Optimization of Laser Welding Process Parameters and Experimental Study on 22MnB5 Thin Sheet

Abstract

The laser welding of 22MnB5 unequal-thickness thin sheets often presents challenges such as incomplete fusion, excessive weld pool width affecting mechanical properties, weld sagging, and splashing. These issues stem from the unique characteristics of laser welding, including deep melting depth, small heat affected zone, and fast welding speed. To address this, ABAQUS software was employed to simulate the welding process of two different thickness of steel sheets under different welding conditions. Using the Box-Behnken Design (BBD) experimental method, welding parameters were optimized, and a response surface model for residual stress and deformation post-welding was established. The effects of laser power, welding speed and beam offset on post-welding deformation and residual stress were studied. In this paper, the residual stress and welding deformation of the weldment after welding are systematically analyzed. Finite element analysis shows that when using optimized welding process parameters for welding, the stress distribution of the welded model is relatively uniform, with a maximum stress value of 547 MPa. The high stress smoothly transitions to the low stress, and deformation occurs at the starting and ending positions of the welding. Experimental results demonstrated that under the optimized parameters, by characterizing the grain structure after laser welding using EBSD, the weld metal exhibits significant fine grain structure and random grain orientation distribution, indicating rapid solidification and crystal growth. In contrast, the grains in the heat affected zone (HAZ) are larger and have a more ordered orientation. The KAM diagram reveals that the strain in the weld metal is higher, the grain interface has a higher dislocation density, and the HAZ dislocation density is lower. EBSD data shows that the grain size of welded joints varies greatly, with an average size of 3.00 µm. There are numerous low angle grain boundaries, joint appearance was enhanced, with no weld sag, bubbles, or splashes. In addition, the yield strength and tensile strength of welded sheet, whether pre-quenching or post-quenching, exhibit good mechanical properties of the welded parts, play an important role in the light-weight work of the automobile.

1. Introduction

Automobile lightweight is a dominant trend in the industry, with laser welding and advanced techniques playing a significant role. Laser welding ensures high-quality and efficient joining of materials, enabling thinner car parts while maintaining safety standards. This approach achieves lightweight body goals by reducing weight, costs, and enhancing design flexibility.^1,2,3,4,5) In the automotive industry, advanced high-strength steel, including DP steel, MS steel, and PH steel or B steel, is widely used in car body structures. Boron steel is preferred for safety parts like A-pillars, B-pillars, bumpers due to its high strength and formability. With a 1500 MPa tensile strength achievable through hot stamping, 22MnB5 contributes to weight reduction and improved safety levels in vehicles.^6,7,8,9)

Laser welding in the automotive industry commonly utilizes the key hole effect, offering benefits like deep penetration, narrow welds and heat-affected zones, and minimal joint deformation. However, it also involves a higher heat input. To enhance productivity, higher welding speeds can be employed while maintaining the advantages of laser welding.^10,11,12,13)

N. Seto et al.¹⁴⁾ studied a welding process of Ti/Fe steel sheet, and used chromium sheet metal to insert into two metals to avoid brittle intermetallic compounds composed of Ti and Fe. By adjusting the irradiation offset of the laser beam, welding metals with different chromium dilutions were obtained. It was found that when the dilution was less than 40%, the formation of intermetallic compounds could be effectively prevented. Welding is widely used in vehicle body assembly. However, high efficiency is a challenge in welding. For example, T. Tsuyama et al.¹⁵⁾ developed a new welding method (F-MAG) on the basis of CO₂ gas shielded arc welding (MAG). The heated filler wire was placed in the back of the molten pool formed by the main electrode used in MAG. MAG and F-MAG were used to prepare welding metals, respectively. It was found that the mechanical properties of the weldments formed by F-MAG were better than those of MAG. Razmpoosh M.H improved the mechanical properties of welded joints in zinc-based coated 22MnB5 by using defocused laser beam welding. The research shifted the failure position from the fusion zone to the base metal, especially under high strain rates. This result coincides with A. Bardelcik’s study on 22MnB5 steel, which attributes it to the complete martensite microstructure of the material.^16,17,18,19)

