Multi-variable optimization of diesel engine fuelled with biodiesel using grey-Taguchi method

Pakistan is currently facing the crises of rising prices of fossil fuel and serious environmental threats. Being an agricultural country, it has a great potential of producing biodiesel. Nowadays biodiesel is gaining considerable attentions as a substitute fuel owing to its renewable, biodegradable, environmentally acceptable, readily available, miscible, and clean burning characteristics [1]. It has the potential to reduce both regulated and unregulated emissions without much disturbance to the engine performance by virtue of its better combustion in the combustion chamber [2–4].

Diesel engines are widely used to power the agricultural pumps and other machinery, heavy-duty transport vehicles, construction machinery, and even to generate electricity. The energy crisis caused by the ever increasing demand of fossil fuels and the progressive tightening of emission standards have converged the attentions of the researchers of automotive industry to explore the alternative fuels for the compression ignition (CI) engines. Consequently, many efforts have been made in this field during the last couple of decades to decrease not only the exhaust emissions but also improve the thermal efficiency of the engines [5, 6]. It has been reported in the literature that a CI engine can perform adequately with biodiesels without any modification in the engine hardware because performance parameters are almost similar to that with fossil diesel [7–10].

The increasing demands of higher efficiency with reduced exhaust emissions have, therefore, led to recognize the parameters which may affect the performance and combustion phenomena of the engine. Fortunately, some optimization techniques are available in the literature which may be used to predict the engine behavior and thus to improve its efficiency. The most widespread optimization approach used for engine analysis is Taguchi method.