Method and device for optimizing drag coefficient of hydrogen vehicle, terminal and storage medium

Abstract

The invention relates to a hydrogen vehicle drag coefficient optimization method and device, a terminal and a storage medium. Comprising the following steps: 1, carrying out initialization design on a hydrogen vehicle wind resistance coefficient prediction device and preparing data required by wind resistance coefficient prediction; 2, performing hydrogen vehicle wind resistance coefficient prediction simulation analysis based on CFD simulation software to obtain whether the hydrogen vehicle wind resistance coefficient is within a set receivable range or not; 3, comparing and verifying a simulation result with existing wind tunnel experiment data; 4, performing optimization design on the hydrogen vehicle wind resistance coefficient which does not meet the requirement by utilizing aerodynamics; and 5, performing experimental verification and effect evaluation on the optimized scheme. By integrating computational fluid dynamics simulation, wind tunnel experiment data and real-time data acquisition and analysis technologies, the aerodynamic performance of the hydrogen vehicle can be comprehensively evaluated and optimized, the wind resistance coefficient can be reduced, meanwhile, the vehicle body shape can be optimized, the air resistance can be reduced, the energy efficiency performance of the hydrogen vehicle can be remarkably improved, and the energy efficiency and the endurance mileage can be improved.

Description

Technical Field

[0001] The present invention belongs to the field of automobile technology, and specifically relates to a method, a device, a terminal and a storage medium for optimizing the wind resistance coefficient of a hydrogen vehicle. Background Art

[0002] With the enhancement of environmental awareness and the transformation of energy structure, hydrogen vehicles, as an important branch of new energy vehicles, are receiving increasing attention for their research and development and application. However, in the research and development process of hydrogen vehicles, the optimization of aerodynamic performance, especially the reduction of wind resistance coefficient, has become the key to improving vehicle energy efficiency and driving stability. At present, the existing prediction methods of the wind resistance coefficient of hydrogen vehicles often cannot comprehensively evaluate and optimize the aerodynamic performance of hydrogen vehicles, which limits the further optimization of wind resistance coefficient. In addition, the energy efficiency utilization rate of hydrogen vehicles is low, and the cruising range is seriously affected. Summary of the invention

[0003] To solve the above problems, the present invention provides a method, device, terminal and storage medium for optimizing the wind resistance coefficient of a hydrogen vehicle. By integrating computational fluid dynamics (CFD) simulation, wind tunnel test data and real-time data acquisition and analysis technology, the aerodynamic performance of the hydrogen vehicle can be comprehensively evaluated and optimized, and the wind resistance coefficient can be reduced. At the same time, the vehicle body shape can be optimized, air resistance can be reduced, and the energy efficiency performance of the hydrogen vehicle can be significantly improved, thereby improving energy efficiency and cruising range.

[0004] The technical solution of the present invention is described as follows in conjunction with the accompanying drawings:

[0005] In a first aspect, an embodiment of the present invention provides a method for optimizing the wind resistance coefficient of a hydrogen vehicle, comprising the following steps:

[0006] Step 1, initializing the design of the hydrogen vehicle drag coefficient prediction device and preparing the data required for drag coefficient prediction; the hydrogen vehicle drag coefficient prediction device includes a data acquisition module, a wind tunnel experiment data module, a CFD simulation module, a data analysis and optimization module and a prediction and evaluation module;

[0007] Step 2: Perform a prediction simulation analysis of the wind resistance coefficient of the hydrogen vehicle based on CFD simulation software to determine whether the wind resistance coefficient of the hydrogen vehicle is within the set acceptable range;

[0008] Step 3: Compare and verify the simulation results with the existing wind tunnel test data;

[0009] Step 4: Use aerodynamics to optimize the wind resistance coefficient of hydrogen vehicles that do not meet the requirements;

[0010] Step 5: Experimentally verify and evaluate the effect of the optimized solution.

[0011] Furthermore, the specific method of step one is as follows:

[0012] 11) System construction: Build a hydrogen vehicle drag coefficient prediction system including data acquisition module, wind tunnel test data module, CFD simulation module, data analysis and optimization module, and prediction and evaluation module, and ensure that the data interface between the modules is unobstructed to achieve real-time data transmission and sharing;

[0013] 12) Data collection: Through the data acquisition module, the real-time data of the hydrogen vehicle under different working conditions is collected while obtaining the static data of the vehicle.

