A fuel cell energy control method, device, vehicle and storage medium

Abstract

The application discloses a fuel cell energy control method and device, a vehicle and a storage medium, and comprises the following steps: obtaining working condition data of a fuel cell at a current time, inputting the working condition data into a pre-trained fuel cell aging model, and determining a voltage attenuation amplitude of the fuel cell according to a model output result; obtaining a state of charge of a power battery in the vehicle, constructing a corresponding cost function of the fuel cell at the current time according to the state of charge, the voltage attenuation amplitude, a corresponding distribution power of the fuel cell and a power response rate; solving the cost function according to a preset constraint condition, obtaining a corresponding target management strategy of the fuel cell at the current time, 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 amplitude load changes of the fuel cell, improve the durability of the fuel cell, and prolong the service life of the fuel cell.

Description

Technical Field

[0001] This invention relates to the field of automotive technology, and in particular to a fuel cell energy control method, device, vehicle, and storage medium. Background Technology

[0002] Fuel cells have advantages such as low greenhouse gas emissions and high energy conversion efficiency, and are usually used in vehicles as a hybrid power source together with power batteries.

[0003] While the durability and reliability of current power batteries have been significantly improved, on-board fuel cell engines are subject to varying degrees of aging due to environmental factors, component aging, and control issues, affecting the overall reliability of the vehicle. Therefore, it is crucial to prevent rapid aging of the fuel cell when developing a vehicle energy management strategy. Based on this, it is necessary to rationally allocate the power between the fuel cell and the power battery, avoiding frequent load changes and start-stop cycles to ensure the fuel cell remains in a healthy operating state.

[0004] However, most existing energy management strategies ensure the rational use of power batteries by setting power battery state ranges, but have not yet optimized the durability of fuel cells. Summary of the Invention

[0005] This invention provides a fuel cell energy control method, device, vehicle, and storage medium, which can avoid frequent and significant load changes in fuel cells, improve fuel cell durability, and extend fuel cell service life.

[0006] In a first aspect, embodiments of the present invention provide a fuel cell energy control method, applied to a vehicle, comprising:

[0007] The operating condition data of the fuel cell at the current moment is obtained, the operating condition data is input into a pre-trained fuel cell aging model, and the voltage decay rate of the fuel cell is determined based on the output of the model.

[0008] The fuel cell aging model is obtained by training the historical operating data of the fuel cell.

[0009] Obtain the state of charge of the power battery in the vehicle, and construct the cost function of the fuel cell at the current moment based on the state of charge, voltage decay rate, power distribution of the fuel cell, and power response rate.

[0010] The cost function is solved according to the preset constraints to obtain the target management strategy corresponding to the fuel cell at the current time, and the fuel cell is controlled to work according to the target management strategy.

[0011] Secondly, embodiments of the present invention also provide a fuel cell energy control device, applied to a vehicle, comprising:

[0012] The model input module is used to acquire the operating condition data of the fuel cell at the current moment, input the operating condition data into the pre-trained fuel cell aging model, and determine the voltage decay rate of the fuel cell based on the output of the model.

[0013] The fuel cell aging model is obtained by training the historical operating data of the fuel cell.

[0014] The cost function construction module is used to obtain the state of charge of the power battery in the vehicle, and construct the cost function of the fuel cell at the current moment based on the state of charge, voltage decay rate, the power distribution of the fuel cell, and the power response rate.

[0015] The management strategy determination module is used to solve the cost function according to preset constraints to obtain the target management strategy corresponding to the fuel cell at the current time, and control the fuel cell to work according to the target management strategy.

[0016] Thirdly, embodiments of the present invention also provide a vehicle, the vehicle comprising:

[0017] At least one processor; and

[0018] A memory that is communicatively connected to at least one processor; wherein,

[0019] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to perform the fuel cell energy control method provided in any embodiment of the present invention.

[0020] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the fuel cell energy control method provided in any embodiment of the present invention.

[0021] The technical solution provided by this invention obtains the operating condition data of the fuel cell at the current moment, inputs the operating condition data into a pre-trained fuel cell aging model, determines the voltage decay amplitude of the fuel cell based on the output of the model, obtains the state of charge of the power battery in the vehicle, constructs a cost function corresponding to the fuel cell at the current moment based on the state of charge, voltage decay amplitude, the allocated power of the fuel cell, and the power response rate, solves the cost function according to preset constraints, obtains the target management strategy corresponding to the fuel cell at the current moment, and controls the fuel cell to work according to the target management strategy. This proposes an effective way to control the energy of the fuel cell, which can avoid frequent and large-scale load changes of the fuel cell, improve the durability of the fuel cell, and extend the service life of the fuel cell.

