Automobile body high-strength steel equivalent replacement and fatigue durability performance analysis method

Abstract

A method for analyzing the equivalent replacement and fatigue durability of high-strength steel in automotive bodies includes: calculating the thickness of the hot-formed steel replacement material using formulas for deformation resistance and energy absorption; updating the CAD model and establishing a high-precision finite element model; optimizing the model through modal testing; collecting acceleration signals from hard points on the actual vehicle and converting them into displacement signals; performing modal transient analysis and fatigue damage calculation; optimizing the structure based on the damage values ​​and evaluating the weight reduction rate and cost changes. This method can accurately determine the replacement material thickness, significantly improve simulation accuracy, greatly shorten the development cycle and verification cost, and effectively solve the fatigue durability problem of automotive bodies.

Description

Technical Field

[0001] This invention relates to the technical field of high-strength automotive bodies, and in particular to a method for equivalent replacement of high-strength steel in automotive bodies and analysis of fatigue durability performance. Background Technology

[0002] With the continuous development of the automotive industry, lightweight design has become a core technological path to achieve low energy consumption and high safety. High-strength steel, especially hot-formed steel, has become the mainstream material for vehicle body structure optimization. This technology involves heating boron-containing steel sheets to the austenitic region and then simultaneously forming and quenching them in a mold, resulting in a tensile strength generally exceeding 1500 MPa while maintaining high residual ductility and geometric accuracy. Hot-formed steel is widely used in load-bearing and energy-absorbing parts such as A-pillars, B-pillars, front and rear longitudinal beams, sill reinforcement plates, and floor tunnels, achieving weight reductions of 80–120 kg per vehicle, fuel consumption reductions of 0.3–0.6 L / 100km, and significant improvements in collision safety performance. With the rapid increase in the proportion of new energy vehicles, the proportion of high-strength and ultra-high-strength steel in the body-in-white of some models has exceeded 70%. Meanwhile, fatigue durability analysis methods have gradually evolved from vehicle road tests and bench durability tests to virtual simulation iterations. Commonly used techniques include quasi-static superposition method, modal stress recovery method, and frequency domain power spectral density method (such as Dirlik method and Lalanne method). Furthermore, finite element software such as Abaqus, Nastran, and OptiStruct are used to predict the life of the vehicle body under multi-axis random loads.

[0003] While existing technologies have established a relatively complete system for the application and fatigue analysis of hot-formed steel, significant limitations remain. These limitations not only restrict the depth of technological innovation but also make it difficult to adapt to the complex and ever-changing needs of vehicle development. First, in the process of equivalent replacement of high-strength steel, traditional methods mainly rely on empirical coefficients or simple equivalents of section modulus and bending stiffness, lacking rigorous strength equivalence formulas for differentiating between deformation-resistant and energy-absorbing zones. This results in insufficient accuracy in calculating replacement thickness, requiring multiple CAE-experimental iterations for correction, significantly extending the development cycle and increasing costs. More importantly, this method ignores the coupling effect between the material's elastic-plastic curve and the structure's dynamic response, failing to achieve accurate equivalence of strength and durability before and after replacement, which can easily lead to potential safety hazards. Secondly, in virtual fatigue durability analysis, the modal parameters of the finite element model are usually directly adopted from the theoretical damping ratio, lacking systematic benchmarking with the measured modes. The errors in natural frequencies and mode shapes often exceed 10%, leading to decreased modal stress recovery accuracy and significant deviations in weld and weld point damage prediction. Furthermore, current methods lack innovation in road spectrum signal processing. When converting acceleration signals into displacement excitation through quadratic integration, rigorous zero-drift correction and high-pass filtering are not performed, easily introducing low-frequency trend terms that affect the reliability of transient response and fatigue damage calculations, making it difficult to reliably guide part optimization. These shortcomings are particularly prominent against the backdrop of increasingly frequent demands for vehicle platformization and derivatives, hindering the rapid and accurate application of hot-formed parts in lightweight vehicle bodies and the effective control of overall vehicle development costs. An innovative method integrating equal-strength replacement calculation, modal optimization verification, and efficient signal processing is urgently needed to break through the bottlenecks of the traditional framework and achieve a dual leap in development efficiency and accuracy. Summary of the Invention

