A fuel cell vehicle control method and control system

Abstract

This invention relates to the field of fuel cell vehicle technology, specifically providing a control method and control system for fuel cell vehicles. The method includes: acquiring the hydrogen quantity in the onboard hydrogen storage tank; determining whether the hydrogen quantity is greater than or equal to a preset hydrogen quantity threshold; if so, activating the fuel cell control system (FCS) and having the FCS supply power to the fuel cell vehicle; if the hydrogen quantity is less than the preset hydrogen quantity threshold, controlling the fuel cell vehicle to enter a parking state; acquiring real-time light intensity and determining whether the real-time light intensity is greater than a preset light intensity threshold; if the real-time light intensity is greater than or equal to the preset light intensity threshold, activating the photovoltaic module to generate electricity and drive the PEM electrolyzer to electrolyze hydrogen; if the real-time light intensity is less than the preset light intensity threshold, switching to V2X mode and using grid power to drive the PEM electrolyzer to electrolyze hydrogen. This invention can solve the energy management and hydrogen supply problems of fuel cell vehicles under multiple operating conditions, improving the intelligence level of energy management in fuel cell vehicles.

Description

Technical Field

[0001] This invention relates to the field of fuel cell vehicle technology, and more specifically, to a control method and control system for fuel cell vehicles. Background Technology

[0002] Fuel cell vehicles (FCEVs) face the following challenges when operating in different environments: 1. Insufficient hydrogen supply: They rely on hydrogen refueling stations, making it difficult to refuel quickly in remote areas or during long-distance travel; 2. Difficulty in energy management: They cannot efficiently utilize driving or parking time for energy recovery or hydrogen production; 3. Insufficient adaptability of existing fuel cell systems under multiple operating conditions: Energy supply is interrupted when camping or parking for extended periods; 4. Low utilization rate of photovoltaic panels: They fail to fully utilize solar energy resources to power the onboard system.

[0003] For example, Chinese invention patents such as CN119749283A ("A self-range extension system and control method for fuel cell vehicles based on photovoltaic hydrogen production"), CN104627002A ("A fuel cell and solar combined power electric vehicle"), and CN105329109A ("A fuel cell vehicle with solar-assisted power generation") all involve technologies for powering fuel cell vehicles through photovoltaic hydrogen production. Furthermore, Chinese invention patents such as CN115935672A ("A method for calculating energy consumption of fuel cell vehicles integrating operating condition prediction information"), CN117644783A ("A method for energy management of fuel cell vehicles combining operating condition prediction and reinforcement learning"), and CN113147512B ("A method and system for energy distribution of fuel cell electric vehicles considering multiple operating conditions") all involve technologies for energy management of fuel cell vehicles under different operating conditions.

[0004] Therefore, for fuel cell vehicles, there are still many technical problems that need to be solved in practical applications, and many technical solutions that need to be proposed. Summary of the Invention

[0005] Based on this, in order to solve the energy management and hydrogen supply problems of fuel cell vehicles under multiple operating conditions, the present invention provides a fuel cell vehicle control method and control system, the specific technical solution of which is as follows:

[0006] A fuel cell vehicle control method includes the following steps:

[0007] The amount of hydrogen in the on-board hydrogen storage tank is obtained, and it is determined whether the amount of hydrogen is greater than or equal to a preset hydrogen amount threshold. If so, the FCS is activated and the FCS supplies power to the fuel cell vehicle.

[0008] If the amount of hydrogen is less than a preset hydrogen amount threshold, the fuel cell vehicle is controlled to enter a parking state, and the real-time light intensity is collected and it is determined whether the real-time light intensity is greater than a preset light intensity threshold.

[0009] If the real-time light intensity is greater than or equal to the preset light intensity threshold, the photovoltaic module is activated, and the photovoltaic module generates electricity to drive the PEM electrolyzer to electrolyze hydrogen.

[0010] If the real-time light intensity is less than the preset light intensity threshold, switch to V2X mode and drive the PEM electrolyzer to produce hydrogen by electrolysis through grid power supply.

[0011] The fuel cell vehicle control method acquires and determines the amount of hydrogen in the on-board hydrogen storage tank, and switches to different operating states based on the different amounts of hydrogen, such as starting the photovoltaic module and switching to V2X mode to produce hydrogen by electrolysis in the PEM electrolyzer. This can solve the energy management and hydrogen supply problems of fuel cell vehicles under multiple operating conditions and improve the intelligence level of energy management of fuel cell vehicles.

[0012] Preferably, the control method further includes:

[0013] Obtain the conversion efficiency, temperature coefficient, and total effective light-receiving area of ​​the photovoltaic module;

[0014] Acquire real-time irradiance, real-time ambient temperature, and solar incidence angle;

[0015] A photovoltaic power generation model is constructed based on the conversion efficiency, temperature coefficient, total effective light-receiving area, real-time irradiance, real-time ambient temperature, and solar incidence angle.

[0016] The photovoltaic power generation model is used to predict the power generation of the photovoltaic module.