[0014] Furthermore, the real-time data includes vehicle speed, acceleration, air pressure and temperature; the static data includes vehicle dimensions, window layout and rearview mirror position.

[0015] Furthermore, the specific method of step 2 is as follows:

[0016] 21) Model establishment: In the CFD simulation module, a three-dimensional model is established based on the actual size and configuration of the hydrogen vehicle; the model includes the body, chassis, windows and accessories;

[0017] 22) Simulation settings: Set different wind speed and wind direction conditions to simulate the air flow in the actual driving environment; set the simulation parameter as the air resistance coefficient;

[0018] 23) Simulation operation and result extraction: Run the CFD simulation module to simulate the air flow of the hydrogen vehicle under different wind speeds and wind directions, and extract the simulation results, including the air resistance coefficient.

[0019] Further, the specific method of step three is as follows:

[0020] 31) Wind tunnel test data comparison: Compare the simulation results with the existing wind tunnel test data to verify the accuracy of the simulation results; the comparison is based on the air resistance coefficient, and it is necessary to ensure that the error between the two is within the set acceptable range;

[0021] 32) Problem identification and analysis: If it is found that the error between the simulation results and the wind tunnel test data is not within the set range, it is necessary to recheck whether the simulation model settings and parameter settings are correct, analyze the reasons for the differences, and take appropriate measures to correct them.

[0022] Furthermore, the specific method of step 4 is as follows:

[0023] 41) Problem diagnosis: Diagnose the problems and room for improvement of the aerodynamic performance of hydrogen vehicles based on simulation results, and analyze the causes of air resistance;

[0024] 42) Optimization scheme design: Develop aerodynamic optimization schemes based on the diagnosed problems, including optimizing the streamlined design of the vehicle body, adjusting the window layout and accessory positions, installing active air intake grilles and air suspension;

[0025] 43) Optimization effect prediction: Use the CFD simulation module to simulate and analyze the optimized hydrogen vehicle model to predict the optimization effect, that is, the optimized air resistance coefficient.

[0026] Furthermore, the specific method of step five is as follows:

[0027] 51) Experimental verification: Conduct experimental verification in a wind tunnel or on actual roads to confirm the actual effect of the optimization scheme;

[0028] 52) Effect evaluation: Compare the experimental data before and after optimization, and evaluate the effect of the optimization scheme on improving the aerodynamic performance of hydrogen vehicles; analyze the effect of the optimization scheme on improving energy efficiency and cruising range.

[0029] In a second aspect, an embodiment of the present invention further provides a device for predicting the wind resistance coefficient of a hydrogen vehicle, comprising:

[0030] A data acquisition module, used for collecting data;

[0031] CFD simulation module, used for simulation analysis based on CFD simulation software;

[0032] Wind tunnel test data module, used for data comparison and verification;

[0033] Data analysis and optimization module, used to optimize the design using aerodynamics;

[0034] The prediction and evaluation module is used for experimental verification and effect evaluation.

[0035] In a third aspect, a terminal is provided, including:

[0036] one or more processors;

[0037] a memory for storing the one or more processor-executable instructions;

[0038] Wherein, the one or more processors are configured to:

[0039] Execute the method described in the first aspect of the embodiment of the present invention.

[0040] In a fourth aspect, a non-temporary computer-readable storage medium is provided. When the instructions in the storage medium are executed by a processor of a terminal, the terminal is enabled to execute the method described in the first aspect of an embodiment of the present invention.

[0041] In a fifth aspect, an application product is provided. When the application product is running on a terminal, the terminal executes the method described in the first aspect of the embodiment of the present invention.

[0042] The beneficial effects of the present invention are:

[0043] The present invention integrates computational fluid dynamics (CFD) simulation, wind tunnel test data, and real-time data acquisition and analysis technology to comprehensively evaluate and optimize the aerodynamic performance of hydrogen vehicles, reduce the drag coefficient, and at the same time optimize the body shape, reduce air resistance, and significantly improve the energy efficiency performance of hydrogen vehicles, thereby increasing energy efficiency and range. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0045] Figure 1 It is a schematic flow chart of a method for optimizing the wind resistance coefficient of a hydrogen vehicle according to the present invention;

[0046] Figure 2 This is a schematic structural diagram of a device for predicting wind resistance coefficient of a hydrogen vehicle according to the present invention;

[0047] Figure 3 The present invention is a schematic block diagram of a terminal structure. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0050] Embodiment 1

