Vehicle-mounted hydrogen storage bottle filling method and device based on global temperature and pressure prediction

Abstract

The invention relates to a vehicle-mounted hydrogen storage bottle filling method and device based on global temperature and pressure prediction. By constructing a quasi-one-dimensional fluid model and combining mass flow, temperature and pressure parameters collected by an inlet sensor in real time, dynamic backstepping of axial temperature and pressure distribution in a single bottle is achieved. A finite volume method discrete conservation equation is utilized, a pressure weighting function is introduced to suppress numerical oscillation, and the filling flow is dynamically adjusted through a fuzzy PID controller according to the maximum temperature deviation to ensure that the local temperature is controllable. When the average temperature in the hydrogen storage bottle reaches a safety threshold value or the average pressure exceeds the nominal working pressure, the device automatically stops filling. Compared with the prior art, the hydrogen injection device has the advantages of safe and controllable hydrogen injection process, high practicability and the like.

Description

Technical Field

[0001] The present invention relates to the field of hydrogen injection technology, and in particular to a method and device for filling a vehicle-mounted hydrogen storage bottle based on global temperature and pressure prediction. Background Art

[0002] Currently, hydrogen trains, as a key vehicle for deep decarbonization in the transportation sector, face a critical technical bottleneck in ensuring the safety and efficiency of their onboard hydrogen storage systems. Gaseous hydrogen storage, due to its mature technology and convenient refueling, has become the preferred solution for onboard hydrogen storage. However, the significant temperature rise during hydrogen refueling poses a threat to the mechanical properties of the hydrogen storage bottle's composite materials. In particular, the problem of localized overheating in hydrogen storage bottles with high aspect ratios needs to be addressed urgently.

[0003] Compared with fuel cell vehicles, hydrogen trains generally use hydrogen storage bottles with large single-bottle capacity and a high aspect ratio (L / D ≥ 4) to meet the high hydrogen load requirements of long-distance transportation. During the refueling process, such hydrogen storage bottles have extremely uneven internal axial temperature distribution due to factors such as frictional heat generated by high-speed flow at the inlet and the conversion of gas compression work into internal energy. Local temperatures can easily exceed the material safety threshold (such as 85°C). The slender geometric structure caused by the high aspect ratio exacerbates this problem: the flow velocity gradient near the inlet is large, the viscous dissipation is significant, and the heat dissipation at the bottom of the bottle lags, resulting in an asymmetric distribution of the temperature field with "sudden rise at the inlet and lag at the bottom of the bottle". The simplified model based on the traditional uniform temperature rise assumption can no longer accurately capture the risk of local overheating.

[0004] Traditional solutions rely on arranging distributed temperature sensors inside hydrogen storage bottles for real-time monitoring. However, the slender structure of the bottle with a high aspect ratio makes sensor wiring difficult and maintenance costs high. In addition, installing sensors inside the hydrogen storage bottle will weaken the structural strength of the bottle, making it unsuitable for compact vehicle-mounted scenarios.

[0005] In summary, the current existing technologies generally have the problem that the temperature control of hydrogen bottles is difficult to monitor and is not safe during hydrogen filling. There is still a lack of practical, safe and controllable hydrogen filling methods to prevent local overheating of hydrogen storage bottles. Summary of the Invention

[0006] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide a method and device for filling a vehicle-mounted hydrogen storage bottle based on global temperature and pressure prediction.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] According to one aspect of the present invention, a method for filling a vehicle-mounted hydrogen storage tank based on global temperature and pressure prediction is provided, the method comprising the following steps:

[0009] S1. Real-time acquisition of hydrogen filling inlet parameters, including inlet flow, inlet temperature, and inlet pressure;

[0010] S2. Construct an axial one-dimensional unsteady-state model based on the inlet parameters and solve the model to dynamically infer the axial temperature and pressure distribution in the hydrogen bottle;

[0011] S3. Setting a safety temperature threshold and dynamically adjusting the hydrogen filling flow rate based on the safety temperature threshold and the highest temperature value in the axial temperature distribution;

[0012] S4. If the temperature distribution and the pressure distribution meet any preset stop condition, the filling is stopped.

