Automobile lightweight design method and system

Abstract

The invention discloses an automobile lightweight design method and system. The method comprises the steps of obtaining a target load and a target attribute of an automobile; defining a design space, establishing an envelope geometric model for the pre-simulation structure, and converting the envelope geometric model into a finite element model; carrying out material replacement on optional parts in the design space by utilizing a first material; performing material replacement on the first matching part in the design space by using a second material; performing first simulation and second simulation on the inherent test working condition and the design element test working condition of the first object respectively; defining a constraint and a design target, and setting a size constraint and a manufacturing constraint for the pre-simulation structure; and carrying out material optimization and topological optimization solution, and iterating the optimization result until the expectation is met. The weight of the automobile body is reduced to the maximum extent, the energy efficiency and safety of the automobile are improved, the production cost is reduced, and an effective solution is provided for the lightweight design of the new energy automobile.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle body design, and in particular to a method and system for lightweight design of an automobile. Background Art

[0002] Lightweighting of automobiles is an important means of energy conservation and emission reduction, and it is an important development trend for the global automotive industry. Lightweighting is the goal pursued by global automakers today, and it is also one of the most effective means of energy conservation and emission reduction. According to statistics, every 100kg reduction in vehicle weight can reduce the vehicle's CO2 emissions by 20g per kilometer. For new energy vehicles, every 10% reduction in vehicle weight can increase the cruising range by 5.5%. In addition to reducing carbon emissions, lightweighting can also improve the safety, fuel economy, power, braking, handling stability and ride comfort of the vehicle. Therefore, the global automotive industry has been actively exploring and adopting various lightweight technologies to achieve more efficient, environmentally friendly and safe vehicle design.

[0003] Automobile lightweighting is to reduce the weight of the automobile by adopting reasonable materials, structures and processes while maintaining the structural performance of the automobile, so as to achieve the purpose of energy conservation and emission reduction and improve the overall performance of the automobile. Countries around the world attach great importance to the research and development of automobile lightweighting. Although the lightweight level of domestic independent brand automobiles is relatively low, there is huge potential for development. Researchers have proposed a variety of lightweighting methods and paths, mainly including the use of high-strength lightweight materials, the use of advanced manufacturing processes and optimized design structures. These measures will bring more energy-saving, environmentally friendly and efficient development to the automotive industry. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for lightweight design of an automobile, comprising:

[0006] Obtaining a target load and a target attribute of the automobile; the target load is a cross-sectional force of a key cross-section based on a first simulation result of at least one benchmark vehicle; the target attribute is but not limited to a deformation capacity and durability of a key design part based on a second simulation result of at least one benchmark vehicle;

[0007] Define the design space, build an envelope geometry model for the pre-simulation structure, and convert it into a finite element model;

[0008] Using a first material to replace a material of an optional part in the design space;

[0009] Replacing the first matching portion in the design space with a second material;

[0010] Performing a first simulation and a second simulation on an inherent test condition and a design element test condition of the first object, respectively;

[0011] Define constraints and design goals, set dimensional constraints and manufacturing constraints for pre-simulated structures;

[0012] Perform material optimization and topology optimization solutions, and iterate the optimization results until they meet expectations.

[0013] As a preferred solution of the automobile lightweight design method of the present invention, the benchmark vehicle includes obtaining a vehicle of the same model as the design vehicle, with a curb weight and a vehicle length, width, and height that differ by less than 20%, and selecting at least one vehicle that meets the requirements as the benchmark vehicle;

[0014] When performing collision simulation on the benchmark vehicles that meet the requirements, the section force of the key section of each vehicle is obtained, the peak value of the section force is used as the equivalent static load, and the average value of the section force analysis results of the key section is used as the input load of the topology optimization analysis;

[0015] By performing a collision test on the benchmark vehicle, a target load of the inherent test condition under the first simulation is obtained;

[0016] The material replacement part of the design vehicle is obtained, and the deformation capacity and durability capacity of the same part of the benchmark vehicle are tested to obtain the test environment and test time under the target deformation degree and the target durability degree under the design element test condition under the second simulation.

[0017] As a preferred solution of the automobile lightweight design method described in the present invention, wherein: the defining of the design space includes, according to the preset space arrangement inner and outer boundaries, respectively establishing the vehicle body frame envelope geometry model and the power battery package envelope geometry model;

[0018] The body frame envelope geometry model is converted into a body frame finite element model for representing the body frame design space, and the battery pack envelope geometry model is converted into a battery pack finite element model for representing the battery pack frame design space;

[0019] The finite element model includes dividing the body frame finite element model into eight parts according to different overall components, namely, a front cabin, a front wall panel, a front floor, a rear floor, a coat rack, a tail end beam, a side wall, and a top cover;

[0020] According to the spatial layout in the model, the connection positions between the body frame finite element model and the battery pack finite element model are determined and connected in a rigid and common node manner to obtain a vehicle-electric frame integration model for characterizing the vehicle-electric structure integration design space.

[0021] As a preferred solution of the automobile lightweight design method of the present invention, the material replacement of the optional part includes designing and optimizing the carbon fiber composite material floor ply, replacing the optimized carbon fiber composite material floor with the corresponding part of the finite element model in the design space, and obtaining the design space after the optional part in the design space is replaced by the first material;

[0022] The material replacement of the first matching part includes designing and optimizing the hybrid material B-pillar, replacing the optimized hybrid material B-pillar with the corresponding part of the finite element model in the design space, and obtaining the design space after the first matching part in the design space is replaced by the second material.

