CN117124933A - Fuel cell energy control method, device, vehicle and storage medium - Google Patents
Fuel cell energy control method, device, vehicle and storage medium Download PDFInfo
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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
- B60L58/30—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling fuel cells
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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
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Abstract
The application discloses a fuel cell energy control method, a device, a vehicle and a storage medium, comprising the following steps: acquiring working condition data of the fuel cell at the current time, inputting the working condition data into a pre-trained fuel cell aging model, and determining the voltage attenuation amplitude of the fuel cell according to the model output result; acquiring the state of charge of a power battery in a vehicle, and constructing a cost function corresponding to the fuel battery at the current moment according to the state of charge, the voltage attenuation amplitude, the allocated power corresponding to the fuel battery and the power response rate; and solving the cost function according to a preset constraint condition to obtain a corresponding target management strategy of the fuel cell at the current moment, and controlling the fuel cell to work according to the target management strategy. The technical scheme of the embodiment of the application can avoid frequent and large-scale load change of the fuel cell, improve the durability of the fuel cell and prolong the service life of the fuel cell.
Description
Technical Field
The present application relates to the field of automotive technologies, and in particular, to a method and apparatus for controlling energy of a fuel cell, a vehicle, and a storage medium.
Background
The fuel cell has the advantages of less greenhouse gas emission, high energy conversion efficiency and the like, and is generally used on the whole vehicle together with the power cell as a hybrid power source.
The durability and the reliability of the current power battery are fully improved, however, the vehicle-mounted fuel battery engine is aged by environmental factors, components, component control and the like during operation, so that the vehicle-mounted fuel battery engine is aged to different degrees, and the operation reliability of the whole vehicle is affected. Therefore, it is desirable to avoid rapid degradation of the fuel cell when making a complete vehicle energy management strategy. Based on the above, the power of the fuel cell and the power cell needs to be reasonably distributed, so that the frequent load-changing start-stop of the fuel cell is avoided, and the fuel cell is ensured to be in a healthy working state.
However, most of the existing energy management strategies are to set a power battery state of charge interval to ensure reasonable use of the power battery, and the durability of the fuel battery is not optimized yet.
Disclosure of Invention
The application provides a fuel cell energy control method, a device, a vehicle and a storage medium, which can avoid frequent and large-scale load change of a fuel cell, improve the durability of the fuel cell and prolong the service life of the fuel cell.
In a first aspect, an embodiment of the present application provides a fuel cell energy control method, applied to a vehicle, including:
acquiring working condition data of the fuel cell at the current time, inputting the working condition data into a pre-trained fuel cell aging model, and determining the voltage attenuation amplitude of the fuel cell according to the output result of the model;
the fuel cell aging model is obtained through training historical operation data corresponding to the fuel cell;
acquiring an electric quantity state of a power battery in the vehicle, and constructing a cost function corresponding to the fuel battery at the current moment according to the electric quantity state, the voltage attenuation amplitude, the distributed power corresponding to the fuel battery and the power response rate;
and solving the cost function according to a preset constraint condition to obtain a corresponding target management strategy of the fuel cell at the current moment, and controlling the fuel cell to work according to the target management strategy.
In a second aspect, an embodiment of the present application further provides a fuel cell energy control device, applied to a vehicle, including:
the model input module is used for acquiring working condition data of the fuel cell at the current moment, inputting the working condition data into a pre-trained fuel cell aging model, and determining the voltage attenuation amplitude of the fuel cell according to the output result of the model;
the fuel cell aging model is obtained through training historical operation data corresponding to the fuel cell;
the cost function construction module is used for acquiring the electric quantity state of the power battery in the vehicle and constructing a cost function corresponding to the fuel battery at the current moment according to the electric quantity state, the voltage attenuation amplitude, the distributed power corresponding to the fuel battery and the power response rate;
and the management strategy determining module is used for solving the cost function according to preset constraint conditions to obtain a target management strategy corresponding to the fuel cell at the current moment, and controlling the fuel cell to work according to the target management strategy.