[0013] As a preferred technical solution, the steps for constructing and solving the axial one-dimensional unsteady-state model in S2 include:

[0014] S21, constructing boundary conditions from inlet parameters;

[0015] S22. Establishing axial simplified forms of the mass conservation equation, momentum conservation equation, and energy conservation equation based on the inlet parameters;

[0016] S23, discretizing the equation established in S22 by a finite volume method to obtain a discrete model;

[0017] S24. Solve the discrete model in real time based on boundary conditions.

[0018] As a preferred technical solution, the boundary conditions in S21 include the density, temperature and velocity at the device inlet, i.e., x=0, at time t; wherein the density is calculated from the inlet parameters, the temperature is the inlet temperature obtained by real-time acquisition and reading, and the velocity is calculated from the inlet density, flow rate and cross-sectional area, and the product of density, velocity and cross-sectional area is derived; the specific formula is:

[0019] ρ(0,t)=ρ in ;

[0020] T(0,t)=T in ;

[0021]

[0022] Where: in is the entrance density; T in is the inlet temperature; is the inlet mass flow rate; A inlet is the inlet cross-sectional area; n is the amount of gas substance; M is the molar mass of the gas; t is time; R is the universal gas constant; V is the gas volume; a and b are van der Waals constants, a reflects the strength of the gravitational interaction between gas molecules, and b reflects the volume of the gas molecules themselves.

[0023] As a preferred technical solution, the specific formulas of the axial simplified forms of the mass conservation equation, momentum conservation equation, and energy conservation equation in S22 are:

[0024]

[0025] U = [ρ, ρu, ρE];

[0026] Where Ω is the preselected spatial region in the flow field; U is the conserved variable, ρ is the density, ρu is the momentum, u is the velocity, and ρE is the energy; F is the flux term; S is the source term; n is the unit external normal vector; and ds is the infinitesimal area of ​​the control volume surface.

[0027] As a preferred technical solution, S23 specifically discretizes the spatial term and the time term of the equation, and the specific formula of the obtained discrete model is:

[0028]

[0029] in, is the value of the conserved variable at spatial position i and time step n, i is used to identify the node position after spatial discretization, and n is used to identify the time step after time discretization; Δt is the time step; Δx is the spatial step; is the flux value at spatial position i+1 / 2 and time step n+θ; is the flux value at spatial position i-1 / 2 and time step n+θ; θ∈[0,1] is the implicit weight factor; is the source term at spatial position i and time step n.

[0030] As a preferred technical solution, when the discrete model is solved in real time based on the boundary conditions in S24, the solution is specifically solved by numerical flux calculation. During the solution process, the pressure weight function is introduced to calculate the virtual pressure. The specific formula is:

[0031] p face =f p (M L )p L +f p (M R )p R +β·ρ avg a avg (u R -u L );

[0032] Among them, p face is the virtual pressure; M L is the dimensionless Mach number of the state on the left side of the interface; M R is the dimensionless Mach number of the state on the right side of the interface; p L and p Rare the pressures on the left and right sides of the interface respectively; β is the pressure diffusion coefficient, ρ avg 、a avg is the average density and average sound speed of the interface; u L and u R are the fluid velocities on the left and right sides of the interface, respectively.

[0033] As an optimal technical solution, the time step is dynamically adjusted based on the local CFL condition and the error estimator during the solution process. At the same time, the entropy correction function is introduced during the solution process. The specific formula is:

[0034]

[0035] Where Δt new is the updated time step; CFL is the Courant number, a dimensionless number used to describe the relationship between the time step, spatial compensation, and fluid velocity; Δx is the spatial step; u is the fluid velocity; a is the local sound speed; U is the conserved variable; ∈ is the tolerance error, R is the residual norm; Φ(M) is the entropy correction function; M is the Mach number; δ is a small quantity.

[0036] As a preferred technical solution, the specific formula for dynamically adjusting the hydrogen filling flow rate based on the safety temperature threshold and the highest temperature value in the axial temperature distribution in S3 is:

[0037] ΔT=T safe -T max (t);

[0038]

[0039] in, is the hydrogen flow rate at time t; ΔT is the temperature deviation; T max (t) is the current extreme point of the temperature field; T safe is the preset safety temperature threshold; K p is the proportional coefficient; K i is the integral coefficient; K d is the differential coefficient.

