Modeling automotive palm oil biodiesel engine using multi-objective optimization differential evolution algorithm

Abstract

Modeling automotive palm oil biodiesel engine using the propose algorithm called multi-objective optimization differential evolution (MOODE) is carried out in this paper. The performance of the system is analyzed to study the dynamic behaviors of using biodiesel in running the engine. An adequate modeling of the system is needed to design an exclusive engine controller. The biodiesel engine is treated as a black box where the acquired input-output data is used in the modeling processes. Two objective functions are considered for optimization; minimizing the number of term of a model structure and minimizing the mean square error between actual and predicted outputs. Nonlinear auto-regressive with exogenous input (NARX) model is used to represent the mathematical model of the investigated system. To obtain an optimal model for representing the dynamic behavior of automotive palm oil biodiesel engine, the model validity tests have been applied. Therefore, MOODE can be applied for other processes to find an optimal model structure as long as those processes have reliable input output data.