In a third aspect, an embodiment of the present application further provides a vehicle, including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the fuel cell energy control method provided by any one of the embodiments of the present application.
In a fourth aspect, embodiments of the present application further provide a computer readable storage medium storing computer instructions for causing a processor to execute the method for controlling energy of a fuel cell according to any one of the embodiments of the present application.
According to the technical scheme provided by the embodiment of the application, the working condition data of the fuel cell at the current moment is obtained, the working condition data is input into a pre-trained fuel cell aging model, the voltage attenuation amplitude of the fuel cell is determined according to the output result of the model, the electric quantity state of the power cell in the vehicle is obtained, the cost function corresponding to the fuel cell at the current moment is constructed according to the electric quantity state, the voltage attenuation amplitude, the distribution power corresponding to the fuel cell and the power response rate, the cost function is solved according to the preset constraint condition, the corresponding target management strategy of the fuel cell at the current moment is obtained, and the fuel cell is controlled to work according to the target management strategy.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the application or to delineate the scope of the application. Other features of the present application will become apparent from the description that follows.
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 skilled in the art.
Fig. 1 is a flowchart of a fuel cell energy control method according to a first embodiment of the present application;
fig. 2 is a flowchart of another fuel cell energy control method according to the second embodiment of the present application;
fig. 3 is a flowchart of another fuel cell energy control method provided according to a third embodiment of the present application;
fig. 4 is a schematic structural view of a fuel cell power control apparatus according to a fourth embodiment of the present application;
fig. 5 is a schematic structural diagram of a vehicle according to a fifth embodiment of the present application.
Detailed Description
In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
Fig. 1 is a flowchart of a fuel cell energy control method according to an embodiment of the present application, which is applicable to a case of controlling energy of a fuel cell in a vehicle, and the method may be performed by a fuel cell energy control device, which may be implemented in hardware and/or software, and the fuel cell energy control device may be configured in the vehicle.
As shown in fig. 1, a fuel cell energy control method disclosed in the present embodiment includes:
s110, working condition data of the fuel cell at the current moment are obtained, the working condition data are input into a pre-trained fuel cell aging model, and the voltage attenuation amplitude of the fuel cell is determined according to the output result of the model.
In this embodiment, the fuel cell aging model is obtained through training of historical operation data corresponding to the fuel cell. Specifically, the working condition data of the fuel cell, such as theoretical current, air flow, stack inlet pressure, cooling water stack inlet temperature, etc. of the fuel cell at the current moment can be determined according to the power requirement of the fuel cell, then the working condition data are input into a fuel cell aging model, the voltage variation trend of the fuel cell under the whole vehicle cycle is predicted according to the working condition data by the fuel cell aging model, and the attenuation range of the predicted voltage of the fuel cell compared with the initial voltage is calculated according to the voltage variation trend
In a specific embodiment, the voltage decay magnitude can be calculated by the following formula
Wherein lambda is I For the preset conversion coefficient of the voltage attenuation amplitude under different currents and rated currents, U (0) is the initial voltage of the fuel cell under the corresponding current, and U (N) is the predicted voltage of the fuel cell under the corresponding current.
S120, acquiring the state of charge of a power battery in the vehicle, and constructing a cost function corresponding to the fuel battery at the current moment according to the state of charge, the voltage attenuation amplitude, the allocated power corresponding to the fuel battery and the power response rate.
In the present embodiment, the State Of Charge (SOC) Of the power battery in the vehicle may be obtained, and then the voltage drop amplitude Of the fuel cell is determined based on the SOC Of the power batteryDistributed power P corresponding to fuel cell FC Power response rate Δp FC And constructing a cost function corresponding to the fuel cell at the current moment. The objective of the cost function is to ensure that the electric quantity state of the power battery in the whole vehicle circulation working condition is within a preset range while optimizing the whole vehicle economy of the fuel battery and the service life of the fuel battery.
And S130, solving the cost function according to a preset constraint condition to obtain a corresponding target management strategy of the fuel cell at the current moment, and controlling the fuel cell to work according to the target management strategy.
