Control method and device of fuel cell vehicle, server and fuel cell vehicle

Abstract

The invention relates to the technical field of fuel cell automobiles, in particular to a control method and device of a fuel cell automobile, a server and the fuel cell automobile, and the method comprises the steps that vehicle data uploaded by the fuel cell automobile are acquired; the actual road condition of the fuel cell vehicle in the vehicle data is recognized, the optimal control strategy of the fuel cell vehicle is matched according to the actual road condition, and the optimal control strategy is obtained through simulation based on experimental data uploaded by a vehicle enterprise and / or the vehicle data uploaded by the fuel cell vehicle; and the optimal control strategy is sent to the fuel cell automobile, so that the fuel cell automobile controls a fuel cell and a power cell of the fuel cell automobile to work based on the optimal control strategy. Therefore, the problems of high lag, high failure, unpredictability, influence on the service life of the fuel cell and the power cell and the like of the control strategy of the fuel cell vehicle in the related technology are solved.

Description

Technical Field

[0001] The present application relates to the technical field of fuel cell vehicles, and in particular to a control method, device, server and fuel cell vehicle for a fuel cell vehicle. Background Art

[0002] Fuel cell vehicles are different from traditional fuel vehicles and electric vehicles, mainly in the following aspects: 1. The economy of fuel cell vehicles is completely determined by the efficiency of the fuel cell system; 2. The life of fuel cell vehicles is also mainly determined by the fuel cell system; 3. The dynamic response capability of fuel cells is very poor and cannot meet the real-time changing working conditions of the vehicle. A more intelligent control method is needed to make up for this shortcoming of the fuel cell system; 4. Fuel cell vehicles must be equipped with both fuel cell systems and power battery systems. Only by adopting more intelligent and sustainably upgraded control strategies can the efficient operation of fuel cells and power batteries be guaranteed and the life of fuel cells and power batteries be predicted.

[0003] The existing energy management strategies are relatively fixed, leading to the following situations: 1. The power generation of the fuel cell is too low, causing the power battery SOC (State of Charge) to continue to decline, and ultimately unable to guarantee the operation of the entire vehicle; 2. The power generation of the fuel cell is too high, causing the power battery SOC to continue to rise, and the fuel cell operates in a low-efficiency area; 3. The power battery SOC is too high, causing the fuel cell to shut down, resulting in unnecessary starts and stops; 4. The power battery SOC is too high, causing the power battery to be unable to effectively absorb braking feedback energy, thereby affecting the energy consumption of the entire vehicle; 5. Due to the characteristics of the power battery itself, the power battery SOC has its own optimal working range, and the power battery SOC is too high or too low, which affects the performance and life of the power battery. Summary of the invention

[0004] The present application provides a control method, device, server and fuel cell vehicle for a fuel cell vehicle to solve the problems in the related art that the control strategy of a fuel cell vehicle has high hysteresis, high failure rate and unpredictability, which affects the service life of the fuel cell and the power battery.

[0005] The first aspect of the present application provides a control method for a fuel cell vehicle, which is applied to a server and includes the following steps: acquiring vehicle data uploaded by the fuel cell vehicle; identifying the actual road conditions of the fuel cell vehicle in the vehicle data, and matching an optimal control strategy for the fuel cell vehicle according to the actual road conditions, wherein the optimal control strategy is a control strategy obtained by simulating experimental data uploaded by the vehicle manufacturer and / or vehicle data uploaded by the fuel cell vehicle; sending the optimal control strategy to the fuel cell vehicle so that the fuel cell vehicle controls the operation of the fuel cell and power battery of the fuel cell vehicle based on the optimal control strategy.

[0006] Optionally, the optimal control strategy is a strategy obtained by simulating experimental data uploaded by the automobile manufacturer and / or vehicle data uploaded by the fuel cell vehicle, including: identifying the target road conditions corresponding to the experimental data and / or the vehicle data; performing control simulation of the fuel cell and the power battery under the target road conditions according to the experimental data and / or the vehicle data uploaded by the fuel cell vehicle; if the simulated strategy meets the performance conditions of the fuel cell vehicle and the service life conditions of the fuel cell and the power battery, the simulation is stopped and the optimal control strategy for the target road conditions is obtained.

