Carbon fiber composite material vehicle body structure and design method thereof

Abstract

The present invention discloses a carbon fiber composite body structure and a design method thereof, wherein the design space, non-design space, constraint conditions, calculation conditions, and optimization targets are used as inputs of simulation software to create a body topology optimization structure model; the body topology optimization structure model is iteratively calculated using a variable density method to obtain a body structure force transmission path under different material utilizations that meet the constraint conditions and working condition requirements, and the optimal body structure configuration is obtained according to the force transmission path. The present invention provides a design method for input parameters to ensure that the desired structure configuration can be obtained, thereby improving simulation efficiency and simulation accuracy.

Description

Technical Field

[0001] The invention relates to the technical field of rail transportation, and in particular to a carbon fiber composite material vehicle body structure and a design method thereof. Background Art

[0002] Compared with wheel-rail trains, maglev trains are suspended on the track by electromagnetic force. The car body has no contact with the track, no friction loss is generated, and it is a new mode of transportation with simple operation and maintenance. Compared with high-speed maglev trains suitable for long-distance trunk line operation, medium- and low-speed maglev trains are more economical, easy to construct, and have low environmental noise, making them very suitable for intercity rail transportation. Since maglev trains rely on suspension force to travel, compared with wheel-rail trains that land directly, maglev trains have higher requirements for lightweight car bodies. The optimized design of the car body structure and the application of new lightweight materials are necessary development directions for lightweight car bodies, but the application of new structures and new materials often brings a series of new problems such as car body stiffness, noise, and fire prevention.

[0003] Carbon fiber composite materials are increasingly widely used in the field of rail transit due to their light weight, high rigidity and high strength, especially in load-bearing structures. While improving the rigidity of the vehicle body, they can significantly reduce the weight of the vehicle body, and have broad application prospects. In the field of rail transit, there have been a number of patent applications for the preparation of vehicle body structures using carbon fiber composite materials. Patent application CN 105128876 B "A carbon fiber composite vehicle body and its manufacturing method" proposes an integrated vehicle body and floor made of carbon fiber. The vehicle body consists of an outer skin, a sandwich layer, an inner skin, and reinforcing ribs bonded to the inner skin. However, this structure does not involve the noise and fire prevention issues of the vehicle body structure. Compared with metal materials, the sound insulation and fire prevention properties of carbon fiber materials themselves are relatively low. When a three-layer sandwich structure is used, the properties of the sandwich layer will bring new and complex effects to the sound insulation performance of the structure. The adhesive of the carbon fiber material is also not resistant to high temperatures and is prone to failure at high temperatures. Patent application CN206187017 U "A carbon fiber composite body structure for medium and low speed rail transit" provides a carbon fiber composite body structure composed of a carbon fiber outer skin, a carbon fiber inner skin, and a flame retardant foam core material between the outer skin and the inner skin, and adds flame retardant epoxy resin to the carbon fiber composite material of the inner and outer skins. The scheme proposes a method for improving the fire resistance of carbon fiber materials, but there is still no specific method for improving the sound insulation performance of carbon fiber sandwich composite materials. Patent CN208325223 U "A low-cost carbon fiber composite air-rail body structure" proposes a carbon fiber composite air-rail body structure for suspension, the body side walls and end walls of which include a reinforcement rib skeleton, an inner skin and an outer skin, the inner and outer skins are attached to the inner and outer surfaces of the reinforcement rib skeleton, and the grid of the reinforcement rib skeleton is filled with sandwich foam blocks, but the body structure does not involve the driver's cab part, and the structural form of the suspended air-rail has significant working condition differences from the body structure of the ground, and does not specifically involve the comprehensive problems of structural strength, sound insulation and fire prevention.

[0004] Patent application CN 110489907 A "An Optimization Design Method for Digital Prototype of Rail Transit Vehicle Body" gives the general steps of body topology optimization design, which is actually the software logic of the topology optimization software itself. The core of body topology optimization design does not lie in the operating logic and general operation steps of the tool software, but in the design skills and ideas of each specific parameter, which is the core key to obtain the required structural configuration. This solution does not involve parameter design content, which may actually fail to obtain the required structural configuration. The actual setting of the design space range, specific constraints, and calculation conditions are the key points and difficulties of topology optimization design. Whether the input parameter range is set reasonably directly determines the convergence of the optimization calculation and the reliability of the simulation calculation.

[0005] The multi-objective optimization method for design parameters given in patent application CN 113033093 A "A multi-objective optimization method for system design parameters based on simulation model" is an optimization method limited to the same computing model system, specifically a simulation calculation of the strength of the spring system based on the Mworks simulation platform. However, no feasible implementation plan is given for the joint simulation between computing models of different dimensions.

[0006] At present, the hollow integral carbon fiber cab hood used in the train body with driver's cab structure made of carbon fiber composite materials cannot withstand the longitudinal impact force of 800KN at the driver's cab. In addition, due to the disadvantages of carbon fiber composite materials in terms of sound insulation and fire prevention, the current carbon fiber body structure has not yet achieved coordination and unity in terms of structural load-bearing, sound insulation and fire prevention. In the field of maglev trains, there is no report on maglev train bodies made of carbon fiber composite materials. Summary of the invention

[0007] The technical problem to be solved by the present invention is to provide a carbon fiber composite material vehicle body structure and a design method thereof in view of the deficiencies in the prior art, so as to ensure that the required structural configuration can be obtained and improve the reliability of simulation calculation.

