Optimization of an Asynchronous Fuel Injection System in Diesel Engines by Means of a Micro-Genetic Algorithm and an Adaptive Gradient Method 2008-01-0925

Optimal fuel injection strategies are obtained with a micro-genetic algorithm and an adaptive gradient method for a nonroad, medium-speed DI diesel engine equipped with a multi-orifice, asynchronous fuel injection system. The gradient optimization utilizes a fast-converging backtracking algorithm and an adaptive cost function which is based on the penalty method, where the penalty coefficient is increased after every line search. The micro-genetic algorithm uses parameter combinations of the best two individuals in each generation until a local convergence is achieved, and then generates a random population to continue the global search.

The optimizations have been performed for a two pulse fuel injection strategy where the optimization parameters are the injection timings and the nozzle orifice diameters. It is demonstrated that the optimal injection strategies have temporally overlapping fuel pulses and that a smaller nozzle orifice diameter of the second pulse leads to improved fuel efficiency while satisfying the emission standards. Further, in comparison with the micro-genetic algorithm, the optima of the adaptive gradient method have practically the same emissions and fuel consumption but at different engine input parameters. This indicates that, for all practical purposes, there are many identical optimal engine operating points. Also, the gradient-based method is computationally much more efficient, but its solution depends on the starting point.