Modeling of the Adaptive HHO Controller to Improve Air-Fuel Ratio of Gasoline Engine

In practice, gasoline engine torque is improved using hydrogen-hydrogen-oxygen gas (HHO) supplementation, which adheres to the fixed HHO flow rate method. However, the arising hypothesis reveals that the fixed HHO flow rate method does not optimally improve an engine’s air-fuel ratio (AFR) for various loads, so engine torque is not optimal. The research aims to propose a model of an adaptive HHO controller, which manages the electric current of the HHO generator so that the produced HHO flow rate adapts to engine speed and load variations. Hence, the AFR is optimal for any engine operation. The Matlab-Simulink-based simulation integrates the models of an adaptive HHO controller, a 1500cc gasoline engine coupled with an HHO generator, and a proportional-integral (PI) engine speed controller. Hence, the research can investigate the improvement of engine torque and AFR error against the commanded AFR due to an adaptive HHO flow rate method. The adaptive HHO controller is designed based on fuzzy logic and polynomial function controls involving real-time engine data, such as AFR, mass airflow (MAF), and the commanded AFR issued by the engine control unit (ECU). The research also compares the results due to the fixed and adaptive HHO flow rates. The results show that the proposed adaptive HHO controller consistently improves the AFR error against the commanded AFR by 100%, so the AFR always meets the commanded AFR for various loads at the commanded AFR = 12.6, 14.7, and 15.4. On the contrary, with the same engine operation, the fixed HHO flow rate provides inferior and uneven AFR error improvement (0%-100%), depending on load and the commanded AFR. As an implication, the adaptive HHO controller improves engine torque by 3.06%-53.6%, better than the fixed HHO flow rate method, improving by 0%-31.42%.