A multi-functional convertible system and method for a vehicle cabin

Abstract

The embodiment of the present specification provides a kind of automobile carriage multifunctional dress changing system and method, which can include determining carriage model based on carriage structure data;Carriage model is corrected based on dress changing data;Based on the first dress changing parameter, the simulation of corrected carriage model is controlled to determine the first limited feature;Determine improvement parameter based on the first limited feature;Improved parameter and the first limited feature are sent to display device.

Description

TECHNICAL FIELD

[0001] The present specification relates to the field of vehicle compartment transformation, and in particular, to a multi-functional vehicle compartment transformation system and method. BACKGROUND

[0002] With the continuous development of the automobile market and the diversification of consumer demand, the functionality and flexibility of automobiles are increasingly valued. In international automobile trade, the Completely Knocked Down (CKD) mode has shown significant economic benefits due to low transportation costs and localized assembly. Modular system design enables flexible switching of vehicle functions through replaceable functional compartments, allowing efficient localized assembly in the global market.

[0003] Traditional automobile design is usually optimized for a single purpose, making it difficult to meet the diverse needs of users in different scenarios. For example, a car exported to the global market has a fixed function as a passenger car. If the user wants to convert it into a logistics vehicle or pickup truck, the compartment and chassis structure need to be significantly modified. This multi-functional requirement has led to the development of automobile compartment transformation systems.

[0004] There are some modular transformation systems on the market. These systems use vehicle control units combined with actuators such as motors, hydraulic rods, and mechanical arms to achieve automatic deformation of the compartment structure and functional conversion. However, during the actual transformation process, problems such as limited component displacement and insufficient rotation angle may occur, affecting the integrity of the transformation and the realization of functions. In addition, due to the lack of effective simulation testing and early warning mechanisms, these problems can only be discovered during the actual transformation process, increasing the risk of use and maintenance costs.

[0005] Therefore, there is an urgent need for a multi-functional automobile compartment transformation system that can simulate testing before transformation, identify and solve potential problems in advance, to ensure the feasibility and safety of transformation. At the same time, the vehicle can not only achieve flexible transformation between different functional compartments, but also realize efficient localized assembly in the global market. This reduces the transportation costs and tariff burden of vehicle exports, such as quickly converting between passenger compartments and cargo compartments to meet user needs in multiple scenarios. SUMMARY

[0006] One or more embodiments of the present specification provide an automobile cabin multifunctional transformation system, comprising: an input device, a sampling sensor, a display device, and a processor. The input device is configured to obtain cabin structure data, the sampling sensor is configured to collect transformation data of the cabin, the display device is configured to display improvement parameters and first limited features, and the processor is configured to: determine a cabin model based on the cabin structure data; correct the cabin model based on the transformation data; control the corrected cabin model to perform simulation based on first transformation parameters to determine first limited features; determine improvement parameters based on the first limited features; and send the improvement parameters and the first limited features to the display device.

[0007] One or more embodiments of the present specification provide an automobile cabin multifunctional transformation device method. The method comprises: determining a cabin model based on the cabin structure data; correcting the cabin model based on the transformation data; controlling the corrected cabin model to perform simulation based on first transformation parameters to determine the first limited features; determining the improvement parameters based on the first limited features; and sending the improvement parameters and the first limited features to the display device.

[0008] One or more embodiments of the present specification provide an automobile cabin multifunctional transformation device, comprising a processor configured to execute an automobile cabin multifunctional transformation method.

[0009] One or more embodiments of the present specification provide a computer readable storage medium storing computer instructions, wherein the computer executes an automobile cabin multifunctional transformation method after reading the computer instructions in the storage medium. BRIEF DESCRIPTION OF DRAWINGS

[0010] The present specification will be further illustrated in the form of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting, and in these embodiments, the same numbers represent the same structures, wherein:

[0011] Figure 1 is a system schematic diagram of an automobile cabin multifunctional transformation system according to some embodiments of the present specification;

[0012] Figure 2 is a method flowchart of an automobile cabin multifunctional transformation according to some embodiments of the present specification;

[0013] Figure 3 is a schematic diagram of determining first limited features according to some embodiments of the present specification;

[0014] Figure 4is a flowchart of a method for determining an improvement parameter according to some embodiments of the present specification;

[0015] Figures 5A-5D is a vehicle cabin assembly for installing different functional cabins according to some embodiments of the present specification;

[0016] Figure 6 is a schematic diagram of assembling cockpit components according to some embodiments of the present specification;

[0017] Figure 7 is a schematic diagram of assembling multiple types of functional cabins according to some embodiments of the present specification; DETAILED DESCRIPTION

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present specification, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some examples or embodiments of the present specification, and for those skilled in the art, the present specification can also be applied to other similar scenarios without creative labor on the basis of these drawings. Unless it is clear from the language context or otherwise indicated, the same reference numbers in the drawings represent the same structure or operation.

[0019] It should be understood that the "system", "device", "unit" and / or "module" used herein is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

[0020] Unless the context clearly indicates otherwise, the words "one", "an", "a", and / or "the" do not mean a single number, but can also include a plurality. Generally speaking, the terms "comprise" and "include" only indicate the inclusion of the steps and elements explicitly identified, and these steps and elements do not constitute an exclusive list, and the method or device can also include other steps or elements.

[0021] Flowcharts are used in the present specification to illustrate the operations performed by the system according to the embodiments of the present specification. It should be understood that the preceding or subsequent operations are not necessarily performed in sequence. On the contrary, each step can be processed in reverse order or simultaneously. At the same time, other operations can also be added to these processes, or one or more steps of the operation can be removed from these processes.

[0022] Figure 1 is a system schematic diagram of a vehicle cabin multifunctional conversion system according to some embodiments of the present specification. In some embodiments, the vehicle cabin multifunctional conversion system 100 includes an input device 110, a sampling sensor 120, a processor 130, and a display device 140.

[0023] The input device 110 can acquire the car structure data, which includes size data, material data, fitting data, etc. of the car components. The car components include the convertible components and the fixed components. The input device 110 can include a keyboard, a mouse, a data interface (e.g. a USB interface), a scanning device (for scanning drawings), etc.

[0024] The sampling sensor 120 is configured to collect the convertible data of the car, which includes the motion data and the stress data, etc. of the convertible components. The sampling sensor 120 can include motion sensors, stress sensors (for collecting stress data during the convertible process), etc. installed on the convertible components.

[0025] In some embodiments, the processor 130 refers to a component with a data processing function, such as an integrated circuit chip. The processor can be of various specifications. The processor 130 can receive the car structure data of the input device 110 and the convertible data of the sampling sensor 120, and output the improvement parameters and the first limited features. For example, the processor can determine a car model based on the car structure data, correct the car model based on the convertible data, control the corrected car model to perform simulation based on the first convertible parameters, determine the first limited features, determine the improvement parameters based on the first limited features, and send the improvement parameters and the first limited features to the display device

[0026] The display device 140 is an electronic device for displaying information. The display device 140 is configured to display the improvement parameters and the first limited features obtained by the processor 130 for the user to view.