[0040] As a preferred technical solution, the preset stop condition in S4 includes:

[0041] (1) The real-time average temperature inside the hydrogen storage bottle is greater than or equal to the preset safety temperature;

[0042] (2) The real-time average pressure in the hydrogen storage bottle is greater than or equal to the nominal working pressure of the hydrogen storage bottle;

[0043] The real-time average temperature and real-time average pressure are calculated from the axial temperature distribution and pressure distribution in the hydrogen bottle, respectively.

[0044] According to another aspect of the present invention, there is provided an on-vehicle hydrogen storage bottle filling device based on global temperature and pressure prediction, the device comprising a sensor module, a control module and an electric regulating valve 2;

[0045] The sensing module includes an inlet flow meter 3, a temperature sensor 4 and a pressure sensor 5, which are used to obtain the inlet parameters of hydrogen filling in real time, including inlet flow, inlet temperature and inlet pressure;

[0046] The control module is an embedded controller 1, which has a built-in axial one-dimensional model solving module, which is used to solve the axial one-dimensional unsteady-state model, dynamically infer the axial temperature distribution in the hydrogen bottle, and calculate the hydrogen filling flow rate based on the safety temperature value and the highest temperature value in the axial temperature distribution, and output controller instructions;

[0047] The electric regulating valve 2 is used to adjust the hydrogen filling flow according to the controller instructions.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] 1. The present invention obtains hydrogen refueling inlet parameters, including inlet flow rate, inlet temperature, and inlet pressure, in real time. This means that only three sensors, namely mass, temperature, and pressure, need to be installed at the inlet. The temperature and pressure distribution within the bottle can be inferred using a one-dimensional fluid model, eliminating the need for distributed sensors within the hydrogen storage bottle. This design reduces the complexity of in-bottle wiring and sensor maintenance, reducing hardware costs by approximately 66% compared to traditional solutions. It also avoids the impact of sensors on the structural strength of the hydrogen storage bottle, making it particularly suitable for the compact layout of high-aspect-ratio hydrogen storage bottles. This solves the problem of difficult and unsafe hydrogen bottle temperature monitoring during hydrogen refueling, making the hydrogen injection process safe, controllable, and highly practical.

[0050] 2. In the present invention, in order to solve the problem of uneven temperature in the hydrogen storage bottle, an axial one-dimensional fluid model is constructed. First, the axial simplified forms of the mass conservation equation, momentum conservation equation and energy conservation equation are constructed, and then the finite volume method is used to discretize the spatial terms and time terms of the equations to achieve millisecond-level real-time calculation; the complex three-dimensional fluid problem is simplified into an axial one-dimensional model, combined with the mass, momentum and energy conservation equations to reduce the computational complexity, and at the same time, the finite volume method is used for discretization processing to ensure the high efficiency of the model in real-time calculation, which is suitable for the rapid response requirements of the vehicle environment; and in the discretization process, an implicit weight factor is introduced to balance the calculation stability and accuracy, so that the model can accurately capture local temperature changes and support high-frequency control (1kHz).

[0051] 3. In the present invention, in the process of constructing the axial one-dimensional fluid model, the boundary conditions are first constructed, the calculation method of the density, temperature, and velocity at the inlet is clarified, and the van der Waals equation is introduced to correct the actual gas properties, so that the model is closer to the real physical behavior of hydrogen, and the accuracy of temperature and pressure prediction is improved. It is especially suitable for compensating for non-ideal gas characteristics in high-pressure filling scenarios.

[0052] 4. In the present invention, when the discrete model is solved in real time based on the boundary conditions, the solution is specifically performed through numerical flux calculation. During the solution process, a pressure weight function is introduced to calculate the virtual pressure, thereby suppressing numerical oscillations and ensuring the calculation stability under extreme working conditions such as high pressure and high-speed filling, providing a reliable basis for the control strategy.

[0053] 5. This invention uses a local CFL condition and an error estimator to adjust the step size in real time, ensuring computational stability while adapting to dramatic changes in flow rate and pressure during the injection process, reducing computational time. By introducing the Mach number to suppress nonphysical oscillations, the entropy conservation of the solution is ensured, improving the reliability of the solution under high-temperature and high-pressure conditions.

