CN117639483A - New energy hydrogen production converter optimal control method - Google Patents
New energy hydrogen production converter optimal control method Download PDFInfo
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- CN117639483A CN117639483A CN202311522585.9A CN202311522585A CN117639483A CN 117639483 A CN117639483 A CN 117639483A CN 202311522585 A CN202311522585 A CN 202311522585A CN 117639483 A CN117639483 A CN 117639483A
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- 229910052739 hydrogen Inorganic materials 0.000 title claims abstract description 45
- 239000001257 hydrogen Substances 0.000 title claims abstract description 45
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 title claims abstract description 44
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 37
- 238000000034 method Methods 0.000 title claims abstract description 21
- 238000013178 mathematical model Methods 0.000 claims abstract description 23
- 238000005070 sampling Methods 0.000 claims abstract description 15
- 241001673102 Jaya Species 0.000 claims description 13
- 238000013461 design Methods 0.000 claims description 4
- 230000000087 stabilizing effect Effects 0.000 claims description 4
- 238000012935 Averaging Methods 0.000 claims description 3
- 230000004044 response Effects 0.000 abstract description 5
- 238000005457 optimization Methods 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 4
- 238000005868 electrolysis reaction Methods 0.000 description 4
- 230000008859 change Effects 0.000 description 3
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 239000002803 fossil fuel Substances 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 229910002092 carbon dioxide Inorganic materials 0.000 description 1
- 239000001569 carbon dioxide Substances 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 239000007789 gas Substances 0.000 description 1
- 150000002431 hydrogen Chemical class 0.000 description 1
- 238000002955 isolation Methods 0.000 description 1
- 238000012804 iterative process Methods 0.000 description 1
- 239000003345 natural gas Substances 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000002407 reforming Methods 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
Abstract
The invention discloses a new energy hydrogen production converter optimization control method, which belongs to the field of hydrogen production converter control and comprises the following steps: s1, detecting a sampling signal of a hydrogen production Cuk converter; s2, converting the sampling signal into a digital signal through an ADC module; s3, establishing a mathematical model of the Cuk converter according to the digital signal; s4, performing disturbance estimation according to the mathematical model; s5, designing a fractional order sliding mode surface according to disturbance and obtaining a control law; s6, obtaining control law parameters by using an improved JAVA algorithm; s7, obtaining a duty ratio according to a control law to control on and off of the switch. The invention can realize the accurate control of the hydrogen production converter on the basis of ensuring the low ripple of the hydrogen production converter, and realize the quick response and the high-efficiency stable operation of the hydrogen production converter.
Description
Technical Field
The invention relates to the field of hydrogen production converter control, in particular to a new energy hydrogen production converter optimal control method.
Background
The hydrogen energy is used as a novel renewable energy source, and has the advantages of rich reserves, high energy density, cleanness, high efficiency and the like. Currently, most of the global hydrogen production comes from fossil fuels, in particular, ash hydrogen produced by reforming natural gas, and occupies a large market share, and electrolysis of water to produce hydrogen (green hydrogen) is considered as a promising alternative in order to reduce fossil fuel consumption and the emission of chamber gases such as carbon dioxide. The hydrogen production power supply is a core device in the water electrolysis hydrogen production, and different hydrogen production power supplies have different influences on the purity and efficiency of hydrogen produced by electrolysis and the service life of the electrolytic tank. Therefore, research and development of efficient hydrogen production power sources has important significance for the development of hydrogen energy.
The hydrogen production power supply is divided into two types according to different sources of electric energy, the electric energy is supplied by a photovoltaic power supply and the like, the electric energy is supplied by electrolysis through a DC/DC converter, and the electric energy is supplied by an electric network or an alternating current supplied by a wind driven generator and the like, and the alternating current is converted into the direct current through an AC/DC converter to supply power for an electrolytic tank. Wherein the DC/DC converter can be divided into non-isolated and isolated by structure. At present, the non-isolated DC/DC converter mostly uses a Buck circuit as a basic structure, but most of the non-isolated converters have the problems of large current ripple and the like due to the structural characteristics of the Buck circuit, and the non-isolated DC/DC converter is only suitable for hydrogen production occasions with small voltage ratio change and no need of electric isolation. And the Cuk converter reduces current ripple due to inductance on both input and output sides.
Disclosure of Invention
The invention aims to solve the technical problem of providing the new energy hydrogen production converter optimal control method, which can realize the accurate control of the hydrogen production converter on the basis of ensuring the low ripple of the hydrogen production converter and realize the quick response, high efficiency and stable operation of the hydrogen production converter.
