Research on the optimizing control technology based on fuzzy-neural network for hydrogen-fueled engines

Hydrogen fuel is regarded as one of the most promising alternative fuels for automobiles in future. Technology of the optimum control on hydrogen-fueled engines is a key to improve its performances in every respect. In this paper, based on the experiments, the policy of optimum control on hydrogen-fueled engines has been shown. Moreover, a new optimizing control model on hydrogen-fueled engines has been constructed, in which ignition timing, injection timing and injection duration were separately selected as control variation, and output power and rate of fuel consumption are separately chosen as performance index function. Further, a new method ingeniously adopting fuzzy-neural network (FNN) system to calculate the optimizing control laws for the optimizing control model has been designed, and a series connection control system has been set up, which is composed of FNN controllers combined with an adaptive controller for ignition timing to realize open-loop or closed-loop control pattern with stepping regulation of ignition timing. Last, the calculated results of the control variations with an improved FNN system were contrasted with experimental results; the contrasting result has shown that the maximum absolute error is less than 1 °C A, the maximum relative error is less than 5%, mean square error is 0.381 °C A. Therefore, the calculation method with FNN system is practical and satisfactory.