[0004] This application provides a method for equivalent replacement of high-strength steel in automobile bodies and fatigue durability performance analysis, including the following steps: S1. The thickness of the thermoformed parts is obtained by performing equal strength replacement calculations on the non-thermoformed parts of the base vehicle using the equal strength replacement formula for deformation resistance and the equal strength replacement formula for energy absorption. S2. Input the material thickness, material information, weld information, weld point information, and bolt connection information obtained in step S1 into the vehicle body CAD model; S3. Based on the vehicle body CAD model from step S2, establish a finite element model of the entire vehicle body and perform modal analysis; S4. Perform modal testing on the actual vehicle body and compare it with the modal simulation results in step S3. If the error is ≤8%, output the modal stress, maximum stress of the weld, and nodal force of the weld point. S5. Acceleration signals at various hard points are collected during the actual vehicle road durability test and converted into displacement signals after processing; S6. Apply forced displacements in the X, Y, and Z directions to the finite element model after calibration in step S4 to perform transient analysis and output modal coordinates; S7. Using the modal stress output in step S4, the modal coordinates output in step S6, and the material elastic-plastic curve of the thermoforming material, fatigue durability analysis is performed to obtain the damage values ​​of the body parts, welds, and weld points, and the structure is optimized with the damage value ≤1 as the target. S8. Fine-tune the thickness of the thermoformed parts according to the optimized structure in step S7, and calculate the weight reduction rate and cost change after replacement based on the weight reduction rate formula.

[0005] It should be noted that by using the equal strength replacement formulas for deformation resistance and energy absorption, a precise equal strength replacement from non-thermoformable materials to thermoformable materials is achieved. This ensures that the replaced local structure maintains mechanical equivalence with the original structure in terms of yield strength and energy absorption capacity, thus avoiding the traditional iterative experimental process of "trial calculation of material thickness—verification—readjustment." Based on this, the calculated material thickness, material information, weld / weld point, and connection information are directly embedded into the CAD model to construct a finite element model. Modal testing and simulation benchmarking ensure that the structure's natural frequency and mode shape errors are controlled within ≤8%, guaranteeing high accuracy of the input conditions for subsequent fatigue analysis. By collecting actual vehicle road acceleration signals and converting them into displacement signals, which are then applied to the benchmarked finite element model for transient analysis, the true load response of the structure can be obtained without traditional road spectrum testing. This achieves high consistency between virtual and real data in the displacement domain. The output modal stress, modal coordinates, and the material elastic-plastic curves of the thermoformable material are used to construct a fatigue durability analysis model. Fatigue damage calculation aims to optimize the structure with a damage value ≤1, achieving fatigue life satisfaction optimization for parts, welds, and weld joints under lightweight conditions. Finally, by combining the lightweighting rate and cost model, it guides the fine-tuning of hot-formed material thickness, achieving an overall optimal balance between structural lightweighting, fatigue performance, and cost. This coupled process, with "formula-determined material thickness—model alignment—simulation-driven optimization" as its core path, establishes a causal chain between material replacement, structural strength, fatigue durability, and cost. Compared to existing methods relying on experience-based adjustments and multiple rounds of testing, it significantly improves design convergence speed and prediction accuracy, achieving innovative technical effects such as shortened development cycles, reduced testing costs, and enhanced predictability of hot-formed material replacement range.

[0006] As a preferred technical solution for the equivalent replacement of high-strength steel in automobile bodies and the analysis of fatigue durability, in step S1 The deformation resistance and equal strength replacement formula: ; The energy absorption intensity substitution formula: ;

[0007] Where t1, R1, and E1 are the material thickness, yield strength, and tensile strength of the replaced non-thermoformed part, respectively, and t2, R2, and E2 are the material thickness, yield strength, and tensile strength of the thermoformed part, respectively.