[0027] It should be noted that the above description of the automobile car multi-functional convertible system 100 and its modules is for the convenience of description, and cannot limit the scope of the present specification to the embodiments. It can be understood that, for those skilled in the art, after understanding the principle of the system, any combination of the modules or connection of the sub-systems and other modules can be made without departing from the principle. In some embodiments, Figure 1 The input device 110, the sampling sensor 120, the processor 130 and the display device 140 disclosed in the present specification can be different modules in a system, or one module can realize the functions of two or more modules as described above. For example, the modules can share a storage module, and the modules can also have their own storage modules. Variations such as this are within the scope of protection of the present specification.

[0028] Figure 2 is an exemplary flowchart of the automobile car multi-functional convertible method according to some embodiments of the present specification. In some embodiments, the flowchart 200 is executed by a processor.

[0029] In some embodiments, the processor can determine a vehicle cabin model based on the vehicle cabin structure data; correct the vehicle cabin model based on the variable configuration data; control the corrected vehicle cabin model to perform simulation based on the first variable configuration parameter to determine the first restricted feature; determine the improvement parameter based on the first restricted feature; and send the improvement parameter and the first restricted feature to the display device; and the display device is configured to display the improvement parameter and the first restricted feature.

[0030] At step 210, a vehicle cabin model is determined based on vehicle cabin structure data.

[0031] The vehicle cabin structure data refers to data related to vehicle cabin components. For example, the vehicle cabin structure data includes at least one of size data, material data, and fitting data of the vehicle cabin components.

[0032] Figures 5A-5D The vehicle cabin components are components that constitute the overall structure of the vehicle cabin according to some embodiments of the present specification. For example, the vehicle cabin components include one or more variable configuration components and fixed components. The fixed components are components that remain stationary during the variable configuration of the vehicle cabin and are responsible for supporting and stabilizing the overall vehicle cabin structure. For example, the fixed components include a vehicle cabin chassis component 530 and the like. The chassis component refers to a component located on the bottom of the vehicle chassis. For example, the chassis component includes tires and the like.

[0033] The variable configuration components are components that need to be moved or changed in posture. For example, the variable configuration components include a vehicle cabin cockpit component 510, a functional cabin 520, and a cold connection component. The cockpit component 510 refers to a component inside the vehicle cabin. For example, the cockpit component 510 includes a steering wheel, an instrument panel, and the like. The functional cabin 520 refers to a cabin that can implement different functions. The cold connection component refers to a component that connects vehicle components. For example, the cold connection component can include self-piercing rivets, flow-drill screws, adhesives, bolts and nuts, and the like.

[0034] In some embodiments, the fixed components and the functional cabin are provided with one or more sets of position corresponding and shape matching fitting positions.

[0035] The fitting position refers to the position at which the fixed component is connected to the functional cabin. In some embodiments, different types of functional cabins are configured to be connected to the fixed components by various cold connection methods based on cold connection components to the fitting positions corresponding to the fixed components of the vehicle. Thus, the vehicle can complete the variable configuration function to adapt to various use scenarios.

[0036] In some embodiments, the types of functional cabins may include, but are not limited to, passenger cabins, truck cabins, sightseeing cabins, and merchandise handling cabins, and can be switched between different types of functional cabins as needed to complete the transformation of the carriage. For example, a passenger cabin can be removed from the carriage and transformed into a logistics cabin.

[0037] In some embodiments, such as Figures 5A-5D As shown, technicians can assemble the cockpit component 510 and the functional compartment 520 according to their needs, so that the vehicle can be transformed into a cargo truck 540, a van 550, a passenger car 560, and a sightseeing vehicle 570, etc.

[0038] In some embodiments, the driver's cabin component 510 and the functional compartment 520 of the passenger compartment assembly can be integrated. For example, passenger compartment assemblies such as cars, SUVs, and vans, where the primary function is passenger seating.

[0039] For example, when the passenger compartment is installed on the fixed component, the vehicle can be transformed into a passenger car, SUV, or passenger commercial vehicle to meet the needs of daily commuting or carrying passengers; when the sightseeing vehicle compartment is installed on the fixed component, the vehicle can be transformed into a sightseeing vehicle to meet the needs of scenic area tourism; when the truck compartment is installed on the fixed component, the vehicle can be transformed into a truck or delivery vehicle to meet the needs of cargo transportation.

[0040] In some embodiments of this specification, diverse functional cabin types can be used to meet diverse needs by changing the functional cabins. For example, the vehicle can be flexibly switched to a passenger car, freight vehicle, or mobile commercial vehicle according to different scenario needs (such as daily commuting, freight transportation, and commercial activities) to meet multiple needs such as riding, freight transportation, and commercial operation. Furthermore, it supports independent maintenance and replacement of functional cabins, thereby improving the vehicle's functional versatility and usage efficiency.

[0041] Figure 6 This is a schematic diagram of the assembled cockpit components according to some embodiments of this specification.

[0042] like Figure 6 As shown, the cockpit functional modules include multiple functional modules such as the lower body module 610, the left side panel module 620, the right side panel module 630, the rear panel module 640, the top crossbeam module 650, the subframe module 660, and the frontal collision module 670.

[0043] In some embodiments, such as Figure 6As shown, different functional modules can be detachably assembled using cold-connect components to achieve the overall assembly of the vehicle body / shell. For example, the lower body module 610 and the subframe module 620 can be positioned and fixed using cold-connect technology first, and then the left side panel module 620 and the right side panel module 630 can be connected to the lower body module 610 in sequence; subsequently, the rear panel module 640, the top crossbeam module 650, and the frontal collision module 670 can be spliced ​​and fixed to the aforementioned assembled parts to assemble the cockpit component 510.

[0044] Figure 7 This is a schematic diagram illustrating the assembly of various types of functional cabins according to some embodiments of this specification.

[0045] In some embodiments, such as Figure 7 As shown, technicians can use cold-joining technology to assemble different vehicle components as needed, thereby forming various types of functional compartments 520. Furthermore, technicians can connect the chassis components 530 with different types of functional compartments 520 as required, allowing the vehicle to be converted into a cargo bed truck 540 or a van 550, etc. For example, an open cargo bed can be assembled onto the chassis first, allowing the vehicle to be converted into a cargo bed truck 540; when conversion to a van 550 is required, cold-joining technology can be used to replace and install a closed cargo box module onto the chassis, thus assembling the van 550.

[0046] By matching and connecting the above modules and using cold connection technology, a complete car body or vehicle body structure can be quickly and reliably formed according to requirements, thereby obtaining vehicles of different models.