[0051] See also Figure 1This embodiment provides a method for optimizing the wind resistance coefficient of a hydrogen vehicle. The method can be performed by a device for predicting the wind resistance coefficient of a hydrogen vehicle in an embodiment of the present invention. The device can be implemented in software and / or hardware, as follows:

[0052] Step 1: Initialize the design of the hydrogen vehicle drag coefficient prediction device and prepare the data required for drag coefficient prediction; the hydrogen vehicle drag coefficient prediction device includes a data acquisition module, a wind tunnel test data module, a CFD simulation module, a data analysis and optimization module, and a prediction and evaluation module, which are as follows:

[0053] 11) System construction: Build a hydrogen vehicle drag coefficient prediction device including data acquisition module, wind tunnel test data module, CFD simulation module, data analysis and optimization module, and prediction and evaluation module, and ensure that the data interface between the modules is unobstructed to achieve real-time data transmission and sharing;

[0054] 12) Data collection: Through the data acquisition module, the real-time data of the hydrogen vehicle under different working conditions is collected while obtaining the static data of the vehicle.

[0055] Step 2: Based on CFD simulation software, a prediction simulation analysis of the hydrogen vehicle drag coefficient is performed to determine whether the hydrogen vehicle drag coefficient is within the set acceptable range, as follows:

[0056] 21) Model establishment: In the CFD simulation module, a three-dimensional model is established according to the actual size and configuration of the hydrogen vehicle; and the three-dimensional model includes the body, chassis, windows and accessory data of the hydrogen vehicle;

[0057] Based on the radial basis function, the interpolation surfaces at the data points corresponding to the body, chassis, windows and accessories in the established three-dimensional model are determined:

[0058]

[0059] Where s(x) represents the value of the interpolation surface at the current data point x; n represents the number of adjacent data points of the current data point; δ represents the three-dimensional interpolation coefficient; φ() represents the radial basis function; x represents the current data point; x j Represents the jth adjacent data point of the current data point; ||xx j || represents the distance between the current data point and the jth adjacent data point; p(x) represents the interpolation stability coefficient at the current data point x; ∑ represents the summation symbol;

[0060] Based on the interpolation surfaces at all data points, a three-dimensional model corresponding to the hydrogen vehicle is constructed, and the three-dimensional model includes the body, chassis, windows and accessory data of the hydrogen vehicle;

[0061] 22) Simulation settings: setting different wind speed and wind direction conditions, including a combination of a first wind speed and a first wind direction, a combination of a second wind speed and a second wind direction, and a combination of a third wind speed and a third wind direction, wherein the first wind speed, the second wind speed, and the third wind speed are all different, and the first wind direction, the second wind direction, and the third wind direction are all different, to simulate the air flow in an actual driving environment; setting the simulation parameter to the air resistance coefficient;

[0062] When the external environmental factors (vehicle speed, air density) are the same, a lower air resistance coefficient and a smaller positive projection area will result in less air resistance during vehicle driving; when the air density cannot be changed and the speed needs to be increased, considering the functionality of the vehicle, the positive projection area cannot be excessively reduced (affecting the passenger and storage space), and the air resistance coefficient is used as the key control parameter, as shown in the following formula:

[0063] D=1 / 2ρV 2 AC d

[0064] Where D is air resistance; ρ is air density; V is vehicle speed; A is the vehicle projection area; C is the vehicle weight. d Represents the air resistance coefficient.

[0065] 23) Simulation operation and result extraction: Run the CFD simulation module to simulate the air flow of the hydrogen vehicle under different wind speeds and wind directions, and extract the simulation results, including the air resistance coefficient.

[0066] Step 3: Compare and verify the simulation results with the existing wind tunnel test data, as follows:

[0067] 31) Wind tunnel test data comparison: Compare the simulation results with the existing wind tunnel test data to verify the accuracy of the simulation results; the comparison is based on the air resistance coefficient, and it is necessary to ensure that the error between the two is within the set acceptable range;

[0068] 32) Problem identification and analysis: If it is found that the error between the simulation results and the wind tunnel test data is not within the set range, it is necessary to recheck whether the simulation model settings and parameter settings are correct, analyze the causes of the differences, and take appropriate measures to correct them, including:

[0069] When checking the settings of the simulation model, confirm whether the model used in the simulation is exactly the same as the model used in the wind tunnel experiment, including size, shape and details; check whether the density, quality and type of the mesh are appropriate; verify whether the boundary conditions set in the simulation, including inlet velocity, outlet pressure and wall conditions, match the conditions in the wind tunnel experiment; the corresponding corrective measures are: adjust the simulation model accordingly according to the analysis results to ensure consistency with the experimental model; re-divide the mesh, improve the mesh quality, and increase the mesh density to capture the flow characteristics; adjust the boundary conditions to be close to the experimental conditions;

[0070] When checking parameter settings, check whether the settings of physical parameters and numerical parameters in the simulation are consistent with the experimental conditions. Physical parameters include density, viscosity and temperature, and numerical parameters include number of iterations, convergence criteria and time step. The corresponding corrective measures are: adjust physical parameters and numerical parameters according to experimental data to improve the accuracy of simulation results; try different iteration methods and convergence criteria to improve the stability and accuracy of simulation results.

[0071] Step 4: Use aerodynamics to optimize the drag coefficient of hydrogen vehicles that do not meet the requirements, as follows:

[0072] 41) Problem diagnosis: Based on the simulation results, diagnose the problems and room for improvement in the aerodynamic performance of hydrogen vehicles, and analyze the causes of air resistance, including:

[0073] Diagnosing the aerodynamic performance problems of hydrogen vehicles based on simulation results includes the following steps:

[0074] 1. Compare simulation and theoretical values: Compare the drag coefficient obtained by simulation with the theoretical expected value to identify whether there is a significant difference between the two. If the difference is significant, there is a problem with the aerodynamic performance of the hydrogen vehicle and further analysis is needed;

[0075] 2. Analyze the flow field distribution: Use the flow field visualization function provided by the simulation software to observe the flow field distribution around the hydrogen vehicle, including the flow field conditions at the front, rear, side and bottom of the hydrogen vehicle to determine whether there is airflow separation and vortex phenomenon.

[0076] Identified areas for improvement include:

[0077] 1. Optimize the body shape: According to the simulation results, adjust the body shape of the hydrogen car, including improving the streamlined design of the front and rear of the car and optimizing the flatness of the bottom of the car body to reduce the separation of airflow and the generation of vortex phenomena, thereby reducing the drag coefficient;

[0078] 2. Adjust the window layout: By adjusting the shape, size and position of the hydrogen car windows, the influence of the window layout on the drag coefficient can be reduced;

[0079] 3. Improve vehicle accessories: Reduce the drag coefficient by improving the layout and shape of accessories on hydrogen vehicles.

[0080] Analysis of the causes of air resistance includes:

[0081] 1. Airflow separation: When the airflow is at the front or rear of the hydrogen vehicle, airflow separation will occur, resulting in a decrease in local pressure and increased air resistance;

[0082] 2. Vortex generation: On the sides and bottom of the hydrogen car body, the airflow will form vortices, which will consume the kinetic energy of the airflow and increase air resistance;

[0083] 3. Airflow obstruction: The windows and vehicle accessories of hydrogen vehicles will block the airflow, resulting in reduced airflow speed, increased pressure, and increased air resistance.

[0084] 42) Optimization scheme design: Develop aerodynamic optimization schemes based on the diagnosed problems, including optimizing the streamlined design of the vehicle body, adjusting the window layout and accessory positions, installing active air intake grilles and air suspension;

[0085] For example:

[0086] 1. Streamlined body design: Adopt a streamlined body design with a low drag coefficient to reduce air resistance and improve energy efficiency. The body lines should transition smoothly and avoid sharp corners to reduce eddy currents and resistance.

[0087] 2. Chassis optimization design: Install deflectors and diffusers on the chassis to guide air to pass smoothly through the bottom of the vehicle, reducing eddy currents and resistance. At the same time, optimize the chassis flatness and reduce the turbulence of the bottom airflow.

[0088] 3. Optimize the layout of windows and accessories: Adjust the layout of windows and the position and shape of accessories (such as rearview mirrors, antennas, etc.) to reduce obstruction to airflow and reduce the air resistance coefficient.

[0089] 4. Active air intake grille and air suspension: Equipped with an active air intake grille and air suspension system, it automatically adjusts the air intake volume and vehicle height according to the vehicle speed and driving conditions to further reduce the drag coefficient.

[0090] 5. Bionic design: Drawing inspiration from streamlined designs in nature, such as the shape of a water drop and the curve of a fish’s back, these are applied to the body and trailer design of hydrogen vehicles to achieve ultimate low wind resistance performance.

