the PID control method includes:

[0035] S10, constructing a theoretical database of the fuel cell, the theoretical database including power parameters and coolant temperature parameters, hydrogen flow parameters and air flow parameters corresponding to the power parameters.

[0036] In this step, the method of constructing the theoretical database is preferably to use MATLAB & Simulink to generate a data model and optimize the data model through experimental data to construct the database, such as calculating the theoretical coolant temperature value, hydrogen flow value and hydrogen flow value required at the current power according to the output power of the fuel cell Air flow value, so that the fuel cell has corresponding theoretical control parameters under each working condition (different output power).

[0037] S20: Obtain the theoretical parameter value of the fuel cell and the actual parameter value corresponding to the theoretical parameter value, and calculate the deviation value between the actual parameter value and the theoretical parameter value. The theoretical parameter value is among the coolant temperature value, hydrogen flow value and air flow value. Any kind of.

[0038] In this step, the method of obtaining theoretical input parameter values can be directly extracted from the control device. For example, in a fuel cell control system, when the control system sends a control signal to each execution component, the theoretical input parameter corresponding to the control signal is uploaded. . The method of obtaining the actual input parameter value preferably adopts sensors for detection, such as a temperature sensor for detecting temperature and a gas flow sensor for detecting gas flow. At this time, the sensor that detects the actual parameter can be set separately, or it can be a data feedback device on the actuator (ie, the output flow of the cooling fan or the water pump, the hydrogen supply proportional valve and the air compressor). At the same time, the obtained actual input parameter value and the theoretical input parameter value are subtracted to calculate the deviation value between the two, thereby determining the deviation range between the actual input parameter value and the theoretical input parameter value.

[0039] S30: Input the deviation value into a preset PID control algorithm to calculate the control amount of the fuel cell.

[0040] In this step, the method of PID control algorithm calculation is to adjust the value of the theoretical input parameter according to the magnitude of the deviation value, so that the actual input parameter value this time corresponds to or reduces the value of the original theoretical input parameter value. The deviation value between the two, thus the deviation value is input into the PID control algorithm and the control quantity of the fuel cell is obtained. For example, the PID control algorithm adopts incremental or discrete, and the control algorithm is embedded in the PID control 器中.

[0041] S40: Control the corresponding actuator according to the control amount to adjust the coolant temperature, hydrogen flow or air flow input to the fuel cell. The actuator is a cooling system, a hydrogen supply system or an air supply system.

[0042] In this step, the control quantity can be the speed value of the cooling fan, hydrogen flow and air flow corresponding to the theoretical input parameter value. That is, when the theoretical input parameter value is the coolant temperature value, the control quantity is the speed value of the cooling fan. The actuator is the heat dissipation system (that is, the cooling fan); when the theoretical input parameter value is the hydrogen flow value, the control quantity is the hydrogen flow value, and the actuator is the hydrogen supply system (that is, the hydrogen supply proportional valve). When the parameter value is the air flow value, the control quantity is the air flow value, and the actuator is the air supply system (ie, air compressor).

[0043] In this embodiment, by obtaining the deviation value between the theoretical input parameter value of the fuel cell and the actual input parameter value, it is advantageous to use the obtained deviation value to calculate the current control value of the fuel cell to compensate the theoretical input parameter value. The difference between the value and the actual parameter value to be input, so as to realize the use of the last input parameter value of the collected fuel cell to control the parameter value to be input this time by the fuel cell, thereby improving the operation control accuracy of the fuel cell system and improving Control the response speed of the fuel cell system.

[0044] In a preferred embodiment, the preferred expression adopted by the PID control algorithm is:

[0045]

[0046] Among them, u(k) is the control quantity, e(k) is the difference of the kth sample, e(k-1) is the difference of the k-1th sample, f[e(k)] is the variable speed integral Coefficient; k p , K i , K d They are the proportional coefficient, the integral coefficient, and the differential coefficient; T is the sampling period, m is the integral separation term coefficient, n is the accumulation coefficient of the anti-integration saturation term, and j is the calculation accumulation operator.