[0047] In some embodiments, the cold joining technology corresponding to the cold joining components may not rely on welding, melting, or other heat treatment processes. For example, cold joining technologies may include, but are not limited to, one or more of self-piercing riveting (SPR), flow drill screw (FDS), adhesive bonding, flange connection, piece-locking connection, crimping, and bolted joints. Technicians can select the appropriate connection method according to requirements, and the form of the mating joint can be designed according to specific needs to adapt to different cold joining methods. Different mating joints use different cold joining components (such as self-piercing rivets, flow drill screws, bolts, etc.).

[0048] For example, when self-piercing riveting is used, the mechanical locking connection between the fixed assembly and the functional cabin can be achieved by self-piercing rivets, such as double-layer and multi-layer connections of homogenous or heterogeneous materials such as aluminum alloy and steel; flow-drilling screw connection can be achieved by flow-drilling screws to achieve threaded connection between the fixed assembly and the functional cabin, such as aluminum alloy material connection or connection of special-shaped structures in the fixed assembly and the functional cabin; adhesive connection uses adhesive to connect between heterogeneous materials in the fixed assembly and the functional cabin; hemming connection can use the curling design of the edge of the material to achieve edge connection of materials such as aluminum alloy sheet, hot-formed ultra-high-strength steel, and ordinary steel through edge adhesive; Piece-locking connection can set pits at a certain distance on the material in the hemming area, and achieve the lamination and fixation of multi-layer materials through rivets and adhesives; crimping can be a process method that plastically deforms metal parts by applying pressure and forms a tight bond with the parts to be connected. For example, crimping can be used to tightly connect the wire terminal in the fixed assembly with the wire core to form an electrical connection with high electrical conductivity and high mechanical stability; it can also be used for fixation of metal pipes in the functional cabin to have good sealing and mechanical strength at the pipe connection site; screw connection can achieve mechanical connection between the fixed assembly and the functional cabin through bolts and nuts, for example, in the connection between the functional cabin and the chassis, screw connection can achieve quick assembly and disassembly through pre-set screw holes.

[0049] In some embodiments of the present specification, through various cold connection methods, different functional cabins can be reliably connected with the fixed assembly, supporting the rapid reconfiguration of the vehicle to adapt to various use scenarios. For example, self-piercing riveting can avoid the influence of heat treatment on the performance of the material, and during the connection process, the coating on the surface of the material will not be damaged; flow-drilling screw connection can connect different materials of metal and non-metal, and adapt to various connection requirements; adhesive connection can firmly connect various types of materials together, and is especially suitable for the connection of heterogeneous materials that cannot be achieved by traditional welding; screw connection can support the repeated disassembly of the fixed assembly and the functional cabin, facilitating the repair, replacement, and functional upgrade of the vehicle, and prolonging the service life of the carriage assembly; different cold connection components are used in different fitting positions to ensure the flexible combination of the reconfiguration assembly, for example, the connection position of the passenger cabin can use screw connection or adhesive connection to ensure the load-bearing strength and comfort; the logistics cabin uses flow-drilling screw connection to meet the high load demand;

[0050] In some embodiments of the present specification, by configuring the functional cabin to be connected with the fixed assembly through the cold connection component, in the CKD export mode, not only the complexity of the vehicle conversion operation is reduced, but also the supply chain process is simplified, facilitating global production and market rapid response. The cold connection technology can greatly reduce the transportation volume and complexity, and increase the reusability and flexibility of the conversion assembly. By designing the functional cabin of the vehicle to be replaceable and convertible, the vehicle can be switched between different types of functional cabins according to the needs of the user. In the CKD export mode in various use environments, the functional cabin of the vehicle can be directly assembled at the transportation destination and reused multiple times when disassembled, greatly improving the functional value of the vehicle. At the same time, the conversion assembly can be shared between different vehicle models, reducing the types and quantities of vehicle-specific parts and reducing overall research and development and manufacturing costs.

[0051] The size data refers to data related to the size of the cabin assembly. In some embodiments, the size data can be in the form of a CAD (Computer-Aided Design, CAD) STP or STEP file format, etc., to completely record the size data of the cabin assembly.

[0052] The material data refers to data related to the material properties of the cabin assembly. For example, the material data includes tensile strength, plasticity, elasticity, density, etc.

[0053] The fitting data refers to data related to the fitting method and relative positional relationship between each cabin assembly. For example, the fitting data can include threaded fitting, pin fitting, freedom of movement of the assembly, etc. In some embodiments, the fitting data can also be in the form of a CAD STP or STEP file format, etc.

[0054] The cabin model refers to a three-dimensional model corresponding to the cabin.

[0055] In some embodiments, the processor can construct a three-dimensional model of the cabin based on the size parameters and fitting data through a three-dimensional modeling tool or modeling platform, and assign values to the mechanical properties such as flexibility, mass, center of gravity, etc. of each cabin assembly according to the material data, to obtain a cabin simulation model (i.e., the cabin model hereinafter) that can exhibit three-dimensional structure and performance attributes. For example, the three-dimensional modeling tool or modeling platform can include CAD, Maya, 3ds Max, etc. three-dimensional modeling software.

[0056] In some embodiments, the cabin model can include a power device for driving the cabin to convert. For example, a motor, a hydraulic device, etc.

[0057] Step 220, correcting the cabin model based on the conversion data.

[0058] The transformation data refers to data generated in the process of transformation of the carriage assembly based on the transformation parameters. For example, the transformation data includes the transformation action sequence of each carriage assembly, stress data of the carriage assembly, torque required for rotation of the driving assembly, etc.

[0059] In some embodiments, the sampling sensor can collect the transformation data during the actual transformation process of the carriage. For example, the processor can collect the transformation data during the transformation process through the motion sensor and the stress sensor installed on the plurality of transformation assemblies, etc.

[0060] The transformation parameter refers to a parameter related to the transformation of the carriage. For example, the transformation parameter includes the transformation action sequence, motion speed, motion displacement (rotation angle, movement distance), torque, etc. of each transformation assembly.

[0061] The control of the transformation parameter can be realized based on the control of the rotation parameters (such as rotation sequence, rotation speed, rotation angle, etc.) of each power device. The transformation parameter can be pre-set by the processor and / or pre-set by the user according to the requirement.

[0062] In some embodiments, the processor can correct the carriage model according to the difference between the actual transformation data collected by the sampling sensor during the actual transformation of the carriage and the simulation transformation data obtained by the computer based on the same transformation parameter for the transformation simulation of the carriage model.

[0063] The correction of the carriage model can include correction of the carriage structure data corresponding to the carriage model. For example, the processor can determine the actual structure parameters corresponding to the corresponding vehicle assembly of the carriage model based on the actual transformation data, and determine the corresponding mechanical property value of the corresponding carriage assembly based on the actual structure parameters, to correct and update the carriage model.

[0064] Step 230, based on the first transformation parameter, control the corrected carriage model to perform simulation simulation, and determine the first limited feature.