[0008] In order to solve the above technical problems, the technical solution adopted by the present invention is: a carbon fiber composite material body structure design method, comprising the following steps:

[0009] S1. Use the design space, non-design space, constraints, calculation conditions, and optimization goals as inputs to the simulation software to create a vehicle body topology optimization structure model;

[0010] S2. Iteratively calculate the vehicle body topology optimization structure model using a variable density method to obtain a vehicle body structure force transmission path under different material utilizations that meet constraint conditions and working condition requirements, and obtain an optimal vehicle body structure configuration according to the force transmission path, wherein the configuration includes a load-bearing frame and a load-bearing panel;

[0011] The design space includes an outer interface of the design space and an inner interface of the design space; the outer interface of the design space is M times the design size of the vehicle body and does not exceed the vehicle operating limit; the inner interface of the design space is set to be Kmm inwardly extended from the design inner surface of the vehicle body; in the present invention, the inward extension is extended from the outside of the vehicle to the center of the vehicle body;

[0012] The non-design space includes interfaces of all devices and components connected to the vehicle body;

[0013] The calculation conditions include all external loads and constraints that ensure safe operation of the vehicle;

[0014] The constraint conditions include: vehicle body weight reduction ratio, maximum displacement condition under vehicle overload condition, and vehicle modal frequency avoiding the floating frequency of the suspension frame; the maximum displacement is selected as the longitudinal displacement at the hook and the vertical displacement in the middle of the vehicle side beam; the vehicle modal frequency avoiding the floating frequency of the suspension frame is defined as the optimized first-order vertical bending mode of the vehicle body simultaneously meeting two conditions, that is, the difference between the vehicle modal frequency and the floating frequency of the suspension frame is not less than 2Hz, and is greater than N times the floating frequency of the suspension frame; preferably, the maximum displacement and the vehicle body weight reduction ratio meet the following formula: D=0.8*d / (1-s); wherein D is the maximum allowable displacement, d is the maximum displacement of the vehicle body structure, and s is the vehicle body weight reduction ratio;

[0015] The optimization objective is set to maximize the weighted stiffness of the vehicle body under all working conditions;

[0016] The load-bearing panel is a multi-layer structural panel.

[0017] In the present invention, the optimal vehicle body structure configuration is obtained by manually interpreting the force transmission path.

[0018] The present invention determines the design space, non-design space, constraints, calculation conditions, and optimization targets as input parameters of the simulation software, studies and analyzes each input parameter, and obtains the setting method of each input parameter. Experiments have proved that the method of the present invention can ensure that the simulation software obtains the required structural configuration, improves the simulation efficiency and the reliability of the simulation calculation, and ensures the convergence of the optimization calculation.

[0019] M=1.1-1.2; K=50-60; the vehicle body weight reduction ratio is set to 20%-40%; N=1.32.

[0020] In the calculation of structural topology optimization, thin shells with abnormally high utilization rates often appear at the inner and outer interfaces, which cannot truly reflect the actual force transmission path of the structure. Within the above parameter range, the outer and inner interfaces of the vehicle body design are expanded outward, and the thin shell units that appear can be swept over, so as to obtain more accurate force transmission path information on the actual design section. The setting of the vehicle body weight reduction ratio is determined according to the weight reduction target. When selecting this numerical range, the present invention selects it on the basis of considering the material density, which can achieve the necessary weight reduction target without causing distortion of the material structure force transmission information due to excessive weight reduction ratio. The range setting of the ratio of the vehicle modal frequency to the floating and sinking frequency of the suspension frame can fully allow the overall mode to completely avoid the floating and sinking frequency of the suspension frame to avoid resonance, and the requirement for the vehicle body modal frequency is not too high, so as to facilitate the orderly optimization of the vehicle body structure topology.

[0021] The operating conditions include main operating conditions, secondary operating conditions and normal operating conditions, and the weighted coefficients of each operating condition are set as follows: the main operating condition coefficient is 1, the secondary operating condition coefficient is 0.63, and the normal operating condition coefficient is 0.45.

[0022] The stress conditions in the topology optimization process depend on the calculated working conditions, but the importance of each working condition to the reliability of the vehicle body structure is different. For example, the pulling and pressing working conditions of the front hook of the vehicle body are the main carrying working conditions of the vehicle body structure and are also the reason for the usual stress excess. The coefficient of the main working condition is set to 1 to fully meet the main working condition's requirements for the vehicle body. The importance of the secondary working condition is weaker than the main working condition, and its coefficient is reduced to facilitate the calculation of the overall stress structure. The force requirements for the vehicle body structure under normal operating conditions are not high, and this working condition coefficient can meet the force requirements of the vehicle body under operation. The weight distribution of the main, secondary and normal working conditions can better reflect the stress conditions of the vehicle body under all required working conditions and can more truly reflect the force transmission path of the vehicle body.

[0023] Furthermore, the method of the present invention also includes: S3, creating a vehicle body strength model, a vehicle body noise model, and a vehicle body fire prevention simulation model; connecting the vehicle body strength model, the vehicle body noise model, and the vehicle body fire prevention simulation model to a simulation computing platform based on Isight software, selecting the associated parameters of strength, noise, and fire prevention indicators, and using the beam rib plate thickness range of the load-bearing skeleton of the optimal vehicle body structure configuration and the thickness range of each layer of the load-bearing multi-layer panel as input design variables of the simulation computing platform, using the constraints of vehicle stiffness, strength, fatigue, mode, noise sound pressure level, heat release rate, and smoke spread rate as constraints, and using the weighted index values ​​of vehicle body weight, sound insulation, and fire prevention as design targets, to establish a strength, noise, and fire prevention joint simulation model;

[0024] S4, using the parameter combination of the input design variables as the input parameters of the optimal super Latin method to obtain a feature sample space, performing sensitivity analysis on the feature sample space, reducing the variable dimension of the feature sample space, and obtaining an optimal sample space; and establishing an optimization proxy model based on the optimal sample space;

[0025] S5. Calling the particle swarm algorithm to search for the best combination among the input and output combinations of the optimization agent model and determine the best combination scheme.