[0023] As a preferred solution of the automobile lightweight design method of the present invention, wherein: the first simulation includes a frontal collision condition and a side collision condition, and during the simulation process, a load is applied according to the loading method under various conditions;

[0024] The second simulation includes a shape change test and a continuous working endurance test, and during the respective tests and during the simulation, characteristic data are applied according to the characteristic performance mode under the respective tests;

[0025] The durability test includes, but is not limited to, high and low temperature test and corrosion test;

[0026] The characteristic data include the force in the shape change test, the test environment and test time in the durability test;

[0027] The defined constraints include load constraints during loading, size constraints set for the pre-simulation structure, manufacturing constraints set for the vehicle body and battery pack, and draft constraints under collision conditions.

[0028] As a preferred solution of the automobile lightweight design method described in the present invention, wherein: the design goal includes defining the overall strain energy response, taking the minimum strain energy, the maximum deformation capacity and the maximum durability as the optimization goal;

[0029] Performing topology optimization on the vehicle according to the optimization target, performing engineering interpretation based on the topology optimization result of the target, judging whether the optimization result meets the design expectation, and if it does not meet the expectation, adjusting the design variables and re-analyzing the load, and repeatedly performing the iterative calculation process until the optimization result meets the expectation;

[0030] When the optimization result does not meet the design expectation, the design variables are adjusted according to the degree of deviation from the preset value; the design variables are graded according to the degree of non-satisfaction with the expectation, and the design variables are adjusted to different degrees for different degrees of deviation;

[0031] When adjusting, the adjustment range of the design variable is positively correlated with the degree of deviation from the preset value;

[0032] The rule of adjusting the design variable once includes: when the deviation between the optimization result and the design expectation decreases after adjusting the design variable once, confirming the adjustment; when the deviation between the optimization result and the design expectation does not decrease after adjusting the design variable once, not confirming the adjustment and resetting the adjustment;

[0033] If the deviation between the optimized design and the expected design does not exceed the upper limit of the deviation, the design variables are adjusted with the minimum adjustment range. When the results of continuous iterations reach the upper limit that meets the expected design, the iteration is stopped and the design variable with the smallest deviation is output as the final result.

[0034] As a preferred solution of the automobile lightweight design method of the present invention, wherein: judging whether the optimization result meets the design expectation includes, when the first design expectation, the second design expectation, and the third design expectation are all met, judging that the optimization result meets the design expectation;

[0035] The situation that does not meet the first design expectation includes: if a weak connection area appears in the optimized force transmission path, the weak connection area is marked and judged as not meeting the first design expectation; if the optimized force transmission path exceeds the upper limit of the deviation from the design expectation, the optimization result is judged as not meeting the first design expectation;

[0036] The situation of not meeting the second design expectation includes that if the maximum value of the deformation range of the optimized vehicle body structure during the second simulation process exceeds the upper limit of the deviation from the design expectation, the optimization result is judged to not meet the second design expectation;

[0037] The situation that does not meet the third design expectation includes that if the wear degree of the optimized vehicle body structure exceeds the upper limit of the deviation from the design expectation during the third simulation process, the optimization result is judged as not meeting the third design expectation.

[0038] As a preferred solution of the automobile lightweight design method described in the present invention, the design of the carbon fiber composite material floor ply and the hybrid material B-pillar includes presetting a resource library of hybrid algorithms, entering different hybrid algorithms, using the hybrid algorithms one by one to design the carbon fiber composite material floor ply and the hybrid material B-pillar, and performing a first simulation and a second simulation;

[0039] The result closest to the design expectation is the optimal design result for the carbon fiber composite floor ply and the hybrid material B-pillar.

[0040] As a preferred solution of the automobile lightweight design method of the present invention, the optimization of the carbon fiber composite floor ply and the hybrid material B-pillar also includes adjusting each design variable output by each algorithm at the same time;

[0041] Obtain the design variables in each output result, and adjust each design variable in any of the three adjustment modes of increase, decrease, and unchanged; obtain all adjustment schemes, and output the scheme with the smallest deviation from the design expectation as the optimization result;

[0042] In each optimization, the adjustment step of the design variables is smaller than the previous adjustment; when the results of continuous iterative optimization do not change, the iteration is stopped and the last design variable is output as the final result.

[0043] An automobile lightweight design system using any method as described in the present invention, characterized in that:

[0044] Acquisition unit, section force of a key section in the first simulation result; the target attribute is but not limited to the deformation capacity and durability of a key design part in the second simulation result based on at least one benchmark vehicle;

[0045] A design unit defines a design space, establishes an envelope geometry model for a pre-simulation structure, and converts the model into a finite element model; and replaces the material of an optional part in the design space with a first material;

[0046] A replacement unit, which replaces the material of the first matching part in the design space with a second material;

[0047] A simulation unit, performing a first simulation and a second simulation on an inherent test condition and a design element test condition of a first object, respectively;

[0048] Constraint unit, which defines constraints and design goals, and sets dimensional constraints and manufacturing constraints for pre-simulated structures;

[0049] The calculation unit performs material optimization and topology optimization solutions, and iterates the optimization results until they meet expectations.

[0050] A computer device comprises: a memory and a processor; the memory stores a computer program, wherein: the processor implements the steps of any one of the methods of the present invention when executing the computer program.

[0051] A computer-readable storage medium stores a computer program, wherein: when the computer program is executed by a processor, the steps of any one of the methods of the present invention are implemented.