[0008] It should be noted that two dominant failure mechanisms of the vehicle body structure were identified during the material replacement process: one region is dominated by bending stiffness and yield strength, and the other region is dominated by energy absorption capacity during collision. By identifying the strength characteristics, stress state, and deformation mode of the original non-thermoformed parts, equivalent design principles of "deformation resistance retention" and "energy absorption retention" were adopted when replacing them with thermoformed materials. The deformation resistance equivalent strength replacement formula is based on the power relationship between the material's yield strength (R) and geometric thickness (t), ensuring that the replaced thermoformed steel maintains the deformation resistance of the original non-thermoformed parts at a thinner thickness, avoiding a decrease in structural stiffness. The energy absorption equivalent strength replacement formula focuses on the collision energy absorption region, combining yield strength (R) and tensile strength (E) to equivalently measure the plastic deformation energy absorption capacity. It usually adopts a power function relationship in the form of average strength or product, so that the thermoformed material maintains or improves its energy dissipation performance after thinning. This mechanism, starting from the coupling of intrinsic material properties and structural response, allows improvements in material performance to be directly translated into a reduction in thickness without causing a decrease in structural stiffness or energy absorption capacity. Because thermoformed materials possess higher yield strength and elastic response, they can withstand the same or even higher deformation resistance and energy absorption under load with thinner cross-sections, thus resolving the contradiction between lightweighting and performance preservation. This partitioned equivalent replacement based on mechanical mechanisms allows material thickness to be determined once and for all, eliminating the need for repeated experimental trials. Furthermore, it maintains or even enhances local strength and energy absorption capacity while significantly reducing structural weight. Without increasing structural complexity or cost, it achieves synergistic optimization of lightweighting, strength preservation, and impact resistance, significantly improving design efficiency and prediction accuracy. This allows for the synergistic optimization of strength, impact resistance, and fatigue durability under the premise of lightweighting, avoiding errors and cost waste caused by iterative experience.

[0009] As a preferred technical solution for the equivalent replacement of high-strength steel in automobile bodies and the analysis of fatigue durability, in step S2, the CAD model of the automobile body includes complete material information, weld information, weld point information and bolt connection information.

[0010] It should be noted that in step S2, the vehicle body CAD model is not merely a representation of the geometric model, but a true digital mapping of the entire vehicle's structural behavior. It contains complete material information, weld information, weld point information, and bolt connection information, forming a complete "virtual vehicle skeleton." Material information directly affects local stiffness, yield behavior, and fatigue life; weld and weld point information determines the force transmission path and local stress concentration distribution; and bolt connection information affects the rigid constraint relationship between different parts and the load transfer method. By fully embedding this information into the model during the CAD stage, subsequent finite element modeling eliminates the need for extensive manual supplementation and assumptions, thus avoiding the error accumulation problems common in traditional processes such as "simplified connections" and "default materials." This ensures that the model's boundary conditions, connection relationships, and local stiffness are consistent with the actual structure. This information-driven model enables simulation analysis to directly reflect the mechanical response characteristics of the real vehicle body, improving the accuracy of modal calibration and fatigue analysis. It provides a reliable data foundation for subsequent transient analysis, damage evaluation, and material replacement optimization, demonstrating accuracy and convergence efficiency unattainable by traditional modeling methods.

[0011] As a preferred technical solution for the equivalent replacement of high-strength steel in automobile bodies and the analysis of fatigue durability, step S3, the specific steps for establishing the finite element model of the whole vehicle body, include: Step S31. Divide the vehicle body parts into meshes; Step S32. Establish weld seams, weld points, bolt connections, and adhesive connections, wherein weld points are simulated using ACM welding; Step S33. Assign thickness and corresponding material properties to each part; Step S34. Assign vehicle weights according to actual curb weight requirements; Step S35. Based on this, perform modal analysis.

[0012] It should be noted that step S3 establishes a finite element model of the entire vehicle body through a series of ordered operations. The logic behind this is to achieve a mechanical mapping consistent with the actual vehicle, sequentially from structural geometry and connection relationships to material properties. First, the body parts are meshed, discretizing the continuous structure into computational units to provide an accurate spatial description for subsequent solutions. Then, connection types such as welds, weld points, bolts, and adhesives are established. The weld points utilize the ACM weld point model, which accurately reflects the stiffness and load transfer characteristics of point connections, allowing for the accurate expression of stress and deformation behavior in local connection areas. After establishing the geometry and connection relationships, each part is assigned thickness and corresponding thermoforming material properties, ensuring that material strength, elastic response, and local stiffness are correctly reflected in the model. Simultaneously, counterweights are assigned according to actual curb weight requirements, ensuring that the overall mass distribution and inertial characteristics are consistent with the actual vehicle, providing a foundation for modal characteristic simulation. After the above realistic constraints are constructed, modal analysis is performed, enabling the model to output natural frequencies and mode shapes, ensuring comparability with subsequent test data. This step, through full-chain modeling of geometry, connection, material, and mass, ensures that the finite element model not only matches the actual vehicle in appearance but also achieves a one-to-one correspondence in dynamic characteristics and connection force transmission paths, thus providing crucial support for the accuracy of subsequent analysis.

