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通过软计算技术 (ANFIS-NSGA-II和RSM) 建模压缩点火发动机,以提高含纳米添加剂的液混合物的性能特性

Osama Khan¹, Mohd Parvez², Pratibha Kumari³

¹Department of Mechanical Engineering, Jamia Millia Islamia, New Delhi, 110025, India.

Scientific reports

|September 18, 2023

概括

将纳米粒子集成到废油生物柴油中可以提高发动机性能并减少排放. 非排序基因算法II (NSGA-II) 模型展示了优越的预测能力,可以优化燃料效率和排气特性.

科学领域:

可持续的燃料和能源
内部燃烧发动机内部燃烧发动机
纳米技术应用纳米技术应用

背景情况:

废油衍生生物柴油为内燃机提供可持续的替代燃料来源.
纳米粒子可以充当燃烧催化剂,提高燃料性能并减少对环境的影响.
优化发动机参数对于最大限度地利用纳米粒子增强生物柴油的好处至关重要.

研究的目的:

调查输入参数对纳米粒子增强废油生物柴油性能和排气特性的影响.
为了比较智能混合模型的预测准确度,包括ANFIS,RSM-GA和NSGA-II.
确定最佳的发动机运行条件,以提高热效率和减少排放.

主要方法:

对生物柴油发动机性能进行了定量和定性分析.
使用智能混合预测模型,包括自适应神经模糊推理系统 (ANFIS),响应表面方法-遗传算法 (RSM-GA) 和非排序遗传算法II (NSGA-II).
发动机负载,混合率,纳米添加剂度和注入压力各不相同,测量了制动热效率,制动特定能耗和排放量.

主要成果:

在预测准确度方面,NSGA-II模型显著超过ANFIS和RSM-GA.
NSGA-II实现了帕雷托最佳前部,确定了发动机性能和排放的最佳值.
确定了制动热效率 (24.45千瓦),制动特定能耗 (2.76),氧化 (159.54 ppm),未燃烧的碳化合物 (4.68 ppm) 和一氧化碳 (0.020243%) 的特定最佳值.

结论:

在废油生物柴油中纳米粒子集成是提高发动机性能和可持续性的可行策略.
该NSGA-II模型为优化纳米粒子增强生物柴油发动机参数提供了卓越和可靠的方法.
将ANFIS预测精度与NSGA-II优化相结合,为现实世界引擎应用提供了强大的方法.

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