A study on the 0D phenomenological model for diesel engine simulation: Application to combustion of Neem methyl esther biodiesel. (1st January 2015)

• Record Type: Journal Article
• Authors: Ngayihi Abbe, Claude Valery; Nzengwa, Robert; Danwe, Raidandi; Ayissi, Zacharie Merlin; Obonou, Marcel
• Is Part Of: Energy conversion and management. Volume 89(2015)
• Page Start: 568
• Page End: 576
• Publication Date: 2015-01-01
• Subjects: Diesel -- 0D model -- Neem methyl ester -- Combustion -- Nitric oxides -- Spray; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2014.10.005
• Languages: English
• ISSNs: 0196-8904

Abstract

Highlights: We elaborate a 0D model for prediction of diesel engine operating parameters. We implement the model for Neem methyl ester biodiesel combustion. We show methyl butanoate and butyrate can be used as surrogates for biodiesel. The model predicts fuel spray, in cylinder gaseous state and NOx emissions. We show the model can be effective both in accuracy and computational speed. Abstract: The design and monitoring of modern diesel engines running on alternative fuels require reliable models that can validly substitute experimental tests and predict their operating characteristics under different load conditions. Although there exists a multitude of models for diesel engines, 0D phenomenological models present the advantages of giving fast and accurate computed results. These models are useful for predicting fuel spray characteristics and instantaneous gas state. However, there are few reported studies on the application of 0D phenomenological models on biodiesel fuel combustion in diesel engines. This work reports the elaboration, validation and application on Neem methyl ester biodiesel (NMEB) combustion of a 0D phenomenological model for diesel engine simulation. The model addresses some specific aspects of diesel engine modeling found in previous studies such as the compromise between computers cost, accurateness and model simplicity, the reduction of the number of empirical fitting constant, the prediction of combustion kinetics with reduction of the need of experimental curve fitting, the ability to simultaneously predict under various loads engine thermodynamic and spray parameters as well as emission characteristics and finally the ability to simulate diesel engine parameters when fueled by alternative fuels. The proposed model predicts fuel spray behavior, in cylinder combustion and nitric oxides (NOx) emissions. The model is implemented through a Matlab code. The model is mainly based on Razlejtsev's spray evaporation model, Watson's double Wiebe function and Ferguson's tabulated chemistry thermodynamic cycle algorithm. NOx emissions are implemented in the model using the extended Zeldovich mechanism, heat transfer and ignition delay are also taken into account in the model. Following the validation in different operating points of the model on a four stroke 1 – cylinder direct injection diesel engine, the operating characteristics were predicted with an average error accuracy of about 15%. The relative error is, respectively, 10% for Sauter diameter, 12% for maximum penetration, 9.8% for peak pressure, 7.38% for peak temperature, 10.7% for NOx emission and 13.7% for engine power output. The model predicts higher Sauter mean diameter, higher fuel spray length and NOx emission for NMEB as compared to conventional diesel fuel which is in accordance with experimental results obtained on biodiesel fuels in previous researches. Methyl butyrate and methyl butanoate thermochemical data were used as surrogates for NMEB, the results obtained from the model were close, independently of the surrogate used for biodiesel. The average simulation time for a full cycle simulation was about 94.22 s, which gives to the model applicability for diesel engine optimization purposes. The results obtained were found satisfactory in terms of accuracy, algorithm simplicity and computer cost.