Artificial neural network approach on forecasting diesel engine characteristics fuelled with waste frying oil biodiesel
用废煎炸油生物柴油预测柴油机性能的人工神经网络方法
作者: D. BabuVinoth ThangarasuAnand Ramanathan
作者单位: 1Department of Mechanical Engineering, National Institute of Technology, Trichy, India
刊名: Applied Energy, 2020, Vol.263
来源数据库: Elsevier Journal
DOI: 10.1016/j.apenergy.2020.114612
关键词: Artificial neural networkCombustionCommon rail direct injection systemMethyl esterMultiple injection
英文摘要: Abstract(#br)The present work investigates the influence of advanced injection strategy on a common rail direct injection assisted diesel engine characteristics fuelled with biodiesel and conventional diesel. Also, an artificial neural network is employed to forecast engine characteristics. Engine test is conducted under 100% load condition through an optimized nozzle opening pressure of 500 bar. Pre-injection timing is fixed permanently at 30 °CA bTDC, main injection timing varied from 15 °CA to 21 °CA bTDC and post-injection varied from 6 °CA bTDC to 6 °CA aTDC sequentially. However, the pre, main and post-injection quantities are changed respectively from 5% to 15%, 70% to 90%, and 5% to 15%. Minimum carbon monoxide, unburned hydrocarbon and smoke emission of 0.01% vol., 8 ppm and 1.59...
全文获取路径: Elsevier  (合作)
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影响因子:4.781 (2012)

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关键词翻译
关键词翻译
  • injection 贯入
  • network 网络
  • neural 神经系统的
  • ester 
  • forecasting 预报
  • frying 话筒噪音
  • waste 岩屑
  • engine 发动机
  • approach 
  • system