[0022] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a flowchart of a fuel cell energy control method provided in Embodiment 1 of the present invention;

[0025] Figure 2 This is a flowchart of another fuel cell energy control method provided in Embodiment 2 of the present invention;

[0026] Figure 3 This is a flowchart of another fuel cell energy control method provided in Embodiment 3 of the present invention;

[0027] Figure 4 This is a schematic diagram of the structure of a fuel cell energy control device according to Embodiment 4 of the present invention;

[0028] Figure 5 This is a structural schematic diagram of a vehicle provided in Embodiment 5 of the present invention. Detailed Implementation

[0029] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0031] Example 1

[0032] Figure 1 This is a flowchart of a fuel cell energy control method according to Embodiment 1 of the present invention. This embodiment is applicable to the situation of controlling the energy of a fuel cell in a vehicle. The method can be executed by a fuel cell energy control device, which can be implemented in hardware and / or software and can be configured in a vehicle.

[0033] like Figure 1 As shown, the fuel cell energy control method disclosed in this embodiment includes:

[0034] S110. Obtain the operating condition data of the fuel cell at the current moment, input the operating condition data into the pre-trained fuel cell aging model, and determine the voltage decay rate of the fuel cell based on the output of the model.

[0035] In this embodiment, the fuel cell aging model is trained using historical operating data corresponding to the fuel cell. Specifically, the operating condition data of the fuel cell can be determined based on its power requirements, such as the theoretical current, airflow, infeed pressure, and cooling water infeed temperature at the current moment. This operating condition data is then input into the fuel cell aging model. Based on the aforementioned operating condition data, the fuel cell aging model predicts the voltage change trend of the fuel cell under vehicle cycle conditions and calculates the rate of voltage decay of the predicted fuel cell voltage compared to the initial voltage based on this voltage change trend.

[0036] In a specific embodiment, the voltage attenuation magnitude can be calculated using the following formula.

[0037]

[0038] Where, λ I U(0) is the preset conversion factor for the voltage decay amplitude under different currents and rated currents, and U(N) is the initial voltage of the fuel cell under the corresponding current and the predicted voltage of the fuel cell under the corresponding current.

[0039] S120. Obtain the state of charge of the power battery in the vehicle, and construct the cost function corresponding to the fuel cell at the current moment based on the state of charge, voltage decay amplitude, power distribution of the fuel cell, and power response rate.

[0040] In this embodiment, the State of Charge (SOC) of the vehicle's power battery can be obtained, and then based on the SOC of the power battery and the voltage decay rate of the fuel cell... The power distribution P corresponding to the fuel cell FC and power response rate ΔP FC A cost function for the fuel cell at the current moment is constructed. The objective of this cost function is to optimize the fuel cell vehicle's economics and fuel cell lifespan while ensuring that the battery's state of charge remains within a preset range during the vehicle's operating cycle.

[0041] S130. Solve the cost function according to the preset constraints to obtain the target management strategy corresponding to the fuel cell at the current time, and control the fuel cell to work according to the target management strategy.

[0042] In this embodiment, by solving the cost function, the target management strategy corresponding to the fuel cell at the current moment can be obtained. The target management strategy includes the optimal power allocation P corresponding to the fuel cell. FC and the optimal power response rate ΔPFC Then, according to the optimal power allocation P FC and the optimal power response rate ΔP FC Control the operation of the fuel cell.

[0043] The technical solution of this embodiment obtains the operating condition data of the fuel cell at the current moment, inputs the operating condition data into a pre-trained fuel cell aging model, and determines the voltage decay amplitude of the fuel cell based on the output of the model. It also obtains the state of charge (SOC) of the power battery in the vehicle, constructs a cost function for the fuel cell at the current moment based on the SOC, voltage decay amplitude, the allocated power of the fuel cell, and the power response rate, solves the cost function according to preset constraints, obtains the target management strategy for the fuel cell at the current moment, and controls the fuel cell to operate according to the target management strategy. This proposes an effective way to control the energy of the fuel cell, which can avoid frequent and large-scale load changes, improve the durability of the fuel cell, and extend its service life.

[0044] Example 2

[0045] Figure 2 This is a flowchart of another fuel cell energy control method provided in Embodiment 2 of the present invention. This embodiment is a further optimization and extension based on the above embodiments and can be combined with various optional technical solutions in the above embodiments.

