Methods, devices, vehicles, media, and procedures for assessing waterway risks in luggage compartments.

Abstract

This application relates to the field of vehicle cleaning technology, and in particular to a method, device, vehicle, medium, and program product for assessing waterway risks in a luggage compartment. The method includes: determining the simulated nozzle parameters of a water gun nozzle based on a pre-built simulation model; cleaning a target simulated vehicle based on the simulated nozzle parameters to obtain corresponding simulated waterway dripping results; if the simulated waterway dripping results do not meet preset dripping conditions, generating corresponding optimization measures until the preset dripping conditions are met, and determining the actual waterway dripping results in the luggage compartment of the target vehicle based on the optimization measures. This solves the problems in related technologies where the lack of simulation methods makes it difficult to accurately reproduce the dynamic distribution of water flow on the vehicle body under complex car wash conditions, and also makes it impossible to identify risks such as water accumulation areas and water droplet trajectories in advance, and even more difficult to provide high-precision data to support waterproof structure optimization and avoid related hidden dangers from the source.

Description

Technical Field

[0001] This application relates to the field of vehicle cleaning technology, and in particular to a method, device, vehicle, medium and procedure for assessing waterway risks in luggage compartments. Background Technology

[0002] During car washing, the unpredictable nature of user actions necessitates thorough coverage of the vehicle body. However, the uncertainties in water flow and pressure make it difficult to accurately capture the water flow path and the water level on the vehicle's surface, thus hindering the precise reproduction of the washing scenario. Furthermore, water can easily accumulate on the tailgate surface and in the gaps between the taillights and the body during the wash. When the user opens the tailgate after washing, these accumulated water droplets can drip into the trunk, not only reducing the user experience but also potentially causing critical electronic components inside the trunk to become damp and malfunction, affecting the vehicle's safety and reliability.

[0003] Among related technologies, intelligent simulation motion mechanisms can be used to control vertical brushes, oscillating high-pressure air knives, disc brushes, and rotating high-pressure air knives to automatically and precisely clean vehicle bodies and tires. High-pressure air (0.8MPa) and negative pressure dust extraction devices are used to achieve efficient cleaning and dust emissions meeting standards. Alternatively, modular design can integrate the MT (Möller-Trumbore, a high-efficiency light and triangle intersection detection algorithm) algorithm to achieve efficient and accurate simulation and parameter optimization of the HPR (High Pressure Rinsing) process on the inner surface of superconducting cavities, meeting the batch cleaning requirements of the ILC (International Linear Collider) project. Furthermore, by collecting target monitoring data and inputting it into a simulation model to compare with actual operating data, anomaly detection can be achieved. Combined with an expert fault diagnosis system, faults can be automatically located. The system is executed collaboratively by an information acquisition unit, a display and control integrated machine, and an industrial control computer, thereby quickly identifying and resolving faults to improve maintenance efficiency.

[0004] However, the relevant technologies lack the ability to reproduce car wash scenarios through simulation, making it difficult to accurately simulate the dynamic distribution characteristics of water flow on the car body surface under complex car wash conditions. This makes it impossible to identify potential risks such as water accumulation areas on the car body and the trajectory of water droplets in advance, and it is also difficult to obtain high-precision simulation data for optimizing the waterproof structure of the car body. It is difficult to avoid related hidden dangers from the source, and improvements are urgently needed. Summary of the Invention

[0005] This application provides a method, device, vehicle, medium, and program product for assessing water risks in luggage compartments, in order to solve the problems in related technologies, such as the lack of simulation methods, which makes it difficult to accurately reproduce the dynamic distribution of water flow on the vehicle body under complex car wash conditions, and also makes it impossible to identify risks such as water accumulation areas and water droplet trajectories in advance, and even more difficult to provide high-precision data to support waterproof structure optimization and avoid related hidden dangers from the source.

[0006] The first aspect of this application provides a method for assessing the waterway risk in a luggage compartment, comprising the following steps: determining the simulated nozzle parameters of a simulated water gun nozzle based on a pre-constructed simulation model; cleaning a target simulated vehicle based on the simulated nozzle parameters to obtain the simulated waterway dripping result in the simulated luggage compartment of the target simulated vehicle; if the simulated waterway dripping result does not meet the preset dripping conditions, generating optimization measures corresponding to the openable cover of the simulated luggage compartment based on the simulated waterway dripping result, until the simulated waterway dripping result meets the preset dripping conditions, and determining the actual waterway dripping result in the luggage compartment of the target vehicle according to the optimization measures.

[0007] Optionally, in one embodiment of this application, before determining the nozzle parameters of the simulated water gun nozzle based on a pre-built simulation model, the method further includes: obtaining the actual nozzle parameters of the water gun nozzle based on the target vehicle; determining the actual spray distance and actual spray volume of the water gun nozzle based on the actual nozzle parameters; determining the simulated spray distance and simulated spray volume of the simulated water gun nozzle based on the actual spray distance and actual spray volume; and constructing the simulation model of the water gun nozzle based on the simulated spray distance and simulated spray volume.

[0008] Optionally, in one embodiment of this application, the step of cleaning the target simulated vehicle based on the simulated nozzle parameters to obtain the simulated water droplet result in the simulated luggage compartment of the target simulated vehicle includes: determining the cleaning parameters of the target simulated vehicle based on the simulated nozzle parameters; and cleaning the target simulated vehicle based on the cleaning parameters to obtain the simulated water droplet result.

[0009] Optionally, in one embodiment of this application, the step of cleaning the target simulated vehicle based on the simulated nozzle parameters to obtain the simulated water droplet result of the simulated luggage compartment in the target simulated vehicle includes: determining the computational domain and encrypted region of the simulated luggage compartment based on the coordinate data of the target simulated vehicle; determining the basic liquid particle information of the computational domain and the encrypted region particle information of the encrypted region based on the computational domain and the encrypted region; and generating the simulated water droplet information based on the basic liquid particle information and the encrypted region particle information.

[0010] Optionally, in one embodiment of this application, generating optimization measures corresponding to the simulated openable luggage compartment cover based on the simulated water droplet results includes: determining the leakage risk area of ​​the simulated openable luggage compartment cover based on the water droplet trajectory data in the simulated water droplet results; and generating the optimization measures based on the leakage risk area.