H. Ashida et al. focused their study on high-strength steel sheets used in automotive laser welding and investigated the factors influencing cold cracking by adjusting the mechanical properties (tensile strength: 0.6–1.5 GPa) and chemical composition (carbon content: 0.20–0.55%) of the steel sheets. Their findings revealed that the carbon content had the most significant impact on cold cracking.²⁰⁾ H. Kong and his team performed laser welding on automotive boron steel and low-carbon CMnSiAl Transformation Induced Plasticity (TRIP) steel. Subsequently, the welded samples were subjected to a one-step quenching and partitioning treatment at an isothermal holding temperature of 290°C for 90 seconds. The findings revealed that this heat treatment significantly altered the hardness of the weld zone and influenced the mechanical properties of the weld joint, presenting a potential solution for enhancing the performance of welded structures.²¹⁾

Farabi et al. investigated the microstructure and mechanical properties of laser-welded DP600 steel joints. The rapid heating and cooling rates during laser welding caused a martensitic microstructure in the weld zone, resulting in increased hardness. A tempering softening zone was observed in the heat-affected zone, and the tensile specimen of the welded joint exhibited a ductile fracture surface. The tensile strength of the joint remained unchanged compared to the base material, while the yield strength was higher, consistent with Donato Coviello’s finding.^22,23) V. Krishnan et al.²⁴⁾ welded Austenitic Stainless Steel (ASS) and Duplex Stainless Steel (DSS), and used the response surface method to optimize the welding process parameters of resistance welding, and predicted the influence of welding process parameters on Tensile Shear Fracture Load (TSFL). The results showed that the welding current had the most significant effect on TSFL. D. C. Ramachandran et al.²⁵⁾ used the method of paint baking to treat the resistance spot welded Q&P 980 steels of resistance spot welding, and found that the treated weldments could increase the peak load and energy absorption.

In this study, the welded joints of 22MnB5 steel with different thickness under different laser power, welding speed and beam offset were studied by experiment and finite element simulation. The welding parameters were optimized by response surface method, and the influence of welding parameters on the mechanical properties of joints was systematically analyzed. The optimal welding process to prevent defects was simulated, and the microstructure evolution and mechanical properties of the welded joints were studied. This study provides a theoretical basis for the production of welded sheets that meet the process requirements.

2. Materials and Methods

The experimental material is 22MnB5 hot-formed high-strength steel with unequal thickness, and its alloy composition is presented in Table 1. The thermal physical properties are calculated using JMatPro and the alloy composition. Figure 1 shows the thermophysical properties of the base metal for welding, where the latent heat is 2.7×10¹¹ mJ/t, the solidus temperature is 1450°C, the liquidus temperature is 1500°C and the Poisson ratio is 0.25. During the welding process, the laser beam is perpendicular to the steel sheet, as shown in Fig. 2. The experimental setup employs an IPG fiber laser capable of delivering a maximum laser power of 4 kW. The apparatus is configured with a 100 mm collimating lens and a 200 mm focusing lens, capable of generating light at a wavelength of 1070 nm. During the experiment, the optical magnification was 2, with a focusing length of 200 mm and a focus spot diameter of 0.4 mm.

Table 1. Alloy elements of 22MnB5 steel (wt.%).

Chemical composition of 22MnB5
C	Mn	Si	Cr	Al
0.23	1.36	0.27	0.23	0.03
B	Fe
0.0034	Margin

Fig. 1. Thermophysical properties of 22MnB5 steel. (Online version in color.)

Fig. 2. (a) Laser welding process (b) Tailored welded blank model. (Online version in color.)

This study uses a 3D conical Gaussian heat source model to simulate welding, which accounts for the heat concentration and large aspect ratio in laser welding.²⁶⁾ This approach produces simulation results that are more representative of actual welding conditions. Figure 3(a) shows a Three-Dimensional (3D) Gauss heat source model in which the steel sheet surface is heated by a Gauss heat source and the steel sheet interior is heated by a conical heat source, as shown in Eqs. (1) (2). Figure 3(b) shows a schematic of the heat source moving across the sheet.

  

$$\{\begin{array}{l}q(r,\mathrm{\hspace{0.17em} }y)={\displaystyle \frac{9\eta P_L{e}^3}{\pi (e^3-1)}}\cdot {\displaystyle \frac{exp\left(-{\displaystyle \frac{3r^3}{r_0^2(y)}}\right)}{c\cdot (a^2+ab+b^2)}}\\ {\mathrm{r}}_0(\mathrm{y})=\mathrm{a}-{\displaystyle \frac{(\mathrm{a}-\mathrm{b})y}{\mathrm{c}}}\end{array}$$(1)

Fig. 3. (a) 3D conical gaussian heat source model. (b) Schematic diagram of heat source application. (Online version in color.)

