CN116834613A - Power battery assisted hydrogen fuel cell automobile system energy management method - Google Patents
Power battery assisted hydrogen fuel cell automobile system energy management method Download PDFInfo
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- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 title claims abstract description 112
- 239000000446 fuel Substances 0.000 title claims abstract description 112
- 229910052739 hydrogen Inorganic materials 0.000 title claims abstract description 112
- 239000001257 hydrogen Substances 0.000 title claims abstract description 112
- 238000007726 management method Methods 0.000 title claims abstract description 30
- 239000002245 particle Substances 0.000 claims abstract description 17
- 238000000034 method Methods 0.000 claims description 20
- 238000005457 optimization Methods 0.000 claims description 12
- 238000004364 calculation method Methods 0.000 description 3
- 229910052799 carbon Inorganic materials 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000004927 fusion Effects 0.000 description 2
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 239000003054 catalyst Substances 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
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- 230000002035 prolonged effect Effects 0.000 description 1
- 238000005096 rolling process Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
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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
- 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
- B60L15/00—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles
- B60L15/20—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles for control of the vehicle or its driving motor to achieve a desired performance, e.g. speed, torque, programmed variation of speed
- B60L15/2045—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles for control of the vehicle or its driving motor to achieve a desired performance, e.g. speed, torque, programmed variation of speed for optimising the use of energy
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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
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/40—Application of hydrogen technology to transportation, e.g. using fuel cells
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- Mechanical Engineering (AREA)
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- Sustainable Energy (AREA)
- Fuel Cell (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
The application provides an energy management method for a power battery assisted hydrogen fuel cell automobile system, and belongs to the field of automobile control. Firstly, acquiring preset parameters, finishing component selection of a hybrid power system model according to the preset parameters, and constructing a power battery-assisted hydrogen fuel cell automobile hybrid power system model; for the hybrid power system model, a two-stage serial fuzzy controller is adopted to realize load-changing limitation and control of the hydrogen fuel cell system, and energy management is realized; and optimizing membership functions and fuzzy rule weights of the two-stage serial fuzzy controllers by using a particle swarm algorithm. The application reduces the change rate of the output power and the frequent start-stop phenomenon when the hydrogen fuel cell works, improves the durability of the hydrogen fuel cell, prolongs the service lives of the hydrogen fuel cell and the power cell, and improves the running economy of the vehicle.
Description
Technical Field
The application belongs to the field of automobile control, and particularly relates to an energy management method for a hydrogen fuel cell automobile system assisted by a power cell.
Background
The hydrogen fuel cell automobile has high energy conversion efficiency, clean water as the emission, and wide hydrogen source, and is receiving wide attention in new energy automobiles. Because of the poor dynamic characteristics of hydrogen fuel cells, it is common in hydrogen fuel cell vehicles to provide the energy required by the vehicle along with an auxiliary energy source to ensure the power demand of the hydrogen fuel cell vehicle. At present, a hydrogen fuel cell automobile mostly uses a hydrogen fuel cell and a power cell together to provide energy for the whole automobile, so that the design of an energy management method of a hybrid power system of the hydrogen fuel cell and the power cell is extremely important.
In the prior art, the design objective of the energy management strategy of the automobile system is to improve the dynamic performance and the economical efficiency of the automobile, but under the working conditions of idling, frequent start-stop, great load change and overload of the hydrogen fuel cell, the carbon carrier and the catalyst in the hydrogen fuel cell are damaged, so that the service life of the hydrogen fuel cell is influenced, and the durability of the hydrogen fuel cell cannot be effectively ensured and improved by the current energy management method.
Disclosure of Invention
In view of the above-mentioned drawbacks or shortcomings in the prior art, the present application is directed to providing a power-cell-assisted energy management method for a hydrogen fuel cell vehicle system, which reduces the rate of change of output power and frequent start-stop phenomena when the hydrogen fuel cell is in operation, improves the durability of the hydrogen fuel cell, prolongs the service lives of the hydrogen fuel cell and the power cell, and improves the running economy of the vehicle.