[0091] 43) Optimization effect prediction: Use the CFD simulation module to simulate and analyze the optimized hydrogen vehicle model to predict the optimization effect, that is, the optimized air resistance coefficient.

[0092] Step 5: Experimental verification and effect evaluation of the optimized solution are carried out as follows:

[0093] 51) Experimental verification: Conduct experimental verification in a wind tunnel or on actual roads to confirm the actual effect of the optimization scheme;

[0094] 52) Effect evaluation: Compare the experimental data before and after optimization, and evaluate the effect of the optimization scheme on improving the aerodynamic performance of hydrogen vehicles; analyze the effect of the optimization scheme on improving energy efficiency and cruising range.

[0095] In summary, the present invention can comprehensively evaluate and optimize the aerodynamic performance of hydrogen vehicles and reduce the drag coefficient by integrating computational fluid dynamics (CFD) simulation, wind tunnel test data, and real-time data acquisition and analysis technology. At the same time, it can optimize the body shape, reduce air resistance, and significantly improve the energy efficiency performance of hydrogen vehicles, thereby improving energy efficiency and cruising range.

[0096] Embodiment 2

[0097] See also Figure 2 This embodiment provides a device for predicting the wind resistance coefficient of a hydrogen vehicle, comprising:

[0098] The data acquisition module is used to collect real-time data of hydrogen vehicles under different working conditions, including parameters such as vehicle speed, acceleration, air pressure, temperature, and static data such as vehicle dimensions, window layout, and rearview mirror position;

[0099] CFD simulation module, which is used to build a three-dimensional model of the hydrogen vehicle based on CFD simulation software, simulate the air flow under different wind speeds and wind directions, and calculate the key parameters of the air resistance coefficient;

[0100] Wind tunnel test data module, which is used to integrate historical wind tunnel test data and provide verification and calibration data for the CFD simulation module to ensure the accuracy of simulation results;

[0101] Data analysis and optimization module, which is used to comprehensively analyze the simulation results, evaluate the aerodynamic performance of hydrogen vehicles, identify existing problems and room for improvement, and propose optimization solutions;

[0102] The prediction and evaluation module is used to predict the drag coefficient of the optimized hydrogen vehicle based on the optimization plan, and evaluate its effect on improving energy efficiency and cruising range.

[0103] Embodiment 3

[0104] Figure 3 1 is a block diagram of a terminal provided in an embodiment of the present application, and the terminal may be a terminal in the above embodiment. The terminal may be a portable mobile terminal, such as a smart phone or a tablet computer. The terminal may also be referred to as a user device, a portable terminal, or other names.

[0105] Typically, the terminal includes: a processor 301 and a memory 302 .

[0106] The processor 301 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 301 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 301 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 301 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 301 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0107] The memory 302 may include one or more computer-readable storage media, which may be tangible and non-transitory. The memory 302 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 302 is used to store at least one instruction, which is used to be executed by the processor 301 to implement a hydrogen vehicle drag coefficient optimization method provided in the present application.

[0108] In some embodiments, the terminal may further include: a peripheral device interface 303 and at least one peripheral device. Specifically, the peripheral device includes: at least one of a radio frequency circuit 304 , a touch display screen 305 , a camera 306 , an audio circuit 307 , a positioning component 308 and a power supply 309 .

[0109] The peripheral device interface 303 may be used to connect at least one peripheral device related to I / O (Input / Output) to the processor 301 and the memory 302. In some embodiments, the processor 301, the memory 302, and the peripheral device interface 303 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 301, the memory 302, and the peripheral device interface 303 may be implemented on a separate chip or circuit board, which is not limited in this embodiment.

[0110] The radio frequency circuit 304 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 304 communicates with the communication network and other communication devices through electromagnetic signals. The radio frequency circuit 304 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals into electrical signals. Optionally, the radio frequency circuit 304 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, and the like. The radio frequency circuit 304 can communicate with other terminals through at least one wireless communication protocol. The wireless communication protocol includes but is not limited to: the World Wide Web, a metropolitan area network, an intranet, various generations of mobile communication networks (2G, 3G, 4G and 5G), a wireless local area network and / or a WiFi (Wireless Fidelity) network. In some embodiments, the radio frequency circuit 304 may also include circuits related to NFC (Near Field Communication), which is not limited in this application.