[0026] In the present invention, according to the optimal sample space, the coupled simulation computing platform calculates the results of each data combination in the sample, and the data combination and the corresponding results are fitted using a machine self-learning algorithm to form an optimal proxy model. In the optimal proxy model, the input and output of the proxy model are optimized to obtain the final optimal solution.

[0027] In view of the defects and shortcomings of the current carbon fiber composite body structure in structural bearing, especially the longitudinal impact force of the driver's cab, as well as in sound insulation, noise reduction and fire safety, the present invention takes into account the disadvantages of carbon fiber composite materials themselves in sound insulation, noise reduction and fire prevention. Through the above-mentioned optimization design process, it is ensured that the carbon fiber body structure achieves coordination and unity in the three aspects of structural bearing, sound insulation, noise reduction and fire prevention. The body structure and optimization design method can take into account the performance requirements of good sound insulation, noise reduction, heat insulation, fire prevention and lightweight while meeting the load-bearing strength conditions of the maglev train.

[0028] In step S3, the process of creating the vehicle body strength model includes: using the thickness and material properties of the carbon fiber layer, the thickness and material properties of the foam layer, the damping layer and the adhesive layer as input parameters of the Optistruct software, and using the static strength, fatigue strength, stiffness and modality of the vehicle body structure as output parameters to obtain the vehicle body strength model. The vehicle body strength model of the present invention takes into account the material and thickness parameters of each layer of the panel to ensure that the static strength, fatigue strength, stiffness and modality of the vehicle body structure meet the design requirements.

[0029] In step S3, the thermal physical property parameters and fire spread parameters of the material are used as input parameters of the FDS software, and the heat release rate, temperature field distribution, and smoke spread characteristics of the vehicle body are used as output parameters to obtain the vehicle body fire prevention simulation model. The present invention takes into account the vehicle body fire prevention requirements and creates a vehicle body fire prevention simulation model. In the subsequent design optimization process, it is ensured that the vehicle body structure is coordinated and unified in terms of structural bearing, sound insulation and noise reduction, and fire prevention.

[0030] In step S3, the associated parameters include: the thickness of each layer of the multi-layer load-bearing panel, and the thickness of the rib plate in the load-bearing skeleton with an angle less than 60° with the corresponding layer of the panel;

[0031] In step S3, the process of obtaining the weighted index values ​​of vehicle weight, sound insulation and fire prevention includes: normalizing the vehicle weight, sound insulation index and fire prevention index, weighting the normalized values ​​to obtain the weighted index values; the weighted coefficients are: fire prevention coefficient 0.4-0.6, weight coefficient 0.2-0.4, noise coefficient 0.1-0.3. It should be noted that the weight index is in kilograms, the sound insulation index is in decibels, and the fire prevention index is the heat release rate and smoke spread rate in millimeters per second. These indexes have different units and cannot be directly added together. Therefore, only the values ​​of these indexes are normalized and their units are ignored, that is, the weighted sum can be performed without unit magnitude.

[0032] In step S4, the parameter combination of the design variables is input, and the optimal super Latin algorithm is called. Based on the principle of the optimal super Latin algorithm, a characteristic sample space that can represent the overall sample information is obtained from the sample space composed of all design variables. The acquisition of the characteristic sample space can significantly reduce the quantity scale of the original design sample space, especially for the coupling of multi-dimensional targets, reducing the sample space amount can effectively improve the model operation speed.

[0033] In step S4, the contribution rate of each variable in the feature sample space to the model calculation results is not the same. A sensitivity analysis is performed on the feature sample space. In the sensitivity analysis, parameters with a sensitivity greater than 40% are selected to reduce the variable dimension of the feature sample space to form an optimal sample space, which can further improve the calculation rate of the joint simulation.

[0034] In step S5, the input parameters of the optimal sample space and the output results obtained through joint simulation are optimized through machine self-learning method to obtain an optimized proxy model.

[0035] In the sample space composed of the input and output of the optimized proxy model, an adaptive particle swarm algorithm is used to search for the best combination in the sample space to determine the best combination solution.

[0036] As an inventive concept, the present invention also provides a carbon fiber composite material body structure, comprising a plurality of load-bearing panels and a plurality of load-bearing frames for supporting the plurality of load-bearing panels; the load-bearing panels include a damping layer; the damping layer is bonded to a foam layer on both sides, and the side of the foam layer away from the damping layer is bonded to a carbon fiber layer; wherein the thickness of the damping layer, the foam layer, the carbon fiber layer, and the thickness of the beam ribs of the load-bearing frame are all determined according to the design method of the present invention.

[0037] The adhesive layer is an epoxy resin adhesive with an inorganic flame retardant added, and the weight percentage of the inorganic flame retardant added is 40 to 50%.

[0038] In the present invention, the foam layer is made of foam material with low shear modulus, and low shear modulus means that the shear modulus is not greater than 60 MPa.

[0039] Specifically, in the present invention, the low shear modulus foam material can be polyethylene foam material.

[0040] The damping layer is made of styrene-based thermoplastic material.

[0041] The arc-shaped panel of the engine room, the middle U-shaped top side panel, the inner surface of the end wall panel and the inner and outer surfaces of the vehicle body frame panel of the vehicle body structure of the present invention are all sprayed with a water-based fire-proof damping coating, thereby further improving the fireproof performance of the vehicle body structure.