In order to achieve the above purpose, the embodiment of the present application adopts the following technical scheme:
a power cell assisted hydrogen fuel cell automotive system energy management method, the method comprising the steps of:
acquiring preset parameters, completing component model selection of the hybrid power system model according to the preset parameters, and constructing a hybrid power system model of the hydrogen fuel cell automobile assisted by the power cell;
and for the hybrid power system model, a two-stage serial fuzzy controller is adopted to realize load-changing limitation and control of the hydrogen fuel cell system, and a particle swarm algorithm is utilized to optimize membership functions and fuzzy rule weights of the two-stage serial fuzzy controller, so that energy management is realized.
As a preferred embodiment of the present application, the implementation of energy management specifically includes:
step S2, a series fuzzy controller comprising a first-stage fuzzy controller and a second-stage fuzzy controller outputs a control signal to the hybrid power system;
step S3, the hybrid power system outputs mileage information to the particle swarm optimization algorithm module;
step S4, the particle swarm optimization algorithm module sets the driving mileage as an objective function, calculates and searches the maximum value of the driving mileage; if not, optimizing the membership function and the fuzzy rule weight of the series fuzzy controller, updating the optimized membership value to the fuzzy controller, and returning to the step S2; if the maximum value of the driving mileage is found, the step S5 is entered;
and S5, outputting the maximum driving mileage, and simultaneously adopting the membership function and fuzzy rule weight of the serial fuzzy controller at the moment to output the corresponding hydrogen fuel cell current.
As a preferred embodiment of the present application, the step S5 of outputting the corresponding hydrogen fuel cell current by using the membership function and fuzzy rule weight of the serial fuzzy controller at this time specifically includes:
with two-stage control, when detecting the output current of the first-stage fuzzy controllerRate of change of 1->When the current is more than 5A/s, the output current of the front hydrogen fuel cell system is +.>Output current of hydrogen fuel cell system at next momentThe method comprises the steps of carrying out a first treatment on the surface of the When detecting the +.>1 rate of change->When the current is less than or equal to 5A/s, the second-stage fuzzy controller is effective, and the second-stage fuzzy controller calculates the change value of the output current of the hydrogen fuel cell from the current moment to the next moment through three input parameters +.>The method comprises the steps of carrying out a first treatment on the surface of the Output current of hydrogen fuel cell system at next moment。
As a preferred embodiment of the present application, the preset parameters include a whole vehicle parameter, a driving motor parameter, a power battery parameter, and a hydrogen fuel battery parameter.
As a preferred embodiment of the present application, the hydrogen fuel cell parameters include: maximum current of the hydrogen fuel cell system, rated voltage of the hydrogen fuel cell system, and rated power.
As a preferred embodiment of the present application, the power battery parameters include: peak power, rated power, maximum rotational speed, rated rotational speed, and peak torque of the motor.
As a preferred embodiment of the application, the two-stage fuzzy controllers are respectively a first-stage fuzzy controller and a second-stage fuzzy controller, and after the two-stage fuzzy controllers are connected in series, the motor is required to currentAnd the current battery power of the power batteryAs an input parameter of the first-stage fuzzy controller, the output current of the first-stage fuzzy controller is +.>The method comprises the steps of carrying out a first treatment on the surface of the Three input parameters of the second-stage fuzzy controller are respectively the output current of the first-stage fuzzy controller +.>Current battery power of power battery +.>A variation value of the motor demand current +.>The method comprises the steps of carrying out a first treatment on the surface of the The output result of the second-stage fuzzy controller is the variation value of the output current of the hydrogen fuel cell system +.>。
As a preferred embodiment of the present application, the particle swarm algorithm uses mileage as an objective function, and determines whether a maximum value of the mileage is found in each iteration; if the maximum value is found, ending iteration, and calculating a two-stage serial fuzzy controller by using the current membership function and the fuzzy rule weight; if not, continuing iteration, and updating the membership function and the fuzzy rule weight of the two-stage serial fuzzy controller.
