推进可再生燃料的整合:为内燃机性能和排放优化提供全面的响应表面方法方法
Johnny Koh Siaw Paw1, Tiong Sieh Kiong1, Mohd Kamal Kamarulzaman2
1Institute of Sustainable Energy, University Tenaga Nasional, Putrajaya Campus, 43000 Kajang, Malaysia.
Heliyon
|December 7, 2023
概括
响应表面方法 (RSM) 有效地模拟了内燃机中的可再生燃料,优化了性能和排放. 这种统计方法有助于评估传统实验分析之外的替代燃料.
科学领域:
- * 内部燃烧发动机技术
- * 可再生能源可再生能源
- * 统计建模 * 统计建模
背景情况:
- * 在内燃机 (ICE) 中对可再生替代燃料的需求不断增长,以减少消耗和排放.
- * 仅仅是实验分析的局限性,以解决复杂的燃烧,性能和排放挑战.
- * 机器学习和RSM等统计方法的引擎建模的重要性日益增加.
研究的目的:
- * 探索响应表面方法 (RSM) 的当代应用,以评估ICE中的可再生替代燃料.
- * 为提供RSM原则和程序的介绍.
- * 综合研究近期替代燃料的应用以及RSM在评估其对燃烧,性能和排放的影响中的作用.
主要方法:
- *应用响应表面方法 (RSM),一种统计技术.
- * 机器学习方法与统计数据的整合.
- *分析使用可再生燃料的发动机的燃烧,性能和排放数据.
主要成果:
- * RSM在发动机建模中促进了增强的分析结果.
- * 该研究详细介绍了各种可再生替代燃料对发动机性能和排放的影响.
- *确定了使用RSM的优点和局限性,以及与其他建模技术集成的可能性.
结论:
- * RSM是评估内燃机中可再生替代燃料的可行性的一个有价值的工具.
- *这项研究有助于了解RSM在优化发动机性能和减少排放方面的有效性.
- *将RSM与其他建模方法相结合,为进一步优化提供了潜力.
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