[0042] The multiple load-bearing panels include a curved panel of the driver's cab, a U-shaped top side panel in the middle of the vehicle body, an end wall panel, and a chassis panel; the end of the curved panel of the driver's cab is fixedly connected to one end of the U-shaped top side panel in the middle of the vehicle body; the other end of the U-shaped top side panel in the middle of the vehicle body is fixedly connected to the end wall panel; the bottom of the curved panel of the driver's cab, the bottom of the U-shaped top side panel in the middle of the vehicle body, and the bottom of the end frame panel are all fixedly connected to the chassis panel.

[0043] The load-bearing frame includes a cab end beam rib arranged at the bottom of the cab arc panel, a cab arc-shaped forked support rib symmetrically arranged on the left and right sides of the top of the cab arc panel, a plurality of closed U-shaped support ribs surrounding the middle U-shaped top side panel and the bottom frame panel of the vehicle body, a top cover side beam rib extending longitudinally along the vehicle body and arranged at the top of the middle U-shaped top side panel, a bottom frame side beam rib connecting all panels at the bottom of the vehicle body, an end wall transverse rib arranged at the upper and lower ends of the end wall panel, an end wall vertical rib arranged on the left and right sides of the end wall panel, a side wall transverse rib arranged on the middle U-shaped top side panel connecting two adjacent U-shaped support ribs, and a plurality of side wall vertical ribs vertically arranged on the middle U-shaped top side panel.

[0044] As an inventive concept, in the present invention, the design parameters of the carbon fiber composite material body structure are determined using the design method of the present invention.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] (1) The present invention provides a design method for input parameters, ensuring that the desired structural configuration can be obtained, thereby improving simulation efficiency and simulation accuracy;

[0047] (2) The present invention obtains the beam rib thickness of the carbon fiber integral load-bearing skeleton at different positions of the vehicle body and the matching carbon fiber multi-layer panel thickness combination through vehicle topology optimization and multi-objective collaborative optimization simulation calculation based on digital prototype; Experiments have shown that the carbon fiber vehicle body prepared by the method of the present invention weighs no more than 3 tons, can bear 800kN of longitudinal compressive stress at the driver's cab, has a noise level in the vehicle of no more than 69 decibels, and has a fire protection level of HL3, meeting the transportation condition requirements of the maglev vehicle body.

[0048] (3) The present invention adopts a carbon fiber beam with a hollow cavity, and performs integral molding or multi-component composite connection according to the force transmission path and rib cross-section configuration obtained by the topological optimization of the whole vehicle, so as to construct an overall load-bearing skeleton of the maglev vehicle body, thereby meeting the structural load-bearing requirements of the maglev vehicle body under the carrying condition;

[0049] (4) The present invention uses a low shear modulus foam material as a sandwich layer and arranges a carbon fiber multilayer panel with a damping layer between the foam sandwich layers, thereby overcoming the disadvantage of poor sound insulation performance of the multilayer sandwich structure. By optimizing the thickness of each layer of the panel, the sound insulation performance of the multilayer panel is effectively improved while meeting the strength, stiffness and mode of the sandwich structure.

[0050] (5) The present invention applies a water-based fire-retardant damping coating on the carbon fiber multilayer panel and adds a specific weight percentage of an inorganic flame retardant to the carbon fiber epoxy resin glue, thereby effectively improving the fire resistance of the carbon fiber structural parts. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 This is a flow chart of the topology optimization design of the overall load-bearing skeleton in Example 1 of the present invention.

[0052] Figure 2 This is the vehicle body structure model obtained in Example 1 of the present invention.

[0053] Figure 3 This is a structural diagram of the carbon fiber overall load-bearing skeleton obtained after manual verification in Example 1 of the present invention;

[0054] Figure 4 This is a structural diagram of a carbon fiber multilayer panel obtained after manual verification in Example 1 of the present invention;

[0055] Figure 5 This is a flow chart of the method of embodiment 2 of the present invention;

[0056] Figure 6 This is a schematic diagram of the carbon fiber multilayer panel structure of Example 3 of the present invention. DETAILED DESCRIPTION

[0057] The optimization design method of the carbon fiber maglev train body structure includes topological optimization of the overall load-bearing frame of the body, manual shape correction, beam and rib thickness of the overall load-bearing frame of the body based on digital prototype, thickness combination of each layer of carbon fiber multi-layer panel, and multi-objective collaborative simulation optimization of strength, stiffness, mode, fatigue, sound insulation and fire protection of the whole vehicle structure.

[0058] like Figure 1 As shown, in Example 1 of the present invention, the topology optimization of the overall load-bearing skeleton of the vehicle body is carried out by a variable density method based on the OptiStruct software. The outer interface of the design space of the vehicle body is the vehicle operating limit, and the inner interface of the design space is the space size inside the vehicle body; the non-design space is all equipment and component interfaces (doors, windows, etc.) connected to the vehicle body; the calculation conditions are all external loads and constraints to ensure the safe operation of the vehicle; the constraints of the topology optimization are the vehicle body weight reduction ratio, the maximum displacement condition under the vehicle overload condition, and the vehicle modal frequency that is fully avoided from the floating frequency of the suspension frame; the optimization goal is to maximize the weighted stiffness of the vehicle body under all conditions.

[0059] A simulation model is created in the Optistruct software, whose input is the set internal and external design space, non-design space, constraints, calculation conditions, optimization targets and other model parameters, and the output of the software is the calculated vehicle body structure configuration under different material utilizations. Designers can read the structural configuration under the desired material utilization, which reflects the force transmission path that meets the design requirements. Based on these force transmission paths, the final vehicle body model can be manually checked.