[0046] like Figure 2 As shown, another fuel cell energy control method disclosed in this embodiment includes:

[0047] S210. Obtain the operating condition data of the fuel cell at the current moment, input the operating condition data into the pre-trained fuel cell aging model, and determine the voltage decay rate of the fuel cell based on the output of the model.

[0048] S220. Obtain the state of charge of the power battery in the vehicle, and use the state of charge of the power battery as the state quantity of the vehicle power system at the current moment.

[0049] In this embodiment, the State of Charge (SOC) of the power battery can be used as the state variable x(k) of the vehicle's power system at the current moment, and the specific expression is as follows:

[0050] x(k)=SOC

[0051] S230. The power distribution and power response rate corresponding to the fuel cell are used as control variables of the vehicle power system at the current moment.

[0052] In this embodiment, the allocated power P corresponding to the fuel cell can be... FC and power response rate ΔP FC As the control variable u(k) of the vehicle's powertrain at the current moment, its specific expression is as follows:

[0053] u(k)=(P FC ,ΔP FC )

[0054] S240. Based on the state variables, control variables, and voltage decay amplitude, construct the cost function corresponding to the fuel cell at the current moment. Solve the cost function according to preset constraints to obtain the target management strategy corresponding to the fuel cell at the current moment, and control the fuel cell to work according to the target management strategy.

[0055] In this embodiment, specifically, the state variable x(k), the control variable u(k), and the voltage attenuation amplitude can be used as the basis. Construct the cost function J corresponding to the fuel cell at the current moment, and then calculate the cost function J to obtain the optimal solution (i.e., the target management strategy) corresponding to the control variable u(k).

[0056] In one embodiment of this example, the cost function is solved according to preset constraints to obtain the target management strategy corresponding to the fuel cell at the current moment, and the fuel cell is controlled to work according to the target management strategy. This includes: solving the cost function according to preset constraints to obtain the target allocated power and target power response rate of the fuel cell at the current moment; and controlling the fuel cell to work according to the target allocated power and target power response rate.

[0057] S250. Obtain a preset state transition matrix, and determine the state of the vehicle power system at the next moment based on the state variables, control variables, and state transition matrix of the vehicle power system at the current moment.

[0058] In this embodiment, the vehicle powertrain system can be discretized into a time-dynamic system, and the corresponding state transition matrix can be represented by the following formula:

[0059] x(k+1)=f(x(k),u(k))k=1,2,.....,N

[0060] Where x(k) is the state variable of the vehicle power system at time k, u(k) is the control variable at time k, and x(k+1) is the state variable at time k+1.

[0061] S260. Based on the state variables and control variables of the vehicle power system at the next moment, and the voltage decay amplitude of the fuel cell at the next moment, construct the cost function corresponding to the fuel cell at the next moment, solve the cost function corresponding to the next moment, and obtain the management strategy corresponding to the fuel cell at the next moment.

[0062] In this embodiment, the same method described above can be used to determine the management strategy for the fuel cell at the next moment.

[0063] The technical solution of this embodiment obtains the operating condition data of the fuel cell at the current moment, inputs the operating condition data into the fuel cell aging model to obtain the voltage decay rate, uses the state of charge of the power battery as the state variable of the vehicle power system at the current moment, and uses the distributed power and power response rate of the fuel cell as control variables. Based on the state variable, control variables, and voltage decay rate, a cost function corresponding to the fuel cell at the current moment is constructed. According to preset constraints, the cost function is solved to obtain the target management strategy, and the fuel cell is controlled to work according to the target management strategy. Based on the state variable, control variables, and state transition matrix of the vehicle power system at the current moment, the state variable of the vehicle power system at the next moment is determined. Based on the state variable, control variables, and voltage decay rate of the fuel cell at the next moment, a cost function corresponding to the fuel cell at the next moment is constructed. The management strategy for the next moment is obtained by solving the cost function corresponding to the next moment. This technical means can avoid frequent and large load changes of the fuel cell, improve the durability of the fuel cell, and extend the service life of the fuel cell.

[0064] Example 3

[0065] Figure 3 This is a flowchart of another fuel cell energy control method provided in Embodiment 3 of the present invention. This embodiment is a further optimization and extension based on the above embodiments and can be combined with various optional technical solutions in the above embodiments.

[0066] like Figure 3 As shown, another fuel cell energy control method disclosed in this embodiment includes:

[0067] S310. Obtain the operating condition data of the fuel cell at the current moment, input the operating condition data into the pre-trained fuel cell aging model, and determine the voltage decay rate of the fuel cell based on the output of the model.