The technical scheme provided by the embodiment of the application has the following beneficial effects:
the power battery assisted energy management method for the hydrogen fuel cell automobile system provided by the embodiment of the application is characterized in that a hybrid power system is established based on the hydrogen fuel cell system and the power cell system, and the current demand of the whole automobile is acquired according to input parameters based on the hybrid power systemI_reqOutput current to hydrogen fuel cell system by series fuzzy controlI_fcAnd performing real-time dynamic regulation and control to ensure the stability of the hydrogen fuel cell system, and optimizing a membership function and a fuzzy rule weight of fuzzy control by using a particle swarm optimization algorithm with the mileage as a target so as to ensure the running economy of the vehicle. The application reduces the change rate of the output power and the frequent start-stop phenomenon when the hydrogen fuel cell works, improves the durability of the hydrogen fuel cell, prolongs the service lives of the hydrogen fuel cell and the power cell, and improves the running economy of the vehicle.
Of course, it is not necessary for any one product or method of practicing the application to achieve all of the advantages set forth above at the same time.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person of ordinary skill in the art.
FIG. 1 is a block diagram of a hybrid power system of a hydrogen fuel cell vehicle to which the system energy management method according to the embodiment of the present application is applied;
FIG. 2 is a flow chart of a method for managing energy of a power-cell assisted hydrogen fuel cell vehicle system according to an embodiment of the application;
FIG. 3 is a flow chart of energy management based on a two-stage series fuzzy controller in an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. It will be apparent that the described embodiments are only some, but not all, embodiments of the application. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. It should be noted that, in the case of no conflict, the embodiments of the present application and features in the embodiments may also be combined with each other.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures. In the description of the present application, the terms "first," "second," "third," "fourth," and the like are used merely to distinguish between descriptions and are not to be construed as indicating or implying relative importance.
The application aims to provide an energy management method of a power battery assisted hydrogen fuel cell automobile system, which improves the durability of a hydrogen fuel cell, reduces the start and stop of the hydrogen fuel cell and greatly changes the load so as to prolong the service life of the hydrogen fuel cell.
As shown in fig. 1, the power-battery-assisted hydrogen-fuel-cell automobile system comprises a hydrogen fuel cell, a power battery, an energy management system for loading an energy control strategy, an overall-vehicle control system, a motor controller, a motor and a transmission system; the method comprises the steps of obtaining the required current of a motor of the whole vehicle through a hybrid power system model, taking a hydrogen fuel cell passenger car type as an example, taking a hydrogen fuel cell system as a main energy source, taking a power cell as an auxiliary energy source, and powering the motor in parallel to form a system structure with hybrid power.
As shown in fig. 2, the power battery assisted hydrogen fuel cell automobile system energy management method comprises the following steps:
step S1, acquiring preset parameters, finishing component selection of a hybrid power system model according to the preset parameters, and constructing a power battery-assisted hydrogen fuel cell automobile hybrid power system.
In this step, the hydrogen fuel cell system needs to be started to charge the power battery when the power level of the power battery is low, and separately supplies power to the driving motor to drive the vehicle. Therefore, the output performance of the hydrogen fuel cell system needs to meet the power demand of the vehicle in the normal state. In addition, when the hydrogen fuel cell system charges the power cell, the output current should be smaller than the allowable charging current of the power cell, which generally refers to the current corresponding to the maximum charging rate of the power cell. A hybrid power system of a hydrogen fuel cell automobile with the assistance of a power cell is constructed, and comprises a hydrogen fuel cell system and a power cell system, and the fusion of the two systems. In this step, the preset parameters include a whole vehicle parameter, a driving motor parameter, a power battery parameter and a hydrogen fuel battery parameter. Wherein the hydrogen fuel cell parameters include: maximum current of the hydrogen fuel cell system, rated voltage of the hydrogen fuel cell system, rated power; the power battery parameters include: peak power, rated power, maximum rotational speed, rated rotational speed, peak torque, etc. of the motor.