[0060] The topological optimization of the overall load-bearing skeleton of the vehicle body of the present invention is carried out by a variable density method based on OptiStruct software, and the specific input parameter ranges are: (1) Design space: a. External interface of the design space: the external interface range of the vehicle body design space is 1.1 times the design size of the vehicle body, and does not exceed the vehicle operating limit; b. Internal interface of the design space: the design inner surface of the vehicle body extends inward by 50 mm; (2) Non-design space: interfaces of all equipment and components connected to the vehicle body (such as doors, windows, equipment installation areas, etc.); (3) Calculation conditions: all external loads and constraints to ensure the safe operation of the vehicle, which is based on the size and position of the load or impact stress required during the actual operation of the vehicle body, such as the 800KN longitudinal compressive stress borne by the present invention at the front end of the driver's cab; (4) Constraint conditions: vehicle body weight reduction ratio, maximum displacement condition under vehicle overload condition, and vehicle modal frequency that fully avoids the floating frequency of the suspension frame. The weight reduction ratio of the vehicle body is set according to the required weight reduction requirements. The present invention selects a weight reduction ratio of 30%; the maximum displacement is selected as the longitudinal displacement at the hook and the vertical displacement in the middle of the vehicle body side beam. The maximum displacement of the present invention and the weight reduction ratio meet the following formula: D = 0.8*d / (1-s) (where D is the maximum displacement allowed by the present invention, d is the maximum displacement of the vehicle body structure, and s is the required weight reduction ratio); the modal requirement of the present invention is that the first-order vertical bending mode of the optimized vehicle body must meet two conditions at the same time, that is, the modal frequency of the whole vehicle minus the floating frequency of the suspension frame should be greater than 2Hz, and the modal frequency of the whole vehicle divided by the floating frequency of the suspension frame should be greater than 1.32. (5) Optimization target: The present invention aims to maximize the weighted stiffness of the vehicle body under all working conditions. The specific weighting coefficients are: the main working condition coefficient is 1, the secondary working condition coefficient is 0.63, and the normal operating condition coefficient is 0.45.

[0061] The vehicle body structure obtained through the above simulation calculation is as follows Figure 2 shown.

[0062] The artificial shape correction is based on the result of topology optimization. According to the calculated force transmission path and topological configuration, and taking into account the carbon fiber molding process conditions, the overall load-bearing frame of the vehicle body is manually corrected. The load-bearing frame and the body cover after artificial shape correction are as follows: Figure 3 and Figure 4 shown.

[0063] The flow chart of embodiment 2 of the present invention is as follows Figure 5 As shown. After the car body simulation model is created, the multi-objective collaborative simulation based on the digital prototype is submitted to the developed digital prototype simulation platform. Based on the digital prototype, the thickness combination of each layer of the carbon fiber multi-layer panel and the cross-sectional size optimization of the overall load-bearing skeleton of the car body are carried out. The multi-objective collaborative coupling of lightweight, sound insulation and fire resistance is comprehensively considered. The yield strength of the materials used in the whole vehicle is used as the stress constraint condition, the fatigue utilization of the materials is used as the fatigue strength constraint condition, the vertical displacement of the middle part of the car body variable is used as the stiffness constraint condition, the first-order vertical bending frequency of the whole vehicle is used as the modal constraint condition, the sound pressure level of the noise in the car is used as the noise constraint condition, and the heat conduction rate and smoke spread characteristics are used as the fire protection constraint condition. The thickness of each layer of the multi-layer load-bearing panel and the thickness of the rib plate with an angle of less than 60° with the multi-layer panel in the load-bearing skeleton are set as the associated parameters of the strength, noise and fire protection simulation model; the multi-objective weighted design target is designed with a fire protection coefficient of 0.5, a weight coefficient of 0.3, and a noise coefficient of 0.2.

[0064] The parameter combination of the design variables is used as the input parameters of the optimal super Latin method to obtain the characteristic sample space, and then a sensitivity analysis is performed to select parameters with a sensitivity greater than 40%. The variable dimension of the characteristic sample space is reduced to obtain the optimal sample space. Based on the optimal sample space, the optimization agent model is established by machine self-learning, and the adaptive particle swarm optimization algorithm is called to optimize the input and output parameters in the agent model, realizing multidisciplinary rapid engineering collaborative optimization simulation calculation of carbon fiber body, and the optimal solution obtained is the optimal design scheme finally determined.

[0065] Through multi-objective collaborative optimization simulation calculation based on digital prototype, the rib thickness of the carbon fiber integral load-bearing skeleton at different positions of the vehicle body and the matching carbon fiber multi-layer panel thickness combination were obtained.

[0066] Simulation experiments show that the carbon fiber car body prepared by the method of Example 2 of the present invention weighs no more than 3 tons, can bear 800kN of longitudinal compressive stress at the driver's cab, has a noise level inside the car that does not exceed 69 decibels, and has a fire protection level of HL3, meeting the transportation operating requirements of the maglev car body.

[0067] The Optistruct software was used to create a vehicle body strength model, with the thickness and material properties of the carbon fiber layer (Poisson's ratio, elastic modulus, tensile strength, compressive strength, and shear strength in the three directions of 0°, 90°, and between layers), the thickness and material properties of the foam layer, damping layer, and adhesive layer (Poisson's ratio, elastic modulus, and tensile strength) as input parameters, and the static strength, fatigue strength, stiffness, and mode of the vehicle body structure as output parameters; the VA-one software was used to create a vehicle body noise model, with the material sound insulation, material sound absorption coefficient, sound source spectrum, and sound source position as input parameters, and the noise sound pressure level inside and outside the vehicle as output parameters; the FDS software was used to create a vehicle body fire protection simulation model, with the material's thermophysical properties (density, specific heat capacity, heat transfer coefficient, etc.) and fire spread parameters (combustion heat, reaction heat, Arrhenius pre-exponential factor, and activation energy) as input parameters, and the heat release rate, temperature field distribution, and smoke spread characteristics (smoke spread velocity, smoke layer height) of the vehicle body as output parameters. The combination of the thickness of the multi-layer panels and the change in the thickness of the beam ribs of the load-bearing frame will cause the material thickness at different positions to have a correlated interactive effect on the output of the vehicle strength model, noise model and fire protection model. For example, the ribs perpendicular to the multi-layer panels have a significant effect on the strength, but the effect on the noise is very limited. Targeted screening of these parameter combinations is required.

