CN113147513B - Fuel cell automobile power distribution method and system based on nonlinear programming algorithm - Google Patents
Fuel cell automobile power distribution method and system based on nonlinear programming algorithm Download PDFInfo
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- 239000000446 fuel Substances 0.000 title claims abstract description 130
- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000005457 optimization Methods 0.000 claims abstract description 12
- 239000011159 matrix material Substances 0.000 claims abstract description 4
- 229910001416 lithium ion Inorganic materials 0.000 claims description 51
- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 claims description 50
- 230000010287 polarization Effects 0.000 claims description 7
- 239000001257 hydrogen Substances 0.000 claims description 4
- 229910052739 hydrogen Inorganic materials 0.000 claims description 4
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 claims description 3
- 230000006870 function Effects 0.000 description 6
- 230000003044 adaptive effect Effects 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000011217 control strategy Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 1
- 230000008094 contradictory effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000002737 fuel gas Substances 0.000 description 1
- 150000002431 hydrogen Chemical class 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
- B60L58/40—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for controlling a combination of batteries and fuel cells
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W2050/0001—Details of the control system
- B60W2050/0019—Control system elements or transfer functions
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
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- Fuel Cell (AREA)
Abstract
The embodiment of the invention provides a fuel cell automobile power distribution method and system based on a nonlinear programming algorithm, and belongs to the technical field of control of fuel cell automobiles. The distribution method comprises the following steps: acquiring a motor power demand value sent by a motor module of an automobile; taking the required value and the power source parameter of the last round of distribution result as initial conditions of the optimization problem to obtain initial point positions of a nonlinear programming algorithm; determining a feasible region of the optimization problem; running a nonlinear programming algorithm, and carrying out one-dimensional search along a search direction by taking an initial point position as a starting point; judging whether the error of the iterative result is smaller than or equal to the allowable error; updating a matrix of the nonlinear programming algorithm under the condition that the judgment error is larger than the allowable error; under the condition that the judgment error is smaller than or equal to the allowable error, determining the current point position as the optimal point in the feasible domain; and controlling and distributing the output power of each power source of the fuel cell automobile according to the optimal power source parameters.
Description
Technical Field
The invention relates to the technical field of control of fuel cell automobiles, in particular to a fuel cell automobile power distribution method and system based on a nonlinear programming algorithm.
Background
The existing power distribution strategy is mainly based on a control strategy based on rules, and the rule is mainly formulated according to the running condition of the automobile. Although the method is simple to set, the method has the problem that boundary conditions are too subjective, and the system dynamics are difficult to accurately describe, so that the method does not have good dynamic characteristics. Meanwhile, the existing methods pay attention to improving the fuel economy of the hybrid power system, but do not consider the durability problem of the system.
Disclosure of Invention
The invention aims to provide a fuel cell automobile power distribution method and system based on a nonlinear programming algorithm, which can improve the durability of a hybrid power system of a fuel cell automobile.
In order to achieve the above object, an embodiment of the present invention provides a fuel cell vehicle power distribution method based on a nonlinear programming algorithm, the distribution method including:
acquiring a motor power demand value sent by a motor module of an automobile;
taking the required value and the power source parameter of the last round of distribution result as initial conditions of an optimization problem to obtain initial points of the nonlinear programming algorithm;
determining constraint conditions of the nonlinear programming algorithm to obtain a feasible domain of the optimization problem;
running the nonlinear programming algorithm, and carrying out one-dimensional search along a search direction by taking the initial point position as a starting point;
judging whether the error between the current iteration result and the previous iteration result is smaller than or equal to a preset allowable error;
under the condition that the error between the current iteration result and the previous iteration result is larger than the allowable error, updating the matrix of the nonlinear programming algorithm, taking the required value and the power source parameter of the previous iteration result as initial conditions of the optimization problem again to obtain initial point positions of the nonlinear programming algorithm, and executing corresponding steps of the method until the error between the current iteration result and the previous iteration result is smaller than or equal to the allowable error;
under the condition that the error between the current iteration result and the previous iteration result is less than or equal to the allowable error, determining the current point position as the optimal point in the feasible domain;
and controlling and distributing the output power of each power source of the fuel cell automobile according to the optimal power source parameters.