In the formula, q(r, y) is the maximum value of volumetric heat flux density, a, b is the effective heating radius of the upper and lower surfaces, respectively. The upper and lower heating radius is parallel to the surface of the steel sheet, c is the height of the heat source. r₀ (y) is the effective heating radius related to the depth “y”, η is the efficiency value, P_L is the laser power, r is the distance from any point on the workpiece to the center of the laser heating spot. The X-axis is perpendicular to the welding direction, the Z-axis is along the welding direction, and the Y-axis is perpendicular to the surface of the steel sheet and aligns with the thickness direction of the workpiece. Table 2 shows the verification of heat source parameters. Through numerical simulations of 5 different heat source parameters, and according to the simulation results and reference,²⁷⁾ the parameters of the heat source model were determined to be a=1.2 mm, b=1 mm, c=1.8 mm, η=0.5.

Table 2. Heat source parameter verification.

	a	b	c	Upper surface melt width in the simulation results	Lower surface melt width in simulation results
Case 1	0.8	0.6	1.8	1.5	1.43
Case 2	1	0.8	1.8	1.34	1.22
Case 3	1.2	1	1.8	1.10	1.06
Case 4	1.4	1.2	1.8	0.99	0.78
Case 5	1.6	1.4	1.8	0.85	0.69

A finite element model with dimensions of 100 mm × 50 mm and thicknesses of 1.8 mm and 1.4 mm was used in this study. The finite element model and boundary condition constraints are shown in Fig. 4, three points on the steel sheet are respectively subjected to boundary constraints in the X-axis, Y-axis, and Z-axis, as well as in the Z-axis, Y-axis, and Y-axis. The mesh number gradually decreases from the weld to the parent metal on both sides. The element size ranges from 1 mm to 4 mm, with a thickness direction of 0.2 mm. Each element is defined as a C3D8T element, allowing for coupled thermal and structural analysis. To incorporate radiation and convective heat transfer, the initial temperature of the model is set at room temperature, specifically 20°C. The numerical simulation process flow is shown in Fig. 5. Define the thermal boundary conditions as follows: the convective heat transfer coefficient is 0.033 W/(mm²°C), the radiation coefficient is 0.6, the Stefan-Boltzmann constant is 5.67×10⁻¹¹, absolute zero is −273.15°C. The above thermal boundary conditions are applied to the entire model surface.

Fig. 4. Finite element model of tailor-welded blanks. (Online version in color.)

Fig. 5. Flowchart of finite element calculation using response surface method. (Online version in color.)

In this study, the Box-Behnken design was adopted for analysis. The maximum residual stress (in MPa) and the maximum deformation (in mm) after welding were chosen as the response values for the central composite design experiment. The laser power, speed, and beam offset were considered as the response variables. A second-order polynomial model, as shown in Formulas (2), was used to fit the numerical simulation experiments.²⁸⁾

  

$$Y=B_0+{\sum }_{i+1}^n{B}_i{x}_i+{\sum }_{i=j=1}^n{B}_{ij}{x}_i{x}_j+{\sum }_{i=1}^n{B}_{ii}{x}_i$$(2)

In the three factors design scheme, n=3, so formulas (2) can be converted into formulas (3):

  

$$\begin{array}{l}Y=B_0+B_1{x}_1+B_2{x}_x+B_3{x}_3+B_{12}{x}_1{x}_2+B_{13}{x}_1{x}_3\\ \hspace{1em}+B_{23}{x}_2{x}_3+B_{11}{x}_1^2+B_{22}{x}_2^2+B_{33}{x}_3^2\end{array}$$(3)

Among them, Y is the response value, B₁, B₂, B₃ is the linear coefficient, B₁₂, B₁₃, B₂₃ is the interaction coefficient.

Based on extensive simulation experiments, the weld pool width was found to range from 1.9 mm to 2.2 mm. An offset of 0.7 mm to 1.2 mm is applied to the side of the thick sheet, which can ensure that the absorption and melting of laser energy on the thick sheet are more concentrated, ensure the welding quality on the side of the thinner sheet, and avoid the problem of incomplete fusion or poor weld quality caused by uneven energy distribution. Design Expert software was used to conduct a central composite experiment using the response surface method, resulting in 17 sets of numerical simulation experiments.