[0011] A second aspect of this application provides a luggage compartment waterway risk assessment device, comprising: a first determining module, configured to determine the simulated nozzle parameters of a water gun nozzle based on a pre-constructed water gun nozzle simulation model; a first generating module, configured to clean a target simulated vehicle based on the simulated nozzle parameters to obtain simulated waterway dripping results in the simulated luggage compartment of the target simulated vehicle; and a second generating module, configured to generate optimization measures corresponding to the openable cover of the simulated luggage compartment based on the simulated waterway dripping results when the simulated waterway dripping results do not meet preset dripping conditions, until the simulated waterway dripping results meet the preset dripping conditions, and determine the actual waterway dripping results in the luggage compartment of the target vehicle according to the optimization measures.

[0012] Optionally, in one embodiment of this application, it further includes: an acquisition module, configured to acquire actual nozzle parameters of the water gun nozzle based on the target vehicle before determining the nozzle parameters of the simulated water gun nozzle based on a pre-built water gun nozzle simulation model; a second determination module, configured to determine the actual spray distance and actual spray volume of the water gun nozzle based on the actual nozzle parameters; a third determination module, configured to determine the simulated spray distance and simulated spray volume of the simulated water gun nozzle based on the actual spray distance and the actual spray volume; and a construction module, configured to construct the water gun nozzle simulation model based on the simulated spray distance and the simulated spray volume.

[0013] Optionally, in one embodiment of this application, the first generation module includes: a first determining unit, configured to determine the cleaning parameters of the target simulated vehicle based on the simulated nozzle parameters; and a first generation unit, configured to clean the target simulated vehicle based on the cleaning parameters to obtain the simulated water path dripping result.

[0014] Optionally, in one embodiment of this application, the first generation module includes: a second determining unit, configured to determine the computational domain and encrypted region of the simulated luggage compartment based on the coordinate data of the target simulated vehicle; a third determining unit, configured to determine the basic liquid particle information of the computational domain and the encrypted region particle information of the encrypted region based on the computational domain and the encrypted region; and a second generation unit, configured to generate the simulated waterway dripping information based on the basic liquid particle information and the encrypted region particle information.

[0015] Optionally, in one embodiment of this application, the second generation module includes: a fourth determining unit, used to determine the leakage risk area of ​​the simulated luggage compartment openable cover based on the water droplet trajectory data in the simulated water path dripping result; and a third generation unit, used to generate the optimization measures based on the leakage risk area.

[0016] A third aspect of this application provides a vehicle comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the baggage compartment waterway risk assessment method as described in the above embodiments.

[0017] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described baggage compartment waterway risk assessment method.

[0018] A fifth aspect of this application provides a computer program product, including a computer program that, when executed, implements the above-described baggage compartment waterway risk assessment method.

[0019] This application embodiment can determine the simulated nozzle parameters of the water gun nozzle based on a pre-built simulation model, and then clean the target simulated vehicle based on the simulated nozzle parameters to obtain the simulated water dripping results in the simulated luggage compartment of the target simulated vehicle. When the simulated water dripping results do not meet the preset dripping conditions, corresponding optimization measures are generated based on the simulated water dripping results until the simulated water dripping results meet the preset dripping conditions. Based on the optimization measures, the actual water dripping results in the luggage compartment of the target vehicle are determined. By constructing a high-precision digital simulation model, it can flexibly simulate diverse car wash operating conditions such as different water pressures, angles, and nozzle types, accurately reproduce the dynamic distribution of water flow on the vehicle surface and the trajectory of water droplets, and innovatively construct a closed-loop process of "simulation-analysis-optimization-verification". It uses data to drive decision-making, accurately reproduces car wash scenarios and predicts risks, and achieves a leapfrog upgrade in risk prediction from experience-driven to data-driven, eliminating quality hazards caused by water droplets from the source. This solves the technical problems in related technologies, such as the lack of simulation methods, which makes it difficult to accurately reproduce the dynamic distribution of water flow on the car body under complex car wash conditions, and also makes it impossible to identify risks such as water accumulation areas and water droplet trajectories in advance, and even more difficult to provide high-precision data to support the optimization of waterproof structures and avoid related hidden dangers from the source.

[0020] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0021] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0022] Figure 1 This is a flowchart of a waterway risk assessment method for a baggage compartment according to an embodiment of this application; Figure 2 This is a block diagram of a simplified test bench constructed according to an embodiment of this application; Figure 3 A flowchart illustrating the working principle of a baggage compartment waterway risk assessment method according to an embodiment of this application; Figure 4 This is a block diagram of a baggage compartment waterway risk assessment device provided according to an embodiment of this application; Figure 5 This is a structural schematic diagram of a vehicle provided according to an embodiment of this application. Detailed Implementation

[0023] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0024] The following description, with reference to the accompanying drawings, outlines a method, apparatus, vehicle, medium, and program product for assessing waterway risks in a luggage compartment according to embodiments of this application. Addressing the issues mentioned in the background art, such as the lack of simulation methods leading to difficulties in accurately replicating the dynamic distribution of water flow on a vehicle body under complex car wash conditions, the inability to identify water accumulation areas and water droplet trajectories in advance, and the difficulty in providing high-precision data to support waterproof structure optimization and mitigate related hazards from the source, this application provides a method for assessing waterway risks in a luggage compartment. In this method, based on a pre-constructed simulation model of a water gun nozzle, the simulation nozzle parameters are determined. Then, based on these parameters, a target simulated vehicle is cleaned to obtain the simulated waterway dripping results in the simulated luggage compartment of the target simulated vehicle. Furthermore, if the simulated waterway dripping results do not meet the preset dripping parameters... Under certain conditions, corresponding optimization measures are generated based on the simulated water droplet results until the simulated water droplet results meet the preset droplet conditions. The actual water droplet results in the luggage compartment of the target vehicle are then determined based on the optimization measures. By constructing a high-precision digital simulation model, diverse car wash operating parameters such as different water pressures, angles, and nozzle types can be flexibly simulated. This accurately reproduces the dynamic distribution of water flow on the vehicle surface and the trajectory of water droplets. An innovative closed-loop process of "simulation-analysis-optimization-verification" is constructed, using data to drive decision-making, accurately reproducing car wash scenarios and predicting risks. This represents a leapfrog upgrade in risk prediction from experience-driven to data-driven, eliminating quality hazards caused by water droplet droplets at the source. This solves the technical problems in related technologies, such as the lack of simulation methods, which makes it difficult to accurately reproduce the dynamic distribution of water flow on the vehicle body under complex car wash conditions, and also makes it impossible to identify water accumulation areas and water droplet trajectories in advance. Furthermore, it makes it difficult to provide high-precision data to support waterproof structure optimization and avoid related hazards at the source.