Optionally, the constraint includes:
wherein,,for the output of the converter at the fuel cell side, < >>Output power of converter at lithium ion battery end, P req The output power of the power source;
the lithium ion battery current constraint expressed by the formula (1) is adopted,
wherein,,representing the minimum value of the charge current of the fuel cell, I bat Is a fuel cell>Is the maximum value of the charge current of the fuel cell;
the lithium ion battery voltage constraint expressed by the formula (2) is adopted,
V b,min ≤V bat ≤V b,max ， (2)
wherein V is b,min Is the minimum value of the output voltage of the lithium ion battery, V bat Is the output voltage of the lithium ion battery, V b,max Is the maximum value of lithium ion output voltage;
the lithium ion battery power constraint expressed by the formula (3) is adopted,
wherein,,minimum charging power for lithium ion battery, P bat Is the charging power of the lithium ion battery,maximum charge power for lithium ion battery;
using the fuel cell current density constraint represented by equation (4),
i fc，mmin ≤i fc ≤i fc，max ， (4)
wherein i is fc，min I is the minimum current density of the fuel cell fc I is the current density of the fuel cell fc，max Maximum current density for the fuel cell;
using the fuel cell voltage constraint represented by equation (5),
V fc，min ≤V fc ≤V fc，max ， (5)
wherein V is fc，min Is the minimum output voltage of the fuel cell, V fc For the output voltage of the fuel cell, V fc，max Maximum output voltage of (2);
using the fuel cell power constraint represented by equation (6),
P fc，min ≤P fc ≤P fc，max ， (6)
wherein P is fc，min P is the maximum output power of the fuel cell fc For the output power of the fuel cell, P fc，max Is the maximum output power of the fuel cell; and
using the fuel cell fluctuation limit constraint shown in equation (7),
-P′ fc_limit ≤P′ fc ≤P′ fc_limit ， (7)
wherein, -P' fc_limit For the lower limit of the limit constraint, P' fc For the rate of change of the fuel cell, P' fc_limit Upper limit of the limit constraintThe method comprises the steps of carrying out a first treatment on the surface of the At least one of them.
Optionally, the fuel cell current density constraint expressed by the formula (4) includes:
determining the maximum current density according to equation (8),
i fc，max ＝min(i fc，pol，max ，i fc，pwr，max ，i fc，efficiency，max )， (8)
wherein i is fc，pol，max For maximum current density of fuel cell determined by polarization curve, i fc，pwr，max I is the current density of the fuel cell at maximum power fc，efficiency，max Is the current density of the fuel cell at maximum efficiency.
Optionally, the fuel cell current density constraint expressed by the formula (4) includes:
determining the minimum current density according to equation (9),
i fc，min ＝max(i fc，pol，min ，i fc，efficiency，min )， (9)
wherein i is fc，pol，min For minimum current density of fuel cell determined by polarization curve, i fc，efficiency，min Is the current density of the fuel cell at minimum efficiency.
Optionally, the determining whether the error between the current iteration result and the previous iteration result is less than or equal to a preset allowable error specifically includes:
the objective function value of the result of the iteration is calculated according to equation (8),
wherein minf (x) represents the minimum value of the objective function f (x),indicating the hydrogen consumption of the fuel cell, I bat Current of lithium ion battery, V bat As lithium ion batteriesVoltage, I stack V is the output current of the fuel cell stack Is the output voltage of the fuel cell.
In another aspect, the present invention further provides a fuel cell vehicle power distribution system based on a nonlinear programming algorithm, the system comprising:
a fuel cell end comprising a fuel cell and an inverter in series;
the lithium ion battery terminal comprises a lithium ion battery and an inverter which are connected in series;
and the power distribution module is connected with the converter at the fuel cell end and the converter at the lithium ion battery end and is used for executing the distribution method.
In yet another aspect, the present invention also provides a storage medium storing instructions for reading by a machine to cause the machine to perform a dispensing method as described in any one of the above.