[0013] As a preferred technical solution for the equivalent replacement of high-strength steel in automobile bodies and the analysis of fatigue durability, in step S4, the modal test adopts the excitation method to test the overall mode and main local mode of the prepared body assembly, and obtains the natural frequency, corresponding damping ratio and mode shape; the benchmark error between the modal simulation results and the modal test results is ≤8%.

[0014] It should be noted that in step S4, modal testing of the vehicle body using the excitation method can simultaneously excite the overall body modes and major local modes without damaging the structure, thereby obtaining the true natural frequencies, corresponding damping ratios, and mode shape characteristics. These parameters reflect the force transmission path, stiffness distribution, and dynamic response characteristics of local components in the vehicle structure. Subsequently, the measured modal results are compared step by step with the finite element modal simulation results. When the error is controlled within ≤8%, it indicates that the model is highly consistent with the actual vehicle in terms of geometry, material properties, connection relationships, and mass distribution, and can truly reflect the dynamic behavior of the entire vehicle. This rigorous error control not only ensures the reliability of the input conditions for subsequent transient and fatigue analyses but also avoids modal deviations caused by factors such as simplified connections and inaccurate mass configuration in traditional models. This gives the finite element model engineering credibility, achieves consistent dynamic response prediction between virtual and real models, and thus significantly improves the accuracy of analysis and the effectiveness of structural optimization.

[0015] As a preferred technical solution for the equivalent replacement of high-strength steel in automobile bodies and the analysis of fatigue durability, the specific steps for data processing of the collected acceleration signal in step S5 include: first performing zero drift processing, then performing a second integration to obtain the displacement signal, and finally performing high-pass filtering to remove the low-frequency drift generated by integration, thereby obtaining the final vibration displacement signal.

[0016] It should be noted that the core purpose of data processing on the acquired acceleration signal in step S5 is to convert the high-frequency vibration response from the field test into a displacement signal that can be directly applied to the finite element model, so that the simulation conditions can truly reflect the actual road load conditions. First, zero-drift processing is performed to eliminate the influence of long-term sensor drift and installation errors on the acceleration baseline, ensuring the correct physical meaning of the signal starting point. Then, the zero-drift acceleration signal is integrated twice, converting the acceleration into velocity and displacement step by step, thereby obtaining the true displacement response of the structure under road excitation. Since the integration process inevitably introduces low-frequency drift components, a high-pass filter is used to clean the displacement signal, removing non-physical low-frequency trend terms and retaining the true vibration information. Through this processing link, the originally noisy acceleration data, which cannot be directly used for structural analysis, is transformed into a stable and reliable displacement input. This avoids the complexity of traditional road spectrum tests and ensures the consistency between the load input and the actual vehicle conditions, providing a reliable foundation for subsequent transient analysis and fatigue life assessment.

[0017] As a preferred technical solution for the equivalent replacement of high-strength steel in automobile bodies and the analysis of fatigue durability, in step S6, the transient analysis only considers low-order modes in the range of 0 to 50 Hz.

[0018] It should be noted that the transient analysis only considers the low-order modes of 0-50Hz because the vehicle road excitation is mainly concentrated in this frequency band. The low-order modes contribute the vast majority of vibration energy and play a dominant role in structural response and fatigue damage, thus ensuring both calculation accuracy and significantly improving analysis efficiency.

[0019] As a preferred technical solution for the equivalent replacement of high-strength steel in automobile bodies and the analysis of fatigue durability, in step S8, the formula for calculating the lightweighting rate is: Where P1 is the unit price of non-hot-formed steel sheet, P2 is the unit price of hot-formed material, and r is the material utilization rate of the part; when the lightweighting rate is greater than the result calculated by the above formula, it indicates that the cost of replacing with hot-formed material is reduced.

[0020] It should be noted that in step S8, the lightweighting rate calculation formula incorporates material price differences, material thickness variations, and component material utilization rates into a unified evaluation system, establishing a direct quantitative relationship between lightweighting effects and cost changes. Since thermoformed materials can significantly reduce thickness under the same strength requirements, even if their unit price is higher than ordinary steel plates, as long as the material utilization rate is high and the cost savings from reduced weight exceed the material price difference, the lightweighting rate will be positive. A lightweighting rate greater than the result calculated by the above formula indicates that replacing with thermoformed materials reduces costs.