[0047] At this time, the PID control algorithm divides the deviation value of the fuel cell system into a large deviation range and a small deviation range. Among them, in the large deviation range, the system needs to quickly respond to the small deviation range; in the small deviation range, the control accuracy is ensured and stabilized in the small deviation range. In order to improve the control accuracy, the integral accumulated acceleration is adjusted according to a certain rule within a small deviation range, so that the control system takes into account both dynamic performance and steady-state performance.

[0048] For example, in the PID control algorithm design, the integral separation control algorithm is used in the large deviation range to perform PD control, which improves the system response speed and reduces the overshoot; in the small deviation range, the variable speed integral control algorithm is used to improve the control accuracy, and the anti- The integral saturation algorithm prevents the maximum value of the controlled air flow, hydrogen flow and coolant temperature from being exceeded when the integral is accumulated.

[0049] Specifically, if the absolute value of the deviation value is less than or equal to the maximum deviation allowable value, then m=1; if the absolute value of the deviation value is greater than the maximum deviation allowable value, m=0,

[0050] Among them, the maximum allowable deviation is the integral separation threshold.

[0051] If the absolute value of u(k-1) is less than or equal to the maximum control amount of the control algorithm, then n=1; if the absolute value of u(k-1) is greater than the maximum control amount of the control algorithm, then n=0,

[0052] Among them, the maximum control quantity is one of the upper limit of the maximum temperature of the coolant, the upper limit of the maximum flow of hydrogen, and the upper limit of the maximum flow of air corresponding to the actual input parameter value.

[0053] The expression of f[e(k)] is:

[0054]

[0055] Among them, A and B are variable speed integral interval parameters.

[0056] If the absolute value of u(k) is less than or equal to A, then f[e(k)]=1; if the absolute value of u(k) is greater than A and less than or equal to A+B, then If the absolute value of u(k) is greater than A+B, then f[e(k)]=0.

[0057] At this time, it should be pointed out that only when the maximum allowable deviation is greater than or equal to A+B, can the PID controller be guaranteed to work normally.

[0058] Among them, such as figure 2 As shown, the PID controller has four control modes, namely:

[0059] Traditional PID control, its expression is

[0060] The variable-speed integral PID control of the accumulation of the new deviation is expressed as

[0061] The new deviation does not accumulate PID control, its expression is

[0062] PD control, the expression is u(k)=k p *e(k)+k d *[e(k)-e(k-1)]

[0063] The PID control method of the present invention adopts the integral separation control algorithm in the large deviation range to perform PD control, which improves the system response speed and reduces the overshoot; in the small deviation range, the variable speed integral control algorithm is used to improve the control accuracy, and at the same time, the anti The integral saturation algorithm prevents the maximum value of the controlled air flow, hydrogen flow and coolant temperature from being exceeded when the integral is accumulated. At the same time, the algorithm can enable the fuel cell system to achieve feedback regulation, automatic control, fast response, reduce overshoot and steady-state error, and improve control accuracy.

[0064] In a preferred embodiment, such as image 3 As shown, the cooling system includes a cooling fan, and if the control amount is greater than the upper limit of the first preset threshold, the rotation speed PWM value of the cooling fan is S(k)=S+S·c1(k)/r1(k); If the control quantity is less than the lower limit of the first preset threshold, the rotation speed PWM value of the cooling fan is S(k)=SS·c1(k)/r1(k); if the control quantity is greater than the lower limit of the first preset threshold If the limit value is less than the upper limit value of the first preset threshold value, the rotation speed PWM value of the cooling fan is S(k)=S;

[0065] Among them, r1(k) is the theoretical input temperature value of the coolant of the fuel cell under a specific operating condition, c1(k) is the actual input temperature value of the coolant of the fuel cell, and S is the reference PWM value of the cooling fan. At the same time, the upper limit of the first preset threshold is the desired threshold of positive coolant temperature, and the lower limit of the first preset threshold is the desired threshold of negative coolant temperature.

[0066] In this embodiment, the use of this control method can reduce the number of times the rotation speed of the cooling fan changes, thereby reducing the temperature change range of the coolant.