In this embodiment, by solving the cost function, a target management policy corresponding to the fuel cell at the current moment may be obtained, where the target management policy includes an optimal allocated power P corresponding to the fuel cell FC Optimal power response rate Δp FC Then according to the optimal distribution power P FC Optimal power response rate Δp FC Controlling the operation of the fuel cell.
According to the technical scheme, working condition data of the fuel cell at the current moment are acquired, the working condition data are input into a pre-trained fuel cell aging model, the voltage attenuation amplitude of the fuel cell is determined according to the output result of the model, the electric quantity state of the power cell in the vehicle is acquired, a cost function corresponding to the fuel cell at the current moment is constructed according to the electric quantity state, the voltage attenuation amplitude, the distribution power corresponding to the fuel cell and the power response rate, the cost function is solved according to preset constraint conditions, a target management strategy corresponding to the fuel cell at the current moment is obtained, and the fuel cell is controlled to work according to the target management strategy.
Example two
Fig. 2 is a flowchart of another fuel cell energy control method according to a second embodiment of the present application, which is based on further optimization and expansion of the above embodiments and can be combined with various alternative solutions in the above embodiments.
As shown in fig. 2, another fuel cell energy control method disclosed in this embodiment includes:
s210, working condition data of the fuel cell at the current moment are obtained, the working condition data are input into a pre-trained fuel cell aging model, and the voltage attenuation amplitude of the fuel cell is determined according to the output result of the model.
S220, acquiring the state of charge of a power battery in the vehicle, and taking the state of charge of the power battery as the state quantity of the whole vehicle power system at the current moment.
In this embodiment, the state of charge SOC of the power battery may be used as the state quantity x (k) of the entire vehicle power system at the current time, and the specific expression is as follows:
x(k)＝SOC
and S230, taking the distributed power and the power response rate corresponding to the fuel cell as control variables of the whole vehicle power system at the current moment.
In the present embodiment, the fuel can be electrically chargedPool-corresponding allocated power P FC Power response rate Δp FC As a control variable u (k) of the whole vehicle power system at the current time, the specific expression is as follows:
u(k)＝(P FC ,ΔP FC )
s240, constructing a cost function corresponding to the fuel cell at the current moment according to the state quantity, the control variable and the voltage attenuation amplitude, solving the cost function according to a preset constraint condition to obtain a target management strategy corresponding to the fuel cell at the current moment, and controlling the fuel cell to work according to the target management strategy.
In the present embodiment, in particular, the state quantity x (k), the control variable u (k), and the voltage attenuation amplitude can be usedAnd constructing a cost function J corresponding to the fuel cell at the current moment, and then calculating the cost function J to obtain an optimal solution (namely a target management strategy) corresponding to the control variable u (k).
In one implementation manner of this embodiment, solving the cost function according to a preset constraint condition, to obtain a target management policy corresponding to the fuel cell at the current moment, and controlling the fuel cell to work according to the target management policy, where the method includes: solving the cost function according to a preset constraint condition to obtain a target distribution power and a target power response rate corresponding to the fuel cell at the current moment; and controlling the fuel cell to work according to the target distributed power and the target power response rate.
S250, acquiring a preset state transition matrix, and determining the state quantity of the whole vehicle power system at the next moment according to the state quantity, the control variable and the state transition matrix of the whole vehicle power system at the current moment.
In this embodiment, the whole vehicle power system may be discretized into a time dynamic system, and the corresponding state transition matrix may be represented by the following formula:
x(k+1)＝f(x(k),u(k))k＝1,2,.....,N
where x (k) is a state quantity of the whole vehicle power system at the time of k, u (k) is a control variable at the time of k, and x (k+1) is a state quantity at the time of k+1.
And S260, constructing a cost function corresponding to the fuel cell at the next moment according to the state quantity and the control variable of the whole vehicle power system at the next moment and the voltage attenuation amplitude of the fuel cell at the next moment, and solving the cost function corresponding to the next moment to obtain a management strategy corresponding to the fuel cell at the next moment.