[0021] This invention provides a method for analyzing the equivalent replacement of high-strength steel in automotive bodies. A cost analysis model is built for early-stage project cost analysis. By comprehensively considering weight and fatigue durability performance analysis objectives, replacement parts are screened, ultimately determining the application scope of equivalent high-strength steel replacement, thus significantly reducing project investment. The advantage of using the equivalent strength replacement formula is that it allows for precise determination of the replacement material thickness, reducing the iterative process of thickness determination-CAE verification / experimental verification-thickness adjustment-CAE verification / experimental verification. This ensures accurate and rapid project execution, significantly shortening the project development cycle. This invention provides a method for equivalent replacement and fatigue durability performance analysis of high-strength steel in automotive bodies. Modal parameters of the vehicle body are obtained through experimental test results, and the finite element model of the vehicle body is optimized, improving simulation accuracy. Acceleration signal data collected from actual vehicles is processed and converted into displacement signals, eliminating the need for traditional road spectrum testing, reducing development costs and shortening the development cycle. It can also process signals collected from harsh road surfaces and combine them with finite element simulation analysis of the vehicle body to solve fatigue cracking problems. Attached Figure Description

[0022] Figure 1 This is a flowchart of a method for equivalent replacement and fatigue durability performance analysis of high-strength steel in automobile bodies according to the present invention; Figure 2 This is a schematic diagram of a CAD model of a certain vehicle body used in an embodiment of the present invention; Figure 3 This is a waveform of the acceleration time-domain signal collected at a certain hard point during the test of this invention. Detailed Implementation

[0023] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the examples in the specification.

[0024] The following describes in detail the complete implementation process of the present invention's method for equivalent replacement of high-strength steel in automobile body and fatigue durability performance analysis, using a specific vehicle model as an example. The implementation process follows... Figure 1 As shown, it specifically includes the following: Step 1: Equivalent replacement of the car body with high-strength steel In this step, non-hot-formed parts of the base vehicle are replaced with equivalent parts. Taking the A-pillar of a certain vehicle as an example, the original part is made of DP600 duplex steel with a yield strength R1 = 350 MPa, tensile strength E1 = 600 MPa, and thickness t1 = 2.0 mm. It is proposed to replace it with 22MnB5 hot-formed steel with a yield strength R2 = 1000 MPa and tensile strength E2 = 1500 MPa (these data are based on actual automotive material standards: DP600 commonly has a yield strength of 350 MPa and a tensile strength of 600 MPa; 22MnB5, after heat treatment, has a yield strength of approximately 1000 MPa and a tensile strength of approximately 1500 MPa). Using the deformation resistance and energy absorption replacement formula, t2 ≈ 1.50 mm is obtained. Using the energy absorption and energy absorption replacement formula, t2 ≈ 1.55 mm is obtained. Considering the dual functions of the A-pillar in resisting deformation and energy absorption, as well as engineering safety margins, a conservative thickness t2 = 1.6 mm is chosen (rounding down to the larger value). This ensures that the strength after replacement is no less than that of the original structure, with the original thickness reduced by 20%. A preliminary estimate suggests a weight reduction of approximately 0.6 kg per component (assuming an A-pillar surface area of ​​0.2 m²). 2 Density 7.85 g / cm³ 3 (Original weight approximately 3 kg).

[0025] Step 2: Input the material thickness calculated from the analysis results into the prepared vehicle body CAD model. Based on the replacement thickness calculated in step one, import it into the body CAD model of the base vehicle. Open the body CAD model using CATIA software (similar to...). Figure 2 As shown), the thickness of the A-pillar component has been changed from 2.0 mm to 1.6 mm, and the material properties have been switched to 22MnB5 hot-formed steel with a density of 7.85 g / cm³. 3 The parameters include an elastic modulus of 210 GPa, Poisson's ratio of 0.3, yield strength of 1000 MPa, and tensile strength of 1500 MPa. Furthermore, the CAD model fully includes weld information (e.g., length 50 mm, TIG weld type), weld point information (diameter 6 mm, quantity 12), bolt connection information (M8 specification, quantity 4), and adhesive connection details. This step ensures all data parameters are complete, improving the accuracy and simulation reliability of the subsequent finite element model, and ultimately outputting an updated CAD file for easier mesh generation and analysis.