[0067] In a preferred embodiment, such as Figure 4 As shown, the hydrogen supply system includes a hydrogen supply proportional valve. If the control amount is greater than the upper limit of the second preset threshold, the hydrogen supply proportional valve opening PWM value is Q(k)=QQ·c2(k)/r2(k) ; If the control quantity is less than the lower limit of the second preset threshold, the hydrogen supply proportional valve opening PWM value is Q(k)=Q+Q·c2(k)/r2(k); if the control quantity is greater than the second preset If the lower limit of the threshold is less than the upper limit of the second preset threshold, the hydrogen supply proportional valve opening PWM value is Q(k)=Q;

[0068] Among them, r2(k) is the theoretical hydrogen input flow value of the fuel cell under specific operating conditions, c2(k) is the actual hydrogen input flow value of the fuel cell, and Q is the reference PWM value of the hydrogen supply proportional valve opening. At the same time, the upper limit of the second preset threshold is the desired threshold of positive hydrogen flow, and the lower limit of the second preset threshold is the desired threshold of negative hydrogen flow.

[0069] In this embodiment, the use of this control method can reduce the wear of the valve core of the hydrogen supply proportional valve and reduce the high frequency fluctuation of the hydrogen flow.

[0070] In a preferred embodiment, such as Figure 5 As shown, the air supply system includes an air compressor. If the control quantity is greater than the upper limit of the third preset threshold, the air compressor speed value is P(k)=PP·c3(k)/r3(k); if the control quantity is Less than the lower limit of the third preset threshold, the air compressor speed value is P(k)=P+P·c3(k)/r3(k); if the control quantity is greater than the lower limit of the third preset threshold, and Less than the upper limit of the third preset threshold, the speed value of the air compressor is P(k)=P;

[0071] Among them, r3(k) is the theoretical air compressor speed input value of the fuel cell under specific conditions, c3(k) is the actual air compressor speed input value of the fuel cell, and Q is the reference speed value of the air compressor. At the same time, the upper limit of the third preset threshold is the desired threshold of positive air flow, and the lower limit of the third preset threshold is the desired threshold of negative air flow.

[0072] In this embodiment, using this control method to set the limiting algorithm can reduce the number of air compressor speed adjustments, increase the operating life of the air compressor, and reduce the howling noise caused by the change of the air compressor motor speed.

[0073] In a preferred embodiment, the expression of the PID control algorithm can also be:

[0074]

[0075] Wherein, the meaning of each symbol can refer to the above-mentioned embodiment, and no detailed description is provided here.

[0076] At this time, the anti-saturation integral algorithm is used. For example, when the PID controller calculates u(k) (that is, the control amount of this fuel cell), it first judges u(k-1) (that is, the control amount of the previous fuel cell system) Whether it exceeds the limit range, where u(k-1)> u max , The PID control algorithm only accumulates negative deviations, if u(k-1) min , The PID control algorithm only accumulates the positive deviation, u max And u min To limit the amplitude, the specific value can be determined according to the type of fuel cell to limit the maximum and minimum values of the control variable of the fuel cell system.

[0077] In a preferred embodiment, the PID controller in the previous embodiment is divided into three adjustment intervals during adjustment, namely, a dead zone, a fine adjustment zone and a fast adjustment zone. In view of the characteristics of the above three intervals, the variable speed integral algorithm is introduced in the fast adjustment zone to increase the area range of the fast adjustment zone to reduce the impact of environmental changes and dynamic load changes on the fuel cell. The expression of the variable speed integral is as follows:

[0078]

[0079] Where t i It is the cycle of the variable speed integral PID algorithm, f[e(k)] is the setting coefficient and the function of the adjustment amount of the fast adjustment zone. The two are divided into linear zone and non-linear zone according to the step relationship. The division rules According to the current output power of the fuel cell system and the relevant external environment settings, as well as calculated by the data model and can be optimized according to the experimental data.

[0080] The above are only part of or preferred embodiments of the present invention. Neither the text nor the drawings should limit the scope of protection of the present invention. Anything that is based on the content of the description and drawings of the present invention under the overall concept of the present invention The equivalent structure transformation, or direct/indirect application in other related technical fields are all included in the protection scope of the present invention.

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