BAIC Motor (China)

Abstract In response to the problem of inaccurate positioning and parking of belt conveyor unloading vehicles during operation, based on the analysis of their actual operating scenarios, This study proposes a sliding mode control strategy for belt conveyor unloading vehicles based on Radial Basis Function Neural Network, establish a dynamic model of unloading vehicle based on RBFNN, designs a sliding mode controller based on RBFNN, and builds a physical experimental model of unloading vehicles. The experimental results show that this control strategy can achieve good tracking effect on the speed and displacement of the unloading vehicle, and the accuracy of the unloading vehicle positioning and parking reaches 98% in the end; Compared with no RBFNN, getting closer to the target position in displacement tracking, meeting the accuracy requirements for positioning and parking of belt conveyor unloading vehicles under actual working conditions. It has engineering practicality and provides a new engineering control solution to solve the problems in the field of bulk material conveying.

With the development of electronic devices toward thinner, lighter, and more flexible, the preparation of transparent electrodes for device assembly has garnered significant attention. Traditional transparent electrodes of indium tin oxides are brittle and difficult to adapt to deformations such as bending and stretching of flexible substrates. Flexible electrodes based on two-dimensional microstructures have become viable alternatives; however, the current electrode fabrication methods are complex, typically requiring the involvement of multiple machining equipment and the combination of multiple fabrication processes for machining and fabrication, and the simple, direct, and efficient integrated fabrication of electrodes is still a great challenge. Herein, an integrated manufacturing strategy for directly printing flexible multilayer composite electrodes based on an electrohydrodynamic printing process is proposed. The printing experimental system was designed. A finite element model was developed to make a preliminary selection of the parameters and the range of values affecting printing. Experiments were designed to analyze the combination of printing parameters to determine the range of applicability. The line width prediction model was used to predict the printing of structures with superior finish quality. Different printing modes were selected for different mesh electrode layers, electrode reinforcement layers, and encapsulation layers of the composite electrodes. Surface modification treatment was combined with direct printing for the direct assembly of electrodes. The electrode of finalized size 20 mm × 20 mm has good light transmission, conductivity, deformation, and mechanical stability; current efficiency and light-emitting diode (LED) light brightness before and after deformation are basically unchanged. The electrode in different bending diameters after 1000 cycles of resistance change is small and lightweight and has stable performance under different working conditions, good environmental adaptability, and excellent overall performance. The potential of composite electrodes for a wide range of applications in emerging wearable multifunctional electronic devices is shown by fabricating wearable strain sensors and heated films based on this electrode. This method can be used to manufacture simple, low-cost, high-performance, and high-efficiency electrodes.

The car chassis design concept is an important part of the car design process. Analyzing the car chassis structure in the conceptual design process is of great significance for improving the efficiency and accuracy of car chassis design. This paper takes SUV models as the research object and uses SFE CONCEPT software to realize the mathematical modeling and multivariate optimization of the SUV chassis structure. The concept of “implicit” parameterization and the concept of “CAE analysis-driven design” are adopted to quickly realize large-scale geometric transformation and consistency of interconnection, while achieving automated production and grid parameters. Through this research, it can be found that in the concept development stage of the vehicle chassis structure, the CAE performance analysis is introduced into the early development stage as soon as possible; combined with the implicit parametric design method, it can quickly and effectively realize the exploration and optimization of a larger range of structures. In addition, the SFE CONCEPT software used in this article can create parametric structural models, and combined with automatic meshing technology, it can realize continuous changes of topology variables, shape variables, size variables, and material variables, and compare the design results with the detailed design results to confirm the feasibility of the design. In addition, the experimental test shows that the success rate of SFE CONCEPT and other CAD software docking reaches 100%.

Taking the combustor composite structure of a high-strength diesel engine as the main research object, dedicated tests have been conducted to verify the accuracy of three distinct cylinder gasket pressure simulation models. Using the measured cylinder gasket compression rebound curve, a gasket unit has been designed and manufactured. For this unit, the influence of the bolt pretension, cylinder body and cylinder head material on gasket sealing pressure has been investigated systematically in conditions of thermo-mechanical coupling. The results show that the bolt pretension force is one of the most important factors affecting the cylinder gasket sealing pressure. The change of the body material has little effect on this pressure. The cylinder gasket seal pressure decreases progressively with the reduction of the elastic module of the cylinder head material.

It is already well known how MT equipped driveline torsional modes are distributed and influenced, and that is successfully applied to MT equipped vehicle noise vibration harshness (NVH) problem solving. However, it is still marginal for systematically continuous variable transmission (CVT) equipped driveline torsional modes sensitivity analysis, hence it is very meaningful to dig out the CVT driveline torsional vibration mode distribution and sensitivity to driveline component inertia/torsional stiffness, hence the right driveline component parameters could be pre-defined from the very start of driveline development or tuned during the refine stage. The aim of this paper is to find out CVT equipped driveline torsional vibration mode sensitivity to driveline component inertia/torsional stiffness and rules to tune the driveline torsional vibration modes to mitigate torsional vibration induced NVH issues.

Based on the finite element method (FEM), this research focused on the trunk lid hinge reinforcement plate welding spot crack problem. The number of the resistance spot welding (structure adhesives) and the structure of the hinge reinforcement plate are analyzed, and we found the method to solve the trunk lid hinge reinforcement plate welding spot crack problem. The stress of trunk lid inner panel was reduced from 128 to 80 Mpa, the fatigue life was increased to more than 10,000,000 from 248,000 by CAE simulations, and the CAE simulations have been effectively verified with the prototype test.

BackgroundThe average sensitivity of conventional cytology for the identification of cancer cells in effusion specimens is only approximately 58%. DNA image cytometry (DNA‐ICM), which exploits the DNA content of morphologically suspicious nuclei measured on digital images, has a sensitivity of up to 91% for the detection of cancer cells. However, when performed manually, to our knowledge to date, an expert needs approximately 60 minutes for the analysis of a single slide.MethodsIn the current study, the authors present a novel method of supervised machine learning for the automated identification of morphologically suspicious mesothelial and epithelial nuclei in Feulgen‐stained effusion specimens. The authors compared this with manual DNA‐ICM and a gold standard cytological diagnosis for 121 cases. Furthermore, the authors retrospectively analyzed whether the amount of morphometrically abnormal mesothelial or epithelial nuclei detected by the digital classifier could be used as an additional diagnostic marker.ResultsThe presented semiautomated DNA karyometric solution identified more diagnostically relevant abnormal nuclei compared with manual DNA‐ICM, which led to a higher sensitivity (76.4% vs 68.5%) at a specificity of 100%. The ratio between digitally abnormal and all mesothelial nuclei was found to identify cancer cell–positive slides at 100% sensitivity and 70% specificity. The time effort for an expert therefore is reduced to the verification of a few nuclei with exceeding DNA content, which to our knowledge can be accomplished within 5 minutes.ConclusionsThe authors have created and validated a computer‐assisted bimodal karyometric approach for which both nuclear morphology and DNA are quantified from a Feulgen‐stained slide. DNA karyometry thus increases the diagnostic accuracy and reduces the workload of an expert when compared with manual DNA‐ICM.