A method, system and apparatus for strengthening steel material for automotive chassis

Abstract

The application discloses a steel material strengthening treatment method, system and equipment for an automobile chassis, and relates to the technical field of metal material processing in automobile manufacturing. The method comprises the following steps: obtaining a three-dimensional dislocation density distribution field of the steel material after cold stamping forming; inputting the three-dimensional dislocation density distribution field as an initial condition into a pre-established multi-physical field collaborative control model, solving a multi-objective optimization function of the model, and generating a corresponding composite electromagnetic pulse control sequence; and applying the composite electromagnetic pulse control sequence to the steel material, and performing differential aging treatment on the micro areas with different dislocation densities in the steel material through electromagnetic induction. The application solves the problems of strength-ductility imbalance and uneven performance caused by the fact that the traditional uniform heat treatment cannot adapt to the uneven deformation of the steel material, improves the mechanical property consistency, strength-ductility synergy and batch production stability of the automobile chassis parts by means of digital mapping of the deformation history of the steel material, intelligent regulation and control of the multi-physical field, accurate execution of the pulse sequence and real-time feedback correction.

Description

Technical Field

[0001] This invention relates to the field of metal material processing technology in automobile manufacturing, and specifically to a method, system and equipment for strengthening steel for automobile chassis. Background Technology

[0002] In the contemporary automotive manufacturing industry, lightweighting and crash safety are two core development directions. To simultaneously meet these two demands, advanced high-strength steel (AHSS) and ultra-high-strength steel (UHSS), with their excellent combination of strength and toughness, are increasingly widely used in key structural components such as automotive chassis and body frames. These high-toughness steels typically need to be formed into parts with complex three-dimensional surfaces through cold stamping. Cold stamping, as an efficient plastic forming method, not only imparts the required geometry to the parts but also enhances the material strength through work hardening. However, its inherent process characteristics also bring significant technical challenges.

[0003] During cold stamping, steel undergoes intense plastic deformation, introducing a large number of dislocations that form a highly entangled microstructure. Dislocation proliferation and entanglement are the core mechanism of work hardening, significantly increasing material strength but also drastically reducing toughness and plasticity reserves. This is particularly pronounced in areas of severe plastic deformation, such as large-curvature bends and drawn corners, where dislocation density is extremely high and toughness loss is even more significant. This uneven mechanical properties across different regions of the part due to variations in deformation history, and the irreconcilable conflict between strength and toughness, directly restrict the service reliability of components and the collision safety of the entire vehicle.

[0004] To address these issues, existing technologies typically add a heat treatment process after cold stamping, such as bake hardening or low-temperature artificial aging. The core idea behind these heat treatment methods is to activate atomic diffusion through thermal energy, prompting the formation of nanoscale precipitates within the material to further enhance strength. Simultaneously, some dislocations recover and reconfigure, thereby restoring toughness to some extent. However, traditional heat treatment methods employ a holistic approach, placing the entire component in a uniform thermal field, which fails to identify the highly uneven microstructure formed within the part during the stamping process.

[0005] This uniform treatment approach has significant drawbacks: for regions with small deformation and low dislocation density, excessive heat treatment can lead to unnecessary softening of the material, reducing strength reserves; while for critical regions with large deformation and high dislocation density, the heat treatment intensity is often insufficient, making it difficult to fully disentangle dislocations and restore toughness. Ultimately, the overall performance of the part remains limited by its weakest link, failing to achieve synergistic optimization of strength and toughness, and making it difficult to guarantee the consistency of part performance and process stability under mass production. This severely restricts the application potential of high-toughness steel in key structural components of automotive chassis.

[0006] Therefore, there is an urgent need to propose a technical method that can adapt to the deformation history of parts and achieve precise and differentiated strengthening in order to solve the problems of strength and toughness imbalance and performance inconsistency caused by traditional heat treatment. Summary of the Invention

[0007] To overcome the shortcomings of existing integral heat treatment methods that cannot precisely control the uneven deformation history inside parts, this application proposes a steel strengthening treatment method, system, and equipment for automotive chassis. It can perform differentiated and adaptive electromagnetic pulse aging treatment based on the spatial distribution of the microscopic damage state inside the material after cold stamping, thereby synergistically optimizing the strength and toughness of the parts and improving the uniformity and consistency of their overall performance.