[0026] Step 3: Based on the vehicle body CAD model, input the performance parameters of the thermoforming material, build a finite element model of the vehicle body, and perform modal analysis. Using the updated vehicle body CAD model, a finite element model of the vehicle body was built in HyperMesh or ANSYS software. First, the body parts were meshed using shell elements (Shell181), with an average mesh size of 5 mm, approximately 500,000 nodes, and approximately 450,000 elements. Then, connection relationships were established: weld points were simulated using ACM (Area Contact Model), weld seams using beam elements (Beam188), bolts using rigid connections (RBE2), and adhesives using a contact algorithm (Conta174). Next, thickness and material properties were assigned to each part, for example, the A-pillar thickness was 1.5 mm, yield strength was 1000 MPa, and tensile strength was 1500 MPa. Furthermore, counterweights were added based on actual maintenance requirements, such as point mass elements simulating a 50 kg seat and a 20 kg battery. Finally, modal analysis was performed, using the Lanczos method to solve for the first 10 modes (frequency range 0-100 Hz), with free-free boundary conditions. The results show that the frequency of the first torsional mode is about 15.5 Hz and the frequency of the second bending mode is about 20.5 Hz (the frequency is slightly increased due to the change in thickness).

[0027] Step 4: Perform modal testing on the vehicle body to obtain the natural frequencies, mode shapes, and modal damping ratios. Physical modal testing of the entire vehicle body was conducted using a vibration method. The test object was the entire vehicle body assembly (excluding the engine and suspension). The LMS Test.Lab system was used, equipped with a vibrator (hammer or vibration table) and accelerometers. The sensors were placed at 20 key hard points, including the A-pillar and chassis. The process included hammer vibration to acquire response signals, and analysis of overall modes (e.g., torsional, bending) and local modes (e.g., A-pillar vibration). The test obtained the natural frequencies (first order 15.8 Hz, second order 20.7 Hz), corresponding mode shapes (torsional mode has a principal amplitude at the A-pillar), and modal damping ratios (average 0.05). This step, based on actual experimental data, provides a benchmark for subsequent simulation model optimization, ensuring that the test environment complies with standard road durability specifications (e.g., GB / T 25749).

[0028] Step 5: Compare the results of the vehicle body modal simulation analysis with the results of the modal test, adjust and optimize the vehicle body simulation model to the target error range, and output the modal stress, maximum weld stress, and weld joint force. The modal simulation results from step three are compared with the experimental results from step four. For example, the error between the simulated first-order frequency of 15.5 Hz and the tested frequency of 15.8 Hz is 1.9%, and the error between the second-order frequency of 20.5 Hz and 20.7 Hz is 1%, both less than the target threshold of 8%. Therefore, no major adjustments are needed; only the material damping parameters are fine-tuned (increased by 0.01 to match the damping ratio). After optimization, the model proceeds to the next step of transient analysis and outputs key data: modal stress (maximum 190 MPa for column A), maximum weld stress of 140 MPa, and weld joint forces (tensile force 45 N, shear force 25 N). This step ensures the accuracy of the simulation model, reduces errors caused by differences in engineer capabilities, and improves overall analysis efficiency.

[0029] Step Six: Collect acceleration signals at each hard point according to the channel sequence of the load spectrum, process the data to convert them into displacement signals, and use them as input for fatigue durability simulation analysis. Real-world road spectrum testing was conducted based on actual road conditions (such as urban roads, highways, and off-road tracks). Accelerometers were installed at 10 hard points, including the A-pillar and chassis, and time-domain signals were collected in channel sequence (X, Y, Z directions) (sampling rate 1000 Hz, 10 minutes per road condition, see reference document). Figure 3 (Signal shown). Data processing includes: first, zero-drift processing (baseline correction); then, quadratic integration to convert to velocity and displacement signals; and finally, high-pass filtering (cutoff frequency 0.5 Hz) to remove low-frequency drift. The resulting displacement signals serve as inputs for fatigue durability simulation, replacing traditional road spectrum testing, reducing costs and shortening the cycle time.

[0030] Step 7: Based on the vehicle body simulation model, apply forced displacements in the X, Y, and Z directions to each hard point to complete the transient analysis and output the modal coordinates. Based on the optimized finite element model of the vehicle body, transient analysis was performed using the ANSYS Transient module. Forced displacement loads in the X, Y, and Z directions were applied to each hard point with a time step of 0.001 s and a total analysis time of 600 s. The analysis considered only the low-order modes (0-50 Hz, the first 10 modes) to cover the main vibration energy, without calculating all modes. Modal coordinates were output, for example, the first-order displacement modal coefficient was 0.70, and the second-order was 0.50 (thickness reduction slightly increased the response). This step simulated the vehicle body response under dynamic loads, providing basic data for subsequent fatigue analysis.

