The transmission is one of the core components of the automotive powertrain system, and the housing serves as a critical structural element. Its performance directly impacts power transmission efficiency, reliability, and driving comfort. This paper reviews research advancements in lightweight design, reliability analysis, casting processes, and vibration-noise control of transmission housings. The optimization of transmission housing structure can reduce weight and enhance durability, while increasing stiffness effectively suppresses radiation noise. Optimizing the stiffener, changing the cross-section design and changing the shell thickness with the help of simulation technology can greatly reduce the design difficulty, and the exploration of new materials will also become a research hotspot. Additionally, optimizing casting process parameters can shorten production cycle and improve casting quality. However, the best process parameters need to be further explored, and the combination of casting process and intelligent manufacturing technology in the future is worthy of in-depth study, which provides reference for improving the comprehensive performance of transmission housing.

The Microstructure, friction and wear reduction and noise performance of FAS3420 steel samples with different surface treatments are investigated using XRD, EDS, SEM, friction and wear testing, fatigue testing, and NVH measurements. The results indicate that after low-temperature ion sulfurization and magnetron sputtering treatment, a sulfurizing layer primarily composed of FeS formed on the surface of the carburized and quenched steel. Supported by a high-hardness fine-needle martensite structure, the friction coefficient and volumetric wear rate are significantly reduced, demonstrating improved friction reduction, wear resistance, and anti-seizure capabilities, which can effectively extend the fatigue life of shaft and gear components. Through the surface protection and repair effects of sulfide solid lubricating films, direct metal contact and collisions, impacts, vibrations, and other noises caused by gear wear and deformation are reduced, thereby achieving friction reduction and noise suppression.

As a critical functional component of the vehicle body, the automobile engine hood's point cloud registration accuracy directly impacts the assembly gap, sealing performance, and collision safety. To address the limitations of traditional registration methods in handling engine hood point clouds—such as large surface registration errors, low precision, and poor efficiency—this paper employs an improved voxel filtering approach for preprocessing and proposes a hybrid registration method based on feature fusion and GICP. The method first performs coarse registration through curvature feature extraction and FPFH descriptors, followed by fine registration using the GICP algorithm. Experimental results demonstrate that our approach achieves an average registration error of 15.11 mm with an average processing time of 9.3 s on a dataset containing 30 engine hood point clouds, showing higher registration accuracy and better computational performance compared to baseline algorithms. This study provides a novel approach for high-precision registration of complex curved surfaces in automotive panels.

As a core load-bearing component of the vehicle, the lightweight and reliability design of the air suspension integrated axle housing is crucial for improving overall vehicle performance. Addressing the limitations of traditional design methods in adapting to complex dynamic loads, this paper proposes a topology optimization method based on dynamic load spectra and the SIMP (Solid Isotropic Material with Penalization) method for non-uniform material distribution. A multi-condition topology optimization strategy applicable to diverse engineering scenarios is established. During the optimization process, the material density is adjusted iteratively based on analytical results to progressively refine the structure, ultimately achieving the optimal material distribution for the integrated axle housing. The study demonstrates that this method significantly reduces the axle housing mass by 90 kg while meeting strength and fatigue life requirements, providing an effective solution for lightweight design of air suspension integrated axle housings.

To achieve accurate prediction of aluminum alloy formability limits, a material hardening model based on the interpolation method of measured stress-strain data was proposed. The theoretical formability limit predictions of measured data, the power exponential, and cubic polynomial hardening models were systematically studied using the M-K theory. Uniaxial tensile tests were conducted to obtain stress-strain data of 6016 aluminum alloy, based on which different material hardening models were constructed. Detailed calculation procedures for limit strains under various models were presented, and forming limit diagrams (FLDs) were plotted. Finally, experimental results of aluminum alloy sheet formability limits were obtained through punch bulging tests and optical non-contact measurement techniques. The results indicate that the material hardening model based on the interpolation method of measured data demonstrates superior prediction accuracy, showing perfect agreement with experimental results. In contrast, commonly used power law and cubic polynomial curve-fitting hardening models tend to overestimate formability limits, particularly under negative strain path conditions. Material hardening models significantly influence the prediction of forming limits for 6016 aluminum alloy sheets, with prediction accuracy positively correlated with the goodness-of-fit of the hardening model fitting curves.