[0008] To achieve the aforementioned objectives, the present invention adopts the following technical solution:

[0009] In a first aspect, the present invention provides a method for strengthening steel for automobile chassis, the method comprising:

[0010] Obtain the three-dimensional dislocation density distribution field of steel after cold stamping;

[0011] Using the three-dimensional dislocation density distribution field as the initial condition, a pre-established multi-physics field cooperative control model is input, the multi-objective optimization function of the model is solved, and a composite electromagnetic pulse control sequence corresponding to the three-dimensional dislocation density distribution field is generated.

[0012] The composite electromagnetic pulse control sequence is applied to the steel, and the micro-regions with different dislocation densities inside the steel are subjected to differentiated aging treatment through electromagnetic induction.

[0013] Optionally, obtaining the three-dimensional dislocation density distribution field of the steel after cold stamping includes:

[0014] The cold stamping process of the steel was numerically simulated using finite element analysis to obtain a three-dimensional equivalent plastic strain field.

[0015] The dislocation evolution constitutive model corresponding to the steel was determined by experimental calibration.

[0016] Based on the dislocation evolution constitutive model, a correlation function between three-dimensional equivalent plastic strain and dislocation density is established;

[0017] By substituting the strain data of each region in the three-dimensional equivalent plastic strain field into the correlation function, the three-dimensional dislocation density distribution field inside the steel is obtained through calculation.

[0018] Optionally, the pre-construction of the multi-physics collaborative control model includes: constructing a multi-objective optimization function with the objectives of maximizing the weighted strength-toughness product of the parts and minimizing the performance inhomogeneity of the parts, as shown in the following equation:

[0019] ;

[0020] in, U represents a multi-objective optimization function. (t) The sequence is a composite electromagnetic pulse control sequence, where V is the volume of the part and t is the volume of the part. f To handle the end time, σ y For yield strength, K IC For fracture toughness, w σ and w K All are weighting coefficients set based on the design requirements of the chassis suspension arm, λ is the penalty coefficient, and Var[・] is the variance function used to characterize the non-uniformity of the component performance;

[0021] Using the three-dimensional dislocation density distribution field as the initial condition, the multi-objective optimization function is solved to calculate and generate an initial composite electromagnetic pulse control sequence, which contains instructions on the pulse frequency, intensity, and shape changing over time.

[0022] Optionally, the composite electromagnetic pulse control sequence includes: dynamic modulation of the electromagnetic pulse frequency; and, based on the skin effect, adjusting the pulse frequency to control the injection depth of electromagnetic energy in the thickness direction of the steel, so that the injection depth of electromagnetic energy matches the distribution characteristics of the three-dimensional dislocation density distribution field in the depth direction, for different distributions of the three-dimensional dislocation density distribution field in the depth direction.

[0023] Optionally, the composite electromagnetic pulse control sequence further includes: dynamically modulating the electromagnetic pulse shape by alternately or in combination applying thermal effect-dominant pulses and non-thermal effect-dominant pulses;

[0024] The parameters of the thermal effect-dominant pulse are set to induce atomic diffusion, and the parameters of the non-thermal effect-dominant pulse are set to promote dislocation motion.

[0025] The non-thermal effect dominant pulse is a pulse with instantaneous, high peak current density.

[0026] Optionally, the multiphysics collaborative control model includes: a multiphysics interaction model; the multiphysics interaction model models the resistivity and permeability of the steel as functions of the dislocation density in the three-dimensional dislocation density distribution field, and then constructs the correlation between the micro-dislocation density and the macro-electromagnetic properties based on the functional relationship.

[0027] Optionally, the application of the composite electromagnetic pulse control sequence includes: an online closed-loop feedback correction process;

[0028] The online closed-loop feedback correction process includes: during the application of electromagnetic pulses, real-time monitoring of the equivalent complex impedance of the electromagnetic coil-part system, and using the equivalent complex impedance as a global feedback signal reflecting the evolution state of the internal microstructure of the steel.

[0029] Optionally, the online closed-loop feedback correction process further includes:

[0030] The real-time monitored equivalent complex impedance is compared with the predicted impedance calculated by the multi-physics field cooperative control model.

[0031] When the deviation between the two exceeds the preset threshold, the actual state of the steel obtained by inversion of the equivalent complex impedance under real-time monitoring is used as the new initial condition, and the subsequent composite electromagnetic pulse control sequence is recalculated and corrected online.

