Search

In this work, a control strategy is presented to produce hydrogen on demand to feed an internal combustion (IC) engine. For this purpose, the modeling of the IC engine fueled by gasoline blended with 10% v/v of anhydrous ethanol (E10) and hydrogen as an additive is developed. It is considered that the hydrogen gas is produced according to the IC engine demand, and that the hydrogen gas is obtained by an alkaline electrolyzer. The gasoline-ethanol blend added into the combustion chamber is determined according to the stoichiometric ratio and the production of hydrogen gas is regulated by a proportional and integral controller (P.I.). The controller reference is varying according to the mass flow air induced into the cylinder, in order to ensure an adequate production of hydrogen gas for any operating condition of the IC engine. The main contribution of this work is the control scheme developed, through simulation, in order to produce hydrogen on demand for any operating point of an internal combustion engine fueled by an E10 blend. The simulation results showed that the use of hydrogen gas as an additive in an E10 blend decreases the E10 fuel consumption 23% on average, and the thermal efficiency is increased approximately 2.13%, without brake power loss in the IC engine. [ABSTRACT FROM AUTHOR]

This work presents the design and application of two control techniques—a model predictive control (MPC) and a proportional integral derivative control (PID), both in combination with a multilayer perceptron neural network—to produce hydrogen gas on-demand, in order to use it as an additive in a spark ignition internal combustion engine. For the design of the controllers, a control-oriented model, identified with the Hammerstein technique, was used. For the implementation of both controllers, only 1% of the overall air entering through the throttle valve reacted with hydrogen gas, allowing maintenance of the hydrogen–air stoichiometric ratio at 34.3 and the air–gasoline ratio at 14.6. Experimental results showed that the average settling time of the MPC controller was 1 s faster than the settling time of the PID controller. Additionally, MPC presented better reference tracking, error rates and standard deviation of 1.03 × 10 − 7 and 1.06 × 10 − 14 , and had a greater insensitivity to measurement noise, resulting in greater robustness to disturbances. Finally, with the use of hydrogen as an additive to gasoline, there was an improvement in thermal and combustion efficiency of 4% and 0.6%, respectively, and an increase in power of 545 W, translating into a reduction of fossil fuel use. [ABSTRACT FROM AUTHOR]