3. Response Surface and Numerical Simulation Analysis

3.1. Regression Model Analysis

Table 3 is the response surface analysis results. After simulating the numerical values in the response surface by ABAQUS, it is found that the maximum position of post-welding deformation usually appears in the position of starting and closing welding, and the proportion of post-welding deformation in the direction of thin sheet is larger. The residual stress after welding is distributed in both sheets, and the maximum residual stress is mostly distributed on the side of the thick sheet, manifested as tensile stress. In order to ensure the forming quality of welded sheets, it is necessary to ensure that the maximum deformation and maximum residual stress after welding are as far as possible within a small level.

Table 3. Simulated experimental conditions and response values.

Experimental group	Welding process parameters			Response value
	Laser power PL/W	Welding speed v/(mm/s)	Beam offset d/mm	Residual stress S/MPa	Post-weld deformation L/mm
1	3500	45	0.95	570.7	0.34
2	3000	30	0.95	532.5	0.45
3	4000	30	0.95	530.3	0.64
4	3500	30	0.7	551.7	0.56
5	3000	45	1.2	568.6	0.28
6	3000	60	0.95	561.2	0.2
7	3500	30	1.2	539.8	0.55
8	4000	45	0.7	572.4	0.39
9	4000	45	1.2	546	0.4
10	3000	45	0.7	563.5	0.26
11	3500	45	0.95	569.7	0.33
12	4000	60	0.95	559.6	0.28
13	3500	45	0.95	575.7	0.3
14	3500	60	0.7	570.3	0.22
15	3500	45	0.95	571.7	0.34
16	3500	60	1.2	570.6	0.24
17	3500	45	0.95	572.7	0.31

The results of variance analysis of residual stress after welding with different welding process parameters are shown in Table 4.

Table 4. Analysis of variance of residual stress model results after welding simulation.

Source	Sum of squares	Freedom	Mean square value	F	P	Significance
Model	3467.20	9	385.24	49.52	<0.0001	Significance
PL	38.28	1	38.28	4.92	0.0620
v	1441.85	1	1441.85	185.34	<0.0001	△△△
d	135.3	1	135.30	17.39	0.0042	△△
PLv	0.09	1	0.09	0.0116	0.9174
PLd	248.06	1	248.06	31,89	0.0008	△△
vd	37.21	1	37.21	4.78	0.0650
PL2	494.53	1	494.53	63.57	<0.0001	△△△
v2	993.71	1	993.71	127.73	<0.0001	△△△
d2	7.82	1	7.82	1.00	0.2496
Residual	54.46	7	7.78
Lack of Fit	33.26	3	11.09	2.09	0.2441	Not significance
Pure of fit	21.20	4	5.30
Cor Total	3521.66	16
R2	0.9845
Adjusted R2	0.9647
Predicted R2	0.8395
C.V.%	0.4977

Note: △ represents a significant level of 0.05; △△represents a significant level of 0.01; △△△ represents a significant level of<0.0001

In the Table 4, “F” is usually used to determine whether the regression equation can significantly explain the change of the dependent variable. When the F-value is larger, it usually means that the model interpretation ability is stronger. Lack of Fit represents that the model does not capture the important trend in the data, resulting in insufficient prediction ability of the model. The F-value of Lack of Fit in the table is 0.2441, indicating that Lack of Fit is not significant for pure error, and the insignificant Lack of Fit is good. The P-value is usually used to test whether the influence of the corresponding variables of each independent variable is significant, when the P-value is less than 0.05, it suggests a good fit of the model within the regression region.²⁹⁾ It can be seen from Table 4 that the F value of the model is 49.52 and the P value is less than 0.0001, indicating that the model is significant. The value of R² is 0.9769 and the Adjusted R² and Predicted R² is less than 2, it shows that the model has high precision. The value of C.V.% is 0.4977, the lower the value, the higher the credibility of the model. Welding speed v, beam offset d, interaction term P_Lv, square term P_L² and square term v² have significant effects on residual stress after welding.

The variance analysis results of welding deformation with different welding process parameters are shown in Table 5.

Table 5. Analysis of variance of deformation model results after welding simulation.