In order to solve the technical problems, the invention adopts the following technical scheme:
the new energy hydrogen production converter optimizing control method includes the following steps:
s1, respectively acquiring output voltage and inductance current signals of a Cuk converter through a voltage sampling module and a current sampling module, and inputting the sampling signals into an ADC module;
s2, converting the acquired output voltage and inductance current signals into digital signals through an ADC module, and inputting the digital signals into a fractional order sliding mode control module;
s3, a fractional order sliding mode control module establishes a mathematical model of the Cuk converter system according to digital signals of the output voltage and the inductance current;
s4, performing disturbance estimation according to a mathematical model of the Cuk converter system;
s5, establishing a fractional order sliding mode surface according to disturbance estimation, and designing a control law of the Cuk converter system based on the fractional order sliding mode surface;
s6, obtaining a control rate parameter by using an improved JAYA algorithm;
and S7, obtaining a corresponding duty ratio according to the control law parameter, and outputting a driving signal to control the on and off of a switching tube of the Cuk converter.
The technical scheme of the invention is further improved as follows: in S3, a mathematical model of the Cuk converter system is established according to the digital signals of the output voltage and the inductance current, and specifically comprises the following steps:
the Cuk converter is divided into two working modes, one mode is switch on, and the duration of the mode is recorded as 0<t<D*T s The second mode is switch off, and the duration of the second mode is recorded as D s <t<T s Wherein D is duty cycle, T s Is a switching period;
the mathematical model of the Cuk converter can be obtained according to the state averaging method:
assume thatThe mathematical model of the Cuk transformer becomes:
wherein L is the inductance of the output side of the Cuk converter, U o The output voltage of the Cuk converter is C is the output side capacitance of the Cuk converter, R is the load resistance of the Cuk converter, U in Inputting voltage for the Cuk converter;
the disturbance estimation is performed according to a mathematical model of the converter system, specifically as follows:
let the output voltage error be e 1 Its derivative is e 2 Obtaining a disturbance error equation:
wherein U is ref L (e, t) is a disturbance generated when the input voltage or the load resistance changes, for a set reference voltage.
The technical scheme of the invention is further improved as follows: in S4, disturbance estimation is carried out according to a mathematical model of the converter system, specifically as follows:
let the output voltage error be e 1 Its derivative is e 2 Obtaining a disturbance error equation:
wherein U is ref L (e, t) is a disturbance generated when the input voltage or the load resistance changes, for a set reference voltage.
The technical scheme of the invention is further improved as follows: the fractional order sliding mode surface and the control law established in S5 are specifically as follows:
design fractional order slip form surfaceWherein->Is t 0 For the starting time, t is the alpha-order Riemann-Liouville of the integral variable and is determined by the fractional derivative, lambda, rho are the control coefficients, sgn (e 2 ) To be about e 2 Is a sign function of (2);
based on the designed fractional order slip plane, the control rate u is designed as:
wherein K is 1 And K 2 Delta is the disturbance bias, which is a parameter of the arrival law.
The technical scheme of the invention is further improved as follows: in S6, the modified JAYA algorithm is specifically as follows:
a1, initializing population parameters T and arrival law parameters K 2 ；
A2, calculating the target value J o ：
A3, obtaining the arrival law parameter K 2 Is marked as the optimal solution of (2)K representing the t th generation 2 The value of the optimal solution in the j-th dimension;
wherein,is the value of the newly generated solution in the j-th dimension, ra (0, 1) represents a random number from 0 to 1, ra (X) l ，X u ) Maximum and minimum values representing target values;
a4, if the generated new parameter is brought into the controller, the obtained target value is more excellent than the target value corresponding to the original parameter, replacing the original parameter with the new parameter, otherwise, not replacing, and then carrying out JAYA iteration on the next parameter; after all parameters are traversed, performing the next iteration;
a5, judging whether the following termination conditions are met:
target value J o Less than or equal to 1 per mill, the stabilizing time is less than or equal to 1S, and if the stabilizing time is not met, returning to S3;
and A6, outputting an optimal solution.
By adopting the technical scheme, the invention has the following technical progress:
1. the invention designs an optimal control method of a new energy hydrogen production converter, which improves the output voltage tracking control performance of a Cuk buck converter. Flexibility is improved through FO calculation, and robustness of disturbance and parameter change provided by a traditional sliding mode controller and limited time convergence characteristic of output voltage error to a balance point during output load change are improved;
2. the invention adopts an improved JAYA algorithm to carry out parameter estimation of the control law, the algorithm is enhanced through advanced learning, incremental population strategy and Powell method, powerful JAYA variants are generated, the parameters obtained by the algorithm are more accurate, the iterative process is faster, and the rapid calculation of the control law can be realized, thereby realizing rapid dynamic response of the converter.
