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基于双子乳化剂的微乳化柴油配比优化
引用本文:周海杰,陈振斌,邓小康,谢荣富,李菲.基于双子乳化剂的微乳化柴油配比优化[J].车用发动机,2016(6):12-18.
作者姓名:周海杰  陈振斌  邓小康  谢荣富  李菲
作者单位:海南大学机电工程学院,海南 海口,570228
基金项目:海南大学科研基金资助项目(kyqd1657)
摘    要:为了研究双子乳化剂对微乳化柴油稳定性的影响,以 Minitab 软件设计单因素试验、Plackett‐Burman 试验、爬坡试验、Box‐Behnken 试验,通过 Box‐Behnken 试验数据,建立响应面模型,通过 Minitab 软件中的寻优模块,对试验结果寻优,得到最优的试验配方(体积分数):复配乳化剂比例2.13%,蓖麻油比例1.02%,柴油比例80.85%, HLB 值6.56,葡萄糖水溶液16%,溶液中葡萄糖质量分数18.68%。试验结果表明:利用双子乳化剂制备的微乳化柴油稳定时间为292.6 h ,通过试验验证得到的稳定时间为286 h ,与理论误差为4.7%,较传统乳化剂稳定时间提高大约10%,复配乳化剂的比例减少12%,助溶剂比例减少5%,溶液中的葡萄糖比例提高9%,且制备的微乳化柴油颜色澄清透明。

关 键 词:柴油  乳化燃料  双子乳化剂  稳定性  制备  参数优化

Optimization of Formula on Micro-emulsified Diesel Based on Gemini Emulsifier
ZHOU Haijie,CHEN Zhenbin,DENG Xiaokang,XIE Rongfu,LI Fei.Optimization of Formula on Micro-emulsified Diesel Based on Gemini Emulsifier[J].Vehicle Engine,2016(6):12-18.
Authors:ZHOU Haijie  CHEN Zhenbin  DENG Xiaokang  XIE Rongfu  LI Fei
Abstract:In order to study the effects of gemini emulsifier on the stability of emulsified diesel ,the single factor test ,Placket Burman test ,Slope‐climbing test and Box Behnken test were designed with Minitab software .The response surface model was built based on Box‐Behnken test data and the optimal test formula was acquired with the best value searching module of Minitab software .The ingredients of 2 .13% compound emulsifier ,1 .02% castor oil ,80 .85% diesel and 16% glucose aqueous solution (18 .68% mass fraction of glucose) and the HLB value of 6 .56 formed the optimal formula of emulsified solution .The results showed that the only 4 .7% difference between 292 .6 h theoretical stability time and 286 h testing stability time proved the sta‐bility of prepared micro‐emulsified diesel .Compared with the traditional emulsifier ,the stability time improved by 10% ,the proportion of compound emulsifier and cosolvent reduced by 12% and 5% respectively ,the amount of dissolved glucose in‐creased by 9% ,and the prepared emulsified diesel was more transparent .
Keywords:diesel  emulsified fuel  gemini emulsifier  stability  preparation  parameter optimization
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