[0068] Each sub-model (i.e., vehicle body strength model, vehicle body noise model, and vehicle body fire protection simulation model) has multiple input parameters and output parameters. When the design variables change, the input parameters of the three sub-models will produce a huge number of input parameter combinations, and the number of combinations that need to be calculated is even larger, far higher than the number of calculation combinations between the sub-models. These huge numbers of calculation input and output parameter combinations are the inputs of the optimal super Latin method. The optimal super Latin method is to systematically compare, arrange and optimize these combinations, so as to optimize the sample space that best reflects the system characteristics and has the most significant impact on the calculation results, so as to reduce the amount of calculation.

[0069] Isight constraints are the limit conditions for the output parameters in each sub-model, that is, the limit boundary conditions that the sub-model can accept. If these conditions are exceeded, it is judged that the optimization goal is not met.

[0070] Specifically, Figure 5 , the implementation process of Example 2 is as follows:

[0071] Create a vehicle body strength model, a vehicle body noise model, and a vehicle body fire prevention simulation model; connect the vehicle body strength model, the vehicle body noise model, and the vehicle body fire prevention simulation model to the simulation computing platform based on the Isight software, select the associated parameters of strength, noise, and fire prevention indicators, and use the beam reinforcement plate thickness range of the load-bearing skeleton of the optimal vehicle body structure configuration and the thickness range of each layer of the load-bearing multi-layer panel as input design variables of the simulation computing platform. Use the constraints of vehicle stiffness, strength, fatigue, mode, noise sound pressure level, heat release rate, and smoke spread rate as constraints, and use the weighted index values ​​of vehicle body weight, sound insulation, and fire prevention as design targets to establish a strength, noise, and fire prevention joint simulation model;

[0072] The parameter combination in the joint simulation model is used as the input parameter of the optimal super Latin method to obtain the characteristic sample space, perform sensitivity analysis on the characteristic sample space, select parameters with a sensitivity greater than 40%, reduce the variable dimension of the characteristic sample space, and obtain the optimal sample space; based on the optimal sample space, an optimization agent model is established using a machine self-learning algorithm;

[0073] The particle swarm algorithm is called to search for the best combination of input and output of the optimization agent model and determine the best combination.

[0074] The vehicle body structure includes a carbon fiber integral load-bearing frame, carbon fiber multi-layer panels, and a water-based fire-retardant damping coating.

[0075] like Figure 2 As shown, the carbon fiber integral load-bearing frame includes a cab end beam rib 1, left-right symmetrical cab arc-shaped forked support ribs 2, four closed U-shaped support ribs 3 consistent with the cross-section of the vehicle body, top cover side beam ribs 4 along the longitudinal direction of the vehicle body, bottom frame side beam ribs 5, end wall transverse ribs 6, end wall vertical ribs 7, side wall transverse ribs 8 and side wall vertical ribs 9. The carbon fiber integral load-bearing frame is formed as a whole by a carbon fiber beam with a hollow cavity, and the hollow carbon fiber beam can also be connected by gluing and riveting.

[0076] The overall load-bearing skeleton of the vehicle body obtained by topological optimization of the whole vehicle is a structure iteratively optimized according to the vehicle body's load-bearing conditions, which reflects the force transmission path of the vehicle body under actual working conditions. According to the force transmission path, a carbon fiber beam with a hollow cavity inside is integrally formed according to the force transmission path to construct the load-bearing skeleton of the vehicle body. According to the position and force of the vehicle body, the hollow cavity cross-sectional configuration and wall thickness of the carbon fiber beam can be adaptively adjusted.

[0077] like Figure 3 and Figure 4As shown, the carbon fiber multilayer panel includes a cab arc panel 10, an intermediate U-shaped top side panel 11, an end wall panel 12 and a chassis panel 13; the cab windows and lights are opened on the corresponding areas of the cab arc panel 10; the doors and windows are opened on the corresponding areas of the intermediate U-shaped top side panel 11; and the through-passage opening is opened on the end wall panel 13; after the cab arc panel 10, the intermediate U-shaped top side panel 11 and the end wall panel 12 are formed separately, they are covered on the corresponding carbon fiber integral load-bearing frame, and are connected to the load-bearing frame by a composite connection method of bonding and riveting, and the cab arc panel 10, the intermediate U-shaped top side panel 11 and the end wall panel 12 are connected as a whole by bonding; the chassis panel 13 is laid flat on a plane composed of the cab end beam ribs, the carbon fiber chassis side beam ribs and the closed U-shaped supporting ribs, and is connected to the load-bearing frame by a composite connection method of bonding and riveting.