[0052] Beneficial effects of the present invention: The automobile lightweight design method provided by the present invention optimizes the vehicle body structure by introducing the simulation data and material replacement strategy of the benchmark vehicle. The method combines multiple simulation conditions with the optimization algorithm library, dynamically adjusts the design variables and material combinations, and significantly improves the deformation capacity and durability of the vehicle. Through topological optimization and multiple iterations, the final design meets the expected requirements, minimizes the vehicle body mass, improves the energy efficiency and safety of the vehicle, reduces the production cost, and provides an effective solution for the lightweight design of new energy vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0054] Figure 1 An overall flow chart of a lightweight vehicle design method provided for the first embodiment of the present invention. DETAILED DESCRIPTION

[0055] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0056] Example 1, reference Figure 1 , as an embodiment of the present invention, provides a lightweight design method for an automobile, comprising:

[0057] S1: Obtaining a target load and target attributes of a vehicle; the target load is a cross-sectional force of a key cross-section based on a first simulation result of at least one benchmark vehicle; the target attributes are but not limited to a deformation capacity and durability of a key design part based on a second simulation result of at least one benchmark vehicle.

[0058] Furthermore, the benchmark vehicle includes obtaining a vehicle that is the same as the design vehicle model and has a curb weight and a length, width, and height that differ by less than 20%, and selecting no less than one vehicle that meets the requirements as the benchmark vehicle.

[0059] In the lightweight design of automobiles, the purpose of introducing benchmark vehicles is to provide reference data for the design vehicles, so as to more accurately set the goals and constraints of lightweight design. Specifically, by selecting a vehicle with the same model as the design vehicle and a curb weight and parameters such as length, width, and height that differ by less than 20% as the benchmark vehicle, it can be ensured that the selected benchmark vehicle has a high similarity with the target vehicle in terms of structural characteristics and dynamic performance. This can make the data such as section force and deformation capacity obtained during the simulation process closer to reality, provide a scientific basis for subsequent material replacement and structural optimization, and thus improve the accuracy and reliability of the design. At the same time, this step also helps reduce errors caused by excessive differences in the design process, and helps to converge to the optimal lightweight solution more quickly.

[0060] When performing collision simulation on the benchmark vehicles that meet the requirements, the section force of the key cross section of each vehicle is obtained, the peak value of the section force is used as the equivalent static load, and the average value of the section force analysis results of the key cross section is used as the input load of the topology optimization analysis.

[0061] By performing a collision test on the benchmark vehicle, the target load of the inherent test condition under the first simulation is obtained. The material replacement part of the design vehicle is obtained, and the deformation capacity and durability capacity of the same part of the benchmark vehicle are tested to obtain the force under the target deformation degree and the test environment and test time under the target durability degree under the design element test condition under the second simulation.

[0062] Specifically, by obtaining the target load under the inherent test conditions through the collision test of the benchmark vehicle, the key mechanical properties of the vehicle structure under real collision conditions can be obtained. These data provide an actual load benchmark for the first simulation, making the simulation results more valuable for practical reference. In addition, by testing the deformation capacity and durability of the same parts of the benchmark vehicle, the durability and stability of the vehicle structure after material replacement can be evaluated to ensure that the deformation and durability characteristics of the designed vehicle under different working conditions are similar to or better than those of the benchmark vehicle. This can not only optimize the lightweight effect of the designed vehicle, but also ensure its safety and durability in real use.

[0063] S2: Define the design space, establish an envelope geometry model for the pre-simulation structure, and convert it into a finite element model.

[0064] Furthermore, according to the preset inner and outer boundaries of the spatial arrangement, the body frame envelope geometry model and the power battery pack envelope geometry model are respectively established for the pre-simulation structure; the body frame envelope geometry model is converted into a body frame finite element model for characterizing the body frame design space, and the battery pack envelope geometry model is converted into a battery pack finite element model for characterizing the battery pack frame design space; the body frame finite element model is divided into multiple parts (for example, front cabin, front panel, front floor, rear floor, coat rack, tail end beam, side panel, top cover) according to different overall components. According to the spatial arrangement in the model, the connection position is determined between the body frame finite element model and the battery pack finite element model and they are connected in a rigid and common node manner to obtain a vehicle-electric frame integrated model for characterizing the vehicle-electric structure integrated design space.

[0065] First, the envelope geometry model of the body frame and battery pack is established according to the preset inner and outer boundaries of the spatial layout, and converted into finite element models respectively, which can truly characterize the spatial and mechanical properties of different components. The body frame is decomposed by assembly, so that designers can independently optimize materials and adjust structures for different components (such as the front compartment, top cover, etc.), thereby improving the lightweight effect of the entire body. In addition, the connection position between the body and the battery pack is clearly defined, and they are connected in a rigid and common node manner, which not only ensures the integrity of the structure and the reliability of force transmission, but also facilitates the integrated finite element model to more accurately reflect the coupling effect of the battery pack and the body frame in the simulation analysis. This integrated model provides a complete vehicle-electric design space for subsequent simulation and optimization, ensuring the safety, rigidity and lightweight effect of the design.

[0066] S3: Using the first material to replace the optional part in the design space.

[0067] Furthermore, the carbon fiber composite material floor ply is designed and optimized, and the optimized carbon fiber composite material floor is replaced with the corresponding part of the finite element model in the design space to obtain the design space after the first material replaces the optional part in the design space.

[0068] S4: Using a second material to replace the material of the first matching part in the design space.

[0069] The hybrid material B-pillar is designed and optimized, and the optimized hybrid material B-pillar is replaced with a corresponding part of the finite element model in the design space to obtain a design space after the second material replaces the first matching part in the design space.

