Optimum fuzzy logic controller applied to a hybrid hydraulic vehicle to minimize fuel consumption and emissions

Abstract

This paper aims to combine the hydraulic hybrid vehicle (HHV) architecture with optimum fuzzy logic control. Besides the expressive fuel savings of the HHV in urban routes, the engine intermittent operation with on–off control may delay the catalyst system warm-up, resulting in a higher level of emissions. Therefore, this study presents a multi-objective optimization in which the HHV drivetrain parameters are optimized, simultaneously with the fuzzy logic membership functions, defuzzification method, rules and weights, aiming to reach a trade-off among fuel savings and the minimization of the tailpipe emissions. To ensure feasible solutions, the engine simulation was based on the ADVISOR™ fuel converter block, which is a well-known tool applied in several similar works. The optimization procedure was carried out under the FTP-72 standard driving cycle, in which the HHV was able to reduce 13.07% HC, 10.55% CO, and 4.74% NOx emissions with 35.67% fuel savings, as compared to a conventional vehicle with similar characteristics and engine. Moreover, the optimized HHV was also evaluated under 3 different real-world driving cycles, resulting in fuel savings up to 43.06% and emissions below the conventional vehicle in all analyzed scenarios.