Specifically, the method comprises the following steps:
step S11, establishing a hydrogen fuel cell system according to the related parameters of the hydrogen fuel cell in the acquired preset parameters, wherein the power of the hydrogen fuel cell system in the hydrogen fuel cell system is equal to or higher than the power of the hydrogen fuel cell systemP fc Calculated from equation (1):
（1）
in the formula (1),indicating one-way hydrogen fuel cell>Working efficiency; />Representing the total electric power of the auxiliary electric power utilization unit; />Indicating maximum cruising speed of the vehicle,/>Representing the mechanical efficiency of the power system, m, f and C D A and A respectively represent the mass of the whole vehicle, the rolling resistance coefficient, the wind resistance coefficient and the windward area.
Step S12, a power battery system is established according to the related parameters of the power battery in the acquired preset parameters, and the power battery output power of the power battery systemThe calculation of (2) is as shown in formula (2):
（2）
power battery electric quantity of power battery systemThe calculation is shown in formula (3):
（3）
in the formulas (2) and (3),and->Respectively outputting voltage and current of the power battery, wherein the power battery outputs voltage＝/>Power battery output current +.>，/>And->The open-circuit voltage and the internal resistance of the power battery are respectively,V ov for the operating voltage +.>Initial battery charge for power battery, < >>The current battery power of the power battery is +.>Is the power battery capacity. And then, according to the required power of the whole vehicle on the power battery and the initial battery electric quantity of the power battery, calculating by adopting the formulas (2) and (3) to obtain the output power of the power battery and the current battery electric quantity of the power battery.
Step S13, feeding the hydrogen fuel cell system and the power cell systemPerforming fusion to obtain a hydrogen fuel cell automobile hybrid power system assisted by a power cell, and calculating the motor required current of the hybrid power system：
（4）
In the formula (4) of the present application,output current for hydrogen fuel cell,/->And outputting current for the power battery, and obtaining the motor required current of the whole vehicle through a hybrid power system.
After the step S1 is executed, the load-changing limitation and control of the hydrogen fuel cell system are realized by adopting a two-stage serial fuzzy controller for the hybrid power system model, and the membership function and fuzzy rule weight of the two-stage serial fuzzy controller are optimized by utilizing a particle swarm (Particle Swarm Optimization, PSO) algorithm, so that the energy management is realized. The implementation of energy management comprises the following steps:
and S2, a series fuzzy controller comprising a first-stage fuzzy controller and a second-stage fuzzy controller outputs a control signal to the hybrid power system.
And S3, the hybrid power system outputs mileage information to the particle swarm optimization algorithm module.
Step S4, the particle swarm optimization algorithm module sets the driving mileage as an objective function, calculates and searches the maximum value of the driving mileage; if not, optimizing the membership function and the fuzzy rule weight of the series fuzzy controller, updating the optimized membership value to the fuzzy controller, and returning to the step S2; if the maximum value of the driving distance is found, the process proceeds to step S5.
The particle swarm algorithm takes the mileage of the automobile as an objective function, and judges whether the maximum value of the mileage is found or not through each iteration; if the maximum value is found, ending iteration, and calculating a two-stage serial fuzzy controller by using the current membership function and the fuzzy rule weight; if not, continuing iteration, and updating the membership function and the fuzzy rule weight of the two-stage serial fuzzy controller.
And the PSO algorithm takes the mileage information as an objective function, and the calculation is continuously iterated until the maximum value of the driving mileage is found. At this time, the corresponding membership function distribution and fuzzy rule weight are the final optimization result. In this way, the expert experience in the original fuzzy control is replaced by the vehicle economy optimization, and the uncertainty of the manual experience is eliminated.
And S5, outputting the maximum driving mileage, and simultaneously adopting the membership function and fuzzy rule weight of the serial fuzzy controller at the moment to output the corresponding hydrogen fuel cell current.