[0070] Selecting different materials (such as carbon fiber composites and hybrid materials) for replacement can be customized and optimized according to the functional requirements of different components. For example, the use of carbon fiber composites in the floor area can reduce weight and enhance impact resistance, while the B-pillar, as a key load-bearing and safety structure, uses a hybrid material to achieve a balance between impact resistance and durability. Through detailed component division and targeted material replacement, the material and structure of each component can be precisely optimized according to its mechanical properties and functional requirements, which not only improves design flexibility but also reduces excess weight burden.

[0071] According to the stress distribution and functional characteristics of the body frame, other parts (such as the front panel, side panels, and roof) are divided into optional parts and matching parts. The optional parts are mainly some auxiliary or secondary stress-bearing areas, which can use lighter materials, such as carbon fiber composite materials; the matching parts are important load-bearing structures or key safety structures, and can choose mixed materials or other reinforced materials.

[0072] Apply a similar optimization process to the floor and B-pillars for other components. The optimization process for each component can include the selection of design materials, simulation testing, and iterative optimization to ensure that each component is lightweight without compromising its structural stability.

[0073] After completing the material replacement of all key components, the structural performance and durability of different material combinations are verified through overall simulation, making the entire body lightweight design have overall coordination and reliability.

[0074] S5: Perform a first simulation and a second simulation on the inherent test condition and the design element test condition of the first object, respectively.

[0075] The first simulation includes frontal collision conditions and side collision conditions, and during the simulation, loads are applied according to the loading methods under various conditions. Through the first simulation, a force transmission path in the collision test is obtained.

[0076] The second simulation includes a shape change test and a durability test of continuous work. During the respective tests, in the simulation process, characteristic data is applied according to the characteristic expression mode under the respective tests; for example, if the physical quantity a represents the deformation ability, then during the simulation, it is necessary to add a numerical value to the physical quantity a. The durability test includes, but is not limited to, high and low temperature tests and corrosion tests. The characteristic data includes the force in the shape change test, the test environment and the test time in the durability test. The durability test is simulated by comprehensively analyzing the physical and chemical properties of the replacement materials, and the simulation process of the durability test is arranged through a neural network. First, the corrosion degree of the material is analyzed according to the chemical properties, and then the physical properties are analyzed according to the physical properties to see whether the physical properties can achieve rigid support. Specifically, the corrosion process of each single material used in the test link is learned through the neural network, and the rigidity of the material under different combinations is learned by the neural network (different combinations include: combinations of different materials, combinations of different materials under different percentages of corrosion). During the test, the corroded material is first analyzed by the neural network, and the uncorroded part is input into the neural network to predict the rigidity. The test process of deformation ability is similar to the simulation process of the durability test.

[0077] Frontal and side collision simulations are mainly used to test the impact resistance of vehicles under extreme accident conditions. This simulation can help designers evaluate whether the structure can effectively absorb energy, whether there are weak connection areas, and provide decision support in ensuring vehicle safety. Shape change tests can analyze whether materials will undergo irreversible deformation during long-term use, affecting structural integrity; durability tests are used to evaluate the durability and fatigue resistance of components to predict the life of key components. These tests ensure that the design can remain structurally stable under daily use. During the simulation process, specific physical quantities (such as deformation capacity) can be more intuitively expressed by numerical additions of materials and structures under actual loads. For example, by adding deformation capacity values ​​to shape change tests, the differences in mechanical performance of different designs can be accurately measured, making the simulation results closer to reality. The numerical addition of feature data can also help identify whether the replacement material meets the design requirements, avoid errors that may be caused by relying solely on static test data, and thus more effectively verify the optimization effect.

[0078] In addition to the shape change test and the endurance test of continuous operation, the design elements can also be other tests, which are related to the design requirements. For example, the vibration fatigue test is suitable for evaluating the fatigue accumulation of components caused by vibration and impact during driving, such as chassis, suspension and frame components. By applying vibration loads with different frequencies and amplitudes, the fatigue life of these components after long-term use can be predicted to determine whether they will fail due to fatigue.

[0079] S6: Define constraints and design goals, and set dimensional constraints and manufacturing constraints for the pre-simulation structure.

[0080] The defined constraints include load constraints during loading, size constraints set for the pre-simulation structure, manufacturing constraints set for the vehicle body and battery pack, and draft constraints under collision conditions.

[0081] For example: set the member size constraints of the body parts between 40-120, set the member size constraints of the battery pack between 40-80, set symmetry constraints for the entire topology optimization design space, and set the volume fraction of the optimization area to <0.3. The load is constrained during loading, and the topology optimization load obtained by the cross-sectional force analysis of the benchmark vehicle is used. Except for the upper A-pillar along the axial direction of the structure, the remaining sections are loaded along the X direction. Under the frontal collision condition, set the Z-direction draft constraint for the top cover, rear floor, and front floor, set the Y-direction draft constraint for the side panel, front door, and rear door, set the X-direction draft constraint for the tail beam, and set the X-direction extrusion constraint for the battery pack; under the side collision condition, set the Y-direction extrusion constraint for the top cover, rear floor, front floor, and battery pack, and set the Y-direction draft constraint for the front door and rear door.

[0082] By setting draft constraints, you can ensure that parts can be removed from the mold smoothly and economically, thereby simplifying the production process and reducing the risk of rejects.

[0083] The design objectives include defining the overall strain energy response and taking the minimum strain energy and the maximum deformation capacity and durability as the optimization objectives.

[0084] S7: Perform material optimization and topology optimization, and iterate the optimization results until they meet expectations.

[0085] The vehicle is topologically optimized according to the optimization target, and an engineering interpretation is performed based on the topological optimization result of the target to determine whether the optimization result meets the design expectation. If it does not meet the expectation, the design variables are adjusted to re-analyze the load, and the iterative calculation process is repeated until the optimization result meets the expectation.