[0007] Optionally, matching the optimal control strategy of the fuel cell vehicle according to the actual road condition includes: using the actual road condition as an index to query a preset database to obtain the optimal control strategy for the actual road condition, wherein if the preset database does not find the control strategy for the actual road condition, then performing control simulation of the fuel cell and the power battery under the actual road condition based on the vehicle data.

[0008] Optionally, the automobile manufacturer and the fuel cell vehicle utilize a digital twin control strategy to synchronize the corresponding latest data to the server.

[0009] The second aspect of the present application provides a control method for a fuel cell vehicle, which is applied to a fuel cell vehicle and includes the following steps: synchronizing vehicle data to a server using a digital twin control strategy; receiving an optimal control strategy for the current road conditions issued by the server based on the vehicle data, wherein the optimal control strategy is based on experimental data uploaded by the vehicle manufacturer and / or a strategy obtained by simulating the vehicle data; upgrading the current control strategy of the fuel cell vehicle to the optimal control strategy using an edge control strategy, and controlling the operation of the fuel cell and power battery of the fuel cell vehicle using the optimal control strategy.

[0010] Optionally, the current control strategy of the fuel cell vehicle is upgraded to the optimal control strategy using an edge control strategy, including: detecting whether the fuel cell vehicle meets the upgrade conditions; if the fuel cell vehicle meets the upgrade conditions, upgrading the current control strategy of the fuel cell vehicle to the optimal control strategy.

[0011] In a third aspect, an embodiment of the present application provides a control device for a fuel cell vehicle, which is applied to a server and includes: an acquisition module for acquiring vehicle data uploaded by the fuel cell vehicle; a matching module for identifying the actual road conditions of the fuel cell vehicle in the vehicle data, and matching the optimal control strategy of the fuel cell vehicle according to the actual road conditions, wherein the optimal control strategy is a control strategy obtained by simulating experimental data uploaded by the vehicle manufacturer and / or vehicle data uploaded by the fuel cell vehicle; and a sending module for sending the optimal control strategy to the fuel cell vehicle, so that the fuel cell vehicle controls the operation of the fuel cell and the power battery of the fuel cell vehicle based on the optimal control strategy.

[0012] The fourth aspect of the present application provides a control device for a fuel cell vehicle, which is applied to a fuel cell vehicle and includes: a synchronization module, which is used to synchronize vehicle data to a server using a digital twin control strategy; a receiving module, which is used to receive the optimal control strategy for the current road conditions sent by the server based on the vehicle data, wherein the optimal control strategy is based on experimental data uploaded by the vehicle manufacturer and / or a strategy obtained by simulating the vehicle data; a control module, which is used to upgrade the current control strategy of the fuel cell vehicle to the optimal control strategy using an edge control strategy, and use the optimal control strategy to control the operation of the fuel cell and power battery of the fuel cell vehicle.

[0013] The fifth aspect of the present application provides a server, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the control method of the fuel cell vehicle as described in the above embodiment.

[0014] The sixth aspect of the present application provides a fuel cell vehicle, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the control method of the fuel cell vehicle as described in the above embodiment.

[0015] Therefore, this application has at least the following beneficial effects:

[0016] The embodiment of the present application can synchronize the data of the vehicle during driving with the latest experimental data of the car company in real time through the digital twin technology, adjust the control strategy according to the road conditions of the vehicle, improve the adaptability in power output and brake energy recovery, and truly realize the multi-operating condition adaptation of fuel cell vehicles in all climates and environments, so that the fuel cell can work stably, thereby reducing its load change and start-stop frequency, improving the performance of the fuel cell and extending its service life, and controlling the power battery to work in the optimal working area, improving the performance of the power battery and extending its service life, and there is no need to formulate a separate control strategy according to different route conditions, reducing the cost of manpower and material resources, thereby reducing the cost of the whole vehicle. Therefore, the technical problems such as high hysteresis, high failure, and unpredictability of the control strategy of fuel cell vehicles in the related technology, which affect the service life of fuel cells and power batteries, are solved.