Source	Sum of squares	Freedom	Mean square value	F	P	Significance
Model	0.2536	9	0.0282	121.77	< 0.0001	Significance
PL	0.0338	1	0.0338	146.05	< 0.0001	△△△
v	0.19845	1	0.19845	857.5	<0.0001	△△△
d	0.0002	1	0.0002	0.8642	0.3835
PLv	0.0030	1	0.0030	13.07	0.0086	△△
PLd	0.0000	1	0.0000	0.1080	0.7520
vd	0.0002	1	0.0002	0.9722	0.3570
PL2	0.0001	1	0.0001	0.3286	0.5844
v2	0.0174	1	0.0174	75.10	<0.0001	△△△
d2	0.0001	1	0.0001	0.3286	0.5844
Residual	0.0016	7	0.0002
Lack of Fit	0.0003	3	0.0001	0.3030	0.8229	Not significance
Pure of fit	0.0013	4	0.0003
Cor Total	0.2552	16
R2	0.9937
Adjusted R2	0.9855
Predicted R2	0.9731
C.V.%	1.25

Note: △ represents a significant level of 0.05; △△represents a significant level of 0.01; △△△ represents a significant level of<0.0001

As can be seen from Table 5, F-value of the regression model of deformation is 121.77, and P-value is less than 0.0001, indicating that the model is significant. The value of R² is 0.9937. The adjusted R² is close to the Predicted R², and the C.V.% value is 1.25, which indicates that the model has high accuracy and the system recommends the model. The influence of welding speed v, interaction term P_Lv and square term v² on the deformation after welding is significant.

3.2. Response Surface Analysis

Figures 6(a)–6(c) present three-dimensional response surface diagrams showing the interaction between different welding parameters and residual stress post-welding. The Fig. 6(a) reveals that the welding speed plays a significant role in determining the residual stress after welding, as evidenced by the steepness of the response surface curve. The influence is such that when the welding speed ranges between 48 and 54 mm/s, the residual stress reaches its peak, only to decrease as the speed continues to rise. This is because as the welding speed increases, the cooling rate also increases, resulting in an increase in residual stress in the welded metal and heat affected zone. With the increase of welding speed, the heat affected zone decreases, resulting in a decrease in thermal stress. This may indirectly affect the distribution of residual stress by changing the microstructure and stress distribution in the heat affected zone. In Fig. 6(b), the interaction between laser power and beam offset can be seen. When the offset increases, the residual stress increases slightly, and the trend is not obvious. With the increase of laser power, the response curve increases first and then decreases slightly, and the residual stress reaches the maximum at 3.6 kW. Figure 6(c) indicates that welding speed has a significant impact on residual stress, with the response curve exhibiting a trend similar to that in Fig. 6(a). Thus, the primary to secondary influence of the three welding process factors on residual stress is in the order of welding speed > beam offset > laser power.

Fig. 6. Effect of welding process parameters on maximum residual stress and post-weld deformation. (Online version in color.)

The Figs. 6(d) to 6(f) depict the interactive influence surfaces of welding process parameters on post-weld deformation. Figure 6(d) reveals that welding speed has a profound impact on post-weld deformation, exhibiting an inverse relationship. As the welding speed increases, the post-weld deformation significantly reduces, from approximately 0.6 mm to 0.2 mm. This reduction may be due to the limitation of solidification time and heat input in the weld pool area as the welding speed increases, which reduces the stress formation during the weld formation process, thereby reducing the post-weld deformation. Figure 6(e) indicates that beam offset has a negligible effect on post-weld deformation, with a slight trend of increasing post-weld deformation as laser power increases, from about 0.28 mm to 0.35 mm, with an insignificant upward trend. Figure 6(f) shows the impact of beam offset and welding speed on post-weld deformation, with the response curve resembling that of Fig. 6(d). Thus, the primary to secondary influence of the three welding process factors on post-weld deformation is in the order of welding speed > laser power > beam offset.

Based on the analysis of variance (ANOVA) and the response surface methodology (RSM), the interaction effects of laser power, weld speed, and beam offset on residual stress and deformation after welding were considered. In order to ensure the minimum residual stress and deformation of the weldment, the optimal welding process parameters were determined: laser power of 3.1 kW, welding speed of 44 mm/s, and beam offset of 0.7 mm.

3.3. Numerical Simulation Results Analysis

Based on the response surface analysis, the optimal laser welding parameters of 22MnB5 are: power 3.1 kW, welding speed 44 mm/s, offset 0.7 mm. At the beginning of welding, the temperature of the local area of the weldment rises rapidly due to the heating of the heat source. As the welding progresses, a dynamic quasi-steady-state temperature distribution is formed on the heat source moving path, that is, although the heat source continues to move, the temperature distribution on its path is relatively stable. As shown in Fig. 7, a well-formed teardrop-shaped molten pool is formed in front of the weld, with a width of 2.3 mm, the width of the molten pool on the thin sheet side is 1.4 mm. The area affected by the laser beam is relatively small, and the core of the molten pool can reach 3000°C, far higher than the surrounding metal, which is in line with the heat concentration characteristics of laser welding.