[0032] In a second aspect, the present invention provides a steel strengthening treatment system for an automobile chassis for implementing the method as described in any one of the first aspects, comprising:

[0033] The information acquisition module is used to acquire the three-dimensional dislocation density distribution field of steel after cold stamping.

[0034] The calculation and generation module is used to take the three-dimensional dislocation density distribution field as the initial condition, input a pre-established multi-physics field cooperative control model, solve the multi-objective optimization function of the model, and generate a composite electromagnetic pulse control sequence corresponding to the three-dimensional dislocation density distribution field.

[0035] The strengthening processing module is used to apply the composite electromagnetic pulse control sequence to the steel and perform differentiated aging treatment on the micro-regions with different dislocation densities inside the steel through electromagnetic induction.

[0036] Thirdly, the present invention provides an electronic device, the electronic device comprising:

[0037] At least one processor; and,

[0038] A memory communicatively connected to the at least one processor; wherein,

[0039] The memory stores a computer program that can be executed by the at least one processor to enable the at least one processor to perform the method described in any of the first aspects.

[0040] Compared with the closest existing technology, the present invention has the following advantages:

[0041] This invention proposes a method, system, and equipment for strengthening steel for automobile chassis. By acquiring a three-dimensional dislocation density distribution field, it accurately identifies the deformation history and micro-damage state of different regions inside the steel. Based on this distribution field, it generates a customized composite electromagnetic pulse control sequence, enabling the aging treatment to be specifically adapted to the dislocation density characteristics of each region. This solves the problems of over-treatment or under-treatment in traditional homogenization heat treatment, and achieves synergistic optimization of steel strength and toughness.

[0042] This invention uses the three-dimensional dislocation density distribution field of cold-stamped steel as the initial condition for aging treatment, and constructs a digital correlation between the deformation process and aging treatment. This breaks through the isolated processing mode of the two in the prior art, realizes deep synergy between deformation strengthening and aging strengthening, and improves the scientificity and precision of the strengthening process.

[0043] Furthermore, by using a multi-objective optimization function to achieve the dual objectives of maximizing the strength product and homogenizing performance, and combined with an online closed-loop feedback correction process, the strengthening deviation is corrected in real time, effectively overcoming the influence of uncertain factors in the production process and significantly improving the consistency of part performance and process stability under mass production.

[0044] This invention is applicable to the strengthening treatment of steel used in key structural components of various automobile chassis. It is not limited by the shape or deformation distribution of the parts, and does not require major modifications to the existing production process, making it easy to promote and apply in industrial applications. Attached Figure Description

[0045] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0046] Figure 1 This is a flowchart of a steel strengthening treatment method for automobile chassis provided by the present invention;

[0047] Figure 2 This is a structural block diagram of a steel strengthening treatment system for automobile chassis according to an embodiment of the present invention;

[0048] Figure 3 This is an internal structural diagram of the electronic device provided by the present invention. Detailed Implementation

[0049] The embodiments of the technical solution of the present invention will now be described in detail with reference to the accompanying drawings. These embodiments are only used to more clearly illustrate the technical solution of the present invention and are therefore merely examples, and should not be construed as limiting the scope of protection of the present invention.

[0050] It should be noted that, unless otherwise stated, the technical or scientific terms used in this application should have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0051] This invention provides a method, system, and equipment for strengthening steel for automobile chassis, particularly suitable for the precise strengthening of steel used in key structural components such as suspension arms, crossbeams, and longitudinal beams of automobile chassis after cold stamping. The aim is to achieve synergistic optimization of steel strength and toughness through differentiated aging treatment, thereby improving the reliability of parts.

[0052] Please refer to Figure 1 , Figure 1 Embodiment 1 of the present invention provides a method for strengthening steel for automobile chassis, the method specifically including the following steps:

[0053] S101, obtain the three-dimensional dislocation density distribution field of steel after cold stamping;

[0054] S102, taking the three-dimensional dislocation density distribution field as the initial condition, inputting a pre-established multi-physics field cooperative control model, solving the multi-objective optimization function of the model, and generating a composite electromagnetic pulse control sequence corresponding to the three-dimensional dislocation density distribution field;

[0055] S103, the composite electromagnetic pulse control sequence is applied to the steel, and the micro-regions with different dislocation densities inside the steel are subjected to differentiated aging treatment through electromagnetic induction.