[0078] like Figure 6 As shown, in Example 3 of the present invention, the cross section of the carbon fiber multilayer panel includes a carbon fiber outer panel, a foam sandwich layer I, a damping layer, a foam sandwich layer II, and a carbon fiber inner panel from the outside to the inside, the carbon fiber outer panel and the carbon fiber inner panel are stacked by carbon fiber woven cloth prepreg, the foam sandwich layer adopts polyethylene foam material, the damping layer adopts styrene-based thermoplastic material, and the carbon fiber adhesive adopts 40% to 50% by weight of inorganic flame retardant added to carbon fiber epoxy resin glue; the inner surface of the driver's cab arc panel, the middle U-shaped top side panel, the end wall panel, and the inner and outer surfaces of the body chassis panel are sprayed with a water-based fire-proof damping coating. The foam sandwich layer is a foam material with a low shear modulus (not higher than 60MPa), and the damping layer is a thermoplastic elastic material.

[0079] In order to meet the rigidity requirements of the vehicle body, the sandwich layer filled with the carbon fiber sandwich structure is often made of a high modulus material, such as PMI foam material. However, in the composite multilayer structure, the high modulus foam sandwich layer will cause the sound insulation performance of the sandwich structure to seriously deviate from the sound insulation curve, resulting in a significant decrease in the sound insulation performance of the overall structure. The present invention adopts a foam material with a low shear modulus, and adds a thermoplastic elastic material damping layer between the foam materials, which can further improve the sound insulation performance of the sandwich structure in the low frequency band. The thickness of the carbon fiber inner and outer panels, foam sandwich layer and damping layer are obtained through coupled iterative calculation of structural strength, stiffness, modality, sound insulation performance and fire resistance. According to the different strength and sound insulation requirements at different positions of the vehicle body, the thickness of each layer of the carbon fiber multilayer panel is adaptively adjusted.

[0080] The curved panel of the driver's cab, the middle U-shaped top side panel, and the end wall panel are covered on the corresponding carbon fiber integral load-bearing frame, and are connected to the load-bearing frame by a composite connection method of bonding and riveting; the chassis panel is laid flat on the plane composed of the driver's cab end beam ribs, carbon fiber chassis side beam ribs and closed U-shaped supporting ribs, and is connected to the load-bearing frame by a composite connection method of bonding and riveting.

[0081] The water-based fire-retardant damping coating is sprayed on the curved panel of the cab, the middle U-shaped top side panel, the inner surface of the end wall panel, and the inner and outer surfaces of the vehicle body chassis panel.

[0082] Compared with metal materials, carbon fiber materials have relatively low fire resistance. At high temperatures, the adhesive layer of carbon fiber will fail at high temperatures, resulting in a significant decrease in the fire resistance of carbon fiber materials. In the present invention, 40-50% by weight of inorganic flame retardant is added to the epoxy resin adhesive of the carbon fiber, and a water-based fire-retardant damping coating is sprayed on the inner and outer surfaces of the body surface and the chassis panel, thereby further improving the fire safety performance of the body structure.

Claims

1. A carbon fiber composite material vehicle body structure design method, characterized in that: The following steps are involved: S1. Use the design space, non-design space, constraints, calculation conditions, and optimization goals as inputs to the simulation software to create a vehicle body topology optimization structure model; S2. Iteratively calculate the vehicle body topology optimization structure model using a variable density method to obtain a vehicle body structure force transmission path under different material utilizations that meet constraint conditions and working condition requirements, and obtain an optimal vehicle body structure configuration according to the force transmission path, wherein the configuration includes a load-bearing frame and a load-bearing panel; S3. Create a vehicle body strength model, a vehicle body noise model, and a vehicle body fire prevention simulation model; connect the vehicle body strength model, the vehicle body noise model, and the vehicle body fire prevention simulation model to the simulation computing platform based on the Isight software, select the associated parameters of strength, noise, and fire prevention indicators, and use the beam rib plate thickness range of the load-bearing skeleton of the optimal vehicle body structure configuration and the thickness range of each layer of the load-bearing panel as input design variables of the simulation computing platform. With the constraints of vehicle stiffness, strength, fatigue, mode, noise sound pressure level, heat release rate, and smoke spread rate as constraints, and with the weighted index values ​​of vehicle body weight, sound insulation, and fire prevention as design targets, establish a strength, noise, and fire prevention joint simulation model; S4, using the parameter combination in the joint simulation model as the input parameter of the optimal super Latin method to obtain a feature sample space, performing sensitivity analysis on the feature sample space, reducing the variable dimension of the feature sample space, and obtaining an optimal sample space; establishing an optimization proxy model based on the optimal sample space; S5, calling the particle swarm algorithm to search for the best combination among the input and output combinations of the optimization agent model to determine the best combination scheme; The design space includes an outer interface of the design space and an inner interface of the design space; the outer interface of the design space is M times the design size of the vehicle body and does not exceed the vehicle operating limit; the inner interface of the design space is set to be Kmm extended inward from the inner surface of the vehicle body design; The non-design space includes interfaces of all devices and components connected to the vehicle body; The calculation conditions include all external loads and constraints that ensure safe operation of the vehicle; The constraints include: vehicle weight reduction ratio, maximum displacement condition under vehicle overload condition, and vehicle modal frequency avoiding the floating frequency of suspension frame; the maximum displacement is selected as the longitudinal displacement at the hook and the vertical displacement in the middle of the vehicle side beam; the vehicle modal frequency avoiding the floating frequency of suspension frame is defined as the optimized first-order vertical bending mode of the vehicle body simultaneously meeting two conditions, namely, the difference between the vehicle modal frequency and the floating frequency of suspension frame is not less than 2Hz, and the vehicle modal frequency is greater than N times the floating frequency of suspension frame; The optimization objective is set to maximize the weighted stiffness of the vehicle body under all working conditions; The load-bearing panel is a multi-layer structural panel.

2. The carbon fiber composite material vehicle body structure design method according to claim 1, characterized in that: The maximum displacement and the vehicle body weight reduction ratio conform to the following formula: D=0.8*d / (1-s); where D is the maximum allowable displacement, d is the maximum displacement of the vehicle body structure, and s is the vehicle body weight reduction ratio.