Fig. 7. Changes of temperature field of welded joint and size of molten pool during welding. (Online version in color.)

Figure 8(a) shows the deformation contour of the welded joint after cooling to room temperature, and shows the tensile deformation of the left sheet starting position and some tensile deformation on the back of the sheet. The maximum deformation measures 0.281 mm. Figure 8(b) displays the von Mises stress contour of the welded sheet after cooling. The highest stress is observed on both sides of the weld, with a valley at the center. The stress distribution on the left thin sheet is relatively uniform, mostly below 450 MPa, which is lower than the yield strength of 22MnB5. Some stress increase occurs around the weld, with the maximum residual stress of 547.9 MPa observed on the right thick sheet.

Fig. 8. (a) Deformation contour diagram when cooling to room temperature after welding. (b) Residual stress contour diagram when cooling to room temperature after welding. (Online version in color.)

The numerical simulation results indicate that welding 22MnB5 dissimilar thickness sheets with a laser power of 3.1 kW, a welding speed of 44 mm/s, and a beam offset of 0.7 mm, the temperature distribution in the welding area shows high stability and uniform residual stress distribution.

4. Test Verification

Figure 9 shows the comparison between the numerical simulation results and the actual welding.

Fig. 9. (a) Numerical simulation results show the dimensions of the weld seam. (b) Actual results show the dimensions of the weld seam surface. (c) Actual results show the weld seam cross-section. (Online version in color.)

In the post-processing phase of the ABAQUS software, the temperature displayed in the calculation results is limited. If the temperature exceeds the melting point of the material (1500°C),³⁰⁾ the area will appear gray, indicating the position of the molten pool.

The optimal welding process parameters were applied to join sheets with thicknesses of 1.8 mm and 1.4 mm, respectively. From Fig. 10, it can be seen that the weld forming is smooth and uniform, the heat affected zone is small, the weld surface has no obvious splash, no obvious porosity, and the appearance is neat.

Fig. 10. (a) Front surface morphology of laser welded joints (b) Back surface morphology of laser welded joints (c) Weld morphology. (Online version in color.)

4.1. Residual Stress Analysis

Figure 11 shows longitudinal and transverse stresses obtained through simulation. The weld seam direction was defined as longitudinal, and the longitudinal residual stress distribution in the heat affected zone was more uniform than that in the transverse residual stress distribution, and is symmetrically distributed along the transverse center line of the welded sheet. The transverse and longitudinal residual stresses of the welded sheet along the longitudinal center line of the welded sheet are uneven and asymmetric. The transverse residual stress on one side of the thin sheet is greater, exhibiting tensile stress. Longitudinal residual stress is more pronounced on the thick sheet side, manifested as compressive stress. The center position of the weld seam exhibits longitudinal stress, manifested as tensile stress.

Fig. 11. (a) Transverse residual stress contour figure and welded joint (b) Longitudinal residual stress contour figure. (Online version in color.)

X-ray residual stress analysis was performed on the regions with high stress values, and results are presented in Fig. 12. As shown in Figs. 12(a) 12(c), the transverse residual stress along line 1 and line 2 is evenly distributed after welding, but there is a large fluctuation at the starting and ending positions of welding. The transverse residual stress at the fluctuating position of line 1 is compressive stress. As shown in Figs. 12(b) 12(d), longitudinal residual stress is manifested along line 1, the maximum value of longitudinal stress is 170 MPa, and the stress is manifested as tensile stress. The longitudinal residual stress distribution along line 2 is more uniform than that along line 1, with a maximum value of 330 MPa and compressive stress at the beginning and end of the weld. Localized high residual stress can impact both meso-mechanical and macro-mechanical properties of the weld. Figure 12 confirms numerical simulation and experimental data agreement regarding residual stress distribution, validating these welding process parameters for practical applications.

Fig. 12. (a) Transverse residual stress along Line 1; (b) Longitudinal residual stress along Line 1; (c) Transverse residual stress along Line 2; (d) Longitudinal residual stress along Line 2. (Online version in color.)