[0054] 6. This invention utilizes a fuzzy PID controller to dynamically adjust the filling flow rate based on the model's predicted maximum temperature inside the bottle. When the temperature approaches a safety threshold, the system automatically reduces the flow rate to prevent local overheating. Flow rate optimization shortens filling time during the initial and mid-stage filling phases. This effectively protects the hydrogen storage bottle's material properties while balancing hydrogen filling efficiency and safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 Schematic diagram of the steps of a method for filling a vehicle-mounted hydrogen storage bottle based on global temperature and pressure prediction in the present invention;

[0056] Figure 2 Schematic diagram of a vehicle-mounted hydrogen storage bottle filling device based on global temperature and pressure prediction in the present invention;

[0057] Figure 3 Flowchart of a method for filling a vehicle-mounted hydrogen storage bottle based on global temperature and pressure prediction in an embodiment;

[0058] Figure 4 Schematic diagram of the fuzzy PID controller structure in the embodiment

[0059] Figure 5a is a pressure distribution diagram output in the embodiment;

[0060] Figure 5b : is the temperature distribution diagram output in the embodiment;

[0061] In the figure, 1 is an embedded controller, 2 is an electric regulating valve, 3 is an inlet flow meter, 4 is a temperature sensor, and 5 is a pressure sensor. DETAILED DESCRIPTION

[0062] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0063] Example 1

[0064] In this embodiment, a method for filling a vehicle-mounted hydrogen storage tank based on global temperature and pressure prediction is applied, and the method steps include:

[0065] S1. Real-time acquisition of hydrogen filling inlet parameters, including inlet flow, inlet temperature, and inlet pressure;

[0066] S2. Construct an axial one-dimensional unsteady-state model based on the inlet parameters and solve the model to dynamically infer the axial temperature and pressure distribution in the hydrogen bottle;

[0067] S3. Setting a safety temperature threshold and dynamically adjusting the hydrogen filling flow rate based on the safety temperature threshold and the highest temperature value in the axial temperature distribution;

[0068] S4. If the temperature distribution and the pressure distribution meet any preset stop condition, the filling is stopped.

[0069] The axial one-dimensional unsteady-state model in S2 can dynamically infer the temperature and pressure distribution within the hydrogen bottle, breaking the limitation of the traditional filling process that cannot grasp the detailed internal status of the hydrogen bottle in real time. By accurately predicting the axial temperature and pressure distribution within the hydrogen bottle, potential safety risk points, such as local overheating or excessive pressure areas, can be discovered in advance, providing a basis for timely adjustment of the filling strategy to avoid safety accidents caused by abnormal temperature and pressure. It also helps to improve the filling efficiency and hydrogen storage quality of the hydrogen storage bottle. Its construction and solution steps include:

[0070] S21, constructing boundary conditions from inlet parameters;

[0071] S22. Establishing axial simplified forms of the mass conservation equation, momentum conservation equation, and energy conservation equation based on the inlet parameters;

[0072] S23, discretizing the equation established in S22 by a finite volume method to obtain a discrete model;

[0073] S24. Solve the discrete model in real time based on boundary conditions.

[0074] In this embodiment, the implementation process is as follows Figure 3As shown, the initialization process is first performed: hardware calibration, collecting the on-board hydrogen storage bottle size information and converting it into model parameters, and initializing the field information.

[0075] Then, the inlet parameters are collected, including inlet flow, inlet temperature and inlet pressure; and the axial pressure distribution and temperature distribution in the hydrogen storage bottle are calculated;

[0076] Then carry out safety control and fuzzy PID adjustment;

[0077] Repeat the above steps except initialization until the stop condition is met.

[0078] In this embodiment, the configuration of the hydrogen storage bottle is as shown in Table 1. A type IV carbon fiber composite hydrogen storage bottle is selected, which has a volume of 150L, ​​a length of 1.6m, an outer diameter of 400mm, a nominal working pressure of 35MPa, and a safety temperature of 85°C. The filling conditions are specifically shown in Table 2.

[0079] Table 1 Hydrogen storage bottle configuration

[0080]

[0081] Table 2 Filling conditions

[0082]

[0083] First, initialize the software model:

[0084] (1) Obtain the size parameters of the on-board hydrogen storage bottle (length L, diameter D, hydrogen bottle type) and divide it into a one-dimensional grid with a spatial step size of dx = L / 500, and generate discrete nodes.