Drawings
FIG. 1 is a schematic circuit diagram of a hydrogen producing Cuk converter of the present invention;
FIG. 2 is a schematic diagram of a fractional order sliding mode controller method for a Cuk converter for producing hydrogen based on an improved JAYA algorithm in accordance with the present invention;
FIG. 3 is a schematic diagram of the process of improving the JAYA algorithm.
Detailed Description
The invention is described in further detail below with reference to the attached drawings and examples:
the invention aims to solve the technical problem of providing the new energy hydrogen production converter optimal control method, which can realize the accurate control of the hydrogen production converter on the basis of ensuring the low ripple of the hydrogen production converter and realize the quick response, high efficiency and stable operation of the hydrogen production converter.
As shown in fig. 1, the hydrogen production Cuk converter is configured with a voltage sampling module, a current sampling module, an ADC module and a fractional slip mode control module, wherein the voltage sampling module collects output voltage signals of the DC-DC converter, the current sampling module collects inductance current signals of the DC-DC converter, the ADC module converts the collected output voltage and inductance current signals into digital signals, and the fractional slip mode control module is used for controlling on-off states of a switching tube of the DC-DC converter;
as shown in fig. 2, the new energy hydrogen production converter optimizing control method comprises the following steps:
s1, respectively acquiring output voltage and inductance current signals of a Cuk converter through a voltage sampling module and a current sampling module, and inputting the sampling signals into an ADC module;
s2, converting the acquired output voltage and inductance current signals into digital signals through an ADC module, and inputting the digital signals into a fractional order sliding mode control module;
s3, a fractional order sliding mode control module establishes a mathematical model of the Cuk converter system according to digital signals of the output voltage and the inductance current;
the mathematical model for establishing the Cuk converter system according to the digital signals of the output voltage and the inductance current is specifically as follows:
from the circuit diagram of the Cuk converter, it can be seen that the Cuk converter is divided into two operation modes, one mode being switch-on, the duration of which can be noted as 0<t<D*T s The second mode is switch off, and the duration of the second mode can be expressed as D s <t<T s Wherein D is duty cycle, T s Is a switching period;
the mathematical model of the Cuk converter can be obtained according to the state averaging method:
assume thatThe mathematical model of the Cuk transformer becomes:
wherein L is the inductance of the output side of the Cuk converter, U o The output voltage of the Cuk converter is C is the output side capacitance of the Cuk converter, R is the load resistance of the Cuk converter, U in Inputting voltage for the Cuk converter;
the disturbance estimation is performed according to a mathematical model of the converter system, specifically as follows:
let the output voltage error be e 1 Its derivative ise 2 Then a disturbance error equation can be derived:
wherein U is ref L (e, t) is a disturbance generated when the input voltage or the load resistance changes, for a set reference voltage.
S4, performing disturbance estimation according to a mathematical model of the Cuk converter system;
in S4, disturbance estimation is carried out according to a mathematical model of the converter system, specifically as follows:
let the output voltage error be e 1 Its derivative is e 2 Obtaining a disturbance error equation:
wherein U is ref L (e, t) is a disturbance generated when the input voltage or the load resistance changes, for a set reference voltage.
S5, establishing a fractional order sliding mode surface according to disturbance estimation, and designing a control law of the Cuk converter system based on the fractional order sliding mode surface;
the fractional order sliding mode surface and the control law established in the step S5 are specifically as follows:
design fractional order slip form surfaceWherein->Is t 0 For the starting time, t is the alpha-order Riemann-Liouville of the integral variable and is determined by the fractional derivative, lambda, rho are the control coefficients, sgn (e 2 ) To be about e 2 Is a sign function of (2);
based on the designed fractional order slip plane, the control rate u is designed as:
wherein K is 1 And K 2 Delta is the disturbance bias, which is a parameter of the arrival law.
S6, obtaining a control rate parameter by using an improved JAYA algorithm;
as shown in fig. 3, the modified JAYA algorithm is specifically as follows:
a1, initializing population parameters T and arrival law parameters K 2 ；
A2, calculating the target value J o ；
A3, obtaining the arrival law parameter K 2 Is marked as the optimal solution of (2)K representing the t th generation 2 The value of the optimal solution in the j-th dimension;
wherein,is the value of the newly generated solution in the j-th dimension, ra (0, 1) represents a random number from 0 to 1, ra (X) l ，X u ) Maximum and minimum values representing target values;
a4, if the generated new parameter is brought into the controller, the obtained target value is more excellent than the target value corresponding to the original parameter, replacing the original parameter with the new parameter, otherwise, not replacing, and then carrying out JAYA iteration on the next parameter; after all parameters are traversed, performing the next iteration;
a5, judging whether the following termination conditions are met:
target value J o Less than or equal to 1%At 1S, if not, returning to S3;
and A6, outputting an optimal solution.
