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Optimization of Fuel-Efficient Driving Strategies for the Freeway Vehicle
|關鍵字:||ADVISOR;ADVISOR;driving strategy;freeway vehicle;fuel efficiency;MAX-MIN ant system;駕駛策略;高速公路車輛;節能;最大－最小螞蟻系統||出版社:||電機工程學系所||引用:|| L. R. Brown, Plan B 4.0 Mobilizing to Save Civilization: W. W. Norton & Company, 2009.  K. McGuffie and A. Henderson-Sellers, A Climate Modelling Primer, 3rd ed.: John Wiley & Sons, Inc, 2005.  T. H. Ortmeyer and P. Pillay, "Trends in Transportation Sector Technology Energy Use and Greenhouse Gas Emissions," Proceedings of the IEEE, vol. 89, pp. 1837-1847, December 2001.  N. Unger, D. T. Shindell, and J. S. Wang, "Climate forcing by the on-road transportation and power generation sectors," Atmospheric Environment, vol. 43, pp. 3077-3085, 2009.  N. Unger, T. C. Bond, J. S. Wang, D. M. Koch, S. Menon, D. T. Shindell, and S. Bauera, "Attribution of Climate Forcing to Economic Sectors," Proceedings of the National Academy of Sciences of the United States of America, vol. 107, pp. 3382-3387, February 2010.  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In the recent years, global warming has been becoming a serious problem to environment. The green house gas emitted by contributors is one of the major factors, especially, from transportation vehicles. Especially, the road transportation is the largest sector of transportation fuel consumption. To improve the fuel efficiency of freeway vehicles, the method for optimizing the driving strategies based on speed and acceleration commands is proposed.
The decision-making problem of driving strategies is transformed as a combinatorial optimization problem by equally dividing the route into the given number of sections and using speed and acceleration commands. A MATLAB-based simulation software ADVISOR is used to calculate fuel consumption under different operation commands for each section. The simulation results are built in a lookup table for reducing the computation time of optimization procedure. The MAX-MIN ant system algorithm is used to optimize the fuel-efficient driving strategies. A real route model is considered for the optimization experiments. A variety of case studies are optimized by the proposed algorithm by considering different parameters, driving strategies, speed limits, etc. Comparing the fuel-efficient driving strategy to the highest speed driving strategy, it is found that the fuel consumption is reduced in the range of 4 to 13.8 %. In each case study, the capability of optimization driving strategy that for improving fuel economy is shown.
|Appears in Collections:||電機工程學系所|
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