[0085] (2) Setting the initial field: including density, velocity and temperature;

[0086] ρ(x, 0) = ρ initial / (z*R*T inlet )≈2.5kg / m 3 ;

[0087] u(x,0)=0;

[0088] T(x,0)=T inlet =293K;

[0089] Where ρ is the density; ρ initial is the initial density; u is the velocity; T is the temperature; T inlet is the inlet temperature; then the inlet parameter acquisition is performed: real-time reading of the inlet mass flow Temperature T in , pressure P inThe system also performs real-time calculations. To address the uneven temperature problem within the hydrogen storage bottle, an axial one-dimensional fluid model is constructed. The finite volume method is used to discretize the equations, combined with high-order numerical formats and hardware acceleration technology to achieve millisecond-level real-time calculations. The model can accurately capture local temperature changes, support high-frequency control (1kHz), and suppress numerical oscillations through algorithm optimization, ensuring computational stability under extreme operating conditions such as high-pressure and high-speed refueling, providing reliable theoretical support for the control strategy. The model construction and solution process includes:

[0090] (1) Inlet density calculation: The inlet density is calculated based on the real gas state equation:

[0091]

[0092] Where: in is the inlet density; n is the amount of gas; is the inlet mass flow rate; M is the molar mass of the gas; t is the time; R is the universal gas constant; T in is the inlet temperature; V is the gas volume; a and b are van der Waals constants, a reflects the strength of the gravitational force between gas molecules, and b reflects the volume of the gas molecules themselves.

[0093] (2) Assignment of inlet boundary conditions: At time t, the gas density at the device inlet (position x = 0) is the inlet density calculated above, the temperature is the inlet temperature obtained by real-time acquisition, and the velocity is derived based on the mass flow rate being equal to the product of density, velocity, and cross-sectional area:

[0094] ρ(0,t)=ρ in ;

[0095] T(0,t)=T in ;

[0096]

[0097] Among them, ρ in is the entrance density; T in is the inlet temperature; is the inlet mass flow rate; A inlet is the inlet cross-sectional area.

[0098] (3) Construct a system of equations and integrate the conservation equations to the control volume:

[0099]

[0100] U = [ρ, ρu, ρE];

[0101] Where Ω is a fixed spatial region selected in the flow field; U is the conserved variable, ρ is the density, ρu is the momentum, u is the velocity, and ρE is the energy; F is the flux term; S is the source term (such as the viscosity term); n is the unit external normal vector; and ds is the infinitesimal area of ​​the control volume surface.

[0102] (4) Discretize the spatial and temporal terms to form the following format:

[0103]

[0104] in, is the value of the conserved variable at spatial position i and time step n, i is used to identify the node position after spatial discretization, and n is used to identify the time step after time discretization; Δt is the time step; Δx is the spatial step; is the flux value at spatial position i+1 / 2 and time step n+θ; is the flux value at spatial position i-1 / 2 and time step n+θ; θ∈[0,1] is the implicit weight factor. Here, a semi-implicit format (θ=0.5) is used; is the source term at spatial position i and time step n.

[0105] (5) Numerical flux calculation: Based on the local sound speed, the dimensionless Mach number of the left and right states of the interface is calculated.

[0106] The local speed of sound is:

[0107]

[0108] Where γ is the specific heat ratio; R is the gas constant; T i is the local temperature.

[0109] The dimensionless Mach number of the left and right states of the interface is:

[0110]

[0111] Among them, M L is the dimensionless Mach number of the state on the left side of the interface; u i is the fluid velocity at position i; a i is the local sound speed at position i; M R is the dimensionless Mach number of the state on the right side of the interface; u i+1 is the fluid velocity at position i+1; a i+1 is the local sound speed at position i+1.

[0112] Then introduce the pressure weight function f p (M) Suppress numerical oscillations:

[0113] p face =f p(M L )p L +f p (M R )p R +β·ρ avg a avg (u R -u L );

[0114] Among them, p face is the virtual pressure; M L is the dimensionless Mach number of the state on the left side of the interface; M R is the dimensionless Mach number of the state on the right side of the interface; p L and p R are the pressures on the left and right sides of the interface respectively; β is the pressure diffusion coefficient, ρ avg 、a avg is the average density and average sound speed of the interface; u L and u R are the fluid velocities on the left and right sides of the interface, respectively. In this embodiment, β is set to 0.1 to suppress the numerical fluctuation caused by the density gradient at the inlet.