[0017] Preferably, the control method further includes:

[0018] Obtain weather forecast data, and based on the weather forecast data, obtain the predicted irradiance value and predicted wind speed value for the future time period;

[0019] A dynamic optimization model for the photovoltaic module angle is constructed based on the predicted irradiance value, predicted wind speed value, real-time ambient temperature, and solar incidence angle.

[0020] Preferably, the photovoltaic power generation model is expressed as follows: ;

[0021] in, Indicates photovoltaic power generation capacity. Indicates conversion efficiency. Indicates the temperature coefficient. Indicates the total effective light-receiving area. Indicates real-time irradiance. Indicates the real-time ambient temperature. Indicates the angle of incidence of the sun.

[0022] Preferably, the dynamic optimization model for the photovoltaic module angle is expressed as follows: ;

[0023] in, This indicates the predicted irradiance value. This represents the predicted wind speed value, and this represents the real-time ambient temperature. This indicates the adjustment amount of the solar incidence angle in the previous period. These represent the preset maximum irradiance value, maximum ambient temperature value, and maximum wind speed value, respectively. These represent the weighting coefficients for the predicted irradiance value, predicted wind speed value, and real-time ambient temperature, respectively. This represents the coefficient of inertia.

[0024] Preferably, the control method further includes:

[0025] The tilt angle adjustment of the photovoltaic module per unit time is obtained based on the dynamic optimization model of the photovoltaic module angle. ;

[0026] Obtain the depreciation cost factor of the photovoltaic module. ;

[0027] An objective function is constructed based on the photovoltaic power generation capacity, tilt angle adjustment, and depreciation cost coefficient. .

[0028] A fuel cell vehicle control system for implementing the aforementioned fuel cell vehicle control method includes:

[0029] The parameter acquisition module is used to acquire the amount of hydrogen in the on-board hydrogen storage tank and the real-time light intensity.

[0030] The control module is used to determine whether the amount of hydrogen is greater than or equal to a preset hydrogen amount threshold. If so, the FCS is activated and the FCS supplies power to the fuel cell vehicle. If the amount of hydrogen is less than the preset hydrogen amount threshold, the fuel cell vehicle is controlled to enter a parking state, and it is determined whether the real-time light intensity is greater than a preset light intensity threshold.

[0031] The control module is also used to start the photovoltaic module when the real-time light intensity is greater than or equal to the preset light intensity threshold, and drive the PEM electrolyzer to produce hydrogen by generating electricity through the photovoltaic module; and to switch to V2X mode when the real-time light intensity is less than the preset light intensity threshold, and drive the PEM electrolyzer to produce hydrogen by generating electricity through the grid.

[0032] Preferably, the parameter acquisition module is further used to acquire the conversion efficiency, temperature coefficient, total effective light-receiving area, real-time irradiance, real-time ambient temperature, and solar incidence angle of the photovoltaic module, and the control system further includes:

[0033] Power prediction module, used to predict based on the conversion efficiency Temperature coefficient Total effective light-receiving area Real-time irradiance Real-time ambient temperature and the angle of solar incidence Constructing a photovoltaic power generation model The power generation of the photovoltaic module is predicted based on the photovoltaic power generation model.

[0034] Preferably, the control system further includes:

[0035] The angle optimization module is used to construct a dynamic optimization model for the photovoltaic module angle based on the predicted irradiance value, predicted wind speed value, real-time ambient temperature, and solar incidence angle. ;

[0036] in, This indicates the predicted irradiance value. This represents the predicted wind speed value, and this represents the real-time ambient temperature. This indicates the adjustment amount of the solar incidence angle in the previous period. These represent the preset maximum irradiance value, maximum ambient temperature value, and maximum wind speed value, respectively. These represent the weighting coefficients for the predicted irradiance value, predicted wind speed value, and real-time ambient temperature, respectively. This represents the coefficient of inertia.

[0037] Preferably, the control system further includes:

[0038] The objective function construction module is used to determine the photovoltaic power generation output. The amount of tilt adjustment of the photovoltaic module per unit time and the depreciation cost coefficient of photovoltaic modules Construct the objective function . Attached Figure Description

[0039] The invention will be further understood from the following description taken in conjunction with the accompanying drawings. The components in the drawings are not necessarily drawn to scale, but rather the emphasis is on illustrating the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0040] Figure 1 This is a schematic diagram of the overall process of a fuel cell vehicle control method according to an embodiment of the present invention;

[0041] Figure 2 This is a flowchart illustrating a fuel cell vehicle control method according to another embodiment of the present invention. Figure 1 ;

[0042] Figure 3 This is a flowchart illustrating a fuel cell vehicle control method according to another embodiment of the present invention. Figure 2 ;

[0043] Figure 4 This is a flowchart illustrating a fuel cell vehicle control method according to another embodiment of the present invention. Figure 3 ;

[0044] Figure 5 This is a schematic diagram of the overall structure of a fuel cell vehicle control system according to one embodiment of the present invention;

[0045] Figure 6 This is a schematic diagram of a fuel cell vehicle control system according to another embodiment of the present invention;

[0046] Figure 7 This is a flowchart illustrating a fuel cell vehicle control method according to another embodiment of the present invention. Figure 4 . Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to its embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the scope of protection of the invention.