In the present embodiment, the management policy corresponding to the fuel cell at the next time may be determined in the same manner as described above.
According to the technical scheme, the working condition data of the fuel cell at the current moment is acquired, the working condition data is input into the fuel cell aging model to obtain the voltage attenuation amplitude, the electric quantity state of the power cell is used as the state quantity of the whole vehicle power system at the current moment, the distribution power and the power response rate corresponding to the fuel cell are used as control variables, the cost function corresponding to the fuel cell at the current moment is constructed according to the state quantity, the control variables and the voltage attenuation amplitude, the cost function is solved according to preset constraint conditions to obtain a target management strategy, the fuel cell is controlled to work according to the target management strategy, the state quantity of the whole vehicle power system at the next moment is determined according to the state quantity, the control variables and the state transition matrix of the whole vehicle power system at the current moment, the cost function corresponding to the fuel cell at the next moment is constructed according to the state quantity, the control variables and the voltage attenuation amplitude of the fuel cell at the next moment, and the technical means for solving the cost function corresponding to the next moment to obtain the management strategy at the next moment are achieved, frequent and large load changes of the fuel cell can be avoided, the durability of the fuel cell is prolonged, and the service life of the fuel cell is prolonged.
Example III
Fig. 3 is a flowchart of another fuel cell energy control method according to a third embodiment of the present application, which is based on further optimization and expansion of the above embodiments and can be combined with various alternative solutions in the above embodiments.
As shown in fig. 3, another fuel cell energy control method disclosed in this embodiment includes:
s310, working condition data of the fuel cell at the current moment is obtained, the working condition data are input into a pre-trained fuel cell aging model, and the voltage attenuation amplitude of the fuel cell is determined according to the output result of the model.
In one implementation manner of the embodiment, before acquiring the working condition data corresponding to the fuel cell at the current moment and inputting the working condition data into the pre-trained fuel cell aging model, the method further includes: acquiring a plurality of historical operation data corresponding to a fuel cell, and dividing the historical operation data into a training set and a testing set; and performing iterative training on the long-term and short-term memory network model by using the training set and the testing set to obtain the fuel cell aging model.
In a specific embodiment, a plurality of historical operating data corresponding to the fuel cell may be obtained, including air flow, air in-stack pressure, cooling water in-stack temperature, fuel cell current, fuel cell voltage, etc., and then 80% of all the historical operating data may be used as a training set, and the remaining 20% may be used as a test set.
In a specific model training process, a training set can be input into a Long Short-Term Memory (LSTM) model, and then the accuracy of the trained model is verified by using the test set. And if the error between the voltage data and the standard voltage data in the prediction result of the model meets the preset numerical condition, the model is considered to meet the training requirement. Otherwise, if the error does not meet the preset numerical condition, retraining the model is needed until the requirement is met.
S320, determining a hydrogen consumption penalty function corresponding to the fuel cell according to the hydrogen low heating value, the distribution power and the power response rate corresponding to the fuel cell.
In a specific embodiment, the hydrogen consumption penalty functionThe expression can be represented by the following formula:
wherein eta FC For fuel cell efficiency, q H2 The low heating value of the hydrogen corresponding to the fuel cell.
S330, determining a state of charge penalty function corresponding to the power battery according to the state of charge penalty coefficient, the battery capacity and the current corresponding to the power battery.
In a specific embodiment, the state of charge penalty function L SOC (k) The expression can be represented by the following formula:
wherein k is P And k I Respectively corresponding electric quantity state punishment coefficients of the power battery, Q bat For battery capacity, I bat Is the current of the power battery.
And S340, determining an aging penalty function corresponding to the fuel cell according to the voltage attenuation amplitude, and constructing a cost function corresponding to the fuel cell at the current moment according to the hydrogen consumption penalty function, the electric quantity state penalty function and the aging penalty function.