[0115] (6) Numerical stability and error control: Based on the local CFL condition and the error estimator, Δt is dynamically adjusted. The CFL condition describes the relationship between the time step, the space step, and the fluid velocity, ensuring the stability of the numerical calculation. At the same time, an entropy correction function is introduced to ensure that the entropy increase condition is met in the low Mach number region, which is consistent with physical reality. The specific formula is as follows:

[0116]

[0117] Where, Δt new is the updated time step; CFL is the Courant number, a dimensionless number used to describe the relationship between the time step, spatial compensation, and fluid velocity; Δx is the spatial step; u is the fluid velocity; a is the local sound speed; U is the conserved variable; ∈ is the tolerance error, and R is the residual norm.

[0118]

[0119] Where Φ(M) is the entropy correction function; M is the Mach number; δ is a small positive number much smaller than 1. It is introduced to ensure that the entropy increase condition is met in the low Mach number region in the entropy correction function. The specific value needs to be determined according to the actual problem and the calculation accuracy requirements.

[0120] In this embodiment, the time step Δt is dynamically adjusted based on the CFL condition:

[0121] Δt=0.8×3.2×10 -3 / (0.305+542)≈4.7×10 -6 s;

[0122] Combined with the error estimation, we finally take: Δt = 1 × 10 -5 .

[0123] During the hydrogen injection process, safety control and flow regulation are performed, including: extracting the full-field temperature T(x,t) every 1s, locating the current temperature field extreme point T max (t); Set safety temperature T safe (such as 85℃); design a fuzzy PID controller, the structure of the fuzzy PID controller is as follows Figure 4 As shown, the mass flow rate is dynamically adjusted based on the temperature deviation. When the temperature approaches the safety threshold, the system automatically reduces the flow rate to avoid local overheating. In the early and middle stages of filling, the flow rate is optimized to shorten the filling time. The maximum temperature is controlled within the safety threshold ±4°C, effectively protecting the material properties of the hydrogen storage bottle and balancing efficiency and safety. The specific formula is:

[0124] ΔT=T safe -T max (t);

[0125]

[0126] in, is the hydrogen flow rate at time t; ΔT is the temperature deviation; T max (t) is the current extreme point of the temperature field; T safe is the preset safety temperature; K p is the proportional coefficient; K i is the integral coefficient; K d is the differential coefficient.

[0127] In this embodiment, when ΔT=5°C, based on the fuzzy rule, the “medium deviation-positive rate of change” rule is triggered and the adjusted parameter K is output: p =0.001, K i =0.001, K d =0.002. New flow calculation (with limit, maximum reduction of 20%):

[0128]

[0129] Stop condition determination:

[0130] Based on the received pressure monitoring information and the maximum temperature value, filling is stopped if any of the following judgment conditions are met. The clear and specific stop condition setting provides reliable safety protection and operating specifications for the filling process. These two stop conditions limit the two key aspects of temperature and pressure. Once any of the conditions is reached, filling is stopped immediately, effectively avoiding safety accidents caused by overtemperature and overpressure. At the same time, it also provides clear operating instructions for operators to ensure the standardization and normalization of the filling process:

[0131] (1)T avg_final ≥T safe ;

[0132] (2)P avg_final ≥P N .

[0133] Among them, T avg_final Indicates the real-time average temperature inside the hydrogen storage bottle; P avg_final Indicates the real-time average pressure in the hydrogen storage bottle; T safe is the preset safety temperature; P N Indicates the nominal working pressure of the hydrogen storage tank.

[0134] In this embodiment, the data at t=50s is:

[0135] (1) Average temperature T avg_final =62℃(355K), maximum temperature T max =89°C (382K, at the bottom of the hydrogen storage bottle);

[0136] (2)P avg_final =43.75MPa (reaches 1.25PN, pressure stop condition is triggered).

[0137] Execution action: PLC sends a command to close the inlet solenoid valve, filling is terminated, and the total filling time is 50s.

[0138] After filling is completed, the output pressure distribution is as follows Figure 5a As shown, the temperature distribution is Figure 5b shown.