[0048] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly attached to the other element or there may be an intervening element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only and do not represent the only possible implementation.

[0049] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0050] In this invention, "first" and "second" do not represent a specific quantity or order, but are merely used to distinguish names.

[0051] like Figure 1 As shown, an embodiment of the present invention provides a fuel cell vehicle control method, including the following steps:

[0052] S1. Obtain the amount of hydrogen in the on-board hydrogen storage tank, determine whether the amount of hydrogen is greater than or equal to a preset hydrogen amount threshold, and if so, start the FCS (Fuel Cell System) and let the FCS power the fuel cell vehicle.

[0053] Specifically, the preset hydrogen quantity threshold can be preset by technicians, for example, it can be set to 0.5kg or 1.0kg, etc.

[0054] S2, if the amount of hydrogen is less than a preset hydrogen amount threshold, then control the fuel cell vehicle to enter a parking state, collect the real-time light intensity and determine whether the real-time light intensity is greater than a preset light intensity threshold.

[0055] S3. If the real-time light intensity is greater than or equal to the preset light intensity threshold, the photovoltaic module is started, and the photovoltaic module generates electricity to drive the PEM (Proton Exchange Membrane) electrolyzer to produce hydrogen.

[0056] The photovoltaic module is preferably a photovoltaic panel. The photovoltaic module generates electricity to drive a PEM (Proton Exchange Membrane) electrolyzer to produce hydrogen until the amount of hydrogen in the hydrogen storage tank exceeds a preset hydrogen storage threshold, such as 2.0 kg or 2.5 kg.

[0057] S4. If the real-time light intensity is less than the preset light intensity threshold, switch to V2X (Vehicle-to-Everything) mode, drive the PEM electrolyzer to electrolyze hydrogen through the power grid, and realize bidirectional energy flow between the vehicle and the power grid.

[0058] In the aforementioned fuel cell vehicle control method, hydrogen production is achieved through an on-board PEM electrolyzer, realizing a closed loop of hydrogen production and storage, which improves the autonomy of the system's hydrogen supply. The collaborative operation of photovoltaic panels, fuel cells, and batteries supports intelligent switching across multiple scenarios, enhancing energy utilization efficiency. The interconnection between the vehicle and the power grid via V2X improves energy flexibility and utilization. Through multi-condition switching, the fuel cell vehicle system supports various scenarios such as long-term parking, driving, and camping, enhancing ease of use.

[0059] In other words, the fuel cell vehicle control method obtains and determines the amount of hydrogen in the on-board hydrogen storage tank, and switches to different working states according to different amounts of hydrogen, such as starting the photovoltaic module and switching to V2X mode to produce hydrogen by electrolysis in the PEM electrolyzer. This can solve the energy management and hydrogen supply problems of fuel cell vehicles under multiple working conditions and improve the intelligence level of energy management of fuel cell vehicles.

[0060] In one embodiment of the present invention, such as Figure 2 As shown, the control method further includes:

[0061] S5, obtain the conversion efficiency, temperature coefficient and total effective light-receiving area of ​​the photovoltaic module.

[0062] S6 obtains real-time irradiance, real-time ambient temperature, and solar incidence angle.

[0063] S7. Construct a photovoltaic power generation model based on the conversion efficiency, temperature coefficient, total effective light-receiving area, real-time irradiance, real-time ambient temperature, and solar incident angle.

[0064] S8, predict the power generation of the photovoltaic module based on the photovoltaic power generation model.

[0065] Preferably, the photovoltaic power generation model is expressed as follows: ;in, Indicates photovoltaic power generation capacity. Indicates conversion efficiency. Indicates the temperature coefficient. Indicates the total effective light-receiving area. Indicates real-time irradiance. Indicates the real-time ambient temperature. Indicates the angle of incidence of the sun.

[0066] The conversion efficiency is defined as the efficiency of the photovoltaic module under standard test conditions (irradiance 1000 W / m²). 2 The theoretical conversion efficiency at 25℃ and AM1.5 spectrum is typically 15%-25%, and is affected by factors such as material type (e.g., monocrystalline silicon, PERC, TOPCon) and manufacturing process. The total effective light-receiving area (m²) is also considered. 2 This includes both the front and back sides (if the photovoltaic module is a bifacial module). The real-time irradiance represents the solar radiation power received per unit time and per unit area (W / m²). 2 The dynamic range is typically 0-1200 W / m, influenced by weather, season, and geographical location. 2 The real-time irradiance can be monitored in real time by combining meteorological satellite data and ground sensors.

[0067] The temperature coefficient represents the linearity (% / ℃) of the photovoltaic module's conversion efficiency with temperature. It is typically negative (e.g., -0.3% / ℃ to -0.5% / ℃), indicating that for every 1℃ increase in temperature, the efficiency decreases by α%. Specifically, if the real-time ambient temperature is 30℃, α = -0.4% / ℃, then the efficiency correction term... =1+(-0.4)(30-25)=0.8, meaning the conversion efficiency decreases by 20%. The real-time ambient temperature refers to the air temperature (°C) of the photovoltaic module's operating environment, which can be monitored in real time via thermocouples or infrared sensors. The solar incidence angle refers to the angle (in degrees) between sunlight and the normal to the photovoltaic module.