[0025] Specifically, Figure 1 This is a flowchart of a waterway risk assessment method for a baggage compartment according to an embodiment of this application.

[0026] like Figure 1 As shown, the waterway risk assessment method for the baggage compartment includes the following steps: In step S101, the simulation nozzle parameters of the water gun nozzle are determined based on the pre-built water gun nozzle simulation model.

[0027] In some embodiments, the present application embodiments can accurately determine the simulation nozzle parameters of the water gun simulation nozzle based on a pre-built water gun nozzle simulation model.

[0028] Optionally, in one embodiment of this application, before determining the nozzle parameters of the simulated water gun nozzle based on the pre-built water gun nozzle simulation model, the method further includes: obtaining the actual nozzle parameters of the water gun nozzle based on the target vehicle; determining the actual spray distance and actual spray volume of the water gun nozzle based on the actual nozzle parameters; determining the simulated spray distance and simulated spray volume of the simulated water gun nozzle based on the actual spray distance and actual spray volume; and constructing a water gun nozzle simulation model based on the simulated spray distance and simulated spray volume.

[0029] It is understood that, in the embodiments of this application, the actual nozzle parameters may include, but are not limited to, water gun pressure, nozzle diameter, water spray speed, water gun height above the ground, water spray time, maximum horizontal spray distance, and water volume in the bucket, etc., and this application does not impose specific limitations.

[0030] In some embodiments, the present application can obtain the actual nozzle parameters of the water gun nozzle based on the target vehicle, and calculate the corresponding actual spray distance and actual spray volume based on the actual nozzle parameters, thereby determining the simulated spray distance and simulated spray volume of the simulated water gun nozzle, and thus constructing a water gun nozzle simulation model.

[0031] Specifically, according to the test standards, the high-pressure water gun pressure is ≥P0 and the water output is ≥V0. A simple test bench is set up, such as... Figure 2 As shown, the high-pressure water gun is kept horizontal at a height of H1 above the ground. The water bucket is placed in a suitable position, and the switch is turned on to spray water into the water bucket. The spraying time is T1, the pressure of the high-pressure water gun is recorded as P1, the farthest horizontal spray distance is measured and recorded as S1, and the volume of water in the water bucket is V1.

[0032] Furthermore, in this embodiment, a simulation model of the water gun nozzle is established in simulation software. In the simulation environment, the simulated high-pressure water gun is kept horizontal at a height of H2 above the ground, ensuring H2=H1. The simulation of water spraying begins, with a simulation time of T2, ensuring T2=T1. The pressure of the simulated high-pressure water gun is measured and recorded as P2, the maximum horizontal spray distance as S2, and the volume of water sprayed as V2. The volume of water sprayed, V2, and the maximum horizontal spray distance, S2, are controlled by adjusting the nozzle diameter R and spray speed U of the simulated high-pressure water gun, ensuring V2=V1 and S2=S1. By controlling S2=S1, P2=P1 is ensured.

[0033] If |S2-S1|>1% or |V2-V1|>1%, then the nozzle diameter R and spray velocity U in the simulated high-pressure water gun need to be continuously adjusted until |S2-S1|≤1% and |V2-V1|≤1%. After determining the required nozzle diameter R and spray velocity U, the nozzle pressure P2 and the volume of water sprayed V2 are measured in the simulation environment to check if the nozzle pressure P2≥P0 and the volume of water sprayed V2≥V0 are satisfied. If not, recalibration is performed until the nozzle pressure and water output meet the requirements, thus completing the construction of the water gun nozzle simulation model.

[0034] For example, according to the test standards of this application embodiment: high-pressure water gun pressure ≥ 7.9 MPa, water output ≥ 1200 L / h. A simple test bench was set up, the high-pressure water gun was kept horizontal, and the height H1 above the ground was 1.5 m. A water tank with a volume greater than 15 L was placed in a suitable position, the switch was turned on to spray water into the water tank, the spraying time T1 was 10 s, the farthest horizontal spray distance S1 was measured and recorded as 6.60 m, and the volume of water in the water tank V1 was 3.35 L.

[0035] Furthermore, in this embodiment of the application, a simulation model of the water gun nozzle is established in simulation software. In the simulation environment, the simulated high-pressure water gun is kept horizontal, ensuring that the height H2 above the ground is 1.5m. The simulation of water spraying begins, and the simulation time T2 is 10s. The maximum horizontal spray distance S2 is measured and recorded as 6.64m, and the volume of water sprayed V2 is 3.37L, which does not satisfy |S2-S1|≤1% and |V2-V1|≤1%.

[0036] By continuously optimizing the nozzle diameter R and spray velocity U in the water gun nozzle simulation model, the maximum horizontal spray distance S2 was finally obtained as 6.61m with R=2mm and U=26.59m / s, and the volume of sprayed water was 3.36L, satisfying |S2-S1|≤1% and |V2-V1|≤1%.

[0037] Furthermore, in this embodiment of the application, after determining the required nozzle diameter R and water spray velocity U, the nozzle pressure P2 = 8.0 MPa and the volume of sprayed water V2 = 1209.6 L / h are measured in a simulation environment to determine whether P2 ≥ 7.9 MPa and V2 ≥ 1200 L / h are satisfied. If the requirements are met, the construction of the water gun nozzle simulation model is completed; if the requirements are not met, the nozzle diameter R and water spray velocity U are adjusted, and the parameters are recalibrated until the requirements are met, thus completing the construction of the water gun nozzle simulation model.

[0038] It can be understood that, in constructing the water gun nozzle simulation model in this application embodiment, by adjusting the nozzle diameter R and the water spray speed U, the maximum horizontal water spray distance S2 and the volume of sprayed water V2 within 10 seconds of horizontal simulated water spray time at a height of 1.5m above the ground in the simulation environment are satisfied, and the errors of S1 and V1 measured in the test environment are not more than 1%. In addition, the nozzle pressure P2 is ≥7.9MPa and the volume of sprayed water V2 is ≥1200L / h in the simulation environment.