In a specific embodiment, the fuel cell aging penalty function L aging (k) The expression can be represented by the following formula:
determining hydrogen consumption penalty function by the above stepsElectric quantity state punishment function L SOC (k) Ageing penalty function L aging (k) The instantaneous indicator function L (x (k), u (k)) can then be calculated by the following formula:
wherein, alpha and beta are preset weight factors respectively.
In one implementation of this embodiment, the cost function J corresponding to the fuel cell at the current moment may be constructed according to the above-mentioned instantaneous indicator function L (x (k), u (k)) by the following formula:
wherein, gamma k Is a function convergence factor.
And S350, solving the cost function according to a preset constraint condition to obtain a corresponding target management strategy of the fuel cell at the current moment, and controlling the fuel cell to work according to the target management strategy.
In a specific embodiment, the constraint may be expressed as follows:
according to the technical scheme, the working condition data of the fuel cell at the current moment is acquired, the working condition data is input into the fuel cell aging model, the voltage attenuation amplitude of the fuel cell is determined according to the output result of the model, the hydrogen consumption penalty function corresponding to the fuel cell is determined according to the low heat value, the distribution power and the power response rate of the hydrogen corresponding to the fuel cell, the electric quantity state penalty function corresponding to the power cell is determined according to the electric quantity state penalty coefficient, the battery capacity and the current corresponding to the power cell, the aging penalty function corresponding to the fuel cell is determined according to the voltage attenuation amplitude, the cost function corresponding to the fuel cell at the current moment is constructed according to the hydrogen consumption penalty function, the electric quantity state penalty function and the aging penalty function, the target management strategy corresponding to the fuel cell at the current moment is obtained according to the preset constraint condition, the fuel cell is controlled according to the target management strategy, frequent and large-amplitude load variation of the fuel cell can be avoided, the durability of the fuel cell is improved, and the service life of the fuel cell is prolonged.
Example IV
Fig. 4 is a schematic structural diagram of a fuel cell energy control device according to a fourth embodiment of the present application, where the present embodiment is applicable to controlling the energy control of an autopilot fuel cell, and the fuel cell energy control device may be implemented in hardware and/or software and may be configured in a vehicle.
As shown in fig. 4, the fuel cell energy control device disclosed in the present embodiment includes:
the model input module 410 is configured to obtain working condition data of the fuel cell at a current time, input the working condition data into a pre-trained fuel cell aging model, and determine a voltage attenuation amplitude of the fuel cell according to an output result of the model;
the fuel cell aging model is obtained through training historical operation data corresponding to the fuel cell;
the cost function construction module 420 is configured to obtain an electric quantity state of a power battery in the vehicle, and construct a cost function corresponding to the fuel battery at a current moment according to the electric quantity state, a voltage attenuation amplitude, a distributed power corresponding to the fuel battery, and a power response rate;
the management policy determining module 430 is configured to solve the cost function according to a preset constraint condition, obtain a target management policy corresponding to the fuel cell at the current moment, and control the fuel cell to work according to the target management policy.
According to the technical scheme, working condition data of the fuel cell at the current moment are acquired, the working condition data are input into a pre-trained fuel cell aging model, the voltage attenuation amplitude of the fuel cell is determined according to the output result of the model, the electric quantity state of the power cell in the vehicle is acquired, a cost function corresponding to the fuel cell at the current moment is constructed according to the electric quantity state, the voltage attenuation amplitude, the distribution power corresponding to the fuel cell and the power response rate, the cost function is solved according to preset constraint conditions, a target management strategy corresponding to the fuel cell at the current moment is obtained, and the fuel cell is controlled to work according to the target management strategy.
On the basis of the above embodiment, optionally, the apparatus further includes:
the follow-up control module is used for acquiring a preset state transition matrix after controlling the fuel cell to work according to the target management strategy, and determining the state quantity of the whole vehicle power system at the next moment according to the state quantity, the control variable and the state transition matrix of the whole vehicle power system at the current moment; constructing a cost function corresponding to the fuel cell at the next moment according to the state quantity and the control variable of the whole vehicle power system at the next moment and the voltage attenuation amplitude of the fuel cell at the next moment; solving the cost function corresponding to the next moment to obtain a management strategy corresponding to the fuel cell at the next moment;
the model training module is used for acquiring a plurality of historical operation data corresponding to the fuel cell and dividing the historical operation data into a training set and a testing set; and performing iterative training on the long-term and short-term memory network model by using the training set and the testing set to obtain the fuel cell aging model.