And S7, obtaining a corresponding duty ratio according to the control law parameter, and outputting a driving signal to control the on and off of a switching tube of the Cuk converter.
In conclusion, the invention can realize the accurate control of the hydrogen production converter on the basis of ensuring the low ripple of the hydrogen production converter, and realize the quick response, high efficiency and stable operation of the hydrogen production converter.
Claims (5)
1. The new energy hydrogen production converter optimizing control method is characterized in that: the method comprises the following steps:
s1, respectively acquiring output voltage and inductance current signals of a Cuk converter through a voltage sampling module and a current sampling module, and inputting the sampling signals into an ADC module;
s2, converting the acquired output voltage and inductance current signals into digital signals through an ADC module, and inputting the digital signals into a fractional order sliding mode control module;
s3, a fractional order sliding mode control module establishes a mathematical model of the Cuk converter system according to digital signals of the output voltage and the inductance current;
s4, performing disturbance estimation according to a mathematical model of the Cuk converter system;
s5, establishing a fractional order sliding mode surface according to disturbance estimation, and designing a control law of the Cuk converter system based on the fractional order sliding mode surface;
s6, obtaining a control rate parameter by using an improved JAYA algorithm;
and S7, obtaining a corresponding duty ratio according to the control law parameter, and outputting a driving signal to control the on and off of a switching tube of the Cuk converter.
2. The new energy hydrogen production converter optimizing control method according to claim 1, characterized in that: in S3, a mathematical model of the Cuk converter system is established according to the digital signals of the output voltage and the inductance current, and specifically comprises the following steps:
the Cuk converter is divided into two working modes, one mode is switch conduction, the other mode is switch conductionThe duration of the mode is recorded as 0<t<D*T s The second mode is switch off, and the duration of the second mode is recorded as D s <t<T s Wherein D is duty cycle, T s Is a switching period;
the mathematical model of the Cuk converter can be obtained according to the state averaging method:
assume thatThe mathematical model of the Cuk transformer becomes:
wherein L is the inductance of the output side of the Cuk converter, U o The output voltage of the Cuk converter is C is the output side capacitance of the Cuk converter, R is the load resistance of the Cuk converter, U in Inputting voltage for the Cuk converter;
the disturbance estimation is performed according to a mathematical model of the converter system, specifically as follows:
let the output voltage error be e 1 Its derivative is e 2 Obtaining a disturbance error equation:
wherein U is ref L (e, t) is a disturbance generated when the input voltage or the load resistance changes, for a set reference voltage.
3. The new energy hydrogen production converter optimizing control method according to claim 1, characterized in that: in S4, disturbance estimation is carried out according to a mathematical model of the converter system, specifically as follows:
let the output voltage error be e 1 Its derivative is e 2 Obtaining a disturbance error equation:
wherein U is ref L (e, t) is a disturbance generated when the input voltage or the load resistance changes, for a set reference voltage.
4. The new energy hydrogen production converter optimizing control method according to claim 1, characterized in that: the fractional order sliding mode surface and the control law established in S5 are specifically as follows:
design fractional order slip form surfaceWherein->Is t 0 For the starting time, t is the alpha-order Riemann-Liouville of the integral variable and is determined by the fractional derivative, lambda, rho are the control coefficients, sgn (e 2 ) To be about e 2 Is a sign function of (2);
based on the designed fractional order slip plane, the control rate u is designed as:
wherein K is 1 And K 2 For the law of arrivalThe parameter, δ, is the disturbance bias.
5. The new energy hydrogen production converter optimizing control method according to claim 1, characterized in that: in S6, the modified JAYA algorithm is specifically as follows:
a1, initializing population parameters T and arrival law parameters K 2 ；
A2, calculating the target value J o ：
A3, obtaining the arrival law parameter K 2 Is marked as the optimal solution of (2)K representing the t th generation 2 The value of the optimal solution in the j-th dimension;
wherein,is the value of the newly generated solution in the j-th dimension, ra (0, 1) represents a random number from 0 to 1, ra (X) l ，X u ) Maximum and minimum values representing target values;
a4, if the generated new parameter is brought into the controller, the obtained target value is more excellent than the target value corresponding to the original parameter, replacing the original parameter with the new parameter, otherwise, not replacing, and then carrying out JAYA iteration on the next parameter; after all parameters are traversed, performing the next iteration;
a5, judging whether the following termination conditions are met:
target value J o Less than or equal to 1 per mill, the stabilizing time is less than or equal to 1S, and if the stabilizing time is not met, returning to S3;
and A6, outputting an optimal solution.
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