[0068] In one embodiment of this example, before acquiring the operating condition data of the fuel cell at the current moment and inputting the operating condition data into the pre-trained fuel cell aging model, the method further includes: acquiring multiple historical operating data corresponding to the fuel cell, dividing the multiple historical operating data into a training set and a test set; using the training set and the test set to iteratively train the long short-term memory network model to obtain the fuel cell aging model.

[0069] In one specific embodiment, multiple historical operating data corresponding to the fuel cell can be obtained, including air flow rate, air inlet pressure, cooling water inlet temperature, fuel cell current, fuel cell voltage, etc. Then, 80% of the data in all historical operating data is used as the training set, and the remaining 20% ​​of the data is used as the test set.

[0070] In the specific model training process, the training set can be input into the Long Short-Term Memory (LSTM) network model, and then the test set can be used to verify the accuracy of the trained model. If the error between the voltage data and the standard voltage data in the model's prediction results meets the preset numerical condition, the model is considered to have met the training requirements. Conversely, if the error does not meet the preset numerical condition, the model needs to be retrained until it meets the requirements.

[0071] S320. Determine the hydrogen consumption penalty function corresponding to the fuel cell based on the hydrogen low calorific value, power distribution, and power response rate corresponding to the fuel cell.

[0072] In one specific embodiment, the hydrogen consumption penalty function It can be expressed by the following formula:

[0073]

[0074] Where, η FC For fuel cell efficiency, q H2 The hydrogen has a low calorific value corresponding to fuel cells.

[0075] S330. Determine the state-of-charge penalty function for the power battery based on the state-of-charge penalty coefficient, battery capacity, and current.

[0076] In one specific embodiment, the power state penalty function L SOC (k) can be expressed by the following formula:

[0077]

[0078]

[0079] Where, k P and k I These are the state-of-charge penalty coefficients for the power battery, Q. bat For battery capacity, I bat This refers to the current of the power battery.

[0080] S340. Based on the voltage decay amplitude, determine the aging penalty function corresponding to the fuel cell, and construct the cost function corresponding to the fuel cell at the current moment based on the hydrogen consumption penalty function, the power state penalty function, and the aging penalty function.

[0081] In one specific embodiment, the fuel cell aging penalty function L aging (k) can be expressed by the following formula:

[0082]

[0083] The hydrogen consumption penalty function is determined through the above steps. Battery status penalty function L SOC (k) and aging penalty function L aging After (k), the instantaneous index function L(x(k),u(k)) can be calculated using the following formula:

[0084]

[0085] Where α and β are preset weighting factors.

[0086] In one embodiment of this example, the cost function J corresponding to the fuel cell at the current moment can be constructed based on the instantaneous index function L(x(k),u(k)) described above using the following formula:

[0087]

[0088] Where, γ k Let be the convergence factor of the function.

[0089] S350. Solve the cost function according to the preset constraints to obtain the target management strategy corresponding to the fuel cell at the current time, and control the fuel cell to work according to the target management strategy.

[0090] In one specific embodiment, the constraint condition can be represented by the following formula:

[0091]

[0092] The technical solution of this embodiment obtains the operating condition data of the fuel cell at the current moment, inputs the operating condition data into the fuel cell aging model, determines the voltage decay rate of the fuel cell based on the model output, determines the hydrogen consumption penalty function of the fuel cell based on the hydrogen lower heating value, distributed power, and power response rate of the fuel cell, determines the state of charge penalty function of the power battery based on the state of charge penalty coefficient, battery capacity, and current, determines the aging penalty function of the fuel cell based on the voltage decay rate, constructs the cost function of the fuel cell at the current moment based on the hydrogen consumption penalty function, state of charge penalty function, and aging penalty function, solves the cost function according to preset constraints, obtains the target management strategy of the fuel cell at the current moment, and controls the operation of the fuel cell according to the target management strategy. This technical means can avoid frequent and large load changes of the fuel cell, improve the durability of the fuel cell, and extend the service life of the fuel cell.

[0093] Example 4

[0094] Figure 4 This is a schematic diagram of a fuel cell energy control device provided in Embodiment 4 of the present invention. This embodiment is applicable to the control of fuel cell energy control in autonomous driving. The fuel cell energy control device can be implemented in hardware and / or software and can be configured in a vehicle.