4.2. Microstructure Morphology Analysis

Figure 13(c) shows the cross-section structure of the laser weld perpendicular to the steel sheet. The joint is divided into the weld metal, heat-affected zone, and base metal based on peak temperature difference during the welding process. The HAZ is further classified into the quenching zone and incompletely quenched zone. The welded joints were etched with 4% nitric acid alcohol.

Fig. 13. (a): Weld metal, (b): Fully quenched zone, (c): Overall view of laser welded 22MnB5 steel joint, (d): The boundary between the fully quenched zone and the incompletely quenched zone, (e): Incompletely quenched zone, (f): Base metal. (Online version in color.)

Figure 13(a) shows the welded metal region of the laser-welded joint with coarse aciculate and lath martensite microstructure, which is due to the presence of element B in 22MnB5, which inhibits the transformation of austenite to ferrite during the welding process. The rapid cooling rate of laser welding promotes the formation of martensite. Figure 13(b) shows fully quenched zone, forming a mixture of martensite and ferrite.³¹⁾ Figure 13(d) shows the boundary between the fully quenched zone and the incompletely quenched zone, while Fig. 13(e) demonstrates lower temperatures in the incompletely quenched zone resulting in carbide redistribution, block-shaped ferrite formation, and the development of pearlite structure with increasing distance from the heat source.

The EBSD characterization data in Fig. 14 reveals that in the weld metal, significant fine-grained structures and a relatively random grain orientation distribution are observed due to the high-temperature transient effects of laser welding and rapid cooling. This indicates the occurrence of rapid solidification and specific crystal growth processes in the weld metal. In contrast, in the heat-affected zone, where direct melting did not occur, the grains are relatively larger, and the grain orientation distribution is more ordered. From the Kernel Average Misorientation (KAM) map, it can be observed that the weld metal has a higher strain level. The formation of martensite during welding result in a higher dislocation density at the grain boundaries in this region. The grain boundaries in the weld metal exhibit different dislocation densities and orientations, while in the HAZ, the temperature is higher but without the abrupt cooling experienced by the weld metal, resulting in a lower dislocation density. In the KAM map, the weld seam region shows relatively high KAM values, reflecting a relatively significant lattice deformation, whereas the HAZ exhibits relatively low KAM values, indicating less lattice deformation. The grain boundaries in the HAZ exhibit some recrystallization characteristics, appearing relatively uniform in the KAM map, contrasting with the weld seam region. Due to the high temperature gradient experienced by the crystals during welding, the grain boundaries in the weld metal exhibit some distortion and irregular shapes, with a higher density, presenting fine. In contrast, the grain boundaries in the HAZ appear relatively uniform and regular. Recrystallization leads to the rearrangement of grain boundaries inside the crystals, forming a more regular structure with a relatively lower grain boundary density, characterized by larger and fewer grain boundaries. This is in contrast to the high-density grain boundaries observed in the weld metal region. The EBSD characterization data in Fig. 14 reveals that the grain size of the WM and HAZ are different. Figure 15 shows the grain size of the welding area. The average size of the welding area is 3.00 μm, and the standard deviation is 1.93 μm. The average misorientation angle is 32.9 degrees, with a significant proportion of low-angle grain boundaries, consistent with the earlier EBSD characterization.

Fig. 14. EBSD characterization of the weld zone of the welded joints (a) IQ diagram of weld area (b) IPF diagram of weld area (c) KAM diagram of weld area (d) Pole diagram of weld area (e) Grain boundary distribution map of weld area. (Online version in color.)

Fig. 15. Grain size and grain boundary angle of welded joints (a) Grain size of welded joints (b) Grain boundary angle of welded joints. (Online version in color.)

The microstructure of the 22MnB5 unequal thickness tailor-welded joints was compared before and after quenching in Fig. 16. It can be observed that the columnar crystal in the weld metal disappears after quenching, and a more regular equiaxed crystal with different directional lath martensite appears. The microstructure after quenching is denser than that before quenching, and the martensite is needle-like.

Fig. 16. (a) Microstructure of joint before quenching (b) Microstructure of joint after quenching. (Online version in color.)

