Statistical and experimental investigation of the influence of fuel injection strategies on CRDI engine assisted CNG dual fuel diesel engine

被引:21
|
作者
Ramachander, J. [1 ]
Gugulothu, S. K. [1 ]
Sastry, G. Ravikiran [1 ]
Surya, M. Siva [2 ]
机构
[1] Natl Inst Technol Andhra Pradesh, Dept Mech Engn, Tadepalligudem, India
[2] GITAM Univ, Dept Mech Engn, Hyderabad, India
关键词
CNG; Injection timings; Injection pressure; ANOVA; Response surface methodology; Performance and emission; EMISSIONS CHARACTERISTICS; HYDROGEN; COMBUSTION; PERFORMANCE; GAS; IMPACT; PARAMETERS; ENRICHMENT; EFFICIENCY; PRESSURE;
D O I
10.1016/j.ijhydene.2021.04.010
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
With an alarming enlargement in vehicular density, there is a threat to the environment due to toxic emissions and depleting fossil fuel reserves across the globe. This has led to the perpetual exploration of clean energy resources to establish sustainable transportation. Researchers are continuously looking for the fuels with clean emission without compromising much on vehicular performance characteristics which has already been set by efficient diesel engines. In this study, the combustion, performance and emission characteristics of CRDI diesel engine assisted CNG dual fuel research engine operated at constant speed of 1500 rpm with variable engine load (16, 20 and 24 NM) to analyses the influence of fuel injection timings (7.5, 12.5 and 17.5 SOI) and fuel injection pressure (500, 750 and 1000 bar) under reactivity-controlled compression ignition (RCCI) mode. In the case of a fuel injection pressure of 1000 bar, the maximum brake specific fuel consumption of 0.42 kg/kWh is registered with a brake mean effective pressure of 3.2 bar. Response surface methodology has been used in this analysis for predicting the optimal input parameters (engine load, fuel injection timing, and fuel injection pressure), which results in an optimal combination of performance (BP, BTHE, and BSFC) and emission (HC, NOx, and CO) parameters. A variety of optimal solutions based on the desirability method is obtained from the model, and optimal input parameters is suggested as load 20(Nm), injection pressure 750(Bar), and injection timing (BTDC) 12.5. Additionally, to obtain a 'regression model' a statistically significant test (ANOVA) is developed. Results have shown that the suggested 'Regression Model' is best fitted to 0.095 standard deviations, 0.972 corrected R2, and 18.482 acceptable accuracy. (c) 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:22149 / 22164
页数:16
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