查看更多>>摘要：The all-wheel drive(AWD)hybrid system is a research focus on high-performance new energy vehicles that can meet the demands of dynamic performance and passing ability.Simultaneous optimization of the power and economy of hybrid vehicles becomes an issue.A unique multi-mode coupling(MMC)AWD hybrid system is presented to real-ize the distributed and centralized driving of the front and rear axles to achieve vectored distribution and full uti-lization of the system power between the axles of vehicles.Based on the parameters of the benchmarking model of a hybrid vehicle,the best model-predictive control-based energy management strategy is proposed.First,the drive system model was built after the analysis of the MMC-AWD's drive modes.Next,three fundamental strategies were established to address power distribution adjustment and battery SOC maintenance when the SOC changed,which was followed by the design of a road driving force observer.Then,the energy consumption rate in the average time domain was processed before designing the minimum fuel consumption controller based on the equivalent fuel consumption coefficient.Finally,the advantage of the MMC-AWD was confirmed by comparison with the dynamic performance and economy of the BYD Song PLUS DMI-AWD.The findings indicate that,in comparison to the com-parative hybrid system at road adhesion coefficients of 0.8 and 0.6,the MMC-AWD's capacity to accelerate increases by 5.26％and 7.92％,respectively.When the road adhesion coefficient is 0.8,0.6,and 0.4,the maximum climbing ability increases by 14.22％,12.88％,and 4.55％,respectively.As a result,the dynamic performance is greatly enhanced,and the fuel savings rate per 100 km of mileage reaches 12.06％,which is also very economical.The proposed control strategies for the new hybrid AWD vehicle can optimize the power and economy simultaneously.
查看更多>>摘要：In the railway system,fasteners have the functions of damping,maintaining the track distance,and adjusting the track level.Therefore,routine maintenance and inspection of fasteners are important to ensure the safe operation of track lines.Currently,assessment methods for fastener tightness include manual observation,acoustic wave detection,and image detection.There are limitations such as low accuracy and efficiency,easy interference and misjudgment,and a lack of accurate,stable,and fast detection methods.Aiming at the small deformation characteristics and large elastic change of fasteners from full loosening to full tightening,this study proposes high-precision surface-structured light technology for fastener detection and fastener deformation feature extraction based on the center-line projec-tion distance and a fastener tightness regression method based on neural networks.First,the method uses a 3D camera to obtain a fastener point cloud and then segments the elastic rod area based on the iterative closest point algorithm registration.Principal component analysis is used to calculate the normal vector of the segmented elastic rod surface and extract the point on the centerline of the elastic rod.The point is projected onto the upper surface of the bolt to calculate the projection distance.Subsequently,the mapping relationship between the projection distance sequence and fastener tightness is established,and the influence of each parameter on the fastener tight-ness prediction is analyzed.Finally,by setting up a fastener detection scene in the track experimental base,collecting data,and completing the algorithm verification,the results showed that the deviation between the fastener tightness regression value obtained after the algorithm processing and the actual measured value RMSE was 0.2196 mm,which significantly improved the effect compared with other tightness detection methods,and realized an effective fastener tightness regression.
查看更多>>摘要：There is no unified planning standard for unstructured roads,and the morphological structures of these roads are complex and varied.It is important to maintain a balance between accuracy and speed for unstructured road extraction models.Unstructured road extraction algorithms based on deep learning have problems such as high model complexity,high computational cost,and the inability to adapt to current edge computing devices.Therefore,it is best to use lightweight network models.Considering the need for lightweight models and the characteristics of unstructured roads with different pattern shapes,such as blocks and strips,a TMB(Triple Multi-Block)feature extraction module is proposed,and the overall structure of the TMBNet network is described.The TMB module was compared with SS-nbt,Non-bottleneck-1D,and other modules via experiments.The feasibility and effectiveness of the TMB module design were proven through experiments and visualizations.The comparison experiment,using multiple convolution kernel categories,proved that the TMB module can improve the segmentation accuracy of the network.The comparison with different semantic segmentation networks demonstrates that theTMBNet network has advantages in terms of unstructured road extraction.
查看更多>>摘要：A novel double side friction stir Z shape lap-butt welding(DS-FSZW)process was proposed to achieve excellent mechanical properties of Al/Cu medium-thick dissimilar joints.The influence of welding parameters on weld micro-structure and properties of DS-FSZW joint were systematically investigated.It indicated that defect-free medium-thick Al/Cu DS-FSZW joint could be achieved under an optimal welding parameter.DS-FSZW joint was prone to form void defects in the bottom of the second-pass weld.The recrystallization mechanisms at the top and middle of the weld nugget zone(WNZ)were continuous dynamic recrystallization(CDRX)and geometric dynamic recrystallization(GDRX).While the major recrystallization mechanism at the bottom of the WNZ was GDRX.DS-FSZW joint of the opti-mal welding condition with 850 r/min-400 mm/min was produced with a continuous thin and crack-free IMCs layer at the Al/Cu interface,and the maximum tensile strength of this joint is 160.57 MPa,which is equivalent to 65.54％of pure Cu base material.Moreover,the corrosion resistance of Al/Cu DS-FSZW joints also achieved its maximum value at the optimal welding parameter of 850 r/min-400 mm/min.It demonstrates that the DS-FSZW process can simulta-neously produce medium-thick Al/Cu joints with excellent mechanical performance and corrosion resistance.
查看更多>>摘要：Copper particles emitted from braking have become a significant source of environmental pollution.However,copper plays a crucial role in resin-based braking materials.Developing high-performance braking materials with-out copper has become a significant challenge.In this paper,the resin-based braking materials were filled with fly-ash cenospheres to develop copper-free braking materials.The effects of fly-ash cenospheres on the physical properties,mechanical and friction and wear properties of braking materials were studied.Furthermore,the wear mechanism of copper-free resin-based braking materials filled with fly-ash cenospheres was discussed.The results indicate that the inclusion of fly-ash cenospheres in the braking materials improved their thermal stability,hard-ness and impact strength,reduced their density,effectively increased the friction coefficient at medium and high temperatures,and enhanced the heat-fade resistance of the braking materials.The inclusion of fly-ash cenospheres contributed to the formation of surface friction film during the friction process of the braking materials,and facilitated the transition of form from abrasive wear to adhesive wear.At 100-350 ℃,the friction coefficient of the optimal for-mulation is in the range of 0.57-0.61,and the wear rate is in the range(0.29-0.65)× 10-7cm3·N-1·m-1,demonstrating excellent resistance to heat-fade and stability in friction coefficient.This research proposes the use of fly-ash ceno-spheres as a substitute for environmentally harmful and expensive copper in brake materials,which not only improves the performance of braking materials but also reduces their costs.
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