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Technical Paper

Maximizing FCEV Stack Cooling Performance: Developing a Performance Prediction Model Based on Machine Learning for Evaporative Cooling Radiator

2024-04-09
2024-01-2586
Recently, regulations on automobile emission have been significantly strengthened to address climate change. The automobile industry is responding to these regulations by developing electric vehicles that use batteries and fuel-cells. Automobile emissions are environmentally harmful, especially in the case of vehicles equipped with high-temperature and high-pressure diesel engines using compression-ignition, the proportion of nitrogen oxides (NOx) emissions reaches as high as 85%. Additionally, air pollution caused by particulate matter (PM) is six to ten times higher compared to gasoline engines. Therefore, the electrification of commercial vehicles using diesel engines could potentially yield even greater environmental benefits. For commercial vehicles battery electric vehicles (BEVs) require a large number of batteries to secure a long driving range, which reduces their maximum payload capacity.
Technical Paper

Vehicle Design Parameter Study for Side Impacts Using Full- Vehicle Simulation

1998-05-31
986174
This paper describes a study that was conducted to determine sensitivity of several design factors for reducing injury values of occupants upon side impact using Taguchi method. The full mid-sized vehicle finite element model is used for the analysis under two different side impact standards~SINCAP and ECE-R 95. The design factors that may have major effect on side impacts were selected and L8 orthogonal array was set up for analysis. Analysis results show that strengthening the passenger compartment improves occupant protection, especially adding a pusher foam is significantly lowering the injury values in SINCAP. No single factor has major effects on rib deflection which is considered as critical occupant injury criterion in ECE- R 95. Taguchi method was found to be a useful tool, although its usage may be limited in crash analysis, for predicting the effect of various design factors on structure.
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