[0017] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0019] Figure 1 A flowchart of a control method for a fuel cell vehicle provided according to an embodiment of the present application;

[0020] Figure 2 A flowchart of a digital twin control strategy provided according to an embodiment of the present application;

[0021] Figure 3 It is a diagram of upgrading strategies for actual working condition comparison provided according to an embodiment of the present application;

[0022] Figure 4 A flowchart of a control method for a fuel cell vehicle provided according to another embodiment of the present application;

[0023] Figure 5 This is an example diagram of a control device for a fuel cell vehicle provided according to an embodiment of the present application;

[0024] Figure 6 This is an example diagram of a control device for a fuel cell vehicle provided according to another embodiment of the present application. DETAILED DESCRIPTION

[0025] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0026] The control method, device, server and fuel cell vehicle of the fuel cell vehicle of the embodiment of the present application are described below with reference to the accompanying drawings. In view of the relatively fixed energy management strategy for fuel cell vehicles mentioned in the above background technology, the vehicle control strategy cannot be adjusted and upgraded as the road conditions and environment change, and the control strategy has high hysteresis, high failure and unpredictability, the present application provides a control method for a fuel cell vehicle, in which the database of the server is linked and coupled with the data model updated as the vehicle driving data increases to further improve the environmental adaptability of the vehicle. By adopting a new digital twin strategy, the dynamic water management technology, lossless start-stop control technology, environmental adaptive control technology and balanced management technology of the fuel cell system can be effectively and continuously upgraded, effectively ensuring the stable reliability and long-life operation of the system. As a result, the control strategy of fuel cell vehicles in the related technology has high hysteresis, high failure, unpredictability, and affects the service life of fuel cells and power batteries.

[0027] Since this application is based on a digital twin control strategy to improve the efficiency and life of fuel cells and power batteries, it is necessary to introduce the factors affecting the efficiency and life of fuel cells and power batteries and the data that need to be improved before specifically elaborating on the control method of the fuel cell.

[0028] Fuel cells are best suited for continuous discharge at a stable power level. Start-stop, open circuit / idling, and variable load are the three key vehicle operating conditions that accelerate the aging of fuel cell stack materials and components. (1) The main reason that affects the durability of fuel cells under start-stop conditions is the high interfacial potential difference caused by the hydrogen / air interface. Start-stop is a special operating condition that can cause abnormal reactions in fuel cells. The main reason for accelerating fuel cell degradation is the high interfacial potential difference (up to 1.5V) at the cathode caused by the hydrogen / air interface at the anode. Under start-stop conditions, the carbon carrier that constitutes the main framework of the catalyst layer will be severely corroded, which will in turn affect the platinum catalyst and ionomer. In addition, the structure of the cathode catalyst layer will be affected and will change or even collapse, reducing the electrochemical active area and increasing the charge transfer resistance and mass transfer resistance. In addition, as a component of the start-stop condition, the freezing / melting cycle of low-temperature start-up also has a significant impact on the key materials and durability of the battery. Therefore, it is particularly necessary to continuously upgrade and optimize the start-stop control strategy. (2) Under open circuit / idling conditions, the oxygen transmembrane permeation effect accelerates the production of H2O2 and increases the generation rate of free radicals (Fenton reaction). Free radicals attack the molecular structure of the proton membrane at specific locations, causing chemical attenuation of the proton membrane. (3) During the load change process, the electrode potential, reactant gas stoichiometry, temperature, pressure and humidity will fluctuate rapidly, thereby accelerating the aging of the fuel cell. The main reasons are that first, the amount of product water and heat dissipation change with the load change, causing heat / humidity cycles. Secondly, the load change causes reactant gas starvation (or lack of gas) during the loading process. Furthermore, the voltage cycle accompanying the load change process accelerates catalyst attenuation. The above three problems need to be solved after continuously upgrading the control strategy based on the vehicle condition and uploaded predictive data.