[0056] In step S101 above, obtaining the three-dimensional dislocation density distribution field of the steel after cold stamping specifically includes the following steps:

[0057] a) Numerical simulation of the cold stamping process of the steel is performed using finite element analysis to obtain the three-dimensional equivalent plastic strain field of the steel; b) The steel is experimentally calibrated to determine the corresponding dislocation evolution constitutive model; c) Based on the dislocation evolution constitutive model, a correlation function between the three-dimensional equivalent plastic strain and the dislocation density is established; d) The strain data of each region in the three-dimensional equivalent plastic strain field are substituted into the correlation function one by one to calculate the three-dimensional dislocation density distribution field inside the steel.

[0058] In step a), the input parameters for the finite element analysis include the initial mechanical properties of the steel (such as yield strength, tensile strength, elastic modulus, etc.), the material constitutive model, the three-dimensional geometric model of the stamping die, and the stamping process parameters (such as blank holder force, stamping speed, die clearance, etc.). Through numerical simulation, the plastic deformation process of the steel during cold stamping can be accurately reproduced, and a three-dimensional equivalent plastic strain field can be output. This strain field can intuitively reflect the magnitude and distribution characteristics of deformation in different regions of the steel.

[0059] The specific process of experimental calibration in step b) is as follows: Select a sample with the same material as the steel to be treated, and obtain dislocation density data of the sample under different deformations through tensile tests, hardness tests, transmission electron microscopy, and other means. Based on this data, a dislocation evolution constitutive model that can describe the dislocation proliferation, entanglement and evolution law of steel is obtained to ensure that the model matches the actual microscopic evolution characteristics of steel.

[0060] In step c), the establishment of the correlation function is based on the dislocation evolution constitutive model. The function form and parameters are determined by fitting experimental data to achieve the quantitative conversion between three-dimensional equivalent plastic strain and dislocation density. In step d), by substituting the data of each region of the strain field into the correlation function one by one, the three-dimensional spatial distribution of dislocation density inside the steel (including the surface, core and different deformation regions) can be obtained, providing accurate initial physical input for subsequent differential processing.

[0061] In step S102 above, the pre-construction of the multiphysics cooperative control model includes the following:

[0062] With the objectives of maximizing the weighted strength-toughness product of parts and minimizing the non-uniformity of part performance, a multi-objective optimization function is constructed as follows:

[0063] ;

[0064] in, U represents a multi-objective optimization function. (t) The sequence is a composite electromagnetic pulse control sequence, where V is the volume of the part and t is the volume of the part. f To handle the end time, σ y For yield strength, K IC For fracture toughness, w σ and w K All are weighting coefficients set based on the design requirements of the chassis suspension arm, λ is the penalty coefficient, and Var[・] is the variance function used to characterize the non-uniformity of the component performance;

[0065] Using the three-dimensional dislocation density distribution field as the initial condition, the above multi-objective optimization function is solved to calculate and generate an initial composite electromagnetic pulse control sequence, which contains instructions on the pulse frequency, intensity, and shape changing over time.

[0066] The core function of the multi-objective optimization function is to achieve the dual objectives of "strength-toughness synergistic optimization" and "performance homogenization": by maximizing the weighted strength-toughness product, it ensures that the overall mechanical properties of the part meet the design requirements; and by using a performance non-uniformity penalty term, it reduces the performance differences between different regions of the part, thereby improving overall consistency. During the solution process, it is necessary to combine the electromagnetic properties of the steel and the evolution of its microstructure to establish a mapping relationship between the control sequence and the performance objectives.

[0067] Furthermore, the composite electromagnetic pulse control sequence includes dynamic modulation of the electromagnetic pulse frequency. Specifically, based on the skin effect, the frequency of the electromagnetic pulse is adjusted to control the injection depth of electromagnetic energy in the thickness direction of the steel, so that the injection depth of electromagnetic energy matches the distribution characteristics of the three-dimensional dislocation density distribution field in the depth direction.

[0068] The skin effect refers to the phenomenon where alternating current concentrates on the surface of a conductor during conduction, and the higher the pulse frequency, the shallower the skin depth of electromagnetic energy. Based on this principle, for regions with high dislocation density on the surface of a three-dimensional dislocation density distribution field, high-frequency pulses are modulated to concentrate electromagnetic energy on the surface, achieving precise strengthening; for regions with high dislocation density in the core, low-frequency pulses are modulated to allow electromagnetic energy to penetrate to the core, ensuring that the strengthening effect covers the entire thickness of the steel.