[0086] When the optimization result does not meet the design expectation, the design variables are adjusted according to the degree of deviation from the preset value; the degree of non-satisfaction is graded according to the degree, and the design variables are adjusted to different degrees for different degrees of deviation. When adjusting, the adjustment range of the design variables is positively correlated with the degree of deviation from the preset value.

[0087] The rule of adjusting the design variables once includes: when the deviation between the optimization result and the design expectation is reduced after adjusting the design variables once, the adjustment is confirmed; when the deviation between the optimization result and the design expectation is not reduced after adjusting the design variables once, the adjustment is not confirmed and the adjustment is reset. If the deviation between the optimized design and the design expectation does not exceed the upper limit of the deviation, the design variables are adjusted with the minimum adjustment amplitude. When the result of continuous iteration reaches the upper limit that meets the design expectation, the iteration is stopped and the design variable with the smallest deviation is output as the final result.

[0088] It is important to know that by adjusting the amplitude of the design variables in different levels according to the degree of deviation, the optimization process can be made more flexible. When the deviation is large, increase the adjustment amplitude to quickly narrow the gap; when the deviation is small, use a smaller adjustment amplitude for precise adjustment to avoid overshoot or overshoot. This design can effectively reduce the number of iterations and ensure more accurate results when the accuracy requirement is high. The adjustment amplitude is positively correlated with the degree of deviation, which can achieve gradual convergence. For example, when the deviation is small, a small adjustment can help to stabilize the target value and avoid repeated oscillations caused by excessive adjustments. Especially when approaching the expected upper limit, the minimum adjustment can help the optimization results gradually converge to the optimal solution. When the optimization deviation is within the allowable range, further optimization according to the minimum adjustment amplitude can avoid the introduction of new deviations due to excessive adjustments, thereby ensuring that the optimization results are both in line with expectations and have high stability and reliability.

[0089] It should be noted that engineering interpretation includes the following steps:

[0090] Result comparison and deviation analysis: Compare the optimization results with the design goals (such as strength, stiffness, and weight) one by one, and quantify the degree of deviation of each indicator. According to the size of the deviation, determine whether it is within the allowable range. If a performance indicator (such as stiffness) is lower than expected or has a large deviation, special attention should be paid and the part should be marked as an area that needs to be optimized.

[0091] Force transmission path analysis: After optimizing the structure, analyze the force transmission paths of key components to ensure that mechanical loads can be efficiently distributed and transmitted. For example, in a collision condition, analyze the transmission path of the collision force from the front cabin to the passenger compartment to see if there are weak connection areas or local stress concentrations. If the optimization results in interruptions or weak connection areas in the force transmission path, the structure or material needs to be adjusted.

[0092] Stress and strain distribution analysis: View stress and strain distribution in finite element simulation, paying special attention to the location and changes of stress concentration. Through visualization methods such as contour plots, the deformation of components under different loads can be analyzed to determine whether it meets design expectations. If the strain in a certain part is too large or the material exceeds the strength limit, further optimization is required.

[0093] Material performance analysis: Analyze the performance of the replaced materials in the new structure, such as wear resistance, impact resistance, etc. For newly replaced material parts (such as carbon fiber composite floor, hybrid material B-pillar), check their mechanical stability and service life in actual working conditions to ensure that the material performance meets the use requirements.

[0094] Manufacturing feasibility check: After optimizing the design, evaluate the manufacturability of the design to determine whether it meets the requirements of the actual manufacturing process. For example, whether a complex structural design can be realized through existing processes (such as stamping, welding, and composite material molding). If the topology optimized structure is too complex and cannot be realized, the design may need to be adjusted to meet the manufacturing requirements.

[0095] Safety and regulatory compliance assessment: Evaluate whether the safety performance of the optimized structure meets compliance requirements based on vehicle design safety standards and regulations (such as collision safety standards). Ensure that the vehicle can achieve the expected safety level and legal standards after optimization.

[0096] Through engineering interpretation, we can ensure that the design meets the requirements of strength, safety, durability, etc. under the premise of lightweight, while taking into account the feasibility of actual production and manufacturing. In this way, we can clarify the adjustment direction and effectively iterate the optimization, and gradually achieve the expected optimization results.

[0097] Further, judging whether the optimization result meets the design expectation includes that when the first design expectation, the second design expectation, and the third design expectation are all met, the optimization result is judged to meet the design expectation. The situation that does not meet the first design expectation includes that if a weak connection area appears in the optimized force transmission path, the weak connection area is marked and judged as not meeting the first design expectation; if the optimized force transmission path exceeds the upper limit of the deviation from the design expectation, the optimization result is judged as not meeting the first design expectation. The situation that does not meet the second design expectation includes that if the maximum value of the deformation range of the optimized body structure exceeds the upper limit of the deviation from the design expectation during the second simulation process, the optimization result is judged as not meeting the second design expectation. The situation that does not meet the third design expectation includes that if the degree of wear of the optimized body structure exceeds the upper limit of the deviation from the design expectation during the third simulation process, the optimization result is judged as not meeting the third design expectation.

[0098] The design of the carbon fiber composite floor ply and the hybrid material B-pillar includes presetting a resource library of hybrid algorithms, entering different hybrid algorithms, using the hybrid algorithms one by one to design the carbon fiber composite floor ply and the hybrid material B-pillar, and performing a first simulation and a second simulation. The result closest to the design expectation is the optimal design result of the carbon fiber composite floor ply and the hybrid material B-pillar.