[0029] The factors that affect the service life of power batteries mainly include the number of balancing times, charge and discharge rate, operating temperature, and the number of full charge and discharge times. (1) When the number of balancing times is small or even non-existent, the voltage difference between battery cells will be too large, which will eventually cause the battery cells with performance deviations to decay too quickly, causing the entire system to decay too quickly as a whole. (2) The charge and discharge rate refers to the maximum charge and discharge current allowed under conditions such as temperature and power battery charge state. If the maximum charge and discharge current is exceeded, the power battery will decay and even thermal runaway caused by battery overheating. (3) Power batteries generally have the longest life when charged and discharged at a temperature of 25°C to 45°C. (4) The life of power batteries is generally calculated based on the number of full charge and discharge times. This is because the battery capacity decreases after thousands of full charge and discharge times, mainly due to the precipitation of lithium ions at the positive electrode and the collapse of the carbon structure of the negative electrode.

[0030] Specifically, Figure 1 A flow chart of a control method for a fuel cell vehicle provided in an embodiment of the present application.

[0031] like Figure 1As shown, the control method of the fuel cell vehicle is applied to a server and includes the following steps:

[0032] In step S101, vehicle data uploaded by the fuel cell vehicle is obtained.

[0033] Among them, vehicle data refers to the operating data collected by the vehicle-side controller, including vehicle condition data, ambient temperature data, vehicle speed data, power data of fuel cells and power batteries, power battery balancing times data, actual road conditions, etc.

[0034] It should be noted that the executor of the control method of the fuel cell vehicle in the embodiment of the present application is a server, and the server can communicate with the fuel cell vehicle to obtain the collected vehicle data uploaded by the fuel cell vehicle.

[0035] In step S102, the actual road condition of the fuel cell vehicle in the vehicle data is identified, and the optimal control strategy of the fuel cell vehicle is matched according to the actual road condition, wherein the optimal control strategy is a control strategy obtained by simulating the experimental data uploaded by the vehicle manufacturer and / or the vehicle data uploaded by the fuel cell vehicle.

[0036] It can be understood that the optimal control strategy refers to the control strategy that enables fuel cell vehicles to achieve optimal performance under actual road conditions. A simulation model can be obtained by simulating one or more of the experimental data uploaded by the car company and the vehicle data uploaded by the fuel cell vehicle. The optimal control strategy is determined through the simulation model, and the vehicle data uploaded by the fuel cell vehicle refers to the vehicle data already stored in the server.

[0037] In an embodiment of the present application, the optimal control strategy is a strategy obtained by simulating the experimental data uploaded by the automobile manufacturer and / or the vehicle data uploaded by the fuel cell vehicle, including: identifying the target road conditions corresponding to the experimental data and / or the vehicle data uploaded by the fuel cell vehicle; simulating the control of the fuel cell and the power battery under the target road conditions according to the experimental data and / or the vehicle data uploaded by the fuel cell vehicle; if the simulated strategy meets the performance conditions of the fuel cell vehicle and the service life conditions of the fuel cell and the power battery, the simulation is stopped and the optimal control strategy for the target road conditions is obtained.

[0038] It can be understood that the embodiments of the present application can perform control simulation of the fuel cell and the power battery under the target road condition based on one or more of the experimental data and the vehicle data uploaded by the fuel cell vehicle, compare the target road condition information with the actual road condition information, and judge whether the target road condition of the vehicle is beneficial to the performance of the whole vehicle based on the strategy obtained by simulation, and whether it can meet the performance and life requirements of the fuel cell and the power battery. If so, stop the simulation and obtain the optimal control strategy for the target road condition. By establishing a simulation model, compare the actual vehicle condition with the simulation model to select the optimal control strategy, thereby reducing the manpower and material costs of formulating energy management strategies separately according to different route conditions, thereby reducing the cost of the whole vehicle.

