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Eric L. Wang Associate Instructor M. L. Hull Professor 《Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility》1996,25(3):223-246
The energy dissipated by the suspension systems used for off-road bicycles is a major concern due to the limited power source in cycling. Rider induced energy losses are those that arise from the muscular action of the rider. The purpose of this study was to develop and verify a dynamic model of a seated cyclist riding an off-road bicycle up a smooth road. With the absence of terrain irregularities, all suspension motion was rider induced. Knowing the stiffness and dissipative characteristics of the suspension elements, the power dissipated by the suspensions was calculated.
Simulation results were compared to suspension deflections that were experimentally measured for a cyclist riding a commercially available dual suspension bicycle up a 6% grade at 6.5m/s. For this particular case, no fork motion was observed in the experiments which was consistent with the simulation results. For the rear suspension, the mean and amplitude of the largest harmonic were experimentally determined to be 6.6 and ±2.7 mm respectively. Simulation results were within 0.7mm of the mean and within 0.3mm of the amplitude. The only major discrepancy between the experiments and the simulations was the presence of a phase lag in the simulation results which was attributed to inter-subject variability. The power dissipated by the rear suspension was calculated to be 6.9 Watts or 1.3% of the total power input by the rider. Given the grade and forward velocity, this translated into an equivalent mass of 1.8 kg. Thus, the bicycle appeared to be roughly 12% heavier than it actually was. 相似文献
Simulation results were compared to suspension deflections that were experimentally measured for a cyclist riding a commercially available dual suspension bicycle up a 6% grade at 6.5m/s. For this particular case, no fork motion was observed in the experiments which was consistent with the simulation results. For the rear suspension, the mean and amplitude of the largest harmonic were experimentally determined to be 6.6 and ±2.7 mm respectively. Simulation results were within 0.7mm of the mean and within 0.3mm of the amplitude. The only major discrepancy between the experiments and the simulations was the presence of a phase lag in the simulation results which was attributed to inter-subject variability. The power dissipated by the rear suspension was calculated to be 6.9 Watts or 1.3% of the total power input by the rider. Given the grade and forward velocity, this translated into an equivalent mass of 1.8 kg. Thus, the bicycle appeared to be roughly 12% heavier than it actually was. 相似文献
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Matthias Waechter Falk Riess Norbert Zacharias 《Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility》2002,37(1):3-28
The paper describes a two-dimensional mathematical model for the motion of a bicycle-rider system with wheel suspensions. It focusses on the prediction of vibrational stress on the rider due to uneven track. The model was evaluated by comparing its predictions with measuring data concerning weighted accelerations on the human body, depending on various bicycle designs and road surfaces. For the intended purpose the predictions for vibrational stress and vibrational behaviour are sufficiently precise, and the model turns out to be adequate for designing and developing bicycle suspensions. 相似文献
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针对轻型载货车的悬架设计,提出一种有效的设计方案。该方案包括弹性元件和阻尼元件的设计过程。同时对设计方案进行了仿真分析及台架试验,以检验方案的可靠性。汽车悬架系统作为保证车轮或车桥与汽车承载系统之间具有弹性联系并能传递载荷、缓和冲击、衰减振动以及调节汽车行驶中的车身位置的装置,对整车性能指标很大的影响。 相似文献
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基于圆管的吸能原理,采用铝质筒元作为吸能元件,研究筒元轴向与径向承载的不同变形模式,以及不同排列方式筒系结构对被撞横梁的缓冲性能的改善效果。试验和模拟计算结果表明,筒系吸能结构能明显降低与横梁碰撞的台车的减速度值,提高横梁的能量吸收能力,缓冲效果显著。 相似文献
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越野车油气悬架的建模与试验研究 总被引:1,自引:0,他引:1
《汽车工程》2015,(8)
在考虑沿程压力损失、局部压力损失和活塞杆与密封装置间的动摩擦等情况下,建立了某越野车用油气悬架非线性模型。通过仿真,研究阻尼阀系的参数对油气悬架阻尼特性的影响。结果表明,在其他参数不变的情况下,可通过更换具有不同锥角的阀芯,方便地获得不同的阻尼特性。仿真结果与试验数据基本吻合,验证了所建油气悬架数学模型的正确性。 相似文献
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《Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility》2012,50(5-6):321-334
SUMMARY The performance of neural networks to be used for identification and optimal control of nonlinear vehicle suspensions is analyzed. It is shown that neuro-vehicle models can be efficiently trained to identify the dynamical characteristics of actual vehicle suspensions. After trained, this neuro-vehicle is used to train both front and rear suspension neuro-controllers under a nonlinear rear preview control scheme. To do that, a neuro-observer is trained to identify the inverse dynamics of the front suspension so that front road disturbances can be identified and used to improve the response of the rear suspension. The performance of the vehicle with neuro-control and with LQ control are compared. 相似文献