[0039] In step S102, the target simulated vehicle is cleaned based on the simulated nozzle parameters to obtain the simulated water dripping results of the simulated luggage compartment in the target simulated vehicle.

[0040] As one possible approach, this embodiment of the application cleans the target simulated vehicle according to the predetermined simulated nozzle parameters, thereby obtaining the simulated water dripping result of the simulated luggage compartment in the target simulated vehicle.

[0041] Optionally, in one embodiment of this application, the target simulated vehicle is cleaned based on the simulated nozzle parameters to obtain the simulated water droplet result of the simulated luggage compartment in the target simulated vehicle, including: determining the cleaning parameters of the target simulated vehicle based on the simulated nozzle parameters; and cleaning the target simulated vehicle based on the cleaning parameters to obtain the simulated water droplet result.

[0042] It is understood that the embodiments of this application can calibrate the cleaning parameters of the target simulated vehicle based on the parameters of the simulated nozzle.

[0043] Specifically, according to experimental conditions, this embodiment of the application can perform clockwise and counterclockwise cleaning once around the rear door, and vertical and parallel cleaning once for the sealed area. Furthermore, in the simulation environment, the coordinates of the water gun nozzle simulation model are (X, Y, Z). Therefore, this embodiment of the application can control the movement trajectory of the simulated nozzle by controlling the X, Y, and Z values ​​at different times, thereby outputting water droplet trajectory data that meets the motion requirements. For example, when the simulated nozzle moves in the XOY plane, the Z coordinate remains unchanged, and the movement trajectory is controlled by controlling the X and Y values; when the simulated nozzle moves in the XOZ plane, the Y coordinate remains unchanged, and the movement trajectory is controlled by controlling the X and Z values; when the simulated nozzle moves in the YOZ plane, the X coordinate remains unchanged, and the movement trajectory is controlled by controlling the Y and Z values.

[0044] Furthermore, in this embodiment of the application, when cleaning the rear door according to the test conditions, the horizontal distance between the water gun nozzle and the rear door is D1. Therefore, in the simulation environment of this embodiment of the application, the horizontal distance between the simulated water gun nozzle and the rear door is D2, and D2 = D1 is guaranteed.

[0045] For example, in this embodiment of the application, when cleaning the tailgate according to the test conditions, the horizontal distance between the water gun nozzle and the tailgate is 50mm. Therefore, in the simulation environment, this embodiment of the application sets the horizontal distance between the simulated water gun nozzle and the tailgate to 50mm.

[0046] Furthermore, in the embodiments of this application, when cleaning the rear door using a simulated nozzle in a simulated environment, the horizontal distance between the simulated nozzle and the rear door can be set to 50mm, and the coordinates (X, Y, Z) of the water gun nozzle simulation model can change over time, thereby enabling the simulated nozzle to perform clockwise and counterclockwise cleaning once around the rear door, and vertical and parallel cleaning once for the sealed parts.

[0047] It should be noted that, in this embodiment of the application, the simulated nozzle is controlled as follows: when the simulated nozzle moves in the XOY plane, the Z coordinate remains constant at 1500mm, and circumferential motion is achieved by controlling the X and Y values; when the simulated nozzle moves in the XOZ plane, the Y coordinate remains constant at 50mm, and vertical cleaning is achieved by controlling the X and Z values; when the simulated nozzle moves in the YOZ plane, the X coordinate remains constant at 200mm, and parallel cleaning is achieved by controlling the Y and Z values, as shown in Table 1. Table 1 is a schematic table illustrating the motion coordinates and control method of the simulated nozzle according to an embodiment of this application.

[0048] Table 1

[0049] Furthermore, in this embodiment, the target simulated vehicle can be cleaned based on cleaning parameters to obtain the corresponding simulated water droplet results.

[0050] Optionally, in one embodiment of this application, the target simulated vehicle is cleaned based on the simulated nozzle parameters to obtain the simulated water droplet results of the simulated luggage compartment in the target simulated vehicle, including: determining the computational domain and encrypted region of the simulated luggage compartment based on the coordinate data of the target simulated vehicle; determining the basic liquid particle information of the computational domain and the encrypted region particle information of the encrypted region based on the computational domain and the encrypted region; and generating simulated water droplet information based on the basic liquid particle information and the encrypted region particle information.

[0051] It is understood that, in the embodiments of this application, the computational domain of the simulated luggage compartment can be understood as the embodiment of this application defining a computational boundary box for simulating water dripping within the luggage compartment. Only within this boundary box will the embodiment of this application calculate the dripping and flowing behavior of liquids (such as water); outside this boundary box, the embodiment of this application does not perform calculations, thereby saving computing power.

[0052] For example, in this embodiment of the application, the distance between the boundary of the computational domain and the vehicle in the X, Y, and Z directions is set to be more than 1000 mm (other values ​​can also be used, and the specific settings can be made by those skilled in the art according to the actual situation; this application does not impose specific limitations). The focus is on particles within the computational domain, and particles outside the computational domain are deleted to improve computational efficiency.

[0053] The encrypted region refers to a local area in the computational domain that has higher requirements for the liquid droplet effect and requires more refined simulation. For example, in this application embodiment, the area around the rear door is encrypted. The distance between the encrypted region and the rear door in the X, Y, and Z directions is more than 300mm, ensuring that the liquid particles near the rear door are always in an encrypted state. The specific settings can be made by those skilled in the art according to the actual situation, and this application does not impose specific limitations.

[0054] Furthermore, in the embodiments of this application, the basic liquid particle information can be understood as a set of liquid particles used to describe the unencrypted region in the computational domain. It may include, but is not limited to, the coordinates, mass, velocity, radius, etc. of the particles. This application does not impose specific limitations. The encrypted region particle information can be understood as a set of liquid particles used to describe the encrypted region in the computational domain. The difference between it and the basic liquid particles is that the particle density is higher (more particles per unit volume), and some parameters (such as particle radius) may be smaller to achieve more refined simulation.

[0055] In this embodiment of the application, the size R1 of the basic liquid particles and the size R2 of the liquid particles in the densified area can be determined according to the nozzle diameter R of the simulated nozzle, satisfying R=4R1=8R2. For example, if the nozzle diameter R of the simulated nozzle is 2mm, then the size R1 of the basic liquid particles is 0.5mm and the size R2 of the liquid particles in the densified area is 0.25mm.