[0099] Carbon fiber composite floor and hybrid material B-pillars often need to meet multiple requirements such as lightweight and strength during design and optimization. Through simulation tests one by one, we can find the material combination that best meets the overall design goals, so that the optimization of the two components can cooperate with each other without interfering with each other, thereby improving the overall performance of the vehicle. Different material combinations differ in stress distribution, deformation characteristics, etc. Through simulation tests with different algorithms, we can find a combination that can meet the requirements of both individual components and the requirements of the entire vehicle structure, ensuring high structural coordination and mechanical stability in actual use.

[0100] It should be noted that the improved hybrid optimization algorithm shows significant advantages in solving multi-objective optimization problems compared with intelligent optimization algorithms, multi-objective optimization algorithms and single-objective optimization algorithms, especially in terms of time consumption and avoiding premature convergence. This algorithm plays a key role in solving the core problems and technical challenges in the design and multi-objective optimization of carbon fiber composite floor plies. Generally speaking, in the process of finding the global optimal solution, fast convergence speed and robustness are difficult to achieve at the same time. To this end, many scholars are committed to developing new optimization methods, among which hybrid algorithms have achieved remarkable results in solving multi-objective optimization problems because they can effectively combine efficiency and accuracy.

[0101] The optimization of the carbon fiber composite floor ply and the hybrid material B-pillar also includes adjusting each design variable output by each algorithm at the same time; (It should be noted that the adjustment mentioned here essentially meets the above-mentioned "single adjustment" rule, which is to find a positive adjustment direction, but the adjustment of the ply or material involves the adjustment of multiple parameters, so the advantage is maximized by adjusting the parameters one by one) Obtain the design variables in each output result, and adjust each design variable in any of the three adjustment methods of increase, decrease, and unchanged; obtain all adjustment schemes, and output the scheme with the smallest deviation from the design expectation as the optimization result. In each optimization, the adjustment step of the design variable is smaller than the previous adjustment; when the results of the continuous iterative optimization have not changed, stop the iteration and output the last design variable as the final result.

[0102] Each design variable is adjusted in three ways: increase, decrease or remain unchanged, and the solution with the least deviation from the expected is taken as the final result, making the optimization process more refined. Especially in the multivariable design of complex structures, this fine adjustment method can reduce potential errors, improve design accuracy, and ensure that the optimization results are closer to the design expectations. Since the floor ply and B-pillar involve multiple parameters, adjusting each parameter one by one to find the best combination helps to fully explore the contribution of each parameter to lightweight and structural performance. For example, adjusting variables such as ply thickness, number of layers, and material distribution can ensure that the optimal balance between weight and strength is found, thereby maximizing the design advantage. "Forward adjustment" in design means ensuring that each adjustment can reduce the deviation from the expected. This adjustment rule automatically identifies the most effective adjustment direction through the comparison of three adjustment methods (increase, decrease, and remain unchanged), avoids unnecessary invalid modifications, quickly finds the forward adjustment path, and improves the adjustment efficiency. As the adjustment step size gradually decreases, the efficiency and convergence speed of iterative optimization continue to improve. By terminating the optimization process when there are continuous invalid adjustments, excessive iterations are avoided, design time and computing resource costs are saved, and reliable optimization solutions are obtained in the shortest time. The iterative process of gradually reducing the adjustment range makes the final result have high stability when approaching the expected target, reducing the fluctuation caused by large adjustments. The final combination of design variables not only meets the requirements of lightweight and durability, but also ensures the long-term reliability of the design.

[0103] On the other hand, this embodiment also provides a vehicle lightweight design system, which includes:

[0104] The acquisition unit is used to collect the cross-sectional force of the key cross-section in the first simulation result; the target attribute is but not limited to the deformation capacity and durability of the key design part in the second simulation result based on at least one benchmark vehicle. The design unit is used to define the design space, establish an envelope geometry model for the pre-simulation structure, and convert it into a finite element model; use the first material to replace the material of the optional part in the design space. The replacement unit is used to replace the material of the first matching part in the design space with the second material. The simulation unit is used to perform a first simulation and a second simulation on the inherent test condition and the design element test condition of the first object, respectively. The constraint unit is used to define constraints and design goals, and set dimensional constraints and manufacturing constraints for the pre-simulation structure. The calculation unit is used to perform material optimization and topology optimization solutions, and iterate the optimization results until expectations are met.

[0105] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0106] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0107] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0108] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0109] Embodiment 2 is an embodiment of the present invention, which provides a method for lightweight design of automobiles. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0110] The test object is the body structure of a certain household electric vehicle, including the floor, B-pillar and body frame. The test materials include conventional steel, carbon fiber composite materials and a new hybrid material. The core of this test is to apply multi-condition simulation and material optimization technology to analyze the mechanical properties of the test materials to verify the effectiveness of the new material in lightweight design. The following specific steps describe the test preparation, simulation operation and data collection process.

[0111] Test preparation: For the test vehicle, first obtain its target load and target attributes. The target load includes the peak load data of frontal collision and side collision, and the target attributes include the deformation capacity and wear resistance of the vehicle structure. The test benchmark vehicle is a traditional vehicle whose body structure, curb weight and appearance size are within 20% of the design vehicle. Its data comes from historical collision tests and related performance evaluation reports. Through the simulated collision test of the benchmark vehicle, the target load under the inherent working conditions is obtained, and the data is used as the benchmark test condition for the design vehicle.

