Evolutionary Optimization of Parametric Models: the Test Case of Combustion in a Diesel Engine

Abstract

The tuning of parameter values in parametric modelling can be viewed as an optimization problem where the outcome of the optimal model is to be as similar as possible to the experimental data. We give a general formulation of the problem with different fitness function definitions, both in terms of single-objective and multi-objective evolutionary optimization. As a test case we show results on a parametric model of combustion in a combustion chamber of a diesel engine. Such an optimal model will therefore be used for a controller design. The outputs (pressure inside combustion chamber versus rotation angle) of the resulting optimal models are compared to experimental data. Results of different optimization runs with Differential Evolution (DE) and Evolution Strategy (ES) as search algorithms and with different fitness definitions are compared.