Current Issue : October - December Volume : 2014 Issue Number : 4 Articles : 4 Articles
In order to improve the curving performance of\nthe conventional wheelset in sharp curves and resolve the\nsteering ability problem of the independently rotating wheel\nin large radius curves and tangent lines, a differential coupling\nwheelset (DCW) was developed in this work. The\nDCW was composed of two independently rotating wheels\n(IRWs) coupled by a clutch-type limited slip differential.\nThe differential contains a static pre-stress clutch, which\ncould lock both sides of IRWs of the DCW to ensure a good\nsteering performance in curves with large radius and tangent\ntrack. In contrast, the clutch could unlock the two IRWs of\nthe DCW in a sharp curve to endue it with the characteristic\nof an IRW, so that the vehicles can go through the tight curve\nsmoothly. To study the dynamic performance of the DCW, a\nmulti-body dynamic model of single bogie with DCWs was\nestablished. The self-centering capability, hunting stability,\nand self-steering performance on a curved track were analyzed\nand then compared with those of the conventional\nwheelset and IRW. Finally, the effect of coupling parameters\nof the DCW on the dynamic performance was investigated....
Introduction Road bends of extra-urban and rural roads\nare known to be particularly relevant for motorcycle riding\nsafety. For this reason a Curve Warning system has been\ndeveloped for assisting the motorcyclists to safely approach\nbends and curves.\nSystem Description The system is organized in three layers:\nthe first is the scenario detection that uses on-board\nsensors and digital maps to feed the second layer, which is\nthe risk assessment layer. This second layer combines road\ngeometry, motorcycle dynamics, and rider style in a holistic\napproach for computing a safe reference maneuver and\nfor detecting potential dangers in the curve negotiation. The\nsafe reference maneuver is continuously recalculated to follow\nthe evolving scenario according to a receding horizon\napproach. In case of potential danger, the third layer warns\nthe rider by a proper Human Machine Interface, leaving to\nthe rider the vehicle control.\nPaper contents This paper explains the Curve Warning concept\nand illustrates its implementation, development, and\ntuning on a motorcycle prototype. The latter has been used\nfor a pilot campaign of road tests, which demonstrated that\nthe system is capable of early detection of potential danger\nsituations, and that riders have a positive attitude towards\nthe Curve Warning system itself....
Abstract\nPurpose This paper outlines a complex simulation model for\nparallel-hybrid diesel railcarswith hydrodynamic power transmission.\nIt contributes to the discussion concerning whether a\nhydrostatic recuperation system can be an alternative to electric\nsystems using double-layer capacitors or flywheels. The\npaper focusses on a hybrid system with realistic parameters\nconcerning mass, power, and energy content that should be\napplicable to both existing and newly built vehicles.\nMethods A simulation process that is based on the 1-d-multidomain\nsimulation tool Imagine.Lab AMESim is presented. The\nsimulation comprises a conventional and an alternative drive\ntrain as well as the longitudinal dynamics of the vehicle along\nwith the control of the vehicle motion. Energy-efficient driving\ntechniques and timetable restrictions are taken into account when\ncomparing train runs of different drivetrain configurations.\nResults Simulations based on real route data for eight different\nrailway lines show a reduction of fuel consumption between\n5 and 16 % due to the hydrostatic recuperation of\nenergy. Station spacing and mean line gradients prove to be\nimportant line-side factors impacting fuel economy.\nConclusions Hydrostatic recuperation represents a feasible solution\nfor railcars, provided that possible spatial and economic\nobstacles can be overcome. As the simulation results are promising,\nfurther hybrid configurations will be considered for simulation.\nA comprehensive comparison to models of hybrid\ndiesel railcars using different energy storages is the next step....
In order to reduce the wheel profile wear of highspeed\ntrains and extend the service life of wheels, a dynamic\nmodel for a high-speed vehicle was set up, in which the\nwheelset was regarded as flexible body, and the actual measured\ntrack irregularities and line conditions were considered.\nThe wear depth of the wheel profile was calculated by the\nwell-known Archard wear law. Through this model, the\ninfluence of the wheel profile, primary suspension stiffness,\ntrack gage, and rail cant on the wear of wheel profile were\nstudied through multiple iterative calculations. Numerical\nsimulation results show that the type XP55 wheel profile has\nthe smallest cumulative wear depth, and the type LM wheel\nprofile has the largest wear depth. To reduce the wear of the\nwheel profile, the equivalent conicity of the wheel should not\nbe too large or too small. On the other hand, a small primary\nvertical stiffness, a track gage around 1,435ââ?¬â??1,438 mm, and a\nrail cant around 1:35ââ?¬â??1:40 are beneficial for dynamic performance\nimprovement and wheel wear alleviation....
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