[0065] The first transformation parameter refers to the transformation parameter used when the corrected carriage model is re-simulated.

[0066] In some embodiments, the first control parameter can be pre-set by the processor and / or pre-set by the user according to the requirement, for example, the first control parameter can be the same as the transformation parameter used in the foregoing transformation simulation.

[0067] The simulation simulation refers to the simulation of the transformation process of the carriage by the computer through the simulation technology.

[0068] In some embodiments, the carriage can be simulated based on the first transformation parameter, and the user can pre-input the first transformation parameter through an input device based on the demand. For example, the processor can control the power device in the carriage model to operate according to the first transformation parameter, so as to transform the carriage into other forms.

[0069] In some embodiments, each component in the carriage model is modeled as an entity that cannot be passed through, and there is weight, so that the simulation can simulate the changes of gravity, the changes of applied power and the effects of interaction forces during the transformation process of the components according to these physical characteristics, so as to reflect the actual physical phenomena that may be encountered during the transformation process.

[0070] The first limited feature refers to a feature that may cause the carriage transformation to fail to be completed normally. For example, the first limited feature includes limited components, limited types, limited degrees, etc. Among them, the situation that the carriage transformation fails to be completed normally includes the situation that the transformation process of the carriage model in the simulation fails to be completed normally, the situation that the carriage components after transformation cannot be used normally, etc.

[0071] The limited component refers to a specific carriage component that appears the above-mentioned transformation problems such as unable to complete the transformation normally or unable to use normally after transformation in the simulation.

[0072] The limited type refers to the reason type that causes the limited component to appear the above-mentioned transformation problems, such as rotation angle limitation, movement distance limitation, strength limitation, and the type that the preposed transformation component is a limited component, etc.

[0073] The limited degree refers to the proportion of the transformation of the limited component that is not completed or exceeds the designed value. For example, the limited degree includes the proportion of the angle that the carriage component cannot continue to rotate to the theoretical angle, the proportion of the distance that the carriage component cannot continue to move to the theoretical distance, the proportion of the strength of the carriage component that exceeds the theoretical design value, etc.

[0074] The preposed transformation component refers to a component that completes the transformation before the postposed transformation component in the simulation. In some embodiments, after the preposed transformation component completes the transformation, the postposed transformation component can start the transformation.

[0075] The postposed transformation component refers to a component that can be transformed only after the preposed transformation component completes the transformation. In some embodiments, if the preposed transformation component is limited, the postposed transformation component is also a limited component, and the limited type of the postposed transformation component can be “the preposed transformation component is a limited component”.

[0076] In some embodiments, the pre-variant component and the post-variant component are relative to two variant components, the pre-variant component needs to be completed before the post-variant component. For example, the variant component B must be completed after the variant component A is completed, then the variant component B is the post-variant component of the variant component A, and the variant component A is the pre-variant component of the variant component B.

[0077] In some embodiments, the processor can control the corrected cabin model to perform simulation based on the first variant parameters. If a variant component has a variant limitation, the component is regarded as a limited component, the processor can record the limited feature corresponding to the limited component as the first limited feature, and skip the simulation of the limited component, and restore the limited component to the initial state without deformation during the simulation, and continue to perform the variant simulation of the remaining components until the variant is completed, that is, all the first limited features are obtained. Wherein, the variant limitation of a variant component includes interference between the variant component and other components during rotation or rotation of the variant component, the proportion of the strength of the cabin component after the variant of the variant component exceeding the theoretical design value, or the pre-variant component of the variant component has a variant limitation.

[0078] Step 240, determining the improvement parameter based on the first limited feature.

[0079] The improvement parameter refers to the parameter for improving the cabin component. For example, the improvement parameter includes changing the size of the cabin component, changing the position of the cabin component, replacing the material of the cabin component, and adding a reinforcing part.

[0080] In some embodiments, the processor can determine the corresponding improvement parameter according to different first limited features. For example, for the limited type of rotation angle limitation or movement distance limitation, the processor can calculate the safe distance between the two components that interfere with each other, determine a plurality of candidate positions according to the safe distance, and take the plurality of candidate positions as the improvement parameter. Wherein, the candidate position refers to the position of the two components that do not interfere with each other according to the safe distance.

[0081] For example, for the limited type of strength limitation, the processor can calculate the performance requirement of the cabin component according to the safety factor and the limited degree (for example, calculate the required tensile and compressive strength of the component); determine a plurality of candidate reinforcing parameters according to the preset rule based on the performance requirement of the component; and take the plurality of candidate reinforcing parameters as the improvement parameter.

[0082] For example, for a limited component B with a limited type of "predecessor refitting component is a limited component", the processor can determine the improvement parameter corresponding to the predecessor refitting component A based on the limited type of the predecessor refitting component A, and the limited type of the limited component B is no longer "predecessor refitting component is a limited component". The processor can continue to perform simulation based on the improvement parameter to determine whether the limited component B is still a limited component. If the limited component B is still a limited component, the corresponding improvement parameter is generated based on the limited type thereof until there is no limited component, and the last improvement parameter is determined as the final improvement parameter.

[0083] The candidate reinforcement parameters include increasing size, replacing material, adding different reinforcement components, etc. The preset rule refers to the calculation relationship between different reinforcement parameters and the performance after reinforcement. The safety factor and the preset rule can be set by default by the processor and / or by the user according to the demand in advance.

[0084] In some embodiments, the processor can also set a score for each candidate position and candidate reinforcement parameter according to the degree of change and reinforcement cost involved in each candidate position and candidate reinforcement parameter, and use the score as an improvement parameter for the user to refer to. For example, the score is higher if the position changes less after some improvement. For example, the score is lower if the cost of the candidate reinforcement parameter of increasing size is higher, and so on.

[0085] In step 250, the improvement parameter and the first limited feature are sent to the display device.

[0086] In some embodiments, the display device is configured to display the improvement parameter and the first limited feature for the user to refer to and select.

[0087] In some embodiments of the present specification, the simulation is performed based on the corrected carriage model to ensure that the carriage model is more in line with the physical characteristics of the actual carriage, thereby improving the accuracy and reliability of the simulation. By identifying the first limited feature in the refitting process, the processor can determine the improvement parameter for each limited component and display it to the user, so that the user can more intuitively understand the problems of the carriage in the simulation, and ensure the safety, reliability and operability of the carriage in the actual refitting scene.

[0088] It should be noted that the above description of the process 200 is only for example and illustration, and does not limit the scope of the present specification. Various modifications and changes can be made to the process under the guidance of the present specification. However, these modifications and changes are still within the scope of the present specification.

[0089] Figure 3 is an exemplary schematic diagram for determining the first limited feature according to some embodiments of the present specification.

[0090] like Figure 3 As shown, in some embodiments, the processor is further configured to: determine a load model 321 based on the load data 311 of the carriage; perform simulation based on the load model 321 and the corrected carriage model 322 to determine the force data 330 of the alteration component; and determine a first restricted feature 390 based on the force data 330 of the alteration component.