[0068] The photovoltaic power generation model Irradiance and temperature compensation can be used to correct the real-time efficiency term by combining real-time irradiance and real-time ambient temperature. And angle optimization (using a solar tracing algorithm to adjust the solar incidence angle and maximize the value of cosθ).

[0069] The photovoltaic power generation model In this system, through the synergistic effect of variables including real-time irradiance and solar incidence angle, high-precision prediction and dynamic optimization of photovoltaic module power generation can be achieved.

[0070] In one embodiment of the present invention, such as Figure 3 As shown, the control method further includes:

[0071] S9, Obtain weather forecast data, and obtain the predicted irradiance value and predicted wind speed value for the future time period based on the weather forecast data.

[0072] S10, construct a dynamic optimization model for the photovoltaic module angle based on the predicted irradiance value, predicted wind speed value, real-time ambient temperature, and solar incidence angle.

[0073] Preferably, the dynamic optimization model for the photovoltaic module angle is expressed as follows: ;in, This indicates the predicted irradiance value. This represents the predicted wind speed value, and this represents the real-time ambient temperature. This indicates the adjustment amount of the solar incidence angle in the previous period. These represent the preset maximum irradiance value, maximum ambient temperature value, and maximum wind speed value, respectively. These represent the weighting coefficients for the predicted irradiance value, predicted wind speed value, and real-time ambient temperature, respectively. This represents the coefficient of inertia.

[0074] Specifically, This represents the dynamically optimized solar incidence angle in degrees, which must satisfy mechanical constraints. , These represent the preset minimum and maximum solar incidence angles, respectively. The predicted irradiance value represents the predicted irradiance (W / m²) for the future period. 2 Wind speeds, which can be obtained through numerical weather prediction or machine learning models, are used to assess mechanical stability risks. As a normalization parameter, it is used to unify the dimensions. The inertia coefficient is used to control the smoothness of angle changes, and it is usually taken as 0.1-0.3.

[0075] for LSTM neural networks can be used to predict weather patterns for the next 3 hours and dynamically update them. The value. For example, during thunderstorms. Increasing the value (e.g., to 0.6 or 0.7) allows the photovoltaic module angle dynamic optimization model to prioritize avoiding mechanical risks.

[0076] In this embodiment, the dynamically optimized solar incidence angle can be solved using gradient descent or a genetic algorithm. By using argmin(1 / cosθ) which is equivalent to maximizing cosθ, the power generation of the photovoltaic module can be maximized; while limiting... If the range of change (e.g., a single adjustment ≤ 5°) is sufficient, the motor life can be extended and the mechanical loss of the system can be minimized.

[0077] The photovoltaic module angle dynamic optimization model integrates weather forecasting, module characteristics, and mechanical constraints to achieve synergistic optimization of power generation efficiency and equipment reliability, which can improve the overall power generation compared with the traditional fixed angle scheme.

[0078] In one embodiment of the present invention, such as Figure 4 As shown, the control method further includes:

[0079] S11, Obtain the tilt angle adjustment of the photovoltaic module per unit time based on the dynamic optimization model of the photovoltaic module angle. ;

[0080] S12, Obtain the depreciation cost coefficient of the photovoltaic module. ;

[0081] S13, construct an objective function based on the photovoltaic power generation capacity, tilt angle adjustment amount, and depreciation cost coefficient. .

[0082] In this objective function, a positive term represents power generation revenue, while a negative term represents loss costs. The optimal tilt angle adjustment can be determined using gradient descent or a genetic algorithm. The tilt adjustment amount can be obtained by acquiring the angle change signal of the photovoltaic module through an angle sensor. The angle change signal can be filtered by a Kalman filter to suppress the angle jitter caused by sensor noise and smooth the control signal.

[0083] The depreciation cost factor can be obtained through regression analysis of historical maintenance data. Preferably, ;in, This represents the tilt adjustment per unit time in historical maintenance data. This represents the cumulative tilt angle adjustment (total adjustment angle during system operation), characterizing the long-term wear accumulation effect. It represents the instantaneous loss coefficient of a single adjustment, characterizing the impact effect of sudden angle changes on mechanical components. It is determined by regression using the least squares method or gradient descent method, or set by technicians based on experience. The long-term attenuation coefficient, representing cumulative wear, reflects the erosive effect of total adjustment on lifespan and can be set by technicians based on experience.

[0084] The depreciation cost factor It can dynamically reflect the real-time loss status of the mechanical system, quantify the nonlinear relationship between the mechanical loss cost coefficient k and the tilt angle adjustment, and provide a quantitative basis for the optimization of the objective function.

[0085] The objective function achieves a dynamic balance between the efficiency and lifespan of the control system by balancing power generation revenue and mechanical loss costs. This not only increases the overall power generation of the system but also extends the lifespan of the system's mechanical components.