As shown in fig. 3, in this step, the membership function and fuzzy rule weight of the serial fuzzy controller are adopted to output the corresponding hydrogen fuel cell current, which specifically includes:
the two-stage series fuzzy controllers are a first-stage fuzzy controller 1 and a second-stage fuzzy controller 2 respectively, and after the two-stage fuzzy controllers are connected in series, the motor is required to currentAnd the current battery capacity of the power battery +.>As an input parameter of the first-stage fuzzy controller 1, the output current of the first-stage fuzzy controller 1 is +.>The method comprises the steps of carrying out a first treatment on the surface of the Three input parameters of the second-stage fuzzy controller 2 are respectively the output current of the first-stage fuzzy controller 1 +.>Current battery power of power battery +.>The motor requires currentChange value->The output result of the second-stage fuzzy controller 2 is the variation value of the output current of the hydrogen fuel cell。
Assume that the output current of the hydrogen fuel cell at the current moment isThe second-stage fuzzy controller calculates the variation value of the output current of the hydrogen fuel cell from the current moment to the next moment through the three input parameters>. Then->And->The vector sum of (2) is the output current of the hydrogen fuel cell at the next moment +.>. In this way, the output current of the hydrogen fuel cell is limited within a predetermined range.
The control logic of the second-stage fuzzy controller is as follows: when detecting output of the first-stage fuzzy controller1 rate of changeAt > 5A/s, the original current value +.>Output of->Output current of hydrogen fuel cell system at next time +.>The method comprises the steps of carrying out a first treatment on the surface of the When detecting +.>When the speed is less than or equal to 5A/s, the second-stage fuzzy controller takes effect and controls in real timeThen->. When the second-stage fuzzy controller is in effect, the current battery capacity of the power battery is +.>Calculating output current change of hydrogen fuel cell from current time to next time。
The purpose of the two-stage series fuzzy controller is to control the output value of the current, so that the current is stabilized in a reasonable interval and the overdischarge of the fuel cell system is not caused; the particle swarm optimization is to optimize the economical efficiency of the vehicle on the basis that the current is in a reasonable interval, so that the driving mileage of the vehicle is maximized. The application of the series fuzzy controller in the application ensures that the output value of the current is stable and optimal.
According to the technical scheme, the energy management method for the power battery assisted hydrogen fuel cell automobile system provided by the embodiment of the application is characterized in that a hybrid power system model is built based on the hydrogen fuel cell system and the power cell system, and the current demand of the whole automobile is acquired according to input parameters based on the hybrid power modelI_reqOutput current of hydrogen fuel cell by series fuzzy controlI_fcAnd performing real-time dynamic regulation and control to ensure the stability of the hydrogen fuel cell system, and optimizing membership functions and fuzzy rule weights of fuzzy control by using a particle swarm optimization algorithm with mileage as a target so as to ensure the running economy of the vehicle. The application reduces the variation of output power of the hydrogen fuel cell during operationThe durability of the hydrogen fuel cell is improved due to the rate and the frequent start-stop phenomenon, the service lives of the hydrogen fuel cell and the power cell are prolonged, and the running economy of the vehicle is also improved.
The above description is only of the preferred embodiments of the present application and the description of the technical principles applied is not intended to limit the scope of the application as claimed, but merely represents the preferred embodiments of the present application. It will be appreciated by persons skilled in the art that the scope of the application referred to in the present application is not limited to the specific combinations of the technical features described above, but also covers other technical features formed by any combination of the technical features described above or their equivalents without departing from the inventive concept. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application.
Claims (8)
1. A method of power cell assisted hydrogen fuel cell automotive system energy management, the method comprising the steps of:
acquiring preset parameters, completing component model selection of the hybrid power system model according to the preset parameters, and constructing a hybrid power system model of the hydrogen fuel cell automobile assisted by the power cell;
and for the hybrid power system model, a two-stage serial fuzzy controller is adopted to realize load-changing limitation and control of the hydrogen fuel cell system, and a particle swarm algorithm is utilized to optimize membership functions and fuzzy rule weights of the two-stage serial fuzzy controller, so that energy management is realized.