[0091] Load data 311 refers to information related to the goods loaded in the car. For example, load data 311 includes the maximum weight of the goods to be loaded in the car, the dimensions of the goods, and the type of goods.

[0092] In some embodiments, the processor may determine load data 311 based on acquired user input.

[0093] Load model 321 refers to the simulation model of the loaded goods. For example, load model 321 includes simulation models of bulk goods, packaged goods, and other simulation models.

[0094] Simulation models of bulk cargo can reflect the characteristics of bulk cargo of different sizes; simulation models of packaged cargo can reflect the characteristics of different packaging methods, such as boxed, bagged, and other packaging methods, as well as different packaging sizes.

[0095] In some embodiments, the processor may determine the load model 321 by modeling the load data 311 using a 3D modeling tool or platform.

[0096] In some embodiments, the processor can apply the load model 321 to the corrected carriage model 322 and simulate the actual cargo loading situation of the carriage after the transformation.

[0097] In some embodiments, the processor can pre-construct the motion equations of the load model 321 using theories such as a priori mechanics and kinematics, and calculate and obtain the properties of the load model 321 based on the motion equations. For example, the properties of the load model 321 may include properties such as the weight of the cargo loaded in the carriage, the force law, and the force motion law.

[0098] Force data 330 refers to data related to the forces experienced by each component of the carriage when bearing a load. For example, force data 330 includes data such as stress and strain experienced by each component of the carriage when bearing a load.

[0099] In some embodiments, the processor can determine the force data 330 in various ways. For example, after the load model 321 is applied to the corrected carriage model 322 for simulation, the processor calculates the force of each component of the carriage when carrying cargo based on the motion equation constructed based on the theory of mechanics and kinematics, combined with the properties of the load model 321, and records the force data 330 of each component, thereby evaluating the mechanical performance of each component under actual load conditions.

[0100] In some embodiments, the simulation includes a driving simulation, and the driving simulation includes obtaining driving posture information 323 of the vehicle; determining the force data 330 further includes determining the force data 330 of the plurality of variable components based on the driving posture information 323 and the load data 311.

[0101] The driving simulation refers to simulating the force state of the carriage components during driving.

[0102] The driving posture information 323 refers to information related to the posture of the carriage during driving of the vehicle. For example, the driving posture information 323 can include posture information such as pitch, roll, and steering angle of the carriage during driving at different speeds on different road surfaces, such as starting, straight driving, turning driving, and different flatness.

[0103] In some embodiments, the sampling sensor can be configured to collect driving posture information 323 during driving simulation under different road conditions and driving conditions.

[0104] In some embodiments, after the load model 321 is applied to the corrected carriage model 322, the processor can perform driving simulation according to various driving posture information 323, and record the force data 330 of each carriage component during the entire driving simulation.

[0105] In some embodiments of the present specification, by recording the force data throughout the driving simulation, it can be identified which components may exceed their design limits, and thus the potential weak links of the carriage components can be found, ensuring the structural stability and durability of the carriage under various driving postures.

[0106] In some embodiments, the processor can determine whether the force data 330 of the variable component exceeds the maximum strength design value; and in response, a first restricted feature 390 is generated based on the variable component. The maximum strength design value can be pre-constructed based on historical data or prior knowledge.

[0107] In some embodiments, the first newly generated restricted feature 390 is of a strength restriction type, which is less intuitive than the rotation and movement restriction types. The user can directly know the rotation and movement restriction types by observing the posture information of the vehicle cabin model in the driving simulation model. However, the strength restriction type is more hidden and cannot be determined by simple observation. Therefore, the processor can determine the first newly generated restricted feature 390 based on the stress data 330 of the plurality of variable dress components.

[0108] In some embodiments, the processor is further configured to determine a stress data sequence 341 based on the stress data 330 of the variable dress components; predict future deformation data 370 based on the stress data sequence 341; determine a reliability value 380 of the variable dress components based on the future deformation data 370; and determine the first restricted feature 390 based on the reliability value 380 and the future deformation data 370.

[0109] The stress data sequence 341 refers to a sequence formed by the stress data of the plurality of variable dress components in the entire simulation simulation process. In some embodiments, the stress data sequence 341 can be represented in chronological order by the component stress data 330 recorded in the simulation simulation. For example, the stress data sequence of the variable dress component a can be (σ1, σ2, σ3), and the elements in the sequence represent the stress σ1 MPa of the variable dress component a at the first time point, the stress σ2 MPa at the second time point, and the stress σ3 MPa at the third time point.

[0110] The future deformation data 370 refers to the deformation data that the vehicle cabin component can occur in the future period.

[0111] In some embodiments, the processor can predict the future deformation data 370 in various ways. For example, the processor can calculate the future deformation data 370 of each component in the future period based on the stress data sequence 341 and the priori material mechanics principle.

[0112] In some embodiments, the processor can determine the length of the future period according to the way that the design service life of the vehicle is positively correlated with the length of the future period.

[0113] For example, given a support rod stress sequence, the processor can obtain a strain sequence corresponding to each time point according to Hooke's law and the simulation simulation process, and further convert the strain into a deformation variable. Then, the deformation variables at each time point are accumulated to obtain the predicted future deformation data 370, i.e., the cumulative deformation of the support rod in the future period.

[0114] In some embodiments, based on the stress data sequence 341, predicting the future deformation data comprises constructing a stress analysis graph 350 based on the stress data sequence 341 and the carriage structure data 342; and predicting the future deformation data 370 based on the stress analysis graph 350 and the deformation model 360, the deformation model 360 being a machine learning model.

[0115] The stress analysis graph 350 refers to a graph used to reflect the stress conditions between various components of the carriage, and is composed of nodes and edges. The nodes of the stress analysis graph 350 include a variable assembly node corresponding to a variable assembly in the carriage, and a fixed assembly node corresponding to a fixed assembly.

[0116] The node features can include size data, material data, stress data sequence, etc. of the corresponding component.

[0117] The plurality of nodes can be connected by edges, and the attributes of the edges can reflect the relationship between the two component nodes. When there is a connection relationship between two nodes, the connection is based on the edge.

[0118] In some embodiments, the attributes of the edges can include the relative position relationship, the fitting mode, the mutual motion freedom degree, etc. between the two components. The attributes of the edges can be represented based on a pre-constructed spatial coordinate system, and the mutual motion freedom degree can include the maximum amplitude of the relative motion of the two components, the motion direction, etc.

[0119] The deformation model 360 refers to a model used to predict the future deformation data 370. In some embodiments, the deformation model 360 can be a machine learning model, such as a graph neural network model, etc.

[0120] In some embodiments, the input of the deformation model can include the stress analysis graph 350 and the length of the future time period (not shown in the figure), and the output of the deformation model can be the future deformation data 370 of each node based on the node output. The length of the future time period can refer to the above related description. Figure 3 The above related description.