[0111] The touch display screen 305 is used to display the UI (User Interface). The UI may include graphics, text, icons, videos and any combination thereof. The touch display screen 305 also has the ability to collect touch signals on the surface or above the surface of the touch display screen 305. The touch signal can be input to the processor 301 as a control signal for processing. The touch display screen 305 is used to provide virtual buttons and / or virtual keyboards, also known as soft buttons and / or soft keyboards. In some embodiments, the touch display screen 305 can be one, and the front panel of the terminal is set; in other embodiments, the touch display screen 305 can be at least two, which are respectively set on different surfaces of the terminal or are folded; in some other embodiments, the touch display screen 305 can be a flexible display screen, which is set on the curved surface or folded surface of the terminal. Even, the touch display screen 305 can also be set to a non-rectangular irregular shape, that is, a special-shaped screen. The touch display screen 305 can be made of materials such as LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode, organic light-emitting diode).

[0112] The camera assembly 306 is used to capture images or videos. Optionally, the camera assembly 306 includes a front camera and a rear camera. Typically, the front camera is used to realize video calls or selfies, and the rear camera is used to realize the shooting of photos or videos. In some embodiments, there are at least two rear cameras, which are any one of a main camera, a depth of field camera, and a wide-angle camera, so as to realize the fusion of the main camera and the depth of field camera to realize the background blur function, and the fusion of the main camera and the wide-angle camera to realize panoramic shooting and VR (Virtual Reality) shooting functions. In some embodiments, the camera assembly 306 may also include a flash. The flash can be a monochrome temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm light flash and a cold light flash, which can be used for light compensation at different color temperatures.

[0113] The audio circuit 307 is used to provide an audio interface between the user and the terminal. The audio circuit 307 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, and convert the sound waves into electrical signals and input them into the processor 301 for processing, or input them into the radio frequency circuit 304 to achieve voice communication. For the purpose of stereo acquisition or noise reduction, there may be multiple microphones, which are respectively arranged at different parts of the terminal. The microphone may also be an array microphone or an omnidirectional acquisition microphone. The speaker is used to convert the electrical signal from the processor 301 or the radio frequency circuit 304 into sound waves. The speaker may be a traditional film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can not only convert the electrical signal into sound waves audible to humans, but also convert the electrical signal into sound waves inaudible to humans for purposes such as ranging. In some embodiments, the audio circuit 307 may also include a headphone jack.

[0114] The positioning component 308 is used to locate the current geographical location of the terminal to implement navigation or LBS (Location Based Service). The positioning component 308 can be a positioning component based on the US GPS (Global Positioning System) or China's Beidou system.

[0115] The power supply 309 is used to power various components in the terminal. The power supply 309 can be an alternating current, a direct current, a disposable battery, or a rechargeable battery. When the power supply 309 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery charged through a wired line, and a wireless rechargeable battery is a battery charged through a wireless coil. The rechargeable battery can also be used to support fast charging technology.

[0116] Those skilled in the art will understand that Figure 3 The structure shown in the figure does not constitute a limitation on the terminal, and may include more or less components than those shown in the figure, or combine certain components, or adopt a different component arrangement.

[0117] Embodiment 4

[0118] In an exemplary embodiment, a computer-readable storage medium is also provided, on which a computer program is stored. When the program is executed by a processor, a method for optimizing the wind resistance coefficient of a hydrogen vehicle as provided in all the inventive embodiments of the present application is implemented.

[0119] Any combination of one or more computer-readable media may be used. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device, or device.

[0120] Computer-readable signal media may include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0121] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0122] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0123] Embodiment 5

[0124] In an exemplary embodiment, an application product is also provided, including one or more instructions, which can be executed by the processor 301 of the above-mentioned device to complete the above-mentioned method for optimizing the wind resistance coefficient of a hydrogen vehicle.

[0125] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and implementation mode. It can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily realized. Therefore, without departing from the general concept defined by the claims and equivalent scope, the present invention is not limited to the specific details and the illustrations shown and described here.

Claims

1. A method for optimizing the wind resistance coefficient of a hydrogen vehicle, characterized in that: The following steps are involved: Step 1: Initialize the design of the hydrogen vehicle drag coefficient prediction device and prepare the data required for drag coefficient prediction; Step 2: Perform a prediction simulation analysis of the wind resistance coefficient of the hydrogen vehicle based on CFD simulation software to determine whether the wind resistance coefficient of the hydrogen vehicle is within the set acceptable range; Step 3: Compare and verify the simulation results with the existing wind tunnel test data; Step 4: Use aerodynamics to optimize the wind resistance coefficient of hydrogen vehicles that do not meet the requirements; Step 5: Experimentally verify and evaluate the effect of the optimized solution.