[0031] Step 8: Construct a fatigue durability analysis workflow using modal stress, modal coordinates, and the material elastic-plastic curves of the thermoforming material to calculate the damage to body parts, welds, and weld joints. A fatigue durability analysis workflow was built using nCode or the ANSYS Fatigue module. Inputs included the modal stresses from step five, the modal coordinates from step seven, and the elastic-plastic curve of the thermoformed material. The rainflow counting method was used to count stress cycles, and the Miner linear cumulative damage rule was used to calculate damage values: 0.50 for A-pillar components, 0.30 for weld damage, and 0.20 for weld point damage. This workflow comprehensively considers the material's fatigue characteristics to ensure analytical accuracy.

[0032] Step 9: Evaluate the damage value of the vehicle body based on the simulation results. If the damage value is greater than 1, further optimization is needed until the simulation results meet the actual requirements. The simulation results from step eight were evaluated as follows: Damage values ​​for the A-pillar component (0.50), weld (0.30), and weld point (0.20) were all less than the threshold of 1, indicating no risk of fatigue failure and meeting actual durability requirements. Therefore, no further optimization is needed. If the damage value exceeds 1, it can be recalculated by increasing the thickness by 0.1 mm or adjusting the weld design until all damage values ​​are less than 1. This evaluation forms a closed loop, ensuring reliable fatigue durability performance of the vehicle body.

[0033] Step 10: Based on the simulation analysis results, confirm the material thickness of the thermoformed parts, calculate the vehicle body lightweighting rate, and complete the construction of the cost analysis model. Based on the fatigue durability simulation analysis results in step nine, it was confirmed that the damage values ​​of the thermoformed A-pillar parts under the target working conditions were all less than 1, which met the requirements for structural strength and durability. Therefore, the material thickness was no longer adjusted, and the target material thickness of the thermoformed A-pillar parts was finally determined to be t2 = 1.6 mm.

[0034] (1) Calculation of vehicle body lightweighting rate The vehicle body lightweight ratio is calculated using the following formula: ;

[0035] in, t1 is the original material thickness of the non-thermoformed part. t2 is the final material thickness of the thermoformed part.

[0036] Substituting the parameters from this embodiment into the above formula yields: ;

[0037] Therefore, by replacing the DP600 dual-phase steel A-pillar parts with 22MnB5 hot-formed steel parts, an equivalent weight reduction rate of about 25% was achieved without compromising structural performance, significantly reducing the body structural weight.

[0038] (2) Single-part cost analysis model In cost analysis, a single-part cost model is established by comprehensively considering factors such as changes in part weight, unit price of materials, and material utilization rate.

[0039] The formula for calculating the vehicle body lightweight ratio is: ;

[0040] Where P1 is the unit price of non-hot-formed steel plate, P2 is the unit price of hot-formed material, and r is the material utilization rate of the part.

[0041] Assuming the original non-thermoformed A-pillar part weighed 3.0 kg, after thermoforming, due to the reduction in material thickness, its weight is reduced to 2.4 kg; The unit price of non-hot-formed steel material is P1 = 5 yuan / kg. The unit price of hot-formed steel is P2 = 8 yuan / kg. The material utilization rate is r = 0.75 The calculation results of the vehicle body lightweighting rate formula are as follows: ; The material cost of the original non-thermoformed parts is: C1 = 3.0 * 5 / 0.75 = 20 yuan The material cost of thermoformed parts is: C2 = 2.4 * 8 = 19.2 yuan Considering that thermoformed parts can reduce the number of local reinforcing plates, overlapping structures, and welding points in structural design, thereby reducing additional material and assembly costs, in this embodiment, based on a reduction of 10-12 yuan per part in additional structure and manufacturing costs, the comprehensive equivalent cost of the thermoformed A-pillar part is: C2′≈7.2~9.2 yuan It can be seen that (1) the equivalent lightweighting rate of 25% is greater than the result of the above formula of 20%, indicating that the cost of replacing with thermoforming materials is reduced; and after comprehensively considering the structural integration benefits, the comprehensive cost of thermoforming A-pillar parts is lower than the cost of the original non-thermoforming parts, thus achieving synergistic optimization of lightweighting and cost reduction.

[0042] (3) Economic evaluation at the vehicle level Furthermore, if the above-mentioned equivalent replacement scheme is applied to 10 similar high-strength structural parts in the vehicle, the overall vehicle weight can be reduced by approximately 6 kg. Combined with the vehicle energy consumption empirical model, the reduction in vehicle weight can lead to a reduction in fuel consumption of approximately 0.02–0.04 L / 100 km, thereby further reducing operating costs over the entire vehicle life cycle.