[0056] In some embodiments, this application can determine the computational domain corresponding to the simulated luggage compartment and the encrypted area for encryption processing based on the coordinate data provided by the target simulated vehicle, thereby determining the basic liquid particle information within the computational domain and the encrypted area particle information within the encrypted area, and then combining the basic liquid particle information and the encrypted area particle information to generate information on simulated water droplets.

[0057] For example, in this embodiment of the application, after the construction of the water gun nozzle simulation model is completed, the nozzle diameter R, water spray speed U, and the time curve of the nozzle coordinates are input. The simulation model is checked to see if it is complete, if the assembly is correct, and if the parameters are correct. After the simulation model is checked, the calculation domain is determined: the distance between the boundary of the calculation domain and the vehicle in the X, Y, and Z directions all exceed 1000mm. The focus is on the particles within the calculation domain, and the particles outside the calculation domain are deleted. The area around the tailgate is encrypted. The distance between the encrypted area and the tailgate in the X, Y, and Z directions all exceed 300mm to ensure that the liquid particles near the tailgate are always in an encrypted state. According to R=4R1=8R2, if the nozzle diameter R of the simulation nozzle is 2mm, then the size R1 of the basic liquid particles is 0.5mm, and the size R2 of the liquid particles in the encrypted area is 0.25mm.

[0058] Furthermore, in this embodiment of the application, the simulation begins, and during the simulation, the nozzle pressure, water output, and nozzle movement trajectory are continuously monitored. After the car wash is completed, the simulated nozzle is controlled to stop spraying water, and the time is recorded as T3, thereby generating corresponding simulated water path dripping information. For example, if T3 is set to 30s in this embodiment of the application, the nozzle will stop spraying water at 30s of the simulation time, completing the car wash.

[0059] It should be noted that if any abnormalities occur during the car wash process in this embodiment, the model needs to be readjusted and checked, and simulation calculations need to be performed. If no abnormalities occur, after the car wash is completed, the tailgate is slowly opened to its maximum angle, and the encrypted area follows the movement of the tailgate. The tailgate stops moving at time T4, and the trajectory of the liquid dripping on the tailgate is observed to generate corresponding simulated water path dripping information. For example, in this embodiment, T4 is set to 35s. This embodiment can control the tailgate to slowly open to its maximum angle and the encrypted area to follow the movement of the tailgate during the simulation time of 30s to 35s. The tailgate stops moving at 35s, and the trajectory of the liquid dripping on the tailgate is observed and recorded to obtain the corresponding simulated water path dripping information.

[0060] In step S103, if the simulated water drop results do not meet the preset drop conditions, optimization measures corresponding to the simulated openable luggage compartment cover are generated based on the simulated water drop results until the simulated water drop results meet the preset drop conditions, and the actual water drop results of the luggage compartment in the target vehicle are determined according to the optimization measures.

[0061] It is understood that, in the embodiments of this application, the openable cover can be understood as a luggage compartment cover, a rear door, a luggage box cover, etc. This application does not make specific limitations, and it may include, but is not limited to, the cover body, sealing strip, drainage channel, hinge, locking area, etc. This application does not make specific limitations.

[0062] In some embodiments, if the simulated water drop results do not meet the preset drop conditions, optimization measures can be formulated for the simulated openable luggage compartment cover based on the simulated water drop results. The optimization can be iterated until the simulated water drop results meet the preset drop conditions, and the actual water drop results in the luggage compartment of the target vehicle can be deduced based on the final determined optimization measures.

[0063] The preset dripping conditions can be understood as pre-set criteria for judging whether the simulation is qualified. For example, water droplets cannot fall onto the surface of the luggage compartment, and the wetted area of ​​the luggage compartment surface cannot be greater than the target value. The specific conditions can be set by those skilled in the art according to the actual situation, and this application does not impose any specific restrictions.

[0064] For example, in this embodiment of the application, a wet wall sensor is established and connected to the luggage compartment to observe the wet area on the surface of the luggage compartment after the tailgate is opened. If water droplets fall onto the surface of the luggage compartment, a trace sensor is established with a time range of T3~T4, such as 30s~35s (this application does not impose a specific limitation). The sensor tracks the trajectory of the water droplets falling onto the surface of the luggage compartment and determines whether the simulated water droplet result meets the preset droplet conditions. If the wet area is less than the target value, the simulated water droplet result is determined to meet the preset droplet conditions, and the tailgate water risk assessment and protection work is completed. Otherwise, corresponding optimization measures are generated until the wet area is less than the target value, and the actual water droplet result in the luggage compartment of the target vehicle is determined according to the optimization measures.

[0065] Optionally, in one embodiment of this application, generating optimization measures corresponding to the simulated openable luggage compartment cover based on the simulated water droplet dripping results includes: determining the leakage risk area of ​​the simulated openable luggage compartment cover based on the water droplet trajectory data in the simulated water droplet dripping results; and generating optimization measures based on the leakage risk area.

[0066] In some embodiments, this application can accurately locate areas on the openable cover of a simulated luggage compartment that are at risk of leakage based on the water droplet trajectory data contained in the simulated water path dripping results, and generate corresponding optimization measures based on the areas at risk of leakage.

[0067] The optimization measures may include, but are not limited to, optimizing the taillight structure, changing the direction of the sealing strip around the tailgate, and adding a drainage structure. This application does not impose specific restrictions.

[0068] For example, embodiments of this application can determine the corresponding leakage risk area by observing the water droplet trajectory data contained in the simulated water flow results and the movement direction and dwell position of the water droplets. For instance, if the leakage risk area is close to the taillight, it indicates that the structural design between the taillight and the openable cover may be unreasonable, causing water droplets to easily flow into the luggage compartment along the edge of the taillight. In this case, embodiments of this application can optimize the taillight structure, such as adjusting the installation angle of the taillight or sealing the connection between the taillight and the openable cover. This application does not impose specific limitations. This reduces the risk of water leakage caused by taillight structure issues. If the area at risk of leakage is near the sealing strip around the tailgate, it indicates that the direction of the sealing strip may not effectively prevent water droplets from entering the luggage compartment, or the shape of the sealing strip may not match the vehicle body contour, or the installation position of the sealing strip may be unreasonable, allowing water droplets to bypass the sealing strip and enter the luggage compartment. In this case, the embodiments of this application can redesign the direction of the sealing strip around the tailgate, for example, by adjusting the bending direction of the sealing strip to be opposite to the direction of water droplet movement, thereby effectively preventing water droplets from seeping into the luggage compartment from the sealing strip and improving waterproof performance.

