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使用基于灰色理论的田口法对使用含添加剂的不同燃料的柴油机进行多目标优化。

Multi-objective optimization of a diesel engine fueled with different fuel types containing additives using grey-based Taguchi approach.

机构信息

Department of Mechanical Engineering, Faculty of Engineering, Karabük University, Karabük, Turkey.

Nigde Vocational School of Technical Sciences, Nigde Omer Halisdemir University, Nigde, Turkey.

出版信息

Environ Sci Pollut Res Int. 2022 Apr;29(20):30277-30284. doi: 10.1007/s11356-021-18012-1. Epub 2022 Jan 8.

Abstract

Due to the reduction of fossil fuels' resources and their contribution to environmental problems, biodiesel fuels have attracted significant attention as substitutes for diesel fuels. However, since their NO emissions are higher than that of diesel fuels in most cases and also because of their higher viscosity than diesel, fuel additives are used to enhance their properties and reduce emissions. In this study, the effect of n-hexane and n-hexadecane addition to biodiesel and diesel fuels on exhaust emissions and performance of a single-cylinder diesel engine was investigated by using grey-based Taguchi method. Fuel additive, the additive amount, and fuel type were considered as the operating parameters. Three fuel types including diesel, rapeseed oil biodiesel, and cottonseed oil biodiesel were used in this investigation, while n-hexane and n-hexadecane were considered as the two fuel additives. As well as, three levels were assigned to the additive amount which were 4, 8, and 12%. Based on the operating parameters and their levels, the plan of experiments was generated according to L orthogonal array. Using grey relational analysis, this multi-response optimization problem was first transformed into a single response optimization. Then, this single system response, which is known as grey relational grade, was utilized in Taguchi approach for statistical evaluations. The results demonstrated that rapeseed was the best selection for fuel type compared to cottonseed and diesel in order to have the optimum system responses and hexadecane gave better results for system optimization in comparison with hexane additive. As well as, the analysis of variance showed that fuel type was the predominant operating factor influencing the grey relational grade which means fuel type was the most important parameter in the simultaneous optimization of exhaust emissions and engine performance. The Taguchi results also revealed that the optimum condition of engine performance and exhaust emissions happened when engine was fueled with rapeseed biodiesel containing 12% hexadecane as an additive. The confirmation test result validated the reliability of Taguchi approach in this investigation.

摘要

由于化石燃料资源的减少及其对环境问题的贡献,生物柴油作为柴油燃料的替代品引起了极大的关注。然而,由于生物柴油的氮氧化物排放通常高于柴油,而且粘度高于柴油,因此需要使用燃料添加剂来改善其性能并减少排放。在这项研究中,使用基于灰色关联度的田口方法研究了正己烷和正十六烷添加到生物柴油和柴油燃料中对单缸柴油机排放和性能的影响。燃料添加剂、添加剂用量和燃料类型被视为操作参数。本研究使用了三种燃料类型,包括柴油、菜籽油生物柴油和棉籽油生物柴油,而正己烷和正十六烷被视为两种燃料添加剂。此外,添加剂用量被分配到三个水平,分别为 4%、8%和 12%。根据操作参数及其水平,根据 L 正交数组生成实验计划。通过灰色关联分析,首先将这个多响应优化问题转化为单响应优化。然后,这个单一的系统响应,即灰色关联度,被用于田口方法进行统计评估。结果表明,与棉籽油和柴油相比,菜籽油是燃料类型的最佳选择,以便获得最佳的系统响应,而与正己烷添加剂相比,正十六烷为系统优化提供了更好的结果。此外,方差分析表明,燃料类型是影响灰色关联度的主要操作因素,这意味着在同时优化排放和发动机性能方面,燃料类型是最重要的参数。田口结果还表明,当发动机使用含有 12%正十六烷添加剂的菜籽油生物柴油作为燃料时,发动机性能和排放的最佳条件发生。验证试验结果验证了田口方法在本研究中的可靠性。

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