[0039] In an embodiment of the present application, the optimal control strategy for a fuel cell vehicle is matched according to actual road conditions, including: using the actual road conditions as an index, querying a preset database, and obtaining the optimal control strategy for the actual road conditions, wherein if the preset database does not query the control strategy for the actual road conditions, then performing control simulation of the fuel cell and the power battery under actual road conditions based on the vehicle data.

[0040] The preset database is used to store the corresponding data of the actual road conditions and the optimal control strategy.

[0041] It can be understood that the embodiment of the present application can use the actual road conditions as an index to query the optimal control strategy that matches the actual road conditions in the preset database. If the optimal control strategy exists, step S103 is performed. If not, the most suitable power of the fuel cell and the power battery is simulated and archived according to the actual road conditions. The optimal control strategy of the vehicle can be adjusted according to the actual road conditions to adjust the performance of the entire vehicle.

[0042] In step S103, the optimal control strategy is sent to the fuel cell vehicle, so that the fuel cell vehicle controls the operation of the fuel cell and the power battery of the fuel cell vehicle based on the optimal control strategy.

[0043] It can be understood that after matching the optimal control strategy of the fuel cell vehicle according to the actual road conditions, the embodiment of the present application sends the optimal control strategy to the fuel cell vehicle, so that the fuel cell vehicle controls the fuel cell and power battery of the fuel cell vehicle to work based on the optimal control strategy, that is, it makes corrections according to the simulation data based on the edge algorithm under the target road conditions, and compares and analyzes the vehicle side, server and automobile enterprise database based on edge computing, and corrects the parameters to improve vehicle performance and ensure the life of the fuel cell and power battery.

[0044] It should be noted that the embodiment of the present application can actively balance according to a monthly balancing cycle under the condition of normal vehicle driving.

[0045] In an embodiment of the present application, the automobile manufacturer and the fuel cell vehicle use a digital twin control strategy to synchronize the corresponding latest data to the server.

[0046] It is understandable that car companies and fuel cell vehicles can synchronize the latest data to the server through the digital twin control strategy. For example, car companies can synchronize the latest experimental data to the server, and can synchronize the vehicle data with better driving conditions to the server, and compare the existing experimental data and vehicle data to correct the existing control strategy. Among them, experimental data refers to the data obtained by car companies through experiments in an experimental environment. Car companies can choose the specific experimental process according to actual conditions without specific restrictions.

[0047] It should be noted that digital twin control strategies have been applied in industries such as medical and manufacturing. It is a control strategy for creating real-time monitoring systems. Of course, different control strategies require professional development in different industries to ensure the normal progress of production work. It is applied in vehicles to improve vehicle adaptability, but the safety of vehicle driving should be guaranteed during the data upgrade of digital twins.

[0048] Specifically, the basic scheme of the digital twin control strategy in the embodiment of the present application is as follows: Figure 2 As shown in the figure, through digital twin technology, the data of the vehicle during driving can be synchronously compared with the existing data and test data through the server computing center, the strategy can be corrected, and the corrected strategy can be input into the vehicle control unit through the server to improve the adaptability in power output and braking energy recovery in advance. The specific process of strategy correction is as follows Figure 3 shown.

[0049] According to the control method of the fuel cell vehicle proposed in the embodiment of the present application, the data during the vehicle's driving process and the latest experimental data of the automobile company can be synchronized in real time through the digital twin technology, the control strategy can be adjusted according to the vehicle's road conditions, the adaptability can be improved in terms of power output and brake energy recovery, etc., and the fuel cell vehicle can truly adapt to multiple working conditions in all climates and all environments. The fuel cell can be made to work stably, thereby reducing its load change and start-stop frequency, improving the performance of the fuel cell and extending its service life. By controlling the power battery to work in the optimal working area, the power battery performance is improved and the service life is extended. There is no need to formulate a separate control strategy according to different route conditions, thereby reducing manpower and material costs, thereby reducing the cost of the entire vehicle.

