Trend and time series analysis by ARIMA model to predict the emissions and performance characteristics of biogas fueled compression ignition engine

ABSTRACT

Biomass-derived biogas is a very promising alternative energy source because of its renewable and clean combustion characteristics compared to fossil petroleum diesel fuel. The forecasting of emissions and performance characteristics is done by using the autoregressive integrated moving average (ARIMA) model. The R², root mean square error (RMSE), and normalized Bayesian information criterion (BIC) are used to test the validity and applicability of the developed ARIMA models revealing adequate accuracy in the model performance. It is inferred from the experimental results that NO_x and smoke opacity emissions were lower at all engine operating loads. There is an increase in CO, CO₂, and HC emissions at all gas flow rates compared to diesel counterparts. The brake thermal efficiency drops with the increase in biogas flow induction at all engine operating modes. This paper explores and highlights the potential of biogas–diesel dual-fuel combustion mode at different engine operating conditions.

KEYWORDS:

• Biogas
• dual fuel
• emissions
• diesel
• time series analysis
• mathematical modeling

Acknowledgments

The financial assistance extended in the project is gratefully acknowledged.

Additional information

Funding

The research reported here is the part of DST-SERB sponsored project (SB/FTP/ETA-306/2013).