[0043] Through the above steps, the material thickness of hot-formed parts was confirmed, the lightweighting rate was calculated, and the cost analysis model was constructed, providing a quantitative basis for the engineering application of equivalent replacement schemes for high-strength steel in automobile bodies and for early-stage project decision-making.

[0044] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for analyzing the equivalent replacement and fatigue durability of high-strength steel in automobile bodies, characterized in that, Includes the following steps: S1. The thickness of the thermoformed parts is obtained by performing equal strength replacement calculations on the non-thermoformed parts of the base vehicle using the equal strength replacement formula for deformation resistance and the equal strength replacement formula for energy absorption. S2. Input the material thickness, material information, weld information, weld point information, and bolt connection information obtained in step S1 into the vehicle body CAD model; S3. Based on the vehicle body CAD model from step S2, establish a finite element model of the entire vehicle body and perform modal analysis; S4. Perform modal testing on the actual vehicle body and compare it with the modal simulation results in step S3. If the error is ≤8%, output the modal stress, maximum stress of the weld, and nodal force of the weld point. S5. Acceleration signals at various hard points are collected during the actual vehicle road durability test and converted into displacement signals after processing; S6. Apply the displacement signal obtained in step S5 to the finite element model after calibration in step S4 to perform transient analysis and output modal coordinates; S7. Using the modal stress output in step S4, the modal coordinates output in step S6, and the material elastic-plastic curve of the thermoforming material, fatigue durability analysis is performed to obtain the damage values ​​of the body parts, welds, and weld points, and the structure is optimized with the damage value ≤1 as the target. S8. Fine-tune the thickness of the thermoformed parts according to the optimized structure in step S7, and calculate the weight reduction rate and cost change after replacement based on the weight reduction rate formula.

2. The method for equivalent replacement and fatigue durability performance analysis of high-strength steel in automobile bodies according to claim 1, characterized in that, In step S1; The deformation resistance and equal strength replacement formula: ; The energy absorption intensity substitution formula: ; Where t1, R1, and E1 are the material thickness, yield strength, and tensile strength of the replaced non-thermoformed part, respectively, and t2, R2, and E2 are the material thickness, yield strength, and tensile strength of the thermoformed part, respectively.

3. The method for equivalent replacement and fatigue durability analysis of high-strength steel in automobile bodies according to claim 2, characterized in that, In step S2, the vehicle body CAD model contains complete material information, weld information, weld point information, and bolt connection information.

4. The method for equivalent replacement and fatigue durability analysis of high-strength steel in automobile bodies according to claim 3, characterized in that, In step S3, the specific steps for establishing the finite element model of the entire vehicle body include: Step S31. Divide the vehicle body parts into meshes; Step S32. Establish weld seams, weld points, bolt connections, and adhesive connections, wherein weld points are simulated using ACM welding; Step S33. Assign thickness and corresponding material properties to each part; Step S34. Assign vehicle weights according to actual curb weight requirements; Step S35. Based on this, perform modal analysis.

5. The method for equivalent replacement and fatigue durability analysis of high-strength steel in automobile bodies according to claim 4, characterized in that, In step S4, the modal test uses the excitation method to test the overall mode and main local modes of the vehicle body assembly, and obtains the natural frequency, corresponding damping ratio and mode shape; the benchmark error between the modal simulation results and the modal test results is ≤8%.

6. The method for equivalent replacement and fatigue durability performance analysis of high-strength steel in automobile bodies according to claim 5, characterized in that, In step S5, the specific steps for processing the acquired acceleration signal include: first performing zero drift processing, then performing a second integration to obtain the displacement signal, and finally performing high-pass filtering to remove the low-frequency drift generated by the integration, thus obtaining the final vibration displacement signal.

7. The method for equivalent replacement and fatigue durability performance analysis of high-strength steel in automobile bodies according to claim 6, characterized in that, In step S6, the transient analysis only considers low-order modes in the range of 0 to 50 Hz.

8. The method for equivalent replacement and fatigue durability performance analysis of high-strength steel in automobile bodies according to claim 7, characterized in that, In step S8, the formula for calculating the lightweight ratio is: Where P1 is the unit price of non-hot-formed steel sheet, P2 is the unit price of hot-formed material, and r is the material utilization rate of the part; when the lightweighting rate is greater than the result calculated by the above formula, it indicates that the cost of replacing with hot-formed material is reduced.

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