[0050] Figure 4 This is a flow chart of a control method for a fuel cell vehicle provided according to another embodiment of the present application.

[0051] like Figure 4 As shown, the control method of the fuel cell vehicle is applied to the fuel cell and comprises the following steps:

[0052] In step S201, the vehicle data is synchronized to the server using the digital twin control strategy.

[0053] In step S202, the optimal control strategy for the current road condition sent by the receiving server based on the vehicle data is received, wherein the optimal control strategy is based on the experimental data uploaded by the automobile manufacturer and / or the strategy obtained by simulating the vehicle data.

[0054] It can be understood that the embodiment of the present application can synchronize the vehicle data obtained in step S201 to the server using the digital twin control strategy, and receive the optimal control strategy for the current road conditions issued by the server based on the number of vehicles.

[0055] In step S203, the edge control strategy is used to upgrade the current control strategy of the fuel cell vehicle to the optimal control strategy, and the optimal control strategy is used to control the operation of the fuel cell and the power battery of the fuel cell vehicle.

[0056] It can be understood that the embodiment of the present application can use the edge control strategy to upgrade the current control strategy of the fuel cell vehicle to the optimal control strategy, control the operation of the fuel cell and power battery of the fuel cell vehicle, achieve optimal control of the vehicle, and improve the life of the fuel cell and power battery.

[0057] In an embodiment of the present application, an edge control strategy is used to upgrade the current control strategy of a fuel cell vehicle to an optimal control strategy, including: detecting whether the fuel cell vehicle meets the upgrade conditions; if the fuel cell vehicle meets the upgrade conditions, upgrading the current control strategy of the fuel cell vehicle to the optimal control strategy.

[0058] It can be understood that the embodiment of the present application determines whether the fuel cell vehicle meets the upgrade conditions. If the upgrade conditions are met, the control strategy of the fuel cell vehicle is upgraded to the optimal one, and the edge control strategy is used to ensure that the vehicle is upgraded in a safe state.

[0059] In summary, the embodiment of the present application can use the edge control strategy to upgrade the current control strategy of the fuel cell vehicle to the optimal control strategy, control the operation of the fuel cell and power battery of the fuel cell vehicle, so as to make the fuel cell work stably, reduce its variable load, start-stop frequency, improve the performance of the fuel cell and extend its service life, control the power battery to work in the optimal working area, improve the performance of the power battery and extend its service life, and truly realize the full climate and full environment multi-operating condition adaptation of the fuel cell vehicle. Among them, the edge control strategy can be closer to the diagnosis of the vehicle side, and at the same time, it can also compare and test the safety of the upgraded new data on the vehicle side, and can quickly compare, screen and upgrade the data downloaded from the server on the vehicle side.

[0060] According to the control method of the fuel cell vehicle proposed in the embodiment of the present application, the digital twin control strategy edge control strategy is used to keep the automobile manufacturer and the vehicle end in contact at all times, and the automobile manufacturer's server and vehicle control program can be continuously upgraded; the latest test data of the automobile manufacturer can be compared with the vehicle-end information, and the data such as different times, driving habits, and the usage time of fuel cells and power batteries for the same vehicle condition can be compared, and ultimately comprehensive prediction and optimization can be achieved; with the help of the fast edge computing equipment of the 5G network, it is installed on the whole vehicle end, which can improve the real-time performance of the vehicle-end data improvement.

[0061] Next, the control device for a fuel cell vehicle according to an embodiment of the present application will be described with reference to the accompanying drawings.

[0062] Figure 5 It is a block diagram of a control device for a fuel cell vehicle according to an embodiment of the present application.

[0063] like Figure 5 As shown, the control device 10 of the fuel cell vehicle is applied to a server, and includes: an acquisition module 101 , a matching module 102 and a sending module 103 .