According to the technical scheme, the nonlinear programming algorithm-based fuel cell automobile power distribution method and system provided by the invention have the advantages that the nonlinear programming algorithm is introduced into the power distribution control of the fuel cell, and constraint conditions are set by combining the working conditions of the fuel cell and the lithium ion battery in the power distribution control, so that the fuel cell and the lithium ion battery can be stabilized under the self adaptive working conditions during power distribution, and the durability of a hybrid power system of the fuel cell automobile is improved.
Additional features and advantages of embodiments of the invention will be set forth in the detailed description which follows.
Drawings
The accompanying drawings are included to provide a further understanding of embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain, without limitation, the embodiments of the invention. In the drawings:
FIG. 1 is a flow chart of a fuel cell vehicle power distribution method based on a nonlinear programming algorithm in accordance with one embodiment of the present invention;
fig. 2 is a block diagram of a fuel cell vehicle power distribution system based on a nonlinear programming algorithm in accordance with one embodiment of the present invention.
Detailed Description
The following describes specific embodiments of the present invention in detail with reference to the drawings. It should be understood that the detailed description and specific examples, while indicating and illustrating the invention, are not intended to limit the invention.
In the embodiments of the present invention, unless otherwise indicated, terms of orientation such as "upper, lower, top, bottom" are used generally with respect to the orientation shown in the drawings or with respect to the positional relationship of the various components with respect to one another in the vertical, vertical or gravitational directions.
In addition, if there is a description of "first", "second", etc. in the embodiments of the present invention, the description of "first", "second", etc. is for descriptive purposes only and is not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions of the embodiments may be combined with each other, but it is necessary to base that the technical solutions can be realized by those skilled in the art, and when the technical solutions are contradictory or cannot be realized, the combination of the technical solutions should be considered to be absent and not within the scope of protection claimed in the present invention.
A flow chart of a fuel cell vehicle power distribution method based on a nonlinear programming algorithm according to one embodiment of the present invention is shown in fig. 1. In fig. 1, the method may include:
in step S10, a motor power demand value issued by a motor module of the automobile is obtained;
in step S11, taking the required value and the power source parameter of the last round of distribution result as the initial condition of the optimization problem to obtain the initial point position of the nonlinear programming algorithm;
in step S12, determining constraint conditions of the nonlinear programming algorithm to obtain a feasible region of the optimization problem;
in step S13, a nonlinear programming algorithm is operated, and one-dimensional search is performed along a search direction by taking an initial point position as a starting point;
in step S14, it is determined whether the error between the current iteration result and the previous iteration result is less than or equal to a preset allowable error;
in step S15, under the condition that the error between the current iteration result and the previous iteration result is greater than the allowable error, updating the matrix of the nonlinear programming algorithm, taking the required value and the power source parameter of the previous iteration result as the initial condition of the optimization problem again to obtain the initial point position of the nonlinear programming algorithm, and executing the corresponding steps of the method until the error between the current iteration result and the previous iteration result is less than or equal to the allowable error;
in step S16, under the condition that the error between the current iteration result and the previous iteration result is less than or equal to the allowable error, determining the current point location as the optimal point in the feasible domain;
in step S17, the output power of each power source of the distributed fuel cell vehicle is controlled according to the optimal power source parameter.
In step 10, the present invention determines the planning objective of the current nonlinear programming algorithm by obtaining the motor power demand value. In step S11, the acquired motor power demand value and the power source parameter of the previous round are converted into initial conditions for the optimization problem. The power source parameter of the previous round is optimized under the power requirement value of the previous round, namely the working state of the current hybrid power system, so that the obtained motor power requirement value and the power parameter of the previous round are used as initial conditions, and the nonlinear programming algorithm can reasonably program in combination with the current situation of the system. In steps S13 to S15, the linear programming algorithm is iterated repeatedly. When the result error of the two iterations is smaller than the allowable error, it is explained that the result of the iteration has already tended to converge at this time, so in step S16 and step S17, the result of the iteration can be directly used as the control strategy of the present round.
