Numerical and experimental investigation of fuel consumption and CO2 emission performance for a parallel hybrid vehicle

In this study, fuel consumption map was created by obtaining a large number of data from gasoline engine passenger car through high-speed data acquisition with ISO-15765-4-CAN Protocol. Subsequently, CO2 map was also generated theoretically. To obtain precise results, ANN was used while creating the maps. Later, conventional vehicle model was created with Matlab/Simulink. Afterwards, hybrid vehicle model was developed by implementing electrical system in compliance with single-shaft pre-transmission parallel configuration with one electric motor. Hybrid powertrain control algorithm was created by considering efficiencies of mechanical and electