940 resultados para Corporate Average Fuel Economy (CAFE) standards


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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

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To maintain its relevance, motorsport cannot be exempt from
the trend of increasing fuel economy. This bears obvious
competitive benefits as well, either in decreasing the
frequency of pit stops or the mass of fuel carried. Given the
increased points weighting of fuel economy for the Formula
Student (FS) competition, a complete analysis was performed
on the Queen's Formula Racing 600cc motorcycle engine in
preparation for the 2011 competition.
The criteria for such high performance fuel economy differ to
a degree from most mass transportation counterparts and were
divided into three distinct regimes; full load, part load and no
load conditions.
Full load positions naturally demand maximum torque for
performance but that does not imply that fuel savings cannot
be made whilst preserving this. The point at which maximum
torque is produced with minimum air -fuel ratio, Leanest
mixture for Best Torque (LBT), was therefore sought and
mapped for full load.
At part load, torque is less of a concern, and maintaining a
sustainable engine temperature and transient response become
more important. With decreasing AFR, engine temperatures
can rise dramatically so temperatures were measured close to
the exhaust port for a wide range of air-fuel ratios.
Competition track data was analysed to highlight key part load
operating regions and these were mapped according to
measured safe temperature limits. Torque response to a step
throttle change was also measured to ensure suitable engine
transient performance was maintained.
At no load conditions, with low engine speed only idle
conditions need to be satisfied. In the situation where the
engine is still at high speed without load, the engine is being
motored and no fuel is required. An overrun fuel cut was
employed to reflect this giving significant fuel savings. The
effect on torque and engine pickup was measured.
Modifications were also made to the fuel injector location to
improve fuel mixing and evaporation at this lower air flow
condition.
These mapping regimes were implemented and tested using
fully transient lap simulations using competition track data
and a four quadrant AC engine dynamometer. The experiment
indicated a reduction in fuel consumption for 22 laps of the FS
track from 5.08litres to 3.67litres, around 27% in total. The
actual fuel used at the 2011 competition was 3.6 litres while
placing 8th in the endurance event, further validating the
benefits of these mapping regimes.

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Globally vehicle operators are experiencing rising fuel costs and increased
running expenses as governments around the world attempt to decrease carbon dioxide emissions and fossil fuel consumption, due to global warming and the drive to reduce dependency on fossil fuels. Recent advances in hybrid vehicle design have made great strides towards more efficient operation, with regenerative braking being widely used to capture otherwise lost energy. In this paper a hybrid series bus is developed a step further, by installing another method of energy capture on the vehicle. In this case, it is in the form of the Organic Rankine Cycle (ORC). The waste heat expelled to the exhaust and coolant streams is recovered and converted to electrical energy which is then stored in the hybrid vehicles batteries. The electrical energy can then be used for the auxiliary power circuit or to assist in vehicle propulsion, thus reducing the load on the engine, thereby improving the overall fuel economy of the vehicle and reducing carbon dioxide emissions.

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National Highway Traffic Safety Administration, Technology Assessment Division, Washington, D.C.

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First edition, 1914, has title: Fuel economy and CO₂ recorders.

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In the world, scientific studies increase day by day and computer programs facilitate the human’s life. Scientists examine the human’s brain’s neural structure and they try to be model in the computer and they give the name of artificial neural network. For this reason, they think to develop more complex problem’s solution. The purpose of this study is to estimate fuel economy of an automobile engine by using artificial neural network (ANN) algorithm. Engine characteristics were simulated by using “Neuro Solution” software. The same data is used in MATLAB to compare the performance of MATLAB is such a problem and show its validity. The cylinder, displacement, power, weight, acceleration and vehicle production year are used as input data and miles per gallon (MPG) are used as target data. An Artificial Neural Network model was developed and 70% of data were used as training data, 15% of data were used as testing data and 15% of data is used as validation data. In creating our model, proper neuron number is carefully selected to increase the speed of the network. Since the problem has a nonlinear structure, multi layer are used in our model.

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Publisher PDF

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National Highway Traffic Safety Administration, Washington, D.C.

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National Highway Traffic Safety Administration, Washington, D.C.

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National Highway Traffic Safety Administration, Washington, D.C.

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For the past three decades the automotive industry is facing two main conflicting challenges to improve fuel economy and meet emissions standards. This has driven the engineers and researchers around the world to develop engines and powertrain which can meet these two daunting challenges. Focusing on the internal combustion engines there are very few options to enhance their performance beyond the current standards without increasing the price considerably. The Homogeneous Charge Compression Ignition (HCCI) engine technology is one of the combustion techniques which has the potential to partially meet the current critical challenges including CAFE standards and stringent EPA emissions standards. HCCI works on very lean mixtures compared to current SI engines, resulting in very low combustion temperatures and ultra-low NOx emissions. These engines when controlled accurately result in ultra-low soot formation. On the other hand HCCI engines face a problem of high unburnt hydrocarbon and carbon monoxide emissions. This technology also faces acute combustion controls problem, which if not dealt properly with yields highly unfavorable operating conditions and exhaust emissions. This thesis contains two main parts. One part deals in developing an HCCI experimental setup and the other focusses on developing a grey box modelling technique to control HCCI exhaust gas emissions. The experimental part gives the complete details on modification made on the stock engine to run in HCCI mode. This part also comprises details and specifications of all the sensors, actuators and other auxiliary parts attached to the conventional SI engine in order to run and monitor the engine in SI mode and future SI-HCCI mode switching studies. In the latter part around 600 data points from two different HCCI setups for two different engines are studied. A grey-box model for emission prediction is developed. The grey box model is trained with the use of 75% data and the remaining data is used for validation purpose. An average of 70% increase in accuracy for predicting engine performance is found while using the grey-box over an empirical (black box) model during this study. The grey-box model provides a solution for the difficulty faced for real time control of an HCCI engine. The grey-box model in this thesis is the first study in literature to develop a control oriented model for predicting HCCI engine emissions for control.

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Mode of access: Internet.

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National Highway Traffic Safety Administration, Technology Assessment Division, Washington, D.C.

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National Highway Traffic Safety Administration, Technology Assessment Division, Washington, D.C.