4.3. Analysis of Mechanical Properties

The base metal rich in Mn and B elements acts as a solid solution strengthener.²⁸⁾ When the molten pool is rapidly cooled, these elements effectively prevent the growth of grains, so that the grains of weld metal remain in a finer state, helping to form a uniform martensitic structure in the welded metal, thereby improving the strength and hardness of weld metal. The cooling rate of HAZ is slow, resulting in sufficient time for the grains to grow, so the grain size is large, which will reduce the hardness of HAZ. Apply a loading load of 500 g to the sample and hold it for 10 seconds. The microhardness curves of two samples are shown in Fig. 17. The welded joint exhibits a sharp increase in hardness from the BM to the HAZ due to the presence of martensite, reaching a maximum hardness of approximately 513 HV in the weld metal. After quenching, the hardness of the welded joint becomes more uniform, with minimal transitional fluctuations, and the maximum hardness reaches 507 HV.

Fig. 17. Hardness distribution of welded joint before and after quenching. (Online version in color.)

Tensile tests were performed on laser tailor-welded joints before and after quenching at room temperature to assess the mechanical properties of the welded sheet. Figure 18(a) illustrates the MTS universal tensile testing machine. While Fig. 18(b) displays the tensile specimen of the welded sheet.

Fig. 18. (a) Universal tensile testing machine (b) The dimensions of tensile test specimen (in mm). (Online version in color.)

Figure 19 depicts the stress-strain curve of room temperature tensile tests. In Fig. 19(a), the unquenched tailor-welded blank fractures on the thin sheet side with noticeable necking. It shows a yield strength of 417 MPa, a tensile strength of 583 MPa, and an elongation at fracture of 11%. The mechanical properties of the raw material are not significantly different from those of the unwelded material.^32,33) In Fig. 20(b), the quenched welded sheet fractures in the HAZ on one side of the thin sheet, demonstrating a yield strength of 1390 MPa, a tensile strength of 1723 MPa, and an elongation at fracture of 2%.³⁴⁾ The fracture surface was observed under a scanning electron microscope, and a tearing ridge was observed in Fig. 20. The existence of pits and micropores confirmed that the fracture behavior was ductile fracture. On the fracture surface, coarse dimples and fine dimples were mixed together, showing good toughness.

Fig. 19. (a) Tensile test of tailor-welded joints without quenching (b) Tensile test of tailor-welded joints after quenching. (Online version in color.)

Fig. 20. Fracture morphology of tensile specimen. (Online version in color.)

5. Conclusion

The key findings are summarized as follows:

(1) The laser welding process parameters for dissimilar thickness hot-stamped joints of 22MnB5 were optimized using the response surface methodology. The welding speed had the greatest influence on residual stress, while laser power had a relatively smaller effect. Both laser power and welding speed had significant effects on joint deformation. The optimal parameters were determined as follows: laser power of 3.1 kW, welding speed of 44 mm/s, and offset of 0.64 mm.

(2) Residual stresses in the weld were found to mainly concentrate on both sides, with transverse stresses appearing in the weld metal and adjacent heat-affected zone. Longitudinal stresses were primarily tensile, while longitudinal stresses exceeded transverse stresses. The maximum deformation occurred at the welding endpoint due to thermal accumulation. Numerical simulations were consistent with experimental results.

(3) Prior to quenching, the weld had a lath martensitic structure, while the heat-affected zone had a fine mixture of martensite. After quenching, the welded joint had a uniform martensitic structure. The weld metal exhibited fine-grained, irregular boundaries with high dislocation density, indicative of rapid solidification and crystal growth processes during welding. Conversely, the heat-affected zone displayed larger, more ordered grains with lower dislocation density. The weld metal had higher microhardness before quenching compared to the base material. After quenching, the overall hardness distribution becomes more uniform. Compared with the unquenched tensile strength, the tensile strength after quenching is increased by 196%.

Ethics Approval

The authors claim that there are no ethical issues involved in this research.

Funding

This work is supported by the Tangshan talent foundation innovation team (A202202008) and funded by S&P Program of Hebe (Grant No. 22281802Z), Key R&D Program of North China University of Science and Technology (ZD-ST-202306-23), Graduate Innovation Program of North China University of Science and Technology (2023S03).

Contribution

Weimin Liu: Writing - original draft, Project administration, Conceptualization.

Yu Yang: Review & editing, Project administration, Conceptualization;

Xiaoli Yu: Experimental, Investigation;

Liyan Feng: Review & editing, conceptualization, Investigation;

Weimin Yin: Experimental, conceptualization, Project administration;

Hongchao Ji: Experimental, Review & editing, Project administration, Conceptualization.

Data Availability

It declares that no data or materials are available for this research.

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