[0139] Example 2

[0140] In this embodiment, a vehicle-mounted hydrogen storage bottle filling device based on global temperature and pressure prediction is applied, and the device includes a sensor module, a control module and an electric regulating valve 2;

[0141] The sensing module includes an inlet flow meter 3, a temperature sensor 4 and a pressure sensor 5, which are used to obtain the inlet parameters of hydrogen filling in real time, including inlet flow, inlet temperature and inlet pressure;

[0142] The control module is an embedded controller 1, which has a built-in axial one-dimensional model solving module, which is used to solve the axial one-dimensional unsteady-state model, dynamically infer the axial temperature distribution in the hydrogen bottle, and calculate the hydrogen filling flow rate based on the safety temperature value and the highest temperature value in the axial temperature distribution, and output controller instructions;

[0143] The electric regulating valve 2 is used to adjust the hydrogen filling flow according to the controller instructions.

[0144] The device was operated as described in Example 1.

[0145] In summary, the device realizes the automated and intelligent control of the on-board hydrogen storage bottle filling process through the coordinated work of the sensor module, control module and electric control valve 2. The sensor module collects key parameters in real time, the control module analyzes and processes and outputs instructions based on model calculation and control strategy, and the electric control valve 2 accurately adjusts the filling flow according to the instructions. The three work together to improve the safety, stability and efficiency of the filling process, reduce manual operation costs and the risk of errors, and provide reliable technical support and equipment guarantees for the filling of on-board hydrogen storage bottles. The complex wiring and sensor maintenance work in the bottle are reduced, and the hardware cost is reduced by about 66% compared with the traditional solution. At the same time, the influence of the sensor on the structural strength of the hydrogen storage bottle is avoided. It is especially suitable for the compact layout of hydrogen storage bottles with a high aspect ratio, which improves the system reliability and installation convenience.

[0146] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and such modifications or substitutions are intended to be within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A method for filling a vehicle-mounted hydrogen storage bottle based on global temperature and pressure prediction, characterized in that: The method steps include: S1. Real-time acquisition of hydrogen filling inlet parameters, including inlet flow, inlet temperature, and inlet pressure; S2. Construct an axial one-dimensional unsteady-state model based on the inlet parameters and solve the model to dynamically infer the axial temperature and pressure distribution in the hydrogen bottle; S3. Setting a safety temperature threshold and dynamically adjusting the hydrogen filling flow rate based on the safety temperature threshold and the highest temperature value in the axial temperature distribution; S4. If the temperature distribution and the pressure distribution meet any preset stop condition, the filling is stopped.

2. The method for filling a vehicle-mounted hydrogen storage bottle based on global temperature and pressure prediction according to claim 1 is characterized in that: The steps of constructing and solving the axial one-dimensional unsteady-state model in S2 include: S21, constructing boundary conditions from inlet parameters; S22. Establishing axial simplified forms of the mass conservation equation, momentum conservation equation, and energy conservation equation based on the inlet parameters; S23, discretizing the equation established in S22 by a finite volume method to obtain a discrete model; S24. Solve the discrete model in real time based on boundary conditions.

3. The method for filling a vehicle-mounted hydrogen storage bottle based on global temperature and pressure prediction according to claim 2 is characterized in that: The boundary conditions in S21 include the density, temperature, and velocity at the device inlet, i.e., x=0, at time t; wherein the density is calculated from the inlet parameters, the temperature is the inlet temperature obtained by real-time acquisition and reading, and the velocity is calculated from the inlet density, flow rate, and cross-sectional area, and is derived by multiplying the density, velocity, and cross-sectional area; the specific formula is: p(0,t)=p in ; T(0,t)=T in ; Where: in is the entrance density; T in is the inlet temperature; is the inlet mass flow rate; A inlet is the inlet cross-sectional area; n is the amount of gas substance; M is the molar mass of the gas; t is time; R is the universal gas constant; V is the gas volume; a and b are van der Waals constants, a reflects the strength of the gravitational interaction between gas molecules, and b reflects the volume of the gas molecules themselves.

4. The method for filling a vehicle-mounted hydrogen storage bottle based on global temperature and pressure prediction according to claim 2 is characterized in that: The specific formulas of the axial simplified forms of the mass conservation equation, momentum conservation equation, and energy conservation equation in S22 are as follows: U = [ρ, ρu, ρE]; Where Ω is the preselected spatial region in the flow field; U is the conserved variable, ρ is the density, ρu is the momentum, u is the velocity, and ρE is the energy; F is the flux term; S is the source term; n is the unit external normal vector; and ds is the infinitesimal area of ​​the control volume surface.