The cost function construction module 420 includes:
the state quantity determining unit is used for taking the electric quantity state of the power battery as the state quantity of the whole vehicle power system at the current moment;
the variable determining unit is used for taking the distributed power and the power response rate corresponding to the fuel cell as control variables of the whole vehicle power system at the current moment;
the function determining unit is used for constructing a cost function corresponding to the fuel cell at the current moment according to the state quantity, the control variable and the voltage attenuation amplitude;
the penalty function determining unit is used for determining a hydrogen consumption penalty function corresponding to the fuel cell according to the hydrogen low heat value, the distributed power and the power response rate corresponding to the fuel cell; determining a state of charge penalty function corresponding to the power battery according to the state of charge penalty coefficient, the battery capacity and the current corresponding to the power battery; determining an aging penalty function corresponding to the fuel cell according to the voltage decay amplitude;
and the punishment function processing unit is used for constructing a cost function corresponding to the fuel cell at the current moment according to the hydrogen consumption punishment function, the electric quantity state punishment function and the ageing punishment function.
The management policy determination module 430 includes:
the target power determining unit is used for solving the cost function according to a preset constraint condition to obtain target distribution power and target power response rate corresponding to the fuel cell at the current moment;
and the control unit is used for controlling the fuel cell to work according to the target distributed power and the target power response rate.
The fuel cell energy control device provided by the embodiment of the application can execute the fuel cell energy control method provided by any embodiment of the application, and has the corresponding functional modules and beneficial effects of the execution method. Reference is made to the description of any method embodiment of the application for details not described in this embodiment.
Example five
Fig. 5 shows a schematic structural diagram of a vehicle 10 that may be used to implement an embodiment of the present application. As shown in fig. 5, the vehicle 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the vehicle 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
Various components in the vehicle 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the vehicle 10 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunications networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as a fuel cell energy control method.
In some embodiments, the fuel cell power control method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the vehicle 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the fuel cell power control method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the fuel cell energy control method in any other suitable manner (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present application, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a vehicle having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or a trackball) by which a user can provide input to the vehicle. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present application may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present application are achieved, and the present application is not limited herein.
The above embodiments do not limit the scope of the present application. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the scope of the present application.
Claims (10)
1. A fuel cell energy control method, characterized by being applied to a vehicle, comprising:
acquiring working condition data of the fuel cell at the current time, inputting the working condition data into a pre-trained fuel cell aging model, and determining the voltage attenuation amplitude of the fuel cell according to the output result of the model;
the fuel cell aging model is obtained through training historical operation data corresponding to the fuel cell;
acquiring an electric quantity state of a power battery in the vehicle, and constructing a cost function corresponding to the fuel battery at the current moment according to the electric quantity state, the voltage attenuation amplitude, the distributed power corresponding to the fuel battery and the power response rate;
and solving the cost function according to a preset constraint condition to obtain a corresponding target management strategy of the fuel cell at the current moment, and controlling the fuel cell to work according to the target management strategy.
2. The method of claim 1, wherein constructing a cost function for the fuel cell at the current time based on the state of charge, the voltage decay magnitude, the allocated power for the fuel cell, and the power response rate, comprises:
taking the state of electric quantity of the power battery as the state quantity of the whole vehicle power system at the current moment;
taking the distributed power and the power response rate corresponding to the fuel cell as control variables of the whole vehicle power system at the current moment;
and constructing a cost function corresponding to the fuel cell at the current moment according to the state quantity, the control variable and the voltage attenuation amplitude.