[0086] like Figure 7 As shown, one embodiment of the present invention also provides a fuel cell vehicle control method, which includes energy management and hydrogen production processes:

[0087] 1. System Start-up: The system first checks whether the amount of hydrogen in the hydrogen storage tank is greater than 0.5 kg. If the hydrogen is sufficient (≥0.5 kg), the fuel cell system (FCS) starts, providing power to the vehicle, and the vehicle enters driving mode; if the hydrogen is insufficient, the vehicle enters parking mode.

[0088] 2. Energy management during parking:

[0089] Detect whether there is light in the current environment.

[0090] With sunlight: The photovoltaic panels start up, supplying power to the electrolyzer to produce hydrogen. When the hydrogen storage reaches 2 kg or sunlight is insufficient, the photovoltaic system shuts down and the vehicle enters driving mode.

[0091] No light: The system switches to V2X mode and produces hydrogen via grid power. When the hydrogen storage reaches 2 kg, the V2X interface is shut off, and the vehicle is ready to move.

[0092] 3. Driving status: Once the hydrogen reserve reaches 2 kg, the system stops producing hydrogen, and the vehicle enters driving status, powered by the fuel cell system.

[0093] The system works in concert with photovoltaic panels, V2X interface and electrolysis hydrogen production system to ensure that vehicles can intelligently replenish hydrogen when hydrogen reserves are low and achieve efficient energy management under various operating conditions.

[0094] like Figure 5 As shown, an embodiment of the present invention also provides a fuel cell vehicle control system for implementing the aforementioned fuel cell vehicle control method, including a parameter acquisition module and a control module.

[0095] The parameter acquisition module is used to acquire the amount of hydrogen in the on-board hydrogen storage tank and the real-time light intensity; the control module is used to determine whether the amount of hydrogen is greater than or equal to a preset hydrogen amount threshold. If so, the FCS is activated and the FCS supplies power to the fuel cell vehicle. If the amount of hydrogen is less than the preset hydrogen amount threshold, the fuel cell vehicle is controlled to enter a parking state, and the real-time light intensity is determined to be greater than a preset light intensity threshold.

[0096] The control module is also used to start the photovoltaic module when the real-time light intensity is greater than or equal to the preset light intensity threshold, and drive the PEM electrolyzer to produce hydrogen by generating electricity through the photovoltaic module; and to switch to V2X mode when the real-time light intensity is less than the preset light intensity threshold, and drive the PEM electrolyzer to produce hydrogen by generating electricity through the grid.

[0097] Specifically, the PEM electrolyzer has a power of 76.5 kW and a hydrogen production rate of 15 Nm / h. The rationale for this selection is that to produce 1 kg of hydrogen per hour, a 76.5 kW PEM electrolyzer is required, providing approximately 2.55 m³ / h of hydrogen. 2 The electrode area. This type of electrolyzer has a hydrogen production rate of approximately 15 Nm³ / h and a total volume of 0.36 m³. 3 The PEM electrolyzer can be placed in the trunk of a fuel cell vehicle, with some space left for other equipment, which can fully meet the needs and ensure the continuity of vehicle operation.

[0098] The control system also includes a compressor that compresses hydrogen gas from 10 MPa to 35 MPa at a flow rate of 15 Nm / h. The compressor's power requirement is approximately 0.7 kW, making a small multi-stage booster pump suitable. The compressor's output pressure is 35 MPa, chosen because it ensures that 5 kg of hydrogen gas can be stored in a high-pressure tank, reducing volume requirements.

[0099] The hydrogen storage tank has a capacity of 5kg of hydrogen, and the energy density of hydrogen is 33.33kWh / kg. It provides 5kg of hydrogen, which can provide 5kg × 33.33kWh / kg = 166.65kWh of energy. The 5kg of hydrogen storage can provide the vehicle with a range of at least 500km, meeting the needs of daily travel and camping, while reducing the volume of the hydrogen storage tank and saving interior space.

[0100] The fuel cell system (FCS) has a power output of 100 kW and is used to provide vehicle drive and power. The control system also includes a 2 kWh battery system for vehicle starting, power compensation during rapid acceleration and deceleration, and regenerative braking.

[0101] The photovoltaic module uses perovskite-silicon tandem solar cells, achieving an efficiency of over 40%. Its advantages include reduced installation area, allowing for efficient power generation even on smaller vehicle roofs or body surfaces. The photovoltaic module can be installed using a modular photovoltaic panel method, dividing a 100-square-meter panel into several smaller pieces that can be unfolded separately as needed and supported using roof, trunk, or side tent brackets. The area of ​​the photovoltaic module is 100m². 2 Power generation capacity: 400W / m 2 Daily power generation: 100m³ 2 ×400W / m 2 ×5h=200kWh.

[0102] By utilizing vehicle-to-grid (V2G) charging technology, vehicles can connect to the grid to produce hydrogen when parked or during off-peak electricity prices, enabling bidirectional energy flow between vehicles and the grid.