[0069] Furthermore, the composite electromagnetic pulse control sequence also includes dynamic modulation of the electromagnetic pulse morphology, specifically by applying thermally dominant pulses and non-thermally dominant pulses alternately or in combination. The parameters of the thermally dominant pulses are set to induce atomic diffusion, and the parameters of the non-thermally dominant pulses are set to promote dislocation motion. The non-thermally dominant pulses are instantaneous pulses with high peak current density.

[0070] The thermal effect-dominant pulse employs a low-to-medium frequency sine or square wave to generate Joule heating through electromagnetic induction, raising the local temperature of the steel and activating thermodynamic processes such as atomic diffusion, nanophase precipitation, and dislocation recovery, thus achieving age strengthening. The non-thermal effect-dominant pulse uses a microsecond-level instantaneous pulse with a high peak current density, utilizing the electroplastic effect to lower the energy barrier for dislocation motion without significantly increasing the steel temperature, promoting the dissociation of malignant dislocation entanglements and restoring the steel's toughness. Through the coordinated scheduling of these two pulse types, a precise balance between strength and toughness can be achieved.

[0071] Furthermore, the multiphysics collaborative control model includes a multiphysics interaction model, which models the resistivity and permeability of steel as functions of dislocation density in a three-dimensional dislocation density distribution field, and then constructs the correlation between microscopic dislocation density and macroscopic electromagnetic properties based on this functional relationship.

[0072] The resistivity and permeability of steel are key macroscopic parameters affecting electromagnetic energy absorption and conversion, and these two parameters are directly related to the microscopic dislocation density: the higher the dislocation density, the more severe the lattice distortion inside the steel, the greater the resistivity, and the corresponding change in permeability. By establishing resistivity-dislocation density functions and permeability-dislocation density functions, a quantitative correlation between microstructure and macroscopic electromagnetic response can be achieved. This enables multi-physics collaborative control models to accurately predict the electromagnetic energy absorption efficiency of different regions of steel based on the three-dimensional dislocation density distribution field, providing a physical basis for the generation of composite electromagnetic pulse control sequences.

[0073] Furthermore, the process of applying the composite electromagnetic pulse control sequence includes an online closed-loop feedback correction process, which specifically includes:

[0074] During the application of electromagnetic pulses, the equivalent complex impedance of the electromagnetic coil-part system is monitored in real time, and the equivalent complex impedance is used as a global feedback signal reflecting the evolution of the internal microstructure of the steel.

[0075] The equivalent complex impedance monitored in real time is compared with the predicted impedance calculated by the multi-physics field cooperative control model.

[0076] When the deviation between the two exceeds the preset threshold, the actual state of the steel obtained by inversion of the equivalent complex impedance under real-time monitoring is used as the new initial condition, and the subsequent composite electromagnetic pulse control sequence is recalculated and corrected online.

[0077] Equivalent complex impedance is a macroscopic comprehensive response to the evolution of the internal microstructure of steel (dislocation density, precipitate state, lattice distortion, etc.), and can sensitively reflect changes in the microstructure of steel during the strengthening process. By monitoring the equivalent complex impedance in real time and comparing it with the model-predicted impedance, strengthening deviations caused by batch differences in incoming materials, tooling positioning errors, environmental factors, etc., can be detected in a timely manner. When the deviation exceeds a threshold, the current actual microstructure of the steel is obtained by inverting the equivalent complex impedance, the multi-objective optimization function is resolved, and a corrected control sequence is generated to ensure that the strengthening process always proceeds along the optimal path, thereby improving process robustness and batch production stability.

[0078] Example 1: This Example 1 provides a method for strengthening steel used in automotive chassis suspension arms. The steel to be strengthened is high-strength steel specifically for automotive chassis suspension arms. The specific steps are as follows:

[0079] Step 1: Obtain the three-dimensional dislocation density distribution field of the steel after cold stamping;

[0080] 1.1 Finite Element Simulation of Cold Stamping Process: Finite element analysis software such as ABAQUS and LS-DYNA were used to numerically simulate the cold stamping forming process of the cantilever arm. The simulation input parameters included: initial mechanical properties of the steel (yield strength, tensile strength, elastic modulus), the Johnson-Cook material constitutive model, the three-dimensional CAD model of the stamping die (punch, die, blank holder), and stamping process parameters (such as blank holder force, stamping speed, and die clearance). The simulation output yielded the three-dimensional equivalent plastic strain field of the formed cantilever arm steel.