3. The carbon fiber composite material vehicle body structure design method according to claim 1, characterized in that: M=1.1~1.2; K=50~60; the vehicle body weight reduction ratio is set to 20%~40%; N=1.

32.

4. The carbon fiber composite material vehicle body structure design method according to claim 1, characterized in that: The operating conditions include main operating conditions, secondary operating conditions and normal operating conditions, and the weighted coefficients of each operating condition are set as follows: the main operating condition coefficient is 1, the secondary operating condition coefficient is 0.63, and the normal operating condition coefficient is 0.

45.

5. The carbon fiber composite material vehicle body structure design method according to claim 1, characterized in that: In step S3, the process of creating the vehicle body strength model includes: using the thickness and material properties of the carbon fiber layer, the thickness and material properties of the foam layer, the damping layer and the adhesive layer as input parameters of the Optistruct software, and using the static strength, fatigue strength, stiffness and mode of the vehicle body structure as output parameters to obtain the vehicle body strength model.

6. The carbon fiber composite material vehicle body structure design method according to claim 1, characterized in that: In step S3, the vehicle body noise model is obtained by taking the material sound insulation, material sound absorption coefficient, sound source spectrum, and sound source position as input parameters of the VA-one software, and taking the noise sound pressure levels inside and outside the vehicle as output parameters.

7. The carbon fiber composite material vehicle body structure design method according to claim 1, characterized in that: In step S3, the thermal physical property parameters and fire spread parameters of the material are used as input parameters of the FDS software, and the heat release rate, temperature field distribution and smoke spread characteristics of the vehicle body are used as output parameters to obtain the vehicle body fire protection simulation model.

8. The carbon fiber composite material vehicle body structure design method according to claim 5, characterized in that: In step S3, the associated parameters of the vehicle body strength model include: the thickness of each layer of the load-bearing panel, and the thickness of the ribs in the load-bearing skeleton whose angle with the corresponding layer of the panel is less than 60°.

9. The carbon fiber composite material vehicle body structure design method according to claim 1, characterized in that: In step S3, the process of obtaining the weighted index values ​​of vehicle body weight, sound insulation and fire prevention includes: normalizing the vehicle body weight, sound insulation index and fire prevention index, and weighting the normalized values ​​to obtain the weighted index values; the weighting coefficients are: fire prevention coefficient 0.4~0.6, weight coefficient 0.2~0.4, noise coefficient 0.1~0.

3.

10. A carbon fiber composite vehicle body structure, comprising a plurality of load-bearing panels and a plurality of load-bearing skeletons for supporting the plurality of load-bearing panels; characterized in that: The load-bearing panel includes a damping layer; the damping layer is bonded to a foam layer on both sides, and the side of the foam layer away from the damping layer is bonded to a carbon fiber layer; wherein the thickness of the damping layer, the foam layer, the carbon fiber layer, and the thickness of the beam rib plate of the load-bearing skeleton are all determined according to one of the methods described in claims 1 to 9.

11. The carbon fiber composite material vehicle body structure according to claim 10, characterized in that: The foam layer is made of foam material with a shear modulus not higher than 60 MPa; the damping layer is made of styrene-based thermoplastic material.

12. The carbon fiber composite material vehicle body structure according to claim 10, characterized in that: The load-bearing panels include a driver's cab curved panel (10), a vehicle body middle U-shaped top side panel (11), an end wall panel (12), and a chassis panel (13); an end of the driver's cab curved panel (10) is fixedly connected to one end of the vehicle body middle U-shaped top side panel (11); the other end of the vehicle body middle U-shaped top side panel (11) is fixedly connected to the end wall panel (12); and the bottom of the driver's cab curved panel (10), the bottom of the vehicle body middle U-shaped top side panel (11), and the bottom of the end wall panel (12) are all fixedly connected to the chassis panel (13).

13. The carbon fiber composite material vehicle body structure according to claim 12, characterized in that: The inner surfaces of the driver's cab curved panel (10), the middle U-shaped top side panel (11), the end wall panel (12), and the inner and outer surfaces of the chassis panel (13) are all sprayed with a water-based fire-proof damping coating.

14. The carbon fiber composite material vehicle body structure according to claim 12, characterized in that: The beam reinforcement of the load-bearing frame comprises a cab end beam reinforcement (1) arranged at the bottom of the cab arc panel (10), a cab arc bifurcated support reinforcement (2) symmetrically arranged on the left and right sides of the top of the cab arc panel (10), a plurality of closed U-shaped support ribs (3) surrounding the middle U-shaped top side panel (11) and the bottom frame panel (13) of the vehicle body, a top cover side beam reinforcement (4) extending longitudinally along the vehicle body and arranged at the top of the middle U-shaped top side panel, a bottom frame side beam reinforcement (5) connecting all panels at the bottom of the vehicle body, an end wall transverse reinforcement (6) arranged at the upper and lower ends of the end wall panel (12), an end wall vertical reinforcement (7) arranged on the left and right sides of the end wall panel (12), a side wall transverse reinforcement (8) arranged on the middle U-shaped top side panel and connecting two adjacent U-shaped support ribs, and a plurality of side wall vertical reinforcements (9) arranged vertically on the middle U-shaped top side panel.

15. A carbon fiber composite vehicle body structure, characterized in that: The design parameters of the vehicle body structure are determined by the method described in one of claims 1 to 9; the design parameters include the thickness range of the beam ribs of the load-bearing skeleton and the thickness range of each layer of the load-bearing panel of the optimal vehicle body structure configuration.

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