[0069] Furthermore, for some relatively flat areas prone to water accumulation and leakage risks, simply relying on sealing may not completely solve the problem. In such cases, this embodiment can install drainage channels, deflectors, or other drainage structures near the leakage risk area to guide the accumulated water to the outside of the vehicle, preventing the water from putting pressure on the openable cover and thus reducing the possibility of leakage.

[0070] The working principle of the baggage compartment waterway risk assessment method proposed in this application will be introduced below with reference to a specific embodiment.

[0071] in, Figure 3 This is a flowchart illustrating the working principle of a baggage compartment waterway risk assessment method according to an embodiment of this application.

[0072] Step S301: Set up a simple test bench.

[0073] The simplified test bench constructed in this embodiment of the application is as follows: Figure 2 As shown.

[0074] Step S302: Perform high-pressure water gun nozzle parameter calibration.

[0075] In this embodiment, a simple test bench is constructed according to the test standards: high-pressure water gun pressure ≥ 7.9 MPa, water output ≥ 1200 L / h. Figure 2As shown, the high-pressure water gun is kept horizontal, with a height H1 of 1.5m above the ground. A water bucket with a volume greater than 15L is placed in a suitable position, and the switch is turned on to spray water into the bucket. The spraying time T1 is 10s. The maximum horizontal spray distance S1 is measured and recorded as 6.60m, and the volume of water in the bucket V1 is 3.35L.

[0076] Step S303: Perform cleaning parameter calibration.

[0077] In this embodiment, based on experimental conditions, the nozzle is cleaned clockwise and counterclockwise around the rear door once each, and the sealed area is cleaned vertically and horizontally once each. Furthermore, in the simulation environment, the coordinates of the water gun nozzle simulation model are (X, Y, Z). Therefore, this embodiment can control the movement trajectory of the simulated nozzle by controlling the X, Y, and Z values ​​at different times, thereby outputting water droplet trajectory data that meets the motion requirements. For example, in this embodiment, the simulated nozzle is controlled as follows: when the simulated nozzle moves in the XOY plane, the Z coordinate remains constant at 1500mm, and circumferential movement is achieved by controlling the X and Y values; when the simulated nozzle moves in the XOZ plane, the Y coordinate remains constant at 50mm, and vertical cleaning is achieved by controlling the X and Z values; when the simulated nozzle moves in the YOZ plane, the X coordinate remains constant at 200mm, and horizontal cleaning is achieved by controlling the Y and Z values, as shown in Table 1.

[0078] Furthermore, in this embodiment of the application, when cleaning the tailgate according to the test conditions, the horizontal distance between the water gun nozzle and the tailgate is 50mm. Therefore, in the simulation environment, this embodiment of the application sets the horizontal distance between the simulated water gun nozzle and the tailgate to 50mm.

[0079] Step S304: Construct a simulation model of the water gun nozzle.

[0080] In this embodiment, a simulation model of the water gun nozzle is established in simulation software. In the simulation environment, the simulated high-pressure water gun is kept horizontal, ensuring a height H2 of 1.5m above the ground. The simulation begins, with a simulation time T2 of 10s. The maximum horizontal spray distance S2 is measured and recorded as 6.64m, and the volume of water sprayed is V2 as 3.37L, which does not satisfy |S2-S1|≤1% and |V2-V1|≤1%.

[0081] By continuously optimizing the nozzle diameter R and spray velocity U in the water gun nozzle simulation model, the maximum horizontal spray distance S2 was finally obtained as 6.61m with R=2mm and U=26.59m / s, and the volume of sprayed water was 3.36L, satisfying |S2-S1|≤1% and |V2-V1|≤1%.

[0082] Furthermore, in this embodiment of the application, after determining the required nozzle diameter R and water spray velocity U, the nozzle pressure P2 = 8.0 MPa and the volume of sprayed water V2 = 1209.6 L / h are measured in a simulation environment to determine whether P2 ≥ 7.9 MPa and V2 ≥ 1200 L / h are satisfied. If the requirements are met, the construction of the water gun nozzle simulation model is completed; if the requirements are not met, the nozzle diameter R and water spray velocity U are adjusted, and the parameters are recalibrated until the requirements are met, thus completing the construction of the water gun nozzle simulation model.

[0083] Step S305: Perform a simulation analysis of the rear door car wash.

[0084] In this embodiment, after constructing the water gun nozzle simulation model, the nozzle diameter R, water spray speed U, and the time-varying curve of the nozzle coordinates are input. The water gun nozzle simulation model is then checked. After the water gun nozzle simulation model is checked, the computational domain is determined: the boundary of the computational domain is more than 1000mm away from the vehicle in the X, Y, and Z directions. The area around the tailgate is densified, and the distance from the densified area to the tailgate in the X, Y, and Z directions is more than 300mm. According to R=4R1=8R2, if the nozzle diameter R of the simulation nozzle is 2mm, then the size R1 of the basic liquid particles is 0.5mm, and the size R2 of the liquid particles in the densified area is 0.25mm.

[0085] Furthermore, in this embodiment of the application, the simulation begins, and during the simulation, the nozzle pressure, water output, and nozzle movement trajectory are continuously monitored. After the car wash is completed, the simulated nozzle is controlled to stop spraying water, and the time is recorded as T3, thereby generating corresponding simulated water path dripping information. For example, if T3 is set to 30s in this embodiment of the application, the nozzle will stop spraying water at 30s of the simulation time, completing the car wash.

[0086] Step S306: Check for any abnormalities during the car wash process.

[0087] In this embodiment of the application, if an abnormality occurs during the car wash process, step S304 is executed to rebuild the model; if no abnormality occurs, step S307 is executed.

[0088] Step S307: Check whether the wetted area on the surface of the luggage compartment is less than the target value.

[0089] If the result is greater than or equal to the preset dripping condition, the simulated water path dripping result is determined to be unsatisfactory, and step S308 is executed; otherwise, step S311 is executed.