[0081] 1.2 Experimental Standard Dislocation Evolution Constitutive Model: Standard specimens of the same material as the cantilever steel were selected and tensile tests were conducted with different deformations. The dislocation morphology of each specimen was then observed by transmission electron microscopy, and the dislocation density was measured by X-ray diffraction. Based on the experimental data, the Kocks-Mecking dislocation evolution constitutive model of the steel was fitted. This model can accurately describe the evolution relationship between deformation and dislocation density.

[0082] 1.3 Establishing the correlation function and transforming it into a three-dimensional dislocation density distribution field: Based on the above Kocks-Mecking dislocation evolution constitutive model, the three-dimensional equivalent plastic strain (PEEQ) field is obtained by fitting using the least squares method, denoted as... This strain field directly reflects the degree of plastic deformation experienced at different locations of the part. To more directly correlate it with the microscopic strengthening mechanism of the material, it needs to be transformed into microstructural parameters. Therefore, based on the Kocks-Mecking dislocation evolution constitutive model, the three-dimensional equivalent plastic strain field is further transformed into... Transformed into the initial three-dimensional dislocation density distribution field The transformation relationship is as follows:

[0083] ;

[0084] in, This represents the constitutive function used to describe the work hardening behavior of materials. This function is obtained through experimental calibration, and the final obtained initial three-dimensional dislocation density distribution field is... This three-dimensional dislocation density distribution field can accurately record the spatial distribution of microscopic damage and work hardening caused by deformation inside the part, providing key initial conditions for subsequent differentiated and adaptive processing.

[0085] The strain data of each region in the three-dimensional equivalent plastic strain field obtained in step 1.1 are substituted into the correlation function one by one, and the three-dimensional dislocation density distribution field inside the cantilever steel is calculated by MATLAB software. The distribution field shows that the dislocation density is the highest in the bending angle region of the cantilever and the lowest in the core region.

[0086] Step 2: Construct a multi-physics field cooperative control model and generate a composite electromagnetic pulse control sequence;

[0087] 2.1 Constructing a multi-objective optimization function: Based on the design requirements of the automotive chassis suspension arm, weighting coefficients are set: yield strength weight w σ Fracture toughness weight w K Penalty coefficient λ, construct a multi-objective optimization function:

[0088] ;

[0089] in, U represents a multi-objective optimization function. (t) The sequence is a composite electromagnetic pulse control sequence, where V is the volume of the part and t is the volume of the part. f To handle the end time, σ y For yield strength, K IC For fracture toughness, w σ and w K All are weighting coefficients set based on the design requirements of the chassis suspension arm, λ is the penalty coefficient, and Var[・] is the variance function used to characterize the non-uniformity of the component performance;

[0090] 2.2 Constructing a multiphysics interaction model: The resistivity and permeability of the steel under different dislocation densities were experimentally measured, and the resistivity-dislocation density function R was established. e (ρ) and permeability-dislocation density function μ r (ρ) establishes the correlation between microscopic dislocation density and macroscopic electromagnetic properties.

[0091] 2.3 Solving the Optimization Function to Generate the Control Sequence: Using the three-dimensional dislocation density distribution field obtained in step 1.3 as the initial condition, the particle swarm optimization algorithm is used to solve the above multi-objective optimization function to generate a composite electromagnetic pulse control sequence. In this sequence, for the high-potential dislocation density region at the bend, high-frequency modulation pulses and non-thermal effect dominant pulses are applied alternately; for the low-potential dislocation density region in the core, low-frequency modulation pulses and thermal effect dominant pulses are applied in combination, and the pulse intensity and duration are dynamically adjusted with time.

[0092] Step 3: Apply composite electromagnetic pulse and perform online closed-loop feedback correction. 3.1 Equipment setup: Place the cold-stamped cantilever part into a multi-region broadband electromagnetic coil system. This system can generate electromagnetic pulses with dynamically modulated frequency, intensity, and shape according to the input composite electromagnetic pulse control sequence.