2. The energy management method of a hydrogen fuel cell vehicle system according to claim 1, characterized in that said realizing energy management specifically comprises:
step S2, a series fuzzy controller comprising a first-stage fuzzy controller and a second-stage fuzzy controller outputs a control signal to the hybrid power system;
step S3, the hybrid power system outputs mileage information to the particle swarm optimization algorithm module;
step S4, the particle swarm optimization algorithm module sets the driving mileage as an objective function, calculates and searches the maximum value of the driving mileage; if not, optimizing the membership function and the fuzzy rule weight of the series fuzzy controller, updating the optimized membership value to the fuzzy controller, and returning to the step S2; if the maximum value of the driving mileage is found, the step S5 is entered;
and S5, outputting the maximum driving mileage, and simultaneously adopting the membership function and fuzzy rule weight of the serial fuzzy controller at the moment to output the corresponding hydrogen fuel cell current.
3. The method for energy management of a hydrogen fuel cell vehicle system according to claim 2, wherein in step S5, the membership function and fuzzy rule weight of the serial fuzzy controller are used to output the corresponding hydrogen fuel cell current, and specifically comprising:
with two-stage control, when detecting the output current of the first-stage fuzzy controllerRate of change of 1->When the current is more than 5A/s, the output current of the hydrogen fuel cell system at the current moment is +.>Output current of hydrogen fuel cell system at next momentThe method comprises the steps of carrying out a first treatment on the surface of the When detecting the +.>1 rate of change->When the speed is less than or equal to 5A/s, the second-stage fuzzy controller is effective, and the second-stage fuzzy controller passes throughThree input parameters, calculate the variation value of output current of hydrogen fuel cell from present moment to next moment +.>The method comprises the steps of carrying out a first treatment on the surface of the Output current of hydrogen fuel cell system at next moment。
4. The method of claim 1, wherein the predetermined parameters include a vehicle parameter, a driving motor parameter, a power cell parameter, and a hydrogen fuel cell parameter.
5. The hydrogen fuel cell automotive system energy management method of claim 4, wherein the hydrogen fuel cell parameters include: maximum current of the hydrogen fuel cell system, rated voltage of the hydrogen fuel cell system, and rated power.
6. The hydrogen fuel cell automotive system energy management method of claim 4, wherein the power cell parameters include: peak power, rated power, maximum rotational speed, rated rotational speed, and peak torque of the motor.
7. The energy management method of a hydrogen fuel cell vehicle system according to claim 1, wherein the two-stage fuzzy controllers are a first-stage fuzzy controller and a second-stage fuzzy controller, respectively, and the motor is required to be powered by the current after the two-stage fuzzy controllers are connected in seriesAnd the current battery capacity of the power battery +.>As an input parameter of the first-stage fuzzy controller, the output current of the first-stage fuzzy controller is +.>The method comprises the steps of carrying out a first treatment on the surface of the Three input parameters of the second-stage fuzzy controller are respectively the output current of the first-stage fuzzy controller +.>Current battery power of power battery +.>A variation value of the motor demand current +.>The method comprises the steps of carrying out a first treatment on the surface of the The output result of the second-stage fuzzy controller is the variation value of the output current of the hydrogen fuel cell system +.>。
8. The energy management method of a hydrogen fuel cell vehicle system according to any one of claims 1 to 7, wherein the particle swarm algorithm uses mileage as an objective function, and each iteration judges whether a maximum value of the mileage is found; if the maximum value is found, ending iteration, and calculating a two-stage serial fuzzy controller by using the current membership function and the fuzzy rule weight; if not, continuing iteration, and updating the membership function and the fuzzy rule weight of the two-stage serial fuzzy controller.
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