[0103] The control system also includes a 100L water tank. 75Nm 3 The hydrogen produced requires approximately 60.26 kg of water. Water consumption during the electrolysis process is typically slightly higher than the theoretical value because some water is also needed for cooling and removing impurities from the system; this water is generated during the operation of the fuel cell system. Therefore, a practical system requires 65-70 kg of water to ensure continuous operation.

[0104] The water tank has a volume of 0.5m × 0.4m × 0.5m = 0.1m. 3 The specific dimensions of the water tank can be determined based on the space available in the vehicle; a rectangular shape would be more appropriate.

[0105] In the fuel cell vehicle control system, the photovoltaic power generation process is as follows: The system uses modular photovoltaic panels with a total area of ​​100m². 2 The photovoltaic panels were divided into several smaller pieces and installed on the roof, trunk, and side tent supports of the vehicle. The power generation efficiency of the photovoltaic panels was set at 400W / m². 2Under ideal lighting conditions (5 hours per day): Photovoltaic power generation E 光伏 =100m 2 ×400W / m 2 ×5h=200kWh.

[0106] The photovoltaic power supply process is as follows: When there is sufficient sunlight, the photovoltaic module prioritizes powering the PEM electrolyzer for hydrogen production. If there is insufficient sunlight, the system prompts the user to switch to V2X mode and use grid power.

[0107] Hydrogen production process: The reaction equation for the PEM electrolyzer is: One mole of water (18g) is needed to produce one mole of hydrogen gas.

[0108] Hydrogen production capacity calculation: To produce 15 Nm³ / h of hydrogen, the following is required: The required water volume is 670mol × 18g / mol = 12.06kg / h.

[0109] The hydrogen compression process is as follows: hydrogen is compressed from 10 MPa to 35 MPa, and per Nm³... 3 The energy consumption of hydrogen is approximately 0.7 kW: P 压缩 =0.7kW×15Nm3 / h=10.5kW.

[0110] The fuel cell power generation process is as follows: The fuel cell converts the energy of 5 kg of hydrogen into electrical energy (assuming an efficiency of 60%). 输出 =166.65kWh×0.6=99.99kWh, which is sufficient to support the vehicle's long-term operation or power supply.

[0111] The workflow of the fuel cell vehicle control system is as follows:

[0112] 1. System startup: Check if the hydrogen in the hydrogen storage tank is below 0.5 kg. If it is insufficient, enter hydrogen production mode.

[0113] 2. Hydrogen production mode: The PEM electrolyzer is started, the compressor compresses the hydrogen to 35MPa and stores it in a 5kg hydrogen storage tank;

[0114] 3. Driving mode: The fuel cell provides driving power and charges the battery through fuel cell power generation or braking energy recovery system;

[0115] 4. Camping mode: Photovoltaic panels power the PEM electrolyzer to produce and store hydrogen.

[0116] 5. V2X mode: Bidirectional energy exchange occurs when the vehicle is connected to the power grid.

[0117] In summary, the fuel cell vehicle control system acquires and determines the amount of hydrogen in the onboard hydrogen storage tank, and switches to different operating states based on the different amounts of hydrogen, such as activating the photovoltaic module and switching to V2X mode for PEM electrolysis to produce hydrogen. This solves the energy management and hydrogen supply problems of fuel cell vehicles under multiple operating conditions and improves the intelligence level of energy management of fuel cell vehicles.

[0118] In one embodiment of the present invention, such as Figure 6 The fuel cell vehicle control system, through the integration of the fuel cell (FCS), PEM electrolyzer, compressor, hydrogen storage tank, photovoltaic module, battery system BAT, and V2X interface, achieves energy self-sufficiency and efficient management of the vehicle, as detailed below:

[0119] 1. Hydrogen Production and Storage: The photovoltaic module generates electricity from solar power or obtains power from the grid via a V2X interface. The alternating current (AC) is converted to direct current (DC) through a transformer and AC / DC converter to power the electrolyzer. The electrolyzer uses water to produce hydrogen, partly from the recovery of the water produced in the reaction. The generated hydrogen is compressed to 35 MPa by a 0.7 kW compressor and stored in a high-pressure hydrogen cylinder for use in fuel cells.

[0120] 2. Fuel Cell Power Generation: During operation, hydrogen enters the 100kW fuel cell system (FCS) from the hydrogen storage tank, reacts with oxygen to generate electricity, and the resulting reaction water flows back to the water tank. The electricity generated by the fuel cell is converted into the electrical energy required to drive the motor via an inverter, propelling the vehicle forward.

[0121] 3. Battery System and Auxiliary Energy Management: Excess electrical energy from the fuel cell is stored in the 2kWh battery system for use during startup or short-term acceleration. The battery system, fuel cell, and electric motor are bidirectionally charged and discharged via a DC / DC converter module.

[0122] 4. Energy Interaction and V2X Mode: When parked or camping, the vehicle exchanges energy with the power grid or other devices through the V2X interface to achieve energy feedback and external power supply.