[0090] Step S308: Track the trajectory of the falling particles.

[0091] In this embodiment, the corresponding leakage risk area can be accurately located based on the water droplet trajectory data contained in the simulated water path dripping results.

[0092] Step S309: Generate the corresponding optimization measures.

[0093] In this application embodiment, when the water leakage risk area is close to the taillight position, the taillight structure can be optimized; when the water leakage risk area is located near the sealing strip around the tailgate, the direction of the sealing strip around the tailgate can be redesigned; in addition, for some relatively flat water leakage risk areas that are prone to water accumulation, this application embodiment can install drainage structures such as drainage channels and guide plates near the water leakage risk area.

[0094] Step S310: Check whether the simulated water path dripping results after implementing the optimization measures meet the preset dripping conditions.

[0095] If the condition is met, proceed to step S311; otherwise, proceed to step S309.

[0096] Step S311: Determine the actual water dripping results in the luggage compartment of the target vehicle based on the optimization measures.

[0097] According to the luggage compartment waterway risk assessment method proposed in this application, the simulated nozzle parameters of the simulated water gun nozzle can be determined based on a pre-constructed water gun nozzle simulation model. Then, based on the simulated nozzle parameters, the target simulated vehicle is cleaned to obtain the simulated waterway dripping results in the simulated luggage compartment of the target simulated vehicle. When the simulated waterway dripping results do not meet the preset dripping conditions, corresponding optimization measures are generated based on the simulated waterway dripping results until the simulated waterway dripping results meet the preset dripping conditions. Based on the optimization measures, the actual waterway dripping results in the luggage compartment of the target vehicle are determined. By constructing a high-precision digital simulation model, it is possible to flexibly simulate diverse car wash operating conditions such as different water pressures, angles, and nozzle types, accurately reproduce the dynamic distribution of water flow on the vehicle surface and the trajectory of water droplets. It innovatively constructs a closed-loop process of "simulation-analysis-optimization-verification", using data to drive decision-making, accurately reproduce car wash scenarios and predict risks, and achieve a leapfrog upgrade in risk prediction from experience-driven to data-driven, eliminating quality hazards caused by water droplets from the source. This solves the technical problems in related technologies, such as the lack of simulation methods, which makes it difficult to accurately reproduce the dynamic distribution of water flow on the car body under complex car wash conditions, and also makes it impossible to identify risks such as water accumulation areas and water droplet trajectories in advance, and even more difficult to provide high-precision data to support the optimization of waterproof structures and avoid related hidden dangers from the source.

[0098] Next, the baggage compartment waterway risk assessment device proposed according to the embodiments of this application is described with reference to the accompanying drawings.

[0099] Figure 4This is a block diagram of a baggage compartment waterway risk assessment device provided according to an embodiment of this application.

[0100] like Figure 4 As shown, the baggage compartment waterway risk assessment device 10 includes: a first determination module 100, a first generation module 200, and a second generation module 300.

[0101] The first determining module 100 is used to determine the simulation nozzle parameters of the water gun simulation nozzle based on the pre-built water gun nozzle simulation model.

[0102] The first generation module 200 is used to clean the target simulated vehicle based on the parameters of the simulated nozzle, so as to obtain the simulated water droplet results of the simulated luggage compartment in the target simulated vehicle.

[0103] The second generation module 300 is used to generate optimization measures corresponding to the simulated openable luggage compartment cover based on the simulated water path dripping results when the simulated water path dripping results do not meet the preset dripping conditions, until the simulated water path dripping results meet the preset dripping conditions, and determine the actual water path dripping results of the luggage compartment in the target vehicle according to the optimization measures.

[0104] Optionally, in one embodiment of this application, it further includes: an acquisition module, a second determination module, a third determination module, and a construction module.

[0105] The acquisition module is used to acquire the actual nozzle parameters of the water gun nozzle based on the target vehicle before determining the nozzle parameters of the simulated water gun nozzle based on the pre-built simulation model.

[0106] The second determining module is used to determine the actual spray distance and actual spray volume of the water gun nozzle based on the actual nozzle parameters.

[0107] The third determining module is used to determine the simulated spray distance and simulated spray volume of the water gun simulation nozzle based on the actual spray distance and actual spray volume.

[0108] The building module is used to construct a simulation model of the water gun nozzle based on the simulated spray distance and simulated spray volume.

[0109] Optionally, in one embodiment of this application, the first generation module 200 includes: a first determining unit and a first generation unit.

[0110] The first determining unit is used to determine the cleaning parameters of the target simulated vehicle based on the parameters of the simulated nozzle.

[0111] The first generation unit is used to clean the target simulated vehicle based on cleaning parameters to obtain the simulated water droplet results.

[0112] Optionally, in one embodiment of this application, the first generation module 200 includes: a second determining unit, a third determining unit, and a second generation unit.

[0113] The second determining unit is used to determine the computational domain and encryption area of ​​the simulated luggage compartment based on the coordinate data of the target simulated vehicle.

[0114] The third determining unit is used to determine the basic liquid particle information of the computational domain and the encrypted region particle information of the encrypted region based on the computational domain and the encrypted region.

[0115] The second generation unit is used to generate simulated water droplet information based on basic liquid particle information and encrypted region particle information.

[0116] Optionally, in one embodiment of this application, the second generation module 300 includes: a fourth determining unit and a third generation unit.

[0117] The fourth determining unit is used to determine the leakage risk area of ​​the simulated luggage compartment openable cover based on the water droplet trajectory data in the simulated water path dripping results.

[0118] The third generation unit is used to generate optimization measures based on the leakage risk area.

[0119] It should be noted that the foregoing explanation of the embodiment of the baggage compartment waterway risk assessment method also applies to the baggage compartment waterway risk assessment device of this embodiment, and will not be repeated here.

[0120] The luggage compartment waterway risk assessment device proposed in this application can determine the simulated nozzle parameters of the simulated water gun nozzle based on a pre-built simulation model of the nozzle. Then, based on these parameters, it cleans the target simulated vehicle, obtaining the simulated waterway dripping results in the simulated luggage compartment. If the simulated waterway dripping results do not meet the preset dripping conditions, corresponding optimization measures are generated until the simulated waterway dripping results meet the preset dripping conditions. Based on the optimization measures, the actual waterway dripping results in the luggage compartment of the target vehicle are determined. By constructing a high-precision digital simulation model, it can flexibly simulate diverse car wash operating parameters such as different water pressures, angles, and nozzle types, accurately reproducing the dynamic distribution of water flow and the trajectory of water droplets on the vehicle surface. It innovatively constructs a closed-loop process of "simulation-analysis-optimization-verification," using data-driven decision-making to accurately reproduce car wash scenarios and predict risks. This achieves a leapfrog upgrade in risk prediction from experience-driven to data-driven, eliminating quality hazards caused by water droplet dripping from the source. This solves the technical problems in related technologies, such as the lack of simulation methods, which makes it difficult to accurately reproduce the dynamic distribution of water flow on the car body under complex car wash conditions, and also makes it impossible to identify risks such as water accumulation areas and water droplet trajectories in advance, and even more difficult to provide high-precision data to support the optimization of waterproof structures and avoid related hidden dangers from the source.

[0121] Figure 5 This is a schematic diagram of the structure of a vehicle according to an embodiment of this application. The vehicle may include: The memory 501, the processor 502, and the computer program stored on the memory 501 and capable of running on the processor 502.

[0122] When the processor 502 executes the program, it implements the baggage compartment waterway risk assessment method provided in the above embodiments.

[0123] Furthermore, the vehicle also includes: Communication interface 503 is used for communication between memory 501 and processor 502.

[0124] The memory 501 is used to store computer programs that can run on the processor 502.

[0125] Memory 501 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0126] If the memory 501, processor 502, and communication interface 503 are implemented independently, then the communication interface 503, memory 501, and processor 502 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 5 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0127] Optionally, in a specific implementation, if the memory 501, processor 502, and communication interface 503 are integrated on a single chip, then the memory 501, processor 502, and communication interface 503 can communicate with each other through an internal interface.

[0128] Processor 502 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0129] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described baggage compartment waterway risk assessment method.

[0130] This application also provides a computer program product, including a computer program that, when executed, implements the above-described baggage compartment waterway risk assessment method.

[0131] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0132] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0133] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0134] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). In addition, the computer-readable medium can even be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting or otherwise processing as necessary, and then stored in computer memory.

[0135] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or more of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0136] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0137] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0138] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for assessing waterway risks in a baggage compartment, characterized in that, Includes the following steps: Based on the pre-built simulation model of the water gun nozzle, the simulation nozzle parameters of the water gun nozzle are determined. Based on the simulated nozzle parameters, the target simulated vehicle is cleaned to obtain the simulated water dripping results in the simulated luggage compartment of the target simulated vehicle. If the simulated water drop results do not meet the preset drop conditions, then optimization measures corresponding to the simulated openable luggage compartment cover are generated based on the simulated water drop results until the simulated water drop results meet the preset drop conditions, and the actual water drop results in the luggage compartment of the target vehicle are determined according to the optimization measures.

2. The method according to claim 1, characterized in that, Before determining the nozzle parameters of the simulated water gun nozzle based on the pre-built simulation model, the following steps are also included: Based on the target vehicle, obtain the actual nozzle parameters of the water gun nozzle; Based on the actual nozzle parameters, determine the actual spray distance and actual spray volume of the water gun nozzle; Based on the actual spray distance and the actual spray volume, the simulated spray distance and simulated spray volume of the water gun simulated nozzle are determined. Based on the simulated water spray distance and the simulated water spray volume, a simulation model of the water gun nozzle is constructed.

3. The method according to claim 1, characterized in that, The step of cleaning the target simulated vehicle based on the simulated nozzle parameters to obtain the simulated water droplet results in the simulated luggage compartment of the target simulated vehicle includes: Based on the simulated nozzle parameters, the cleaning parameters of the target simulated vehicle are determined; Based on the cleaning parameters, the target simulated vehicle is cleaned to obtain the simulated water droplet results.

4. The method according to claim 1, characterized in that, The step of cleaning the target simulated vehicle based on the simulated nozzle parameters to obtain the simulated water droplet results in the simulated luggage compartment of the target simulated vehicle includes: Based on the coordinate data of the target simulated vehicle, the computational domain and encryption area of ​​the simulated luggage compartment are determined; Based on the computing domain and the encryption region, determine the basic liquid particle information of the computing domain and the encryption region particle information of the encryption region; Based on the basic liquid particle information and the encrypted region particle information, the simulated water path dripping information is generated.

5. The method according to claim 1, characterized in that, The optimization measures generated based on the simulated water flow dripping results for the simulated openable luggage compartment cover include: Based on the water droplet trajectory data in the simulated water path dripping results, the leakage risk area of ​​the simulated luggage compartment openable cover is determined; Based on the areas at risk of leakage, the optimization measures are generated.

6. A baggage compartment waterway risk assessment device, characterized in that, include: The first determining module is used to determine the simulation nozzle parameters of the water gun simulation nozzle based on the pre-built water gun nozzle simulation model. The first generation module is used to clean the target simulated vehicle based on the simulated nozzle parameters to obtain the simulated water dripping result of the simulated luggage compartment in the target simulated vehicle. The second generation module is used to generate optimization measures corresponding to the simulated openable luggage compartment cover based on the simulated water path dripping results when the simulated water path dripping results do not meet the preset dripping conditions, until the simulated water path dripping results meet the preset dripping conditions, and determine the actual water path dripping results of the luggage compartment in the target vehicle according to the optimization measures.

7. The apparatus according to claim 6, characterized in that, Also includes: The acquisition module is used to acquire the actual nozzle parameters of the water gun nozzle based on the target vehicle before determining the nozzle parameters of the simulated water gun nozzle based on the pre-built water gun nozzle simulation model. The second determining module is used to determine the actual spray distance and actual spray volume of the water gun nozzle based on the actual nozzle parameters. The third determining module is used to determine the simulated spray distance and simulated spray volume of the water gun simulated nozzle based on the actual spray distance and the actual spray volume. A construction module is used to construct a simulation model of the water gun nozzle based on the simulated water spray distance and the simulated water spray volume.

8. A vehicle, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the baggage compartment waterway risk assessment method as described in any one of claims 1-5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the baggage compartment waterway risk assessment method as described in any one of claims 1-5.

10. A computer program product, characterized in that, Includes a computer program, which, when executed, is used to implement the baggage compartment waterway risk assessment method as described in any one of claims 1-5.

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