2. A method for optimizing the wind resistance coefficient of a hydrogen vehicle according to claim 1, characterized in that: The specific method of step one is as follows: 11) System construction: Build a hydrogen vehicle drag coefficient prediction device including data acquisition module, wind tunnel test data module, CFD simulation module, data analysis and optimization module, and prediction and evaluation module, and ensure that the data interface between the modules is unobstructed to achieve real-time data transmission and sharing; 12) Data collection: Through the data acquisition module, the real-time data of the hydrogen vehicle under different working conditions is collected while obtaining the static data of the vehicle.

3. A method for optimizing the wind resistance coefficient of a hydrogen vehicle according to claim 2, characterized in that: The real-time data includes vehicle speed, acceleration, air pressure and temperature; the static data includes vehicle dimensions, window layout and rearview mirror position.

4. The method for optimizing the wind resistance coefficient of a hydrogen vehicle according to claim 1, characterized in that: The specific method of step 2 is as follows: 21) Model establishment: In the CFD simulation module, a three-dimensional model is established based on the actual size and configuration of the hydrogen vehicle; the model includes the body, chassis, windows and accessories; 22) Simulation settings: Set different wind speed and wind direction conditions to simulate the air flow in the actual driving environment; set the simulation parameter as the air resistance coefficient; 23) Simulation operation and result extraction: Run the CFD simulation module to simulate the air flow of the hydrogen vehicle under different wind speeds and wind directions, and extract the simulation results, including the air resistance coefficient.

5. The method for optimizing the wind resistance coefficient of a hydrogen vehicle according to claim 1, characterized in that: The specific method of step three is as follows: 31) Wind tunnel test data comparison: Compare the simulation results with the existing wind tunnel test data to verify the accuracy of the simulation results; the comparison is based on the air resistance coefficient, and it is necessary to ensure that the error between the two is within the set acceptable range; 32) Problem identification and analysis: If it is found that the error between the simulation results and the wind tunnel test data is not within the set range, it is necessary to recheck whether the simulation model settings and parameter settings are correct, analyze the reasons for the differences, and take appropriate measures to correct them.

6. A method for optimizing the wind resistance coefficient of a hydrogen vehicle according to claim 1, characterized in that: The specific method of step 4 is as follows: 41) Problem diagnosis: Diagnose the problems and room for improvement of the aerodynamic performance of hydrogen vehicles based on simulation results, and analyze the causes of air resistance; 42) Optimization scheme design: Develop aerodynamic optimization schemes based on the diagnosed problems, including optimizing the streamlined design of the vehicle body, adjusting the window layout and accessory positions, installing active air intake grilles and air suspension; 43) Optimization effect prediction: Use the CFD simulation module to simulate and analyze the optimized hydrogen vehicle model to predict the optimization effect, that is, the optimized air resistance coefficient.

7. The method for optimizing the wind resistance coefficient of a hydrogen vehicle according to claim 1, characterized in that: The specific method of step five is as follows: 51) Experimental verification: Conduct experimental verification in a wind tunnel or on actual roads to confirm the actual effect of the optimization scheme; 52) Effect evaluation: Compare the experimental data before and after optimization, and evaluate the effect of the optimization scheme on improving the aerodynamic performance of hydrogen vehicles; analyze the effect of the optimization scheme on improving energy efficiency and cruising range.

8. A hydrogen vehicle drag coefficient optimization device, characterized in that: include: A data acquisition module, used for collecting data; CFD simulation module, used for simulation analysis based on CFD simulation software; Wind tunnel test data module, used for data comparison and verification; Data analysis and optimization module, used to optimize the design using aerodynamics; The prediction and evaluation module is used for experimental verification and effect evaluation.

9. A terminal, characterized in that: include: one or more processors; a memory for storing the one or more processor-executable instructions; Wherein, the one or more processors are configured to: Execute a method for optimizing the wind resistance coefficient of a hydrogen vehicle as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that: When the instructions in the storage medium are executed by the processor of the terminal, the terminal is enabled to execute a method for optimizing the wind resistance coefficient of a hydrogen vehicle as described in any one of claims 1 to 7.

Images