[0121] In some embodiments, the processor can train the deformation model based on a large number of first training samples with first labels by gradient descent method, etc. The first training sample can include a sample stress analysis graph of a sample vehicle and the length of a sample future time period, and the first label of the first training sample can be the deformation data collected during the actual variable assembly process of the carriage of the sample vehicle.

[0122] In some embodiments, the processor can perform multiple variable assembly tests based on multiple sample vehicles, and collect related data to construct the first training sample. At the same time, the actual deformation data of each component at each time point in the variable assembly test is used as a label.

[0123] In some embodiments, the processor can input the plurality of labeled first training samples into the initial morphing model, construct a loss function based on the labels and the output of the initial morphing model, and iteratively update the parameters of the initial morphing model based on the loss function by gradient descent or other methods. When a preset condition is met, the model training is completed, and a trained morphing model is obtained. The preset condition can be convergence of the loss function, number of iterations reaching a threshold, etc.

[0124] In some embodiments of the present specification, by constructing a stress analysis graph, the connection relationship between the car components can be intuitively represented in the form of nodes and edges, and the complex interaction relationship of the car in future stress and deformation can be more comprehensively and accurately described. By using the trained morphing model, the mutual influence between components can be considered comprehensively, so that more accurate and comprehensive future deformation prediction can be realized.

[0125] The reliability value 380 of the deformation component is a value that indicates whether the deformation component can remain within an acceptable deformation range under the future deformation data 370.

[0126] In some embodiments, the processor can obtain the reliability value 380 based on the difference between the preset allowable deformation data of the deformation component and the future deformation data 370. The larger the difference, the higher the reliability value. For example only, the reliability value = preset allowable deformation data of the deformation component - future deformation data of the deformation component. The processor can determine the preset allowable deformation data of the deformation component based on the user input.

[0127] In some embodiments, if the reliability value 380 is negative, it indicates that the predicted future deformation data 370 exceeds the allowable deformation data set by the user, and the component cannot maintain its structural stability under the future deformation data 370, and the strength is limited. The processor can determine a new first limited feature 390 based on the deformation component. The limited degree in the first limited feature can be represented as the exceeding proportion of the future deformation data 370 relative to the allowable deformation data.

[0128] In some embodiments of the present specification, by predicting the future deformation data based on the stress data sequence and further determining the reliability value, the stress changes of the component at different time periods can be evaluated, so that the reliability of the component can be more accurately judged, the components with insufficient reliability can be found in advance, and the reliability and safety of the car in the long-term use process can be ensured.

[0129] In some embodiments of the present specification, by considering the load data, the working state of the train car during actual use can be better simulated and simulated, and the influence of the load on the strength of the car component is revealed, so that the deformation component can still maintain stability when carrying goods, and excessive deformation caused by load can be avoided, so that the car design is more safe and reliable in actual use, and the safety of the car is improved.

[0130] Figure 4 FIG. 4 is a flowchart illustrating an example process 400 of determining the improvement parameter according to some embodiments of the present disclosure. In some embodiments, the process 400 is performed by the processor.

[0131] In some embodiments, the processor is further configured to, in response to the first restricted feature not satisfying the preset condition, determine a second dressing parameter based on the first dressing parameter; perform simulation based on the second dressing parameter to determine a second restricted feature; perform at least one iteration on the second dressing parameter based on the second restricted feature to determine a target dressing parameter; and determine the improvement parameter based on the target dressing parameter.

[0132] At step 410, in response to the first restricted feature not satisfying the preset condition, a second dressing parameter is determined based on the first dressing parameter.

[0133] The preset condition can be that the restricted degree in the first restricted feature exceeds a preset restricted threshold.

[0134] In some embodiments, the user can input the maximum change data allowed by each component in advance through the input device based on the dressing requirement; the processor calculates the maximum restricted degree that the component can withstand based on the input maximum change data and in combination with the principles of material mechanics, etc., and takes it as the preset restricted threshold of the component. The maximum change data can include the position range of the dressing component that the user can accept, the material performance that can be replaced, the material size that can be added, etc.

[0135] The second dressing parameter refers to the improved first dressing parameter.

[0136] In some embodiments, in response to the first restricted feature not satisfying the preset condition, the processor updates the first dressing parameter within the maximum change data based on the first dressing parameter to obtain the second dressing parameter. For example, the movement order of the first dressing parameter of each component can be changed to avoid some restrictions in terms of rotation angle, movement distance, etc.

[0137] At step 420, simulation is performed based on the second dressing parameter to determine a second restricted feature.

[0138] The second restricted feature refers to the restricted feature determined based on the second dressing parameter.

[0139] In some embodiments, the processor can control the corrected carriage model to perform simulation based on the second variable dressing parameter. If variable dressing limitation occurs, the processor can record the limited feature corresponding to the variable dressing component causing the variable dressing limitation as a second limited feature, skip the variable dressing simulation of the component, restore the component to the initial state without deformation, and continue the variable dressing simulation of the remaining components until the variable dressing is completed, thereby obtaining all the second limited features.

[0140] In some embodiments, if the front variable dressing component and the rear variable dressing component have a dependency relationship, and the front variable dressing component has variable dressing limitation based on the second variable dressing parameter, the determination method of the second limited feature is similar to the foregoing, which will not be described here. For more information, please refer to the manner of determining the first limited feature in Figure 2

[0141] Step 430: Based on the second limited feature, at least one iteration is performed on the second variable dressing parameter to determine a target variable dressing parameter.

[0142] The target variable dressing parameter refers to the variable dressing parameter obtained after iteration optimization.

[0143] In some embodiments, the processor can determine the target variable dressing parameter in various ways. For example, the processor can randomly generate a second variable dressing parameter based on the first variable dressing parameter, perform simulation on the carriage model based on the generated second variable dressing parameter, and determine whether the second limited feature exists according to the simulation result. If the second limited feature does not exist and the preset condition is met, the iteration process is stopped, and the second variable dressing parameter is taken as the target variable dressing parameter. If the second limited feature exists and the preset condition is not met, the second variable dressing parameter is generated again for the next iteration.

[0144] In some embodiments, performing at least one iteration on the second variable dressing parameter based on the second limited feature includes: comparing the initial feature of the current iteration with the initial feature of the previous iteration to determine the feature change information; determining the update parameter based on the feature change information and its associated sub-parameter; performing simulation based on the update parameter to determine the update feature; in response to the iteration completion condition not being met, determining the iteration parameter and the iteration feature based on the update feature and the update parameter, and taking the iteration feature and the iteration parameter as the initial feature of the next iteration and the associated sub-parameter of the initial feature for the next iteration; and in response to the iteration completion condition being met, taking the update parameter of the current iteration as the target variable dressing parameter.

