使用最优预测模型预测使用纯柴油和氢化植物油的柴油机排放和性能,提高柴油机可靠性

IF 2.2 3区 工程技术 Q2 ENGINEERING, MULTIDISCIPLINARY
Tadas Žvirblis, Jacek Hunicz, Jonas Matijošius, Alfredas Rimkus, Artūras Kilikevičius, Michał Gęca
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引用次数: 0

摘要

内燃机的可靠性成为传统燃料与生物燃料结合的一个重要方面。因此,发展预测模型对于评估和预测内燃机中生物燃料替代传统燃料的情况变得非常重要。采用三级统计回归模型对AVL 5402发动机的排放、振动和声压参数进行了建模。这15个参数可以通过这里给出的一个统计量来准确地预测。由于该分析遵循了方法的对称性,因此考虑了可调整的燃料类型(柴油和HVO)和发动机参数。数据分析过程包括三个不同的步骤,并进行对称统计回归检验。该算法检查了各种发动机设置的有效性。最后,利用最优固定发动机参数和最优统计量构建了ANCOVA模型。ANCOVA模型提高了对所有15个缺失参数的预测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving Diesel Engine Reliability Using an Optimal Prognostic Model to Predict Diesel Engine Emissions and Performance Using Pure Diesel and Hydrogenated Vegetable Oil
The reliability of internal combustion engines becomes an important aspect when traditional fuels with biofuels. Therefore, the development of prognostic models becomes very important for evaluating and predicting the replacement of traditional fuels with biofuels in internal combustion engines. The models have been made to model AVL 5402 engine emission, vibration, and sound pressure parameters using a three-stage statistical regression models. The fifteen parameters might be accurately predicted by a single statistic presented here. Both fuel type (diesel fuel and HVO) and engine parameters that can be adjusted were considered, since this analysis followed the symmetry of the methods. The data analysis process included three distinct steps and symmetric statistical regression testing was performed. The algorithm examined the effectiveness of various engine settings. Finally, the optimal fixed engine parameter and the optimal statistic were used to construct an ANCOVA model. The ANCOVA model improved the accuracy of prediction for all fifteen missing parameters.
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来源期刊
CiteScore
5.70
自引率
24.00%
发文量
55
审稿时长
3 months
期刊介绍: The quarterly Eksploatacja i Niezawodność – Maintenance and Reliability publishes articles containing original results of experimental research on the durabilty and reliability of technical objects. We also accept papers presenting theoretical analyses supported by physical interpretation of causes or ones that have been verified empirically. Eksploatacja i Niezawodność – Maintenance and Reliability also publishes articles on innovative modeling approaches and research methods regarding the durability and reliability of objects.
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