[0095] like Figure 4 As shown, the fuel cell energy control device disclosed in this embodiment includes:

[0096] The model input module 410 is used to acquire the operating condition data of the fuel cell at the current moment, input the operating condition data into the pre-trained fuel cell aging model, and determine the voltage decay rate of the fuel cell based on the output results of the model.

[0097] The fuel cell aging model is obtained by training the historical operating data of the fuel cell.

[0098] The cost function construction module 420 is used to obtain the state of charge of the power battery in the vehicle, and construct the cost function corresponding to the fuel cell at the current moment based on the state of charge, voltage decay amplitude, the power distribution of the fuel cell and the power response rate.

[0099] The management strategy determination module 430 is used to solve the cost function according to preset constraints to obtain the target management strategy corresponding to the fuel cell at the current time, and control the fuel cell to work according to the target management strategy.

[0100] The technical solution in this embodiment obtains the operating condition data of the fuel cell at the current moment, inputs the operating condition data into a pre-trained fuel cell aging model, and determines the voltage decay amplitude of the fuel cell based on the output of the model. It also obtains the state of charge (SOC) of the power battery in the vehicle, constructs a cost function for the fuel cell at the current moment based on the SOC, voltage decay amplitude, the allocated power of the fuel cell, and the power response rate, solves the cost function according to preset constraints, obtains the target management strategy for the fuel cell at the current moment, and controls the fuel cell to operate according to the target management strategy. This proposes an effective way to control the energy of the fuel cell, which can avoid frequent and large-scale load changes, improve the durability of the fuel cell, and extend its service life.

[0101] Optionally, based on the above embodiments, the apparatus further includes:

[0102] The subsequent control module is used to, after controlling the fuel cell to operate according to the target management strategy, obtain a preset state transition matrix, determine the state variables of the vehicle power system at the next moment based on the state variables, control variables, and state transition matrix of the vehicle power system at the current moment; construct the cost function corresponding to the fuel cell at the next moment based on the state variables, control variables, and voltage decay magnitude of the fuel cell at the next moment; and solve the cost function corresponding to the next moment to obtain the management strategy corresponding to the fuel cell at the next moment.

[0103] The model training module is used to acquire multiple historical operating data corresponding to the fuel cell, divide the multiple historical operating data into a training set and a test set; and use the training set and the test set to iteratively train the long short-term memory network model to obtain the fuel cell aging model.

[0104] Cost function construction module 420 includes:

[0105] The state quantity determination unit is used to determine the state of charge of the power battery as the state quantity of the vehicle power system at the current moment.

[0106] The variable determination unit is used to use the allocated power and power response rate of the fuel cell as control variables of the vehicle power system at the current moment.

[0107] The function determination unit is used to construct the cost function of the fuel cell at the current moment based on the state variables, control variables, and voltage decay magnitude.

[0108] The penalty function determination unit is used to determine the hydrogen consumption penalty function corresponding to the fuel cell based on the hydrogen low calorific value, power distribution, and power response rate corresponding to the fuel cell; to determine the state of charge penalty function corresponding to the power battery based on the state of charge penalty coefficient, battery capacity, and current corresponding to the power battery; and to determine the aging penalty function corresponding to the fuel cell based on the voltage decay amplitude.

[0109] The penalty function processing unit is used to construct the cost function corresponding to the fuel cell at the current moment based on the hydrogen consumption penalty function, the power state penalty function, and the aging penalty function.

[0110] The management strategy determination module 430 includes:

[0111] The target power determination unit is used to solve the cost function according to preset constraints to obtain the target allocated power and target power response rate of the fuel cell at the current time.

[0112] The control unit is used to control the fuel cell to operate according to the target power allocation and the target power response rate.

[0113] The fuel cell energy control device provided in this embodiment of the invention can execute the fuel cell energy control method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method. Content not described in detail in this embodiment can be referred to the description in any method embodiment of this application.

[0114] Example 5

[0115] Figure 5 A schematic diagram of the structure of a vehicle 10 that can be used to implement an embodiment of the present invention is shown. For example... Figure 5 As shown, vehicle 10 includes at least one processor 11 and a memory, such as read-only memory (ROM) 12 and random access memory (RAM) 13, communicatively connected to at least one processor 11. The memory stores computer programs executable by at least one processor. Processor 11 can perform various appropriate actions and processes based on the computer program stored in ROM 12 or loaded from storage unit 18 into RAM 13. RAM 13 can also store various programs and data required for the operation of vehicle 10. Processor 11, ROM 12, and RAM 13 are interconnected via bus 14. Input / output (I / O) interface 15 is also connected to bus 14.