[0093] Specifically, cold-stamped parts are placed in a multi-zone, broadband electromagnetic coil system, which can respond to input control sequences. It generates composite electromagnetic pulses whose frequency, intensity, and shape can be dynamically modulated, and then initiates an online closed-loop feedback correction process. The core of this process is that it does not blindly execute a pre-calculated initial control sequence. Instead, it adaptively adjusts the sequence based on the actual response of the component during processing. During the application of electromagnetic pulses, the equivalent complex impedance of the entire electromagnetic coil-component system is monitored in real time and at high frequency using high-precision measuring equipment. Since the macroscopic electromagnetic properties of a component are the integral response of the evolution of all its internal microscopic structural states (including dislocation density, precipitate state, etc.), this equivalent complex impedance... It can serve as a precise, sensitive, and real-time global feedback signal. Simultaneously, the multiphysics cooperative control model calculates, in real-time, the predicted impedance of the system under ideal conditions based on the applied pulse sequence. The control system will monitor in real time. Compared with the prediction Compare and calculate the deviation between the two. ;

[0094] When this deviation When the preset tolerance threshold is exceeded, it indicates that the actual microstructure evolution rate of the part does not match the model's prediction (this may stem from uncertainties in actual working conditions, such as batch differences in incoming materials or placement errors of the part in the tooling). At this point, the system will trigger an online replanning: it will recalculate the current actual state (which can be accessed via...). The result (obtained through inversion) is used as a new initial condition. The processing procedure for the remaining time period is then immediately recalculated to generate a corrected composite electromagnetic pulse control sequence. The control system then seamlessly switched to this revised new sequence. Continue processing and continuously execute the closed-loop cycle of "prediction-execution-measurement-correction" until the entire processing is completed.

[0095] Example 2: Based on the same inventive concept, this application also provides a steel strengthening treatment system for an automobile chassis to implement the above method. The solution provided by this system is similar to the solution described in the above embodiment. Therefore, the specific limitations of one or more system embodiments provided below can be found in the above-described limitations of a steel strengthening treatment method for an automobile chassis, and will not be repeated here.

[0096] In one embodiment, Embodiment 2 of the present invention provides a steel strengthening treatment system for an automobile chassis, the system as follows: Figure 2 As shown, it includes: an information acquisition module 210, a calculation and generation module 220, and a reinforcement processing module 230, wherein:

[0097] Information acquisition module 210 is used to acquire the three-dimensional dislocation density distribution field of steel after cold stamping.

[0098] The calculation and generation module 220 is used to take the three-dimensional dislocation density distribution field as the initial condition, input a pre-established multi-physics field cooperative control model, solve the multi-objective optimization function of the model, and generate a composite electromagnetic pulse control sequence corresponding to the three-dimensional dislocation density distribution field.

[0099] The strengthening processing module 230 is used to apply the composite electromagnetic pulse control sequence to the steel and perform differentiated aging treatment on the micro-regions with different dislocation densities inside the steel through electromagnetic induction.

[0100] The various modules of the system in the above embodiments work together to automate and intelligently strengthen the steel, ensuring the accuracy and stability of the strengthening effect.

[0101] In one embodiment, an electronic device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 3 As shown. The electronic device includes a processor, memory, communication interface, display screen, and input device connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements the steel strengthening treatment method for an automobile chassis as described in any one of steps S101 to S103. The display screen can be a liquid crystal display (LCD) or an e-ink display. The input device can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the device's casing, or an external keyboard, touchpad, or mouse.

[0102] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0103] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0104] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0105] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0106] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0107] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of the claims of the present invention pending approval.

Claims

1. A method for strengthening steel for automobile chassis, characterized in that, The method includes: Obtain the three-dimensional dislocation density distribution field of steel after cold stamping; Using the three-dimensional dislocation density distribution field as the initial condition, a pre-established multi-physics field cooperative control model is input, the multi-objective optimization function of the model is solved, and a composite electromagnetic pulse control sequence corresponding to the three-dimensional dislocation density distribution field is generated. The composite electromagnetic pulse control sequence is applied to the steel, and the micro-regions with different dislocation densities inside the steel are subjected to differentiated aging treatment through electromagnetic induction.