[0064] Among them, the acquisition module 101 is used to acquire the vehicle data uploaded by the fuel cell vehicle; the matching module 102 is used to identify the actual road conditions of the fuel cell vehicle in the vehicle data, and match the optimal control strategy of the fuel cell vehicle according to the actual road conditions, wherein the optimal control strategy is based on the experimental data uploaded by the car manufacturer and / or the control strategy obtained by simulating the vehicle data uploaded by the fuel cell vehicle; the sending module 103 is used to send the optimal control strategy to the fuel cell vehicle, so that the fuel cell vehicle controls the operation of the fuel cell and the power battery of the fuel cell vehicle based on the optimal control strategy.

[0065] It should be noted that the above explanation of the control method embodiment of the fuel cell vehicle is also applicable to the control device of the fuel cell vehicle of this embodiment, and will not be repeated here.

[0066] According to the control device of the fuel cell vehicle proposed in the embodiment of the present application, the data during the vehicle's driving process and the latest experimental data of the automobile company can be synchronized in real time through the digital twin technology, and the control strategy can be adjusted according to the road conditions of the vehicle. The adaptability can be improved in terms of power output and brake energy recovery, and the fuel cell vehicle can truly adapt to multiple working conditions in all climates and environments. The fuel cell can be made to work stably, thereby reducing its load change and start-stop frequency, improving the performance of the fuel cell and extending its service life. By controlling the power battery to work in the optimal working area, the power battery performance is improved and the service life is extended. There is no need to formulate a separate control strategy according to different route conditions, thereby reducing manpower and material costs, thereby reducing the cost of the entire vehicle.

[0067] Figure 6 It is a block diagram of a control device for a fuel cell vehicle according to another embodiment of the present application.

[0068] like Figure 6 As shown, the control device 20 of the fuel cell vehicle is applied to the fuel cell vehicle, and includes: a synchronization module 201 , a receiving module 202 and a control module 203 .

[0069] Among them, the synchronization module 201 is used to synchronize vehicle data to the server using the digital twin control strategy; the receiving module 202 is used to receive the optimal control strategy for the current road conditions sent by the server based on the vehicle data, wherein the optimal control strategy is based on the experimental data uploaded by the vehicle company and / or the strategy obtained by simulating the vehicle data; the control module 203 is used to upgrade the current control strategy of the fuel cell vehicle to the optimal control strategy using the edge control strategy, and use the optimal control strategy to control the operation of the fuel cell and power battery of the fuel cell vehicle.

[0070] It should be noted that the above explanation of the control method embodiment of the fuel cell vehicle is also applicable to the control device of the fuel cell vehicle of this embodiment, and will not be repeated here.

[0071] According to the control device of the fuel cell vehicle proposed in the embodiment of the present application, the digital twin control strategy edge control strategy is used to keep the automobile manufacturer and the vehicle end in contact at all times, and the automobile manufacturer's server and vehicle control program can be continuously upgraded; the latest test data of the automobile manufacturer can be compared with the vehicle-end information, and the data such as different times, driving habits, and the usage time of fuel cells and power batteries for the same vehicle condition can be compared, and ultimately comprehensive prediction and optimization can be achieved; with the help of the fast edge computing equipment of the 5G network, it is installed on the whole vehicle end, which can improve the real-time performance of the vehicle-end data improvement.

[0072] An embodiment of the present application also provides a server, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-mentioned fuel cell vehicle control method.

[0073] An embodiment of the present application also provides a fuel cell vehicle, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above fuel cell vehicle control method.

[0074] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms are not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0075] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0076] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0077] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array, a field programmable gate array, etc.

[0078] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0079] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A control method for a fuel cell vehicle, characterized in that: The method is applied to a server, wherein the method comprises the following steps: Obtain vehicle data uploaded by fuel cell vehicles; Identify the actual road condition of the fuel cell vehicle in the vehicle data, and match the optimal control strategy of the fuel cell vehicle according to the actual road condition, wherein the optimal control strategy is a control strategy obtained by simulating the experimental data uploaded by the vehicle manufacturer and / or the vehicle data uploaded by the fuel cell vehicle; The optimal control strategy is sent to the fuel cell vehicle, so that the fuel cell vehicle controls the operation of the fuel cell and the power battery of the fuel cell vehicle based on the optimal control strategy.