[0112] Experimental implementation:

[0113] Model construction: Define the design space according to the vehicle space layout, establish the envelope geometry model for the body frame and the battery pack, and generate the body frame finite element model and the battery pack finite element model. Divide the finite element model into multiple components such as the front cabin, the front panel, the front floor, the rear floor, the coat rack, the tail beam, the side wall and the top cover. According to the space layout, determine the connection position between the body frame and the battery pack, and use rigid connection and common node processing to accurately simulate the load transfer process.

[0114] Material replacement: Use the first material (carbon fiber composite material) to replace and optimize the floor ply, simulate and adjust the material thickness, number of layers and distribution to achieve the best strength-weight balance. Then, replace the B-pillar with the second material (mixed material), and simulate different thicknesses, material proportions and distribution forms, and finally get the best design solution for lightweight and impact resistance.

[0115] Simulation and optimization: Set up the first simulation (frontal and side collision) and the second simulation (deformation capacity test and durability test under continuous operation), apply loads to the finite element model of the replacement material, and apply characteristic data according to the working conditions. In each simulation, the strategy of gradually adjusting variables is adopted to fine-tune the structure and material thickness, and finally form a design with the smallest deviation. During the optimization process, the appropriate step size is selected according to the deviation level to ensure that each adjustment is made within the design range.

[0116] Data recording: All simulation results are recorded in a table. By comparing the data before and after optimization, the performance improvement effect after the new material replacement can be clearly demonstrated.

[0117] Table 1 Test result data record

[0118]

[0119] From the data in the above table, it can be seen that after adopting the material optimization and lightweight design method in the present invention, the vehicle has achieved significant improvements in quality, structural strength, deformation capacity and wear resistance. First, the weight of the optimized vehicle is reduced from 180 kg of the original frame to 148 kg, a weight reduction of 17.8%. The introduction of carbon fiber composite floor and hybrid material B-pillar has reduced the weight of the two key components by 67% and 37.5% respectively compared with the benchmark steel, fully demonstrating the advantages of lightweight design.

[0120] In terms of structural strength, the tensile strength of the optimized body frame increased from 240MPa to 290MPa, and the bending stiffness increased from 11500N / m to 12000N / m, indicating that the structural rigidity and tensile strength were significantly enhanced after the material replacement. The frontal and side collision simulation data showed the advantages of the optimization scheme in terms of safety. The residual deformation of the frontal collision was reduced from 14mm of the benchmark vehicle to 9mm, and the residual deformation of the side collision was also reduced from 10mm to 7mm, proving that the optimized material design has stronger anti-deformation ability and significantly improves the safety performance of the vehicle.

[0121] In addition, in terms of durability, wear resistance has also been significantly improved. For example, the wear resistance of the carbon fiber floor has been reduced from 0.8g of the benchmark steel to 0.5g, while the wear resistance of the hybrid material B-pillar has been reduced by about 26.7% compared to the original steel. This improvement effectively improves the durability of the vehicle in long-term use, reduces the probability of component wear, and further ensures the service life of the vehicle.

[0122] The present invention not only achieves lightweight, but also ensures structural strength and durability by precisely adjusting the material combination and layer design, and has obvious innovation and novelty compared with the prior art. Traditional designs often face the problem of balancing weight and strength, while the present invention successfully achieves both through multi-condition simulation and material optimization, while ensuring lightweight while improving the tensile, wear and impact resistance of the structure, thus solving the problem of insufficient performance of lightweight solutions commonly found in the prior art, and showing high practicality and industrial application value.

[0123] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for lightweight design of an automobile, characterized in that: include: Get the target load and target properties of the car; The target load is a cross-sectional force of a key cross-section in a first simulation result based on at least one benchmark vehicle; The target attributes include but are not limited to deformation capacity and durability of key design parts based on the second simulation results of at least one benchmark vehicle; Define the design space, build an envelope geometry model for the pre-simulation structure, and convert it into a finite element model; Using a first material to replace a material of an optional part in the design space; Replacing the first matching portion in the design space with a second material; Performing a first simulation and a second simulation on an inherent test condition and a design element test condition of the first object, respectively; Define constraints and design goals, set dimensional constraints and manufacturing constraints for pre-simulated structures; Perform material optimization and topology optimization solutions, and iterate the optimization results until they meet expectations.

2. The method for lightweight design of an automobile according to claim 1, characterized in that: The benchmark vehicle includes obtaining a vehicle that is the same as the design vehicle model and has a curb weight and a length, width, and height that differ by less than 20%, and selecting at least one vehicle that meets the requirements as the benchmark vehicle; When performing collision simulation on the benchmark vehicles that meet the requirements, the section force of the key section of each vehicle is obtained, the peak value of the section force is used as the equivalent static load, and the average value of the section force analysis results of the key section is used as the input load of the topology optimization analysis; By performing a collision test on the benchmark vehicle, a target load of the inherent test condition under the first simulation is obtained; The material replacement part of the design vehicle is obtained, and the deformation capacity and durability capacity of the same part of the benchmark vehicle are tested to obtain the test environment and test time under the target deformation degree and the target durability degree under the design element test condition under the second simulation.

3. The automobile lightweight design method according to claim 2, characterized in that: Defining the design space includes establishing a vehicle body frame envelope geometry model and a power battery package envelope geometry model respectively according to a preset spatial arrangement of inner and outer boundaries; The body frame envelope geometry model is converted into a body frame finite element model for representing the body frame design space, and the battery pack envelope geometry model is converted into a battery pack finite element model for representing the battery pack frame design space; The finite element model includes dividing the body frame finite element model into eight parts according to different overall components, namely, a front cabin, a front wall panel, a front floor, a rear floor, a coat rack, a tail end beam, a side wall, and a top cover; According to the spatial layout in the model, the connection positions between the body frame finite element model and the battery pack finite element model are determined and connected in a rigid and common node manner to obtain a vehicle-electric frame integration model for characterizing the vehicle-electric structure integration design space.