[0145] The initial feature refers to the second limited feature that is not updated in an iteration, which can be determined based on the iteration feature output in the previous iteration. The initial feature of the first iteration can be determined based on the second limited feature determined as described above.

[0146] ​The feature change information refers to the change information of the restricted feature in the current iteration process. For example, the feature change information can include improvement or deterioration of the restricted condition in the current iteration process, wherein the improvement of the restricted condition can include reduction of the restricted component and reduction of the restricted degree.

[0147] In some embodiments, the processor can determine the feature change information by comparing the initial feature in the current iteration with the initial feature in the previous iteration.

[0148] The associated sub-parameter of the feature change information refers to the sub-parameter in the second deformation parameter of the current iteration that causes the change of the restricted feature. For example, the sub-parameter can include the rotation speed, the rotation torque, and the rotation angle of each component in the second deformation parameter of the current iteration.

[0149] In some embodiments, the associated sub-parameter of the feature change information of the first iteration is determined based on the second deformation parameter without updating, and the associated sub-parameter of each subsequent iteration is determined based on the iteration parameter of the previous iteration.

[0150] In some embodiments, the determination of the associated sub-parameter of the feature change information further includes: determining the force change information of the force data when different sub-parameters are executed in the simulation; and determining the associated sub-parameter based on the force change information.

[0151] The force change information refers to the change information of the force data of the deformation component. In some embodiments, when performing simulation, the processor can record the force data of each deformation component under different sub-parameters, and mark the components and the force data change by comparing the force data before and after.

[0152] In some embodiments, the processor can take the sub-parameter corresponding to the component whose force changes as the associated sub-parameter corresponding to the component.

[0153] In some embodiments, if the component whose force changes is a restricted feature, the sub-parameter that causes the force to change can be taken as the associated sub-parameter of the restricted feature. For example, due to the rotation parameter (e.g., rotation of 45°) of component A, the force of component B increases, causing its restricted degree to exceed the preset restricted threshold. Based on component B, the second restricted feature can be determined, and the rotation parameter of component A is regarded as the associated sub-parameter that causes the feature change of component B, and the feature change information corresponding to the feature change is the deterioration of the restricted condition.

[0154] In some embodiments of the present specification, by analyzing the force change information, the processor can identify the significant change information of the force of each car compartment component when certain deformation sub-parameters are executed, and the restricted condition corresponding to the change information. The processor can optimize the sub-parameters associated with the restricted features to reduce or avoid the restriction of the components.

[0155] The update parameter refers to the second variable dressing parameter updated in the current iteration.

[0156] In some embodiments, the processor can determine the update parameter based on the feature change information and its associated sub-parameter. For example, if the feature change information obtained in the last iteration is that the restricted condition is improved, the update parameter in the current iteration can be determined based on the direction and amplitude of the adjustment of the associated sub-parameter reserved or along the associated sub-parameter in the last iteration (for example, the adjustment direction of the rotation sequence of the component, the rotation speed, etc.), and then the second variable dressing parameter is determined.

[0157] In some embodiments, if the feature change information obtained in the last iteration is that the restricted condition is deteriorated, the update parameter in the current iteration can be determined based on the associated sub-parameter restored to the state before the update or the associated sub-parameter determined by the reverse adjustment of the corresponding associated sub-parameter, and if necessary, other sub-parameters in the second variable dressing parameter can be adjusted to reduce the deterioration.

[0158] The update feature refers to the restricted feature determined when the simulation is performed based on the update parameter in the current iteration.

[0159] In some embodiments, the processor can perform simulation using the update parameter, and if there is still a restricted feature in the simulation under the update parameter, the update feature is obtained.

[0160] In some embodiments, the processor can determine whether the iteration completion condition is met based on the update feature or the iteration round, and in response to the iteration completion condition not being met, determine the iteration parameter and the iteration feature based on the update feature and the update parameter, and use the iteration feature and the iteration parameter as the initial feature and the associated sub-parameter of the initial feature in the next iteration to perform the next iteration.

[0161] The iteration completion condition can include that the update feature converges or the iteration round meets a preset number of times. Wherein, the update feature converges can be that the number of rounds in which the change of the update feature of the adjacent two rounds is less than a preset change threshold exceeds a preset round threshold or the update feature is 0 (i.e. there is no longer a restricted feature).

[0162] In some embodiments, in response to the iteration completion condition being met, the processor can use the update parameter in the current iteration as the target variable dressing parameter.

[0163] In some embodiments of the present specification, through multiple iterations, the second variable dressing parameter is continuously optimized, the convergence speed of the second restricted feature is accelerated, and the iteration efficiency is improved; by determining the associated sub-parameter, unnecessary adjustment of irrelevant parameters is avoided, and the optimization efficiency and reliability of the entire iteration process are improved.

[0164] At step 440, the improvement parameter is determined based on the target variable dressing parameter.

[0165] In some embodiments, the processor can determine the corresponding improvement parameter based on the limited feature corresponding to the target variable dressing parameter. This way is the same as determining the improvement parameter based on the first limited feature. For details of how to determine the improvement parameter, please refer to Figure 2 and the related description.

[0166] In some embodiments of the present specification, when the first limited feature of the carriage assembly is greater than the preset limited threshold, the limitation of the assembly exceeds the designed safety range and cannot meet the reliability requirements. By generating the second variable dressing parameter and continuously iterating, the processor can finally find a set of target variable dressing parameters that can completely solve the limitation problem and meet the preset conditions, so that the carriage assembly has stronger adaptability in actual driving operation.

[0167] One or more embodiments of the present specification provide a passenger flow guiding device, comprising a processing device, the processing device being configured to execute the multi-functional variable dressing method of the automobile carriage.

[0168] Some embodiments of the present specification also provide a computer-readable storage medium, the storage medium storing computer instructions, when the computer reads the computer instructions in the storage medium, the computer executes the method of any one of the above embodiments.

[0169] The above has described the basic concept, and it is obvious that the above detailed disclosure is only used as an example and does not limit the present specification. Although it is not explicitly stated here, those skilled in the art can make various modifications, improvements and corrections to the present specification. Such modifications, improvements and corrections are suggested in the present specification, so such modifications, improvements and corrections still belong to the spirit and scope of the exemplary embodiments of the present specification.

[0170] At the same time, the present specification uses specific words to describe the embodiments of the present specification. As "one embodiment", "an embodiment", and / or "some embodiments" means a certain feature, structure or characteristic related to at least one embodiment of the present specification. Therefore, it should be emphasized and noted that the "an embodiment" or "one embodiment" or "one alternative embodiment" mentioned in different places in the present specification does not necessarily refer to the same embodiment. In addition, some features, structures or characteristics in one or more embodiments of the present specification can be properly combined.

[0171] Furthermore, the order of the processing elements and sequences described in this specification are not intended to be construed as a limitation, unless specifically stated, but are included to provide a complete description of one or more embodiments of the present specification. Regardless of the particular sequence of processing elements and sequences, however, the description herein of a process should be understood to include any and all combinations of one or more elements, and sequences that can be perceived as either open-ended or specific.