2. The method according to claim 1, characterized in that The optimal control strategy is a strategy obtained by simulating experimental data uploaded by the automobile manufacturer and / or vehicle data uploaded by the fuel cell vehicle, including: Identifying a target road condition corresponding to the experimental data and / or the vehicle data; Performing control simulation on the fuel cell and the power battery under target road conditions according to the experimental data and / or the vehicle data uploaded by the fuel cell vehicle; If the strategy obtained by simulation meets the performance conditions of the fuel cell vehicle and the service life conditions of the fuel cell and the power battery, the simulation is stopped and the optimal control strategy for the target road condition is obtained.

3. The method according to claim 1 or 2, characterized in that: The optimal control strategy for matching the fuel cell vehicle according to the actual road conditions includes: The actual road condition is used as an index to query a preset database to obtain an optimal control strategy for the actual road condition, wherein if the preset database does not query the control strategy for the actual road condition, a control simulation is performed on the fuel cell and the power battery under the actual road condition based on the vehicle data.

4. The method according to claim 1, characterized in that The automobile manufacturer and the fuel cell vehicle utilize a digital twin control strategy to synchronize the corresponding latest data to the server.

5. A control method for a fuel cell vehicle, characterized in that: The method is applied to a fuel cell vehicle, wherein the method comprises the following steps: Use digital twin control strategies to synchronize vehicle data to the server; Receiving an optimal control strategy for the current road condition sent by the server based on the vehicle data, wherein the optimal control strategy is based on experimental data uploaded by the vehicle manufacturer and / or a strategy obtained by simulating the vehicle data; The edge control strategy is used to upgrade the current control strategy of the fuel cell vehicle to the optimal control strategy, and the optimal control strategy is used to control the operation of the fuel cell and the power battery of the fuel cell vehicle.

6. The method according to claim 5, characterized in that The current control strategy of the fuel cell vehicle is upgraded to the optimal control strategy by using the edge control strategy, including: Detecting whether the fuel cell vehicle meets the upgrade conditions; If the fuel cell vehicle meets the upgrade condition, the current control strategy of the fuel cell vehicle is upgraded to the optimal control strategy.

7. A control device for a fuel cell vehicle, characterized in that: The device is applied to a server, wherein the device comprises: An acquisition module is used to acquire vehicle data uploaded by fuel cell vehicles; A matching module, used to identify the actual road condition of the fuel cell vehicle in the vehicle data, and match the optimal control strategy of the fuel cell vehicle according to the actual road condition, wherein the optimal control strategy is based on the experimental data uploaded by the vehicle manufacturer and / or the strategy obtained by simulating the vehicle data; The sending module is used to send the optimal control strategy to the fuel cell vehicle, so that the fuel cell vehicle controls the operation of the fuel cell and the power battery of the fuel cell vehicle based on the optimal control strategy.

8. A control device for a fuel cell vehicle, characterized in that: The device is applied to a fuel cell vehicle, wherein the device comprises: A synchronization module, used to synchronize vehicle data to the server using the digital twin control strategy; A receiving module, configured to receive an optimal control strategy for the current road condition sent by the server based on the vehicle data, wherein the optimal control strategy is based on experimental data uploaded by the vehicle manufacturer and / or a strategy obtained by simulating the vehicle data; The control module is used to upgrade the current control strategy of the fuel cell vehicle to the optimal control strategy using the edge control strategy, and use the optimal control strategy to control the operation of the fuel cell and the power battery of the fuel cell vehicle.

9. A server, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the control method for a fuel cell vehicle as described in any one of claims 1 to 4.

10. A fuel cell vehicle, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the control method for a fuel cell vehicle as claimed in claim 5 or 6.

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