4. The automobile lightweight design method according to claim 3, characterized in that: The material replacement of the optional part includes designing and optimizing the carbon fiber composite material floor ply, replacing the optimized carbon fiber composite material floor with the corresponding part of the finite element model in the design space, and obtaining the design space after the first material replaces the optional part in the design space; The material replacement of the first matching part includes designing and optimizing the hybrid material B-pillar, replacing the optimized hybrid material B-pillar with the corresponding part of the finite element model in the design space, and obtaining the design space after the first matching part in the design space is replaced by the second material.

5. The method for lightweight design of an automobile according to claim 4, characterized in that: The first simulation includes a frontal collision condition and a side collision condition, and during the simulation, a load is applied according to a loading method under various conditions; The second simulation includes a shape change test and a continuous working endurance test, and during the respective tests and during the simulation, characteristic data are applied according to the characteristic performance mode under the respective tests; The durability test includes, but is not limited to, high and low temperature test and corrosion test; The characteristic data include the force in the shape change test, the test environment and test time in the durability test; The defined constraints include load constraints during loading, size constraints set for the pre-simulation structure, manufacturing constraints set for the vehicle body and battery pack, and draft constraints under collision conditions.

6. The method for lightweight design of an automobile according to claim 5, characterized in that: The design objectives include defining the overall strain energy response, minimizing the strain energy, maximizing the deformation capacity and the durability as the optimization objectives; Performing topology optimization on the vehicle according to the optimization target, performing engineering interpretation based on the topology optimization result of the target, judging whether the optimization result meets the design expectation, and if it does not meet the expectation, adjusting the design variables and re-analyzing the load, and repeatedly performing the iterative calculation process until the optimization result meets the expectation; When the optimization result does not meet the design expectation, the design variables are adjusted according to the degree of deviation from the preset value; the design variables are graded according to the degree of non-satisfaction with the expectation, and the design variables are adjusted to different degrees for different degrees of deviation; When adjusting, the adjustment range of the design variable is positively correlated with the degree of deviation from the preset value; The rule of adjusting the design variables once includes: when the deviation between the optimization result and the design expectation decreases after adjusting the design variables once, confirming the adjustment; When the deviation between the optimization result and the design expectation does not decrease after adjusting the design variable once, the adjustment is not confirmed and the adjustment is reset; If the deviation between the optimized design and the expected design does not exceed the upper limit of the deviation, the design variables are adjusted with the minimum adjustment range. When the results of continuous iterations reach the upper limit that meets the expected design, the iteration is stopped and the design variable with the smallest deviation is output as the final result.

7. The automobile lightweight design method according to claim 6, characterized in that: Determining whether the optimization result meets the design expectation includes: when the first design expectation, the second design expectation, and the third design expectation are all met, determining that the optimization result meets the design expectation; The situation that does not meet the first design expectation includes: if a weak connection area appears in the optimized force transmission path, the weak connection area is marked and judged as not meeting the first design expectation; if the optimized force transmission path exceeds the upper limit of the deviation from the design expectation, the optimization result is judged as not meeting the first design expectation; The situation of not meeting the second design expectation includes that if the maximum value of the deformation range of the optimized vehicle body structure during the second simulation process exceeds the upper limit of the deviation from the design expectation, the optimization result is judged to not meet the second design expectation; The situation that does not meet the third design expectation includes that if the wear degree of the optimized vehicle body structure exceeds the upper limit of the deviation from the design expectation during the third simulation process, the optimization result is judged as not meeting the third design expectation.

8. The automobile lightweight design method according to claim 4, characterized in that: The design of the carbon fiber composite material floor ply and the hybrid material B-pillar includes presetting a resource library of hybrid algorithms, entering different hybrid algorithms, using the hybrid algorithms one by one to design the carbon fiber composite material floor ply and the hybrid material B-pillar, and performing a first simulation and a second simulation; The result closest to the design expectation is the optimal design result for the carbon fiber composite floor ply and the hybrid material B-pillar.

9. The automobile lightweight design method according to any one of claims 7 or 8, characterized in that: The optimization of the carbon fiber composite floor ply and the hybrid material B-pillar also includes adjusting each design variable of the output of each algorithm simultaneously; Obtain the design variables in each output result, and adjust each design variable in any of the three adjustment modes of increase, decrease, and unchanged; obtain all adjustment schemes, and output the scheme with the smallest deviation from the design expectation as the optimization result; In each optimization, the adjustment step of the design variables is smaller than the previous adjustment; When the results of continuous iterative optimization do not change, stop the iteration and output the last design variable as the final result.

10. An automobile lightweight design system using the method according to any one of claims 1 to 9, characterized in that: Acquisition unit, section force of a key section in the first simulation result; The target attributes include but are not limited to deformation capacity and durability of key design parts based on the second simulation results of at least one benchmark vehicle; Design unit, defines the design space, establishes an envelope geometry model for the pre-simulation structure, and converts it into a finite element model; Using a first material to replace a material of an optional part in the design space; A replacement unit, which replaces the material of the first matching part in the design space with a second material; A simulation unit, performing a first simulation and a second simulation on an inherent test condition and a design element test condition of a first object, respectively; Constraint unit, which defines constraints and design goals, and sets dimensional constraints and manufacturing constraints for pre-simulated structures; The calculation unit performs material optimization and topology optimization solutions, and iterates the optimization results until they meet expectations.

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