[0123] In summary, the fuel cell vehicle control system can achieve the following:

[0124] 1. Energy self-sufficiency: A closed-loop system for hydrogen production and storage is achieved by integrating photovoltaic cells with electrolyzers and hydrogen storage tanks.

[0125] 2. Multi-scenario adaptability: Supports different working conditions such as long-distance driving, camping, and parking.

[0126] 3. Efficient energy interaction: V2X technology makes energy utilization between vehicles and the power grid more flexible.

[0127] 4. Reduce reliance on hydrogen refueling stations: Onboard hydrogen production capabilities improve vehicle range and autonomy.

[0128] In one embodiment of the present invention, the parameter acquisition module is further used to acquire the conversion efficiency, temperature coefficient, total effective light-receiving area, real-time irradiance, real-time ambient temperature and solar incident angle of the photovoltaic module, and the control system further includes a power prediction module.

[0129] The power prediction module is used to predict the conversion efficiency. Temperature coefficient Total effective light-receiving area Real-time irradiance Real-time ambient temperature and the angle of solar incidence Constructing a photovoltaic power generation model The power generation of the photovoltaic module is predicted based on the photovoltaic power generation model.

[0130] The photovoltaic power generation model In this system, through the synergistic effect of variables including real-time irradiance and solar incidence angle, high-precision prediction and dynamic optimization of photovoltaic module power generation can be achieved.

[0131] In one embodiment of the present invention, the control system further includes an angle optimization module.

[0132] The angle optimization module is used to construct a dynamic optimization model for the photovoltaic module angle based on the predicted irradiance value, predicted wind speed value, real-time ambient temperature, and solar incidence angle. ;in, This indicates the predicted irradiance value. This represents the predicted wind speed value, and this represents the real-time ambient temperature. This indicates the adjustment amount of the solar incidence angle in the previous period. These represent the preset maximum irradiance value, maximum ambient temperature value, and maximum wind speed value, respectively. These represent the weighting coefficients for the predicted irradiance value, predicted wind speed value, and real-time ambient temperature, respectively. This represents the coefficient of inertia.

[0133] The dynamically optimized solar incidence angle can be solved using gradient descent or a genetic algorithm. Maximizing the photovoltaic module's power generation can be achieved by using argmin(1 / cosθ), which is equivalent to maximizing cosθ; while limiting... If the range of change (e.g., a single adjustment ≤ 5°) is sufficient, the motor life can be extended and the mechanical loss of the system can be minimized.

[0134] The photovoltaic module angle dynamic optimization model integrates weather forecasting, module characteristics, and mechanical constraints to achieve synergistic optimization of power generation efficiency and equipment reliability, which can improve the overall power generation compared with the traditional fixed angle scheme.

[0135] In one embodiment of the present invention, the control system further includes an objective function construction module.

[0136] The objective function construction module is used to determine the photovoltaic power generation output. The amount of tilt adjustment of the photovoltaic module per unit time and the depreciation cost coefficient of photovoltaic modules Construct the objective function .

[0137] The depreciation cost factor It can dynamically reflect the real-time loss status of the mechanical system, quantify the nonlinear relationship between the mechanical loss cost coefficient k and the tilt angle adjustment, and provide a quantitative basis for the optimization of the objective function.

[0138] The objective function achieves dynamic control of system efficiency and lifespan by balancing power generation revenue and mechanical loss costs.

[0139] In summary, the fuel cell vehicle control method and system described above have the following beneficial effects:

[0140] 1. Energy self-sufficiency: A closed-loop system for hydrogen production and storage is achieved by integrating photovoltaic cells with electrolyzers and hydrogen storage tanks.

[0141] 2. Multi-scenario adaptability: Supports different working conditions such as long-distance driving, camping, and parking.

[0142] 3. Efficient energy interaction: V2X technology makes energy utilization between vehicles and the power grid more flexible.

[0143] 4. Reduce reliance on hydrogen refueling stations: Onboard hydrogen production capabilities improve vehicle range and autonomy.

[0144] 5. By combining variables such as real-time irradiance and solar incidence angle, high-precision prediction and dynamic optimization of photovoltaic module power generation can be achieved.

[0145] 6. By integrating weather forecasting, module characteristics, and mechanical constraints, the system achieves synergistic optimization of power generation efficiency and equipment reliability, which can improve overall power generation compared to the traditional fixed-angle solution.

[0146] 7. The objective function achieves dynamic control of the system efficiency and lifespan by balancing power generation revenue and mechanical loss costs.

