This study aims to investigate the feasibility of hydroforming (HF) technology coupled with response surface optimization for producing high-quality five-branched AISI 304 stainless steel tubes with different diameters, addressing the shortcomings of traditional manufacturing processes. Conventional techniques often result in issues with multiple consumables, low precision, and subpar performance. The research focuses on finding optimal forming parameters for a more effective process. Initial attempts at a five-branched tube proved unfeasible. Instead, a multi-step forming approach was adopted, starting with the formation of the upper branch tube followed by the two reducing lower branch tubes, a strategy termed “first three, then five”. This method, enhanced by a subsequent solid solution treatment, yielded promising results: the combined height of the upper and lower branches was 141.1 mm, with a maximum thinning rate of 26.67%, reduced to 25.33% after trimming. These outcomes met the product usage requirements. Additionally, the study involved designing and developing dies for manufacturing five-branched tubes with different diameters using servo HF equipment. The effectiveness of the multi-step forming process and parameter combinations was confirmed through experimental validation, aligning closely with the FE simulation results. The maximum thinning rate observed in the experiments was 27.60%, indicating that FE simulation and response surface methodology can effectively guide the production of high-quality parts with superior performance.

Bipolar plates are one of the most important components of proton exchange membrane fuel cells. With the miniaturization of bipolar plate flow channel sizes and the increasing demand for precision, springback has become a key focus of research in the bipolar plate forming process. In this paper, the hydroforming process for 316L stainless steel bipolar plates was studied, and an FEM model was built to examine the stress and strain at various locations on the longitudinal section of the plate. Modeling accuracy was validated by the comparison of experimental profile and thickness distribution. The effects of forming pressure and grain size on springback behavior are discussed. The results show that with increasing forming pressure, the springback value decreases initially, followed by an increase, but then again decreases. When the forming pressure is 80 MPa–100 MPa, the deformation of the lower element of the upper rounded corner is not uniform with more elastic regions, and the springback is positively correlated with forming pressure. The springback distribution pattern on the cross-section of the bipolar plate changes from a normal distribution to a distribution of “M” shape with increased pressure. The larger the grain size, the lower the yield strength elastic proportion, resulting in a decrease in springback of the sheet. The maximum amount of springback of the bipolar plate is 3.1 μm when the grain size is 60.7 μm. The research results provide a reference for improving the forming quality of metal bipolar plates with different flow channel shapes.

The hot metal gas forming process can significantly improve the formability of a tube and is suitable for the manufacturing of parts with complex shapes. In this paper, a double wave tube component is studied. The effects of different temperatures (400 °C, 425 °C, 450 °C and 475 °C) and different pressures (1 MPa, 1.5 MPa, 2 MPa, 2.5 MPa and 3 MPa) on the formability of 6063 aluminum alloy tubes were studied. The influence of hot metal gas forming process parameters on the microstructure was analyzed. The optimal hot metal gas forming process parameters of 6063 aluminum alloy tubes were explored. The results show that the expansion rate increases with the increase in pressure. The pressure affects the deformation of the tube, which in turn has an effect on the dynamic softening of the material. The expansion rate of parts also increases with the increase in forming temperature. The increased deformation temperature is beneficial to the dynamic recrystallization of 6063, resulting in softening of the material and enhanced deformation uniformity between grains, so that the formability of the material is improved. The optimum hot metal gas forming process parameters of 6063 aluminum alloy tubes are the temperature of 475 °C and the pressure of 2.5 MPa; the maximum expansion ratio is 41.6%.

The design of the loading path is one of the important research contents of the tube hydroforming process. Optimization of loading paths using optimization algorithms has received attention due to the inefficiency of only finite element optimization. In this paper, the hydroforming process of 5A02 aluminum alloy variable diameter tube was as the research object. Fuzzy control was used to optimize the loading path, and the fuzzy rule base was established based on FEM. The minimum wall thickness and wall thickness reduction rate were determined as input membership functions, and the axial feeds variable value of the next step was used as output membership functions. The results show that the optimized loading path greatly improves the uniformity of wall thickness and the forming effect compared with the linear loading path. The round corner lamination rate of the tube is 91.2% under the fuzzy control optimized loading path, which was increased by 47.1% and 22.6% compared with linear loading Path 1 and Path 2, respectively. Based on the optimized loading path in the experiment, the minimum wall thickness of the variable diameter tube was 1.32 mm and the maximum thinning rate was 12.4%. The experimental results were consistent with the simulation results, which verified the accuracy of fuzzy control. The research results provide a reference for improving the forming quality of thin-walled tubes and plates.

To predict the forming behaviour of aluminium alloy variable diameter tubes during hydroforming, a genetic algorithm-enhanced particle swarm optimisation (GA-PSO) is used to optimise a backpropagation neural network (BP-NN). A fast prediction model based on the GA-PSO-BP neural network for the hydroforming of aluminium alloy variable diameter tubes was established. The loading paths (internal pressure, axial feeds, and coefficient of friction) were randomly sampled using the Latin hypercube random sampling method. The minimum wall thickness, maximum wall thickness, and maximum expansion height of the formed tubes are included in the main evaluation factors of the forming results. A variety of machine learning algorithms are used to predict, and the prediction results are compared with the finite element model in terms of error. The maximum average absolute value error and mean square error of the proposed model are less than 0.2, which improves the accuracy by 20.4% compared to the unoptimised PSO-BP neural network algorithm. The maximum error between simulated and predicted results is within 4%. The model allows effective prediction of the hydroforming effect of aluminium alloy variable diameter tubes and improves the computational rate and model accuracy of the model. The same process parameters are experimentally verified, the minimum wall thickness of the formed part is 1.27 mm, the maximum wall thickness is 1.53 mm, and the maximum expansion height is 5.11 mm. The maximum thinning and the maximum thickening rate comply with the standard of hydroforming, and the tube has good formability without obvious defects.

To further enhance the fuel cell stack efficiency and reduce weight, the thickness of stainless steel bipolar plates is showing a decreasing trend, and the thickness of 0.075 mm is being considered. In this paper, 316L stainless steel with a thickness of 0.075 mm is taken as the research object. Different grain sizes were obtained and the effect of grain size on mechanical properties was studied. Based on the Swift hardening model, a phenomenological constitutive model containing t/d (ratio of plate thickness t to grain size d) was established. The flow stress shows a decreasing trend with the decrease of d − 1 / 2 . When t/d ≥ 2.59, the flow stress follows the traditional Hall-Petch relation, while when t/d < 2.59, the flow stress deviates from Hall-Petch relation curve, and the size effect of ‘smaller is weaker’ appears. When t/d decreases, the deformation mechanism shifts from ‘dislocation-dominated within grains’ to ‘dominated by grain boundary/surface activity’. The increase of grain size reduces the obstruction of dislocation motion by grain boundaries, leading to a decrease in the strength coefficient K . Dislocations in large grains move a longer distance within the grains, resulting in more dislocation proliferation and enhancing the strain hardening effect. Local strain concentration leads to a larger ε 0 to correct the nonlinear response in the initial stage of stress–strain curve in large grains. The calculated values of phenomenological constitutive model are in excellent agreement with the experimental values with maximum error of 0.024386. This research can provide material selection and finite element simulation support for lightweight ultra-thin stainless steel bipolar plate forming.