[0172] Similarly, it is to be noticed that the term "comprising", used in the description, should not be interpreted as being restricted only to the elements or steps listed thereafter; it does not exclude other elements or steps. It is thus to be interpreted as specifying the presence of the stated elements or steps as well as the presence of yet unrecited elements or steps. Furthermore, the word "a" or "an" preceding an element or step of the description does not exclude the presence of a plurality of such elements or steps, that is, "a" or "an" means "one or more".

[0173] Some embodiments use numerical designations to describe components, quantities of attributes. It is to be understood that such numerical designations used in the description of embodiments are, in some examples, modified by the adjectives "about", "approximately", or "generally". Unless otherwise stated, "about", "approximately", or "generally" indicates that the stated numerical value is permitted to vary by ±20%. Accordingly, numerical values used in the description and claims are approximations that can vary depending on the desired properties of the individual embodiments. In some embodiments, numerical values should be considered in the context of the number of significant figures used in the description and claims. Although the numerical ranges and parameters setting forth the broadest scope of the embodiments herein are approximations, the numerical values set forth in the specific examples are reported as precisely as practicable. The numerical values set forth in the specific examples are provided to be as precise as reasonably possible. However, some variations may occur depending on the implementation desired.

[0174] Each patent, patent application, patent publication, and other material, articles, books, instructions, documents, that has been incorporated by reference into this specification, is hereby incorporated by reference herein in its entirety. This incorporation by reference is done solely to comply with the requirement of a specification section 1.57. Due to MPEP 2006.87, the incorporation by reference is not to be construed as an admission that the material is prior art with respect to the present specification. The material incorporated by reference into the present specification is not admitted to be new, novel, non-obvious, non- obvious, or otherwise eligible for patent protection to the extent that it contradicts the patentability of the present specification. To the extent that such material is similar to the present specification, it is either inconsequential or is admitted to be prior art with respect to the present specification. In the event that any conflict is deemed to exist between the material incorporated by reference into this specification and the description, drawings, or examples set forth herein, the description, drawings, or examples set forth herein shall control.

[0175] Finally, it should be understood that the embodiments described herein are only given by way of example and that other modifications can occur to persons skilled in the art. Therefore, the scope of the present description is not intended to be limited to the embodiments described herein but is only limited by the claims that follow.

Claims

1. A multi-functional conversion system for a vehicle bed, comprising: The system comprises an input device, a sampling sensor, a display device and a processor; The input device is configured to acquire carriage structure data; The sampling sensor is configured to collect variable dressing data of the carriage; The processor is configured to: determine a carriage model based on the carriage structure data; correct the carriage model based on the variable dressing data; control the corrected carriage model to perform simulation based on first variable dressing parameters to determine first restricted features; determine improvement parameters based on the first restricted features; send the improvement parameters and the first restricted features to the display device; The display device is configured to display the improvement parameters and the first restricted features; The simulation includes driving simulation, which includes obtaining driving posture information of the vehicle; determining first restricted features includes: determine a load model based on load data of the carriage; apply the load model to the corrected carriage model and perform the driving simulation according to multiple driving posture information to record the force data of the variable dressing assembly during the whole driving simulation; determine a force data sequence based on the force data of the variable dressing assembly; construct a force analysis atlas based on the force data sequence and the carriage structure data; predict future deformation data through a deformation model based on the force analysis atlas, the deformation model being a machine learning model; determine the reliability value of the variable dressing assembly based on the future deformation data; determine the first restricted features based on the reliability value and the future deformation data; The determination of the improvement parameters includes: determine second variable dressing parameters based on the first variable dressing parameters in response to the first restricted features not meeting preset conditions; determine second restricted features based on the second variable dressing parameters through the simulation; determine target variable dressing parameters through at least one iteration of the second variable dressing parameters based on the second restricted features; determine the improvement parameters based on the target variable dressing parameters.

2. The system of claim 1, wherein, The carriage structure data includes at least one of size data, material data and fitting data of carriage components, which include the variable dressing assembly and fixed components; The fixed components include chassis components, and the variable dressing assembly includes cockpit components, functional cabins and cold connection components; the fixed components and the functional cabins are provided with one or more sets of fitting positions corresponding in position and matching in shape; different types of functional cabins are configured to be connected with the fixed components through the cold connection components based on the fitting positions.

3. The system of claim 2, wherein, The types of the functional cabins include at least one of passenger cabins, cargo cabins and commodity operation cabins.

4. The system of claim 2, wherein, The connection modes corresponding to the cold connection components include one or more of self-punching riveting, flow-drill screwing, gluing, edge rolling, Piece-locking, crimping and screwing; the cold connection components used in different fitting positions are different.

5. A multi-purpose conversion method for a vehicle cabin, characterized by, The method is executed by a processor of a multi-functional variable dressing system of an automobile carriage; The automobile cabin multifunctional transformation system comprises an input device, a sampling sensor, a display device and the processor; the input device is configured to acquire cabin structure data; The sampling sensor is configured to collect transformation data of the cabin; The display device is configured to display improvement parameters and first limited features; The method comprises: determining a cabin model based on the cabin structure data; correcting the cabin model based on the transformation data; controlling the corrected cabin model to perform simulation based on first transformation parameters to determine the first limited features; determining the improvement parameters based on the first limited features; sending the improvement parameters and the first limited features to the display device; wherein the simulation comprises driving simulation, the driving simulation comprises acquiring driving posture information of the vehicle; the determination of the first limited features comprises: determining a load model based on load data of the cabin; applying the load model to the corrected cabin model and performing the driving simulation according to the driving posture information to determine stress data of transformation components; determining a stress data sequence based on the stress data of the transformation components; constructing a stress analysis atlas based on the stress data sequence and the cabin structure data; predicting future deformation data through a deformation model based on the stress analysis atlas, the deformation model being a machine learning model; determining a reliability value of the transformation components based on the future deformation data; determining the first limited features based on the reliability value and the future deformation data; the determination of the improvement parameters comprises: determining second transformation parameters based on the first transformation parameters in response to the first limited features not meeting preset conditions; determining second limited features based on the second transformation parameters through the simulation; determining target transformation parameters through at least one round of iteration of the second transformation parameters based on the second limited features; determining the improvement parameters based on the target transformation parameters.

6. A multi-purpose conversion device for a vehicle compartment, characterized by The device comprises at least one processor and at least one memory; The at least one memory is used to store computer instructions; The at least one processor is used to execute at least part of the computer instructions to realize the automobile cabin multifunctional transformation method of claim 5.

7. A computer-readable storage medium, characterized in that, The storage medium stores computer instructions, and when a computer reads the computer instructions in the storage medium, the computer executes the automobile cabin multifunctional transformation method of claim 5.

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