[0147] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0148] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A fuel cell vehicle control method characterized by comprising: The control method includes: The amount of hydrogen in the on-board hydrogen storage tank is obtained, and it is determined whether the amount of hydrogen is greater than or equal to a preset hydrogen amount threshold. If so, the FCS is activated and the FCS supplies power to the fuel cell vehicle. If the amount of hydrogen is less than a preset hydrogen amount threshold, the fuel cell vehicle is controlled to enter a parking state, and the real-time light intensity is collected and it is determined whether the real-time light intensity is greater than a preset light intensity threshold. If the real-time light intensity is greater than or equal to the preset light intensity threshold, the photovoltaic module is activated, and the photovoltaic module generates electricity to drive the PEM electrolyzer to electrolyze hydrogen. If the real-time light intensity is less than the preset light intensity threshold, switch to V2X mode and drive the PEM electrolyzer to produce hydrogen by electrolysis through grid power supply. The control method further includes: Obtain the conversion efficiency, temperature coefficient, and total effective light-receiving area of ​​the photovoltaic module; Acquire real-time irradiance, real-time ambient temperature, and solar incidence angle; A photovoltaic power generation model is constructed based on the conversion efficiency, temperature coefficient, total effective light-receiving area, real-time irradiance, real-time ambient temperature, and solar incidence angle. The power generation of the photovoltaic module is predicted based on the photovoltaic power generation model. Obtain weather forecast data, and based on the weather forecast data, obtain the predicted irradiance value and predicted wind speed value for the future time period; A dynamic optimization model for the photovoltaic module angle is constructed based on the predicted irradiance value, predicted wind speed value, real-time ambient temperature, and solar incidence angle. The tilt angle adjustment of the photovoltaic module per unit time is obtained based on the dynamic optimization model of the photovoltaic module angle. ; Obtain the depreciation cost factor of the photovoltaic module. ; An objective function is constructed based on the photovoltaic power generation capacity, tilt angle adjustment amount, and depreciation cost coefficient. ; in, Indicates photovoltaic power generation capacity. , This represents the tilt adjustment per unit time in historical maintenance data. This indicates the cumulative tilt adjustment. This represents the instantaneous loss coefficient for a single adjustment. This represents the long-term attenuation coefficient of cumulative wear.

2. The fuel cell vehicle control method as described in claim 1, characterized in that, The photovoltaic power generation model is expressed as follows: ; in, Indicates conversion efficiency. Indicates the temperature coefficient. Indicates the total effective light-receiving area. Indicates real-time irradiance. Indicates the real-time ambient temperature. Indicates the angle of incidence of the sun.

3. The fuel cell vehicle control method as described in claim 2, characterized in that, The dynamic optimization model for the photovoltaic module angle is expressed as follows: ; in, This indicates the predicted irradiance value. This represents the predicted wind speed, and this represents the real-time ambient temperature. This indicates the adjustment amount of the solar incidence angle in the previous period. These represent the preset maximum irradiance value, maximum ambient temperature value, and maximum wind speed value, respectively. These represent the weighting coefficients for the predicted irradiance value, predicted wind speed value, and real-time ambient temperature, respectively. This represents the coefficient of inertia.

4. A fuel cell vehicle control system for implementing the fuel cell vehicle control method as described in any one of claims 1-3, characterized in that, The control system includes: The parameter acquisition module is used to acquire the amount of hydrogen in the on-board hydrogen storage tank and the real-time light intensity. The control module is used to determine whether the amount of hydrogen is greater than or equal to a preset hydrogen amount threshold. If so, the FCS is activated and the FCS supplies power to the fuel cell vehicle. If the amount of hydrogen is less than the preset hydrogen amount threshold, the fuel cell vehicle is controlled to enter a parking state, and it is determined whether the real-time light intensity is greater than a preset light intensity threshold. The control module is also used to start the photovoltaic module when the real-time light intensity is greater than or equal to the preset light intensity threshold, and drive the PEM electrolyzer to produce hydrogen by generating electricity through the photovoltaic module; and to switch to V2X mode when the real-time light intensity is less than the preset light intensity threshold, and drive the PEM electrolyzer to produce hydrogen by generating electricity through the grid.

5. A fuel cell vehicle control system as described in claim 4, characterized in that, The parameter acquisition module is also used to acquire the conversion efficiency, temperature coefficient, total effective light-receiving area, real-time irradiance, real-time ambient temperature, and solar incidence angle of the photovoltaic module. The control system further includes: Power prediction module, used to predict based on the conversion efficiency Temperature coefficient Total effective light-receiving area Real-time irradiance Real-time ambient temperature and the angle of incidence of the sun Constructing a photovoltaic power generation model The power generation of the photovoltaic module is predicted based on the photovoltaic power generation model.

6. A fuel cell vehicle control system as described in claim 5, characterized in that, The control system further includes: The angle optimization module is used to construct a dynamic optimization model for the photovoltaic module angle based on the predicted irradiance value, predicted wind speed value, real-time ambient temperature, and solar incidence angle. ; in, This indicates the predicted irradiance value. This represents the predicted wind speed, and this represents the real-time ambient temperature. This indicates the adjustment amount of the solar incidence angle in the previous period. These represent the preset maximum irradiance value, maximum ambient temperature value, and maximum wind speed value, respectively. These represent the weighting coefficients for the predicted irradiance value, predicted wind speed value, and real-time ambient temperature, respectively. This represents the coefficient of inertia.

7. A fuel cell vehicle control system as described in claim 6, characterized in that, The control system further includes: The objective function construction module is used to determine the photovoltaic power generation output. The amount of tilt adjustment of the photovoltaic module per unit time and the depreciation cost coefficient of photovoltaic modules Construct the objective function .

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