화학공학소재연구정보센터
Energy Conversion and Management, Vol.71, 217-226, 2013
LHV predication models and LHV effect on the performance of CI engine running with biodiesel blends
The heating value of fuel is one of its most important physical properties, and is used for the design and numerical simulation of combustion processes within internal combustion (IC) engines. Recently, there has been a significant increase in the use of dual fuel and blended fuels in compression ignition (Cl) engines. Most of the blended fuels include biodiesel as one of the constituents and hence the objective of this study is to investigate the effect of biodiesel content to lower heating value (LHV) and to develop new LHV prediction models that correlate the LHV with biodiesel fraction, density and viscosity. Furthermore, this study also investigated the effects of the LHV on Cl engines performance parameters experimentally. To achieve the above mentioned objectives density, viscosity and LHV of rapeseed oil biodiesel, corn oil biodiesel and waste oil biodiesel at different blend fraction values (B0, B5, B10, B20, B50, B75, and B100, where 'B5' denotes a blend of 5% biodiesel and 95% mineral diesel, etc.) were measured as per EN ISO 3675:1998, EN ISO 3104:1996 and DIN 51900 standards. The engine experimental work was conducted on a four-cylinder, four-stroke, direct injection (DI) and turbocharged diesel engine by using rapeseed oil and normal diesel blends. Based on the experimental results, models were developed which have the capability to predict the LHV corresponding to different fractions, densities and viscosities of biodiesel. The models are shown to produce consistent results with experimentally measured ones and compared with previous researches' models. Furthermore the effects of LHV on brake specific fuel consumption (BSFC) and thermal efficiency were analysed and it has been seen that for the neat biodiesel which its LHV is lower by 8% than diesel resulted in an increment of BSFC and thermal efficiency by 18% and 25% respectively. (C) 2013 Elsevier Ltd. All rights reserved.