[0116] Multiple components in vehicle 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows vehicle 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0117] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with 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 special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as fuel cell energy control methods.

[0118] In some embodiments, the fuel cell energy control method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on vehicle 10 via ROM 12 and / or 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 energy control method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the fuel cell energy control method by any other suitable means (e.g., by means of firmware).

[0119] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0120] Computer programs used to implement the methods of the present invention 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, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0121] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0122] To provide interaction with the user, the systems and technologies described herein can be implemented in a vehicle having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the vehicle. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0123] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0124] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0125] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and no limitation is imposed herein.

[0126] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A fuel cell energy control method, characterized in that, Applied to vehicles, the method includes: The operating condition data of the fuel cell at the current moment is obtained, the operating condition data is input into a pre-trained fuel cell aging model, and the voltage decay rate of the fuel cell is determined based on the output of the model. The fuel cell aging model is obtained by training the historical operating data of the fuel cell. The state of charge of the power battery in the vehicle is obtained, and the state of charge of the power battery is used as the state variable of the vehicle power system at the current moment; the power distribution and power response rate of the fuel cell are used as the control variables of the vehicle power system at the current moment. Based on the hydrogen calorific value, power distribution, and power response rate of the fuel cell, a hydrogen consumption penalty function is determined for the fuel cell; based on the state of charge penalty coefficient, battery capacity, and current of the power battery, a state of charge penalty function is determined for the power battery; based on the voltage decay amplitude, an aging penalty function is determined for the fuel cell; based on the hydrogen consumption penalty function, the state of charge penalty function, and the aging penalty function, a cost function for the fuel cell at the current moment is constructed. Based on preset constraints, the cost function is solved to obtain the target management strategy corresponding to the fuel cell at the current moment, and the fuel cell is controlled to work according to the target management strategy.

2. The method according to claim 1, characterized in that, After controlling the fuel cell to operate according to the stated target management strategy, the process also includes: Obtain a preset state transition matrix, and determine the state of the vehicle power system at the next moment based on the state variables, control variables, and state transition matrix of the vehicle power system at the current moment. Based on the state variables and control variables of the vehicle power system at the next moment, and the voltage decay of the fuel cell at the next moment, construct the cost function corresponding to the fuel cell at the next moment; The cost function corresponding to the next time step is solved to obtain the management strategy of the fuel cell at the next time step.

3. The method according to claim 1, characterized in that, Based on preset constraints, the cost function is solved to obtain the target management strategy for the fuel cell at the current time, and the fuel cell is controlled to operate according to the target management strategy, including: The cost function is solved according to the preset constraints to obtain the target power allocation and target power response rate of the fuel cell at the current moment. The fuel cell is controlled to operate according to the target power allocation and target power response rate.

4. The method according to claim 1, characterized in that, Before acquiring the operating condition data of the fuel cell at the current moment and inputting the operating condition data into the pre-trained fuel cell aging model, the process also includes: Acquire multiple historical operating data points corresponding to the fuel cell, and divide the multiple historical operating data points into a training set and a test set; Using the training and test sets, the long short-term memory network model is iteratively trained to obtain the fuel cell aging model.

5. A fuel cell energy control device, characterized in that, Applied to vehicles, the device includes: The model input module is used to acquire the operating condition data of the fuel cell at the current moment, input the operating condition data into the pre-trained fuel cell aging model, and determine the voltage decay rate of the fuel cell based on the output of the model. The fuel cell aging model is obtained by training the historical operating data of the fuel cell. The cost function construction module is used to obtain the state of charge (SOC) of the power battery in the vehicle, and use the SOC of the power battery as the state variable of the vehicle power system at the current moment; use the power distribution and power response rate of the fuel cell as the control variables of the vehicle power system at the current moment; determine the hydrogen consumption penalty function of the fuel cell based on the hydrogen calorific value, power distribution, and power response rate of the fuel cell; determine the SOC penalty function of the power battery based on the SOC penalty coefficient, battery capacity, and current of the power battery; determine the aging penalty function of the fuel cell based on the voltage decay amplitude; and construct the cost function of the fuel cell at the current moment based on the hydrogen consumption penalty function, SOC penalty function, and aging penalty function. The management strategy determination module is used to solve the cost function according to preset constraints to obtain the target management strategy corresponding to the fuel cell at the current time, and control the fuel cell to work according to the target management strategy.

6. A vehicle, characterized in that, The vehicles include: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the fuel cell energy control method according to any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the fuel cell energy control method according to any one of claims 1-4.

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