To facilitate the green transformation of the automotive industry, this study investigates the application of Biomass-modified Polypropylene (Bio-PP) in automotive interior and exterior components. It analyzes the processing techniques and material properties of PP modified with biomass fillers such as straw and coconut shell fibers. The results indicate that Bio-PP components offer advantages in lightweight design and reduced carbon emissions while meeting performance requirements. Despite challenges such as balancing cost and performance, Bio-PP holds promise as a key sustainable material for automotive applications.

In this paper, a systematic study of niobium-vanadium composite microalloyed aluminum-silicon coated hot-forming steel 34MnB5NbV is carried out by various material mechanical property tests and microstructure characterization methods, such as room temperature tensile test, three-point bending test, scanning electron microscope, and transmission electron microscope. The results show that after quenching, the yield strength of the material is 1 365 MPa, the tensile strength is 2 056 MPa, the elongation is 4.9%, and the bending angle is 58.7°. After bake hardening process, the yield strength of the material is increased by 127 MPa, the tensile strength is decreased by 144 MPa, the elongation is increased by 0.5%, and the bending angle is increased by 6.1°. After niobium-vanadium composite microalloyed 34MnB5NbV steel hot forming, the precipitation phase is (Nb, V) C composite precipitated phase, which has better fine grain strengthening and precipitation strengthening effect to improve the strength and toughness of the hot forming steel, so that the comprehensive mechanical properties achieve better. Moreover, in order to fully evaluate the bending toughness of the material, the three-point bending test is carried out on the door anti-collision beam part made by 34MnB5NbV steel. The maximum bending force and bending energy of the part showed significant improvements compared to those of the 1 500 MPa part, indicating good bending toughness and meeting the application requirements.

To investigate the influence of an ultraviolet (UV) coating on the bonding performance between the polypropylene housing and the polycarbonate lens of automotive lamps, this study prepares standard shear specimens with and without a sprayed UV coating. Two mainstream adhesive types in the lamp industry including a room-temperature curing sealant (cold adhesive) and a hot-melt adhesive (hot adhesive), which are evaluated by systematically assessing their shear strength after exposure to six harsh environmental conditions. The results show that the shear strengths of both the cold and hot adhesives under all environmental conditions significantly exceed the design requirement, indicating that the presence of a UV coating doesn't negatively affect the bonding performance of either adhesive type.

To study the application performance of galvanized hot-formed steel, the usage performance of pure zinc-coated hot-formed steel is analyzed from aspects such as welding, bonding, coating, and hot stamping. Some of the usage performances are compared and analyzed with those of aluminum-silicon-coated hot-formed steel. The results show that the galvanized hot-formed steel has excellent spot welding, bonding and painting performance, which is comparable to that of the Al-Si coated hot-formed steel. Among them, the electrophoretic corrosion resistance of the pure zinc coating is significantly better than that of the Al-Si coating, which can better improve the anti-corrosion performance of the vehicle body. The hot stamping performance of the galvanized hot-formed steel is good, and no cracking occurs after forming, and the depth of the micro-cracks under the coating is less than 10 μm. Under the existing working conditions, the galvanized hot-formed steel can obtain good stamping, bonding, welding and painting performance.

As the automotive industry accelerates its transformation toward intelligence, digitalization, and flexibility, logistics simulation technology centered on Plant Simulation has gradually become a core tool for factory material flow design and production capacity optimization. Taking the welding workshop of a specific vehicle model as an example, this paper systematically analyzes the principles, business processes, project prerequisites, and model construction of logistics simulation technology. It focuses on discussing simulation optimization scenarios such as full-line output simulation, single-factor multi-level experiments, and multi-factor cross-validation. Additionally, it comprehensively introduces 2 forward-looking trends in logistics simulation technology: sequential production for cost reduction and efficiency improvement, and real-time linkage between digital twins and Internet of Things (IoT) data.