2. The method according to claim 1, characterized in that, The process of obtaining the three-dimensional dislocation density distribution field of the steel after cold stamping includes: The cold stamping process of the steel was numerically simulated using finite element analysis to obtain a three-dimensional equivalent plastic strain field. The dislocation evolution constitutive model corresponding to the steel was determined by experimental calibration. Based on the dislocation evolution constitutive model, a correlation function between three-dimensional equivalent plastic strain and dislocation density is established; By substituting the strain data of each region in the three-dimensional equivalent plastic strain field into the correlation function, the three-dimensional dislocation density distribution field inside the steel is obtained through calculation.

3. The method according to claim 1, characterized in that, The pre-construction of the multiphysics collaborative control model includes: constructing a multi-objective optimization function with the objectives of maximizing the weighted strength-toughness product of the parts and minimizing the performance inhomogeneity of the parts, as shown in the following equation: ； in, U represents a multi-objective optimization function. (t) The sequence is a composite electromagnetic pulse control sequence, where V is the volume of the part and t is the volume of the part. f To handle the end time, σ y For yield strength, K IC For fracture toughness, w σ and w K All are weighting coefficients set based on the design requirements of the chassis suspension arm, λ is the penalty coefficient, and Var[・] is the variance function used to characterize the non-uniformity of the component performance; Using the three-dimensional dislocation density distribution field as the initial condition, the multi-objective optimization function is solved to calculate and generate an initial composite electromagnetic pulse control sequence, which contains instructions on the pulse frequency, intensity, and shape changing over time.

4. The method according to claim 1, characterized in that, The composite electromagnetic pulse control sequence includes: dynamic modulation of the electromagnetic pulse frequency; based on the skin effect, adjusting the pulse frequency to control the injection depth of electromagnetic energy in the thickness direction of the steel, so that the injection depth of electromagnetic energy matches the distribution characteristics of the three-dimensional dislocation density distribution field in the depth direction, for different distributions of the three-dimensional dislocation density distribution field in the depth direction.

5. The method according to claim 4, characterized in that, The composite electromagnetic pulse control sequence further includes: dynamically modulating the electromagnetic pulse shape, and applying thermal effect-dominant pulses and non-thermal effect-dominant pulses alternately or in combination; The parameters of the thermal effect-dominant pulse are set to induce atomic diffusion, and the parameters of the non-thermal effect-dominant pulse are set to promote dislocation motion. The non-thermal effect dominant pulse is a pulse with instantaneous, high peak current density.

6. The method according to claim 5, characterized in that, The multiphysics collaborative control model includes a multiphysics interaction model. The multiphysics interaction model models the resistivity and permeability of the steel as functions of the dislocation density in the three-dimensional dislocation density distribution field, and then constructs the correlation between the micro-dislocation density and the macro-electromagnetic properties based on this functional relationship.

7. The method according to claim 1, characterized in that, The applied composite electromagnetic pulse control sequence includes: an online closed-loop feedback correction process; The online closed-loop feedback correction process includes: during the application of electromagnetic pulses, real-time monitoring of the equivalent complex impedance of the electromagnetic coil-part system, and using the equivalent complex impedance as a global feedback signal reflecting the evolution state of the internal microstructure of the steel.

8. The method according to claim 7, characterized in that, The online closed-loop feedback correction process also includes: The real-time monitored equivalent complex impedance is compared with the predicted impedance calculated by the multi-physics field cooperative control model. When the deviation between the two exceeds the preset threshold, the actual state of the steel obtained by inverting the equivalent complex impedance under real-time monitoring is used as the new initial condition, and the subsequent composite electromagnetic pulse control sequence is recalculated and corrected online.

9. A steel strengthening system for an automobile chassis for implementing the method as described in any one of claims 1-8, characterized in that, include: The information acquisition module is used to acquire the three-dimensional dislocation density distribution field of steel after cold stamping. The calculation and generation module is used to take the three-dimensional dislocation density distribution field as the initial condition, input a pre-established multi-physics field cooperative control model, solve the multi-objective optimization function of the model, and generate a composite electromagnetic pulse control sequence corresponding to the three-dimensional dislocation density distribution field. The strengthening processing module is used to apply the composite electromagnetic pulse control sequence to the steel and perform differentiated aging treatment on the micro-regions with different dislocation densities inside the steel through electromagnetic induction.

10. An electronic device, characterized in that, The electronic device includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1-8.

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