In addition, in FIG. 1, although this constraint may take a variety of forms as known to those skilled in the art. However, in a preferred example of the present invention, the inventors consider that under the special conditions of the fuel cell vehicle, the working conditions of the lithium ion battery, the fuel cell, and the different converters need to be considered at the same time when performing the power distribution control, and thus, the constraint conditions may include the following formulas (1) to (7),
wherein,,for the output of the converter at the fuel cell side, < >>Output power of converter at lithium ion battery end, P req The output power of the power source;
the lithium ion battery current constraint expressed by the formula (1) is adopted,
wherein,,representing the minimum value of the charge current of the fuel cell, I bat Is a fuel cell>Is the maximum value of the charge current of the fuel cell;
the lithium ion battery voltage constraint expressed by the formula (2) is adopted,
V b,min ≤V bat ≤V b,max ， (2)
wherein V is b,min Minimum value of output voltage of lithium ion battery，V bat Is the output voltage of the lithium ion battery, V b,max Is the maximum value of lithium ion output voltage;
the lithium ion battery power constraint expressed by the formula (3) is adopted,
wherein,,minimum charging power for lithium ion battery, P bat Is the charging power of the lithium ion battery,maximum charge power for lithium ion battery;
using the fuel cell current density constraint represented by equation (4),
i fc，min ≤i fc ≤i fc，max ， (4)
wherein i is fc，min I is the minimum current density of the fuel cell fc I is the current density of the fuel cell fc，max Maximum current density for the fuel cell;
using the fuel cell voltage constraint represented by equation (5),
V fc，min ≤V fc ≤V fc，max ， (5)
wherein V is fc，min Is the minimum output voltage of the fuel cell, V fc For the output voltage of the fuel cell, V fc，max Maximum output voltage of (2);
using the fuel cell power constraint represented by equation (6),
P fc，min ≤P fc ≤P fc，max ， (6)
wherein P is fc，min P is the maximum output power of the fuel cell fc For the output power of the fuel cell, P fc，max Is the maximum output power of the fuel cell; and
using the fuel cell fluctuation limit constraint shown in equation (7),
-P′ fc_limit ≤P′ fc ≤P′ fc_limit ， (7)
wherein, -P' fc_limit For the lower limit of the limit constraint, P' fc P 'is the rate of change of the fuel cell' fc_limit Is the upper limit of the limit constraint; at least one of them.
Further, considering the specificity of the fuel cell, unlike the conventional cell, the maximum current density of the fuel cell is not the output current density of the conventional cell at full power. Because the fuel cell is filled with fuel gas such as hydrogen, the fuel cell generates energy after chemical reaction and conversion, and finally, the current can be output. Therefore, to obtain this maximum current density, it is necessary to combine the characteristics of the fuel cell. When obtaining the maximum current density, the inventors found that the three values of the maximum value of the current density of the polarization curve of the fuel cell, the current density at the maximum power and the current density at the maximum efficiency have different relationships in different types of fuel cells and different working conditions. Thus, the maximum current density can be determined according to equation (8),
i fc，max ＝min(i fc，pol，max ，i fc，pwr，max ，i fc，efficiency，max )， (8)
wherein i is fc，pol，max For maximum current density of fuel cell determined by polarization curve, i fc，pwr，max I is the current density of the fuel cell at maximum power fc，efficiency，max Is the current density of the fuel cell at maximum efficiency.
Similarly to this maximum current density, in this embodiment, the minimum current density may also be determined according to equation (9) for a particular operating condition of the fuel cell,
i fc，min ＝max(i fc，pol，min ，i fc，efficiency，min )， (9)
wherein i is fc，pol，min Minimum current for fuel cell determined by polarization curveDensity, i fc，efficiency，min Is the current density of the fuel cell at minimum efficiency.
In addition, in step S14, in order to facilitate calculation of an error between the results of the two iterations, one objective function value may be calculated for the results of the two iterations, respectively, and the error may be calculated in combination with the two objective function values. Specifically, the objective function value of the result of the iteration is calculated according to formula (8),
wherein minf (x) represents the minimum value of the objective function f (x),indicating the hydrogen consumption of the fuel cell, I bat Current of lithium ion battery, V bat For the voltage of lithium ion battery, I stack V is the output current of the fuel cell stack Is the output voltage of the fuel cell.