3. The method of claim 2, further comprising, after controlling the fuel cell to operate in accordance with the target management strategy:
acquiring a preset state transition matrix, and determining the state quantity of the whole vehicle power system at the next moment according to the state quantity, the control variable and the state transition matrix of the whole vehicle power system at the current moment;
constructing a cost function corresponding to the fuel cell at the next moment according to the state quantity and the control variable of the whole vehicle power system at the next moment and the voltage attenuation amplitude of the fuel cell at the next moment;
and solving the cost function corresponding to the next moment to obtain a management strategy corresponding to the fuel cell at the next moment.
4. The method of claim 2, wherein constructing a cost function for the fuel cell at a current time based on the state quantity, the control variable, and the voltage decay magnitude, comprises:
determining a hydrogen consumption penalty function corresponding to the fuel cell according to the low heat value, the distributed power and the power response rate of the hydrogen corresponding to the fuel cell;
determining a state of charge penalty function corresponding to the power battery according to the state of charge penalty coefficient, the battery capacity and the current corresponding to the power battery;
determining an aging penalty function corresponding to the fuel cell according to the voltage decay amplitude;
and constructing a cost function corresponding to the fuel cell at the current moment according to the hydrogen consumption penalty function, the electric quantity state penalty function and the aging penalty function.
5. The method of claim 1, wherein solving the cost function according to a preset constraint condition to obtain a target management policy corresponding to the fuel cell at a current moment, and controlling the fuel cell to operate according to the target management policy, comprises:
solving the cost function according to a preset constraint condition to obtain a target distribution power and a target power response rate corresponding to the fuel cell at the current moment;
and controlling the fuel cell to work according to the target distributed power and the target power response rate.
6. The method of claim 1, further comprising, prior to obtaining operating condition data for the fuel cell at the current time and inputting the operating condition data to the pre-trained fuel cell aging model:
acquiring a plurality of historical operation data corresponding to a fuel cell, and dividing the historical operation data into a training set and a testing set;
and performing iterative training on the long-term and short-term memory network model by using the training set and the testing set to obtain the fuel cell aging model.
7. A fuel cell energy control apparatus, characterized by being applied to a vehicle, comprising:
the model input module is used for acquiring working condition data of the fuel cell at the current moment, inputting the working condition data into a pre-trained fuel cell aging model, and determining the voltage attenuation amplitude of the fuel cell according to the output result of the model;
the fuel cell aging model is obtained through training historical operation data corresponding to the fuel cell;
the cost function construction module is used for acquiring the electric quantity state of the power battery in the vehicle and constructing a cost function corresponding to the fuel battery at the current moment according to the electric quantity state, the voltage attenuation amplitude, the distributed power corresponding to the fuel battery and the power response rate;
and the management strategy determining module is used for solving the cost function according to preset constraint conditions to obtain a target management strategy corresponding to the fuel cell at the current moment, and controlling the fuel cell to work according to the target management strategy.
8. The apparatus of claim 7, wherein the cost function construction module comprises:
the state quantity determining unit is used for taking the electric quantity state of the power battery as the state quantity of the whole vehicle power system at the current moment;
the variable determining unit is used for taking the distributed power and the power response rate corresponding to the fuel cell as control variables of the whole vehicle power system at the current moment;
and the function determining unit is used for constructing a cost function corresponding to the fuel cell at the current moment according to the state quantity, the control variable and the voltage attenuation amplitude.
9. A vehicle, characterized in that the vehicle comprises:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the fuel cell energy control method of any one of claims 1-6.
10. A computer readable storage medium storing computer instructions for causing a processor to execute the fuel cell energy control method according to any one of claims 1 to 6.
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| CN202311153014.2A CN117124933A (en) | 2023-09-07 | 2023-09-07 | Fuel cell energy control method, device, vehicle and storage medium |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311153014.2A CN117124933A (en) | 2023-09-07 | 2023-09-07 | Fuel cell energy control method, device, vehicle and storage medium |
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| CN202311153014.2A Pending CN117124933A (en) | 2023-09-07 | 2023-09-07 | Fuel cell energy control method, device, vehicle and storage medium |
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