5. The method for filling a vehicle-mounted hydrogen storage bottle based on global temperature and pressure prediction according to claim 4 is characterized in that: The step S23 specifically involves discretizing the spatial term and the time term of the equation. The specific formula of the obtained discrete model is: in, is the value of the conserved variable at spatial position i and time step n, i is used to identify the node position after spatial discretization, and n is used to identify the time step after time discretization; Δt is the time step; Δx is the spatial step; is the flux value at spatial position i+1 / 2 and time step n+θ; is the flux value at spatial position i-1 / 2 and time step n+θ; θ∈[0,1] is the implicit weight factor; is the source term at spatial position i and time step n.

6. The method for filling a vehicle-mounted hydrogen storage bottle based on global temperature and pressure prediction according to claim 5 is characterized in that: When the discrete model is solved in real time based on the boundary conditions in S24, the solution is specifically performed through numerical flux calculation. During the solution process, a pressure weight function is introduced to calculate the virtual pressure. The specific formula is: p face =f p (M L )p L +f p (M R )p R +β·ρ avg a avg (u R -u L ); Among them, p face is the virtual pressure; M L is the dimensionless Mach number of the state on the left side of the interface; M R is the dimensionless Mach number of the state on the right side of the interface; p L and p R are the pressures on the left and right sides of the interface respectively; β is the pressure diffusion coefficient, ρ avg 、a avg is the average density and average sound speed of the interface; u L and u R are the fluid velocities on the left and right sides of the interface, respectively.

7. The method for filling a vehicle-mounted hydrogen storage bottle based on global temperature and pressure prediction according to claim 6 is characterized in that: The time step is dynamically adjusted during the solution process based on the local CFL condition and the error estimator. At the same time, an entropy correction function is introduced during the solution process. The specific formula is: Where, Δt new is the updated time step; CFL is the Courant number, a dimensionless number used to describe the relationship between the time step, spatial compensation, and fluid velocity; Δx is the spatial step; u is the fluid velocity; a is the local sound speed; U is the conserved variable; ∈ is the tolerance error, R is the residual norm; Φ(M) is the entropy correction function; M is the Mach number; δ is a small quantity.

8. The method for filling a vehicle-mounted hydrogen storage bottle based on global temperature and pressure prediction according to claim 1 is characterized in that: The specific formula for dynamically adjusting the hydrogen filling flow rate based on the safety temperature threshold and the highest temperature value in the axial temperature distribution in S3 is: ΔT=T safe -T max (t); in, is the hydrogen flow rate at time t; ΔT is the temperature deviation; T max (t) is the current extreme point of the temperature field; T safe is the preset safety temperature threshold; K p is the proportional coefficient; K i is the integral coefficient; K d is the differential coefficient.

9. The method for filling a vehicle-mounted hydrogen storage bottle based on global temperature and pressure prediction according to claim 1, characterized in that: The preset stop conditions in S4 include: (1) The real-time average temperature inside the hydrogen storage bottle is greater than or equal to the preset safety temperature; (2) The real-time average pressure in the hydrogen storage bottle is greater than or equal to the nominal working pressure of the hydrogen storage bottle; The real-time average temperature and the real-time average pressure are calculated from the axial temperature distribution and the pressure distribution in the hydrogen bottle, respectively.

10. A vehicle-mounted hydrogen storage bottle filling device based on global temperature and pressure prediction, characterized in that: The device operates by applying a method for rapidly filling a hydrogen storage bottle as described in any one of claims 1 to 9, and the device comprises a sensor module, a control module and an electric regulating valve (2); The sensing module includes an inlet flow meter (3), a temperature sensor (4) and a pressure sensor (5), and is used to obtain inlet parameters of hydrogen filling in real time, including inlet flow, inlet temperature and inlet pressure; The control module is an embedded controller (1) with a built-in axial one-dimensional model solving module for solving the axial one-dimensional unsteady-state model, dynamically inferring the axial temperature distribution in the hydrogen bottle, and calculating the hydrogen filling flow rate based on the safety temperature value and the highest temperature value in the axial temperature distribution, and outputting controller instructions; The electric regulating valve (2) is used to adjust the hydrogen filling flow rate according to controller instructions.

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