In another aspect, the present invention also provides a fuel cell vehicle power distribution system based on a nonlinear programming algorithm, as shown in fig. 2, which may include a fuel cell end 10 and a lithium ion cell end 20. The fuel cell terminal 10 may include a fuel cell 11, an inverter 12, and a power distribution module 30 in series. The lithium ion battery terminal 20 may include a lithium ion battery 21 and an inverter 22 in series. The power distribution module 30 may be coupled to the converter 12 of the fuel cell end 10 and the converter 22 of the lithium ion battery end 20 for performing the distribution method as described above.
In yet another aspect, the present invention also provides a storage medium storing instructions for reading by a machine to cause the machine to perform a dispensing method as described in any one of the above.
According to the technical scheme, the nonlinear programming algorithm-based fuel cell automobile power distribution method and system provided by the invention have the advantages that the nonlinear programming algorithm is introduced into the power distribution control of the fuel cell, and constraint conditions are set by combining the working conditions of the fuel cell and the lithium ion battery in the power distribution control, so that the fuel cell and the lithium ion battery can be stabilized under the self adaptive working conditions during power distribution, and the durability of a hybrid power system of the fuel cell automobile is improved.
The optional embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the embodiments of the present invention are not limited to the specific details of the foregoing embodiments, and various simple modifications may be made to the technical solutions of the embodiments of the present invention within the scope of the technical concept of the embodiments of the present invention, and all the simple modifications belong to the protection scope of the embodiments of the present invention.
In addition, the specific features described in the above embodiments may be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the various possible combinations of embodiments of the invention are not described in detail.
Those skilled in the art will appreciate that all or part of the steps in implementing the methods of the embodiments described above may be implemented by a program stored in a storage medium, including instructions for causing a single-chip microcomputer, chip or the like or processor (processor) to perform all or part of the steps of the methods of the embodiments described herein. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In addition, any combination of the various embodiments of the present invention may be made between the various embodiments, and should also be regarded as disclosed in the embodiments of the present invention as long as it does not deviate from the idea of the embodiments of the present invention.
Claims (7)
1. A fuel cell vehicle power distribution method based on a nonlinear programming algorithm, the distribution method comprising:
acquiring a motor power demand value sent by a motor module of an automobile;
taking the required value and the power source parameter of the last round of distribution result as initial conditions of an optimization problem to obtain initial points of the nonlinear programming algorithm;
determining constraint conditions of the nonlinear programming algorithm to obtain a feasible domain of the optimization problem;
running the nonlinear programming algorithm, and carrying out one-dimensional search along a search direction by taking the initial point position as a starting point;
judging whether the error between the current iteration result and the previous iteration result is smaller than or equal to a preset allowable error;
under the condition that the error between the current iteration result and the previous iteration result is larger than the allowable error, updating the matrix of the nonlinear programming algorithm, taking the required value and the power source parameter of the previous iteration result as initial conditions of the optimization problem again to obtain initial point positions of the nonlinear programming algorithm, and executing corresponding steps of the method until the error between the current iteration result and the previous iteration result is smaller than or equal to the allowable error;
under the condition that the error between the current iteration result and the previous iteration result is less than or equal to the allowable error, determining the current point position as the optimal point in the feasible domain;
and controlling and distributing the output power of each power source of the fuel cell automobile according to the optimal power source parameters.
2. The allocation method according to claim 1, wherein the constraint comprises:
wherein,,for the output of the converter at the fuel cell side, < >>Output power of converter at lithium ion battery end, P req The output power of the power source;
the lithium ion battery current constraint expressed by the formula (1) is adopted,
wherein,,representing the minimum value of the charge current of the fuel cell, I bat Is a fuel cell>Is the maximum value of the charge current of the fuel cell;
the lithium ion battery voltage constraint expressed by the formula (2) is adopted,
V b，min ≤V bat ≤V b，max ， (2)
wherein V is b，min Is the minimum value of the output voltage of the lithium ion battery, V bat Is the output voltage of the lithium ion battery, V b，max Is the maximum value of lithium ion output voltage;
the lithium ion battery power constraint expressed by the formula (3) is adopted,
wherein,,minimum charging power for lithium ion battery, P bat Charging power for lithium ion battery, +.>Maximum charge power for lithium ion battery;
using the fuel cell current density constraint represented by equation (4),
i fc，min ≤i fc ≤i fc，max ， (4)
wherein i is fc，min I is the minimum current density of the fuel cell fc I is the current density of the fuel cell fc，max Maximum current density for the fuel cell;
using the fuel cell voltage constraint represented by equation (5),
V fc，min ≤V fc ≤V fc，max ， (5)
wherein V is fc，min Is the minimum output voltage of the fuel cell, V fc For the output voltage of the fuel cell, V fc，max Maximum output voltage of (2);
using the fuel cell power constraint represented by equation (6),
P fc，min ≤P fc ≤P fc，max ， (6)
wherein P is fc，min P is the maximum output power of the fuel cell fc For the output power of the fuel cell, P fc，max Is the maximum output power of the fuel cell; and
using the fuel cell fluctuation limit constraint shown in equation (7),
-P′ fc_limit ≤P′ fc ≤P′ fc_limit ， (7)
wherein, -P' fc_limit For the lower limit of the limit constraint, P' fc For the rate of change of the fuel cell, P' fc_limit An upper limit that is the limit constraint; at least one of them.
3. The distribution method according to claim 2, wherein the fuel cell current density constraint represented by the formula (4) includes:
determining the maximum current density according to equation (8),
i fc，max ＝min(i fc，pol，max ，i fc，pwr，max ，i fc，efficiency，max )， (8)
wherein i is fc，pol，max For maximum current density of fuel cell determined by polarization curve, i fc，pwr，max I is the current density of the fuel cell at maximum power fc，efficiency，max Is the current density of the fuel cell at maximum efficiency.
4. The distribution method according to claim 2, wherein the fuel cell current density constraint represented by the formula (4) includes:
determining the minimum current density according to equation (9),
i fc，min ＝max(i fc，pol，min ，i fc，efficiency，min )， (9)
wherein i is fc，pol，min For minimum current density of fuel cell determined by polarization curve, i fc，efficiency，min Is the current density of the fuel cell at minimum efficiency.
5. The allocation method according to claim 1, wherein determining whether an error between a result of a current iteration and a result of a previous iteration is less than or equal to a preset allowable error specifically includes:
the objective function value of the result of the iteration is calculated according to equation (8),
wherein min f (x) represents the minimum value of the objective function f (x),indicating the hydrogen consumption of the fuel cell, I bat Is a lithium ion batteryCurrent of V bat For the voltage of lithium ion battery, I stack V is the output current of the fuel cell stack Is the output voltage of the fuel cell.
6. A fuel cell vehicle power distribution system based on a nonlinear programming algorithm, the system comprising:
a fuel cell end comprising a fuel cell and an inverter in series;
the lithium ion battery terminal comprises a lithium ion battery and an inverter which are connected in series;
a power distribution module connected to the converter at the fuel cell side and the converter at the lithium ion battery side for performing the distribution method according to any one of claims 1 to 5.
7. A storage medium storing instructions for reading by a machine to cause the machine to perform the allocation method of any one of claims 1 to 5.
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| CN202110435060.6A CN113147513B (en) | 2021-04-22 | 2021-04-22 | Fuel cell automobile power distribution method and system based on nonlinear programming algorithm |
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| WO2014009505A2 (en) * | 2012-07-13 | 2014-01-16 | Commissariat à l'énergie atomique et aux énergies alternatives | Motor vehicle drive unit including a fuel cell and an energy storage system |
| CN110834625A (en) * | 2019-11-11 | 2020-02-25 | 常熟理工学院 | Double-electric-coupling fuel cell automobile energy efficiency optimization method of self-adaptive asynchronous particle swarm |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2014009505A2 (en) * | 2012-07-13 | 2014-01-16 | Commissariat à l'énergie atomique et aux énergies alternatives | Motor vehicle drive unit including a fuel cell and an energy storage system |
| CN110834625A (en) * | 2019-11-11 | 2020-02-25 | 常熟理工学院 | Double-electric-coupling fuel cell automobile energy efficiency optimization method of self-adaptive asynchronous particle swarm |
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| Title |
|---|
| 燃料电池混合动力汽车动力***匹配与优化研究;魏跃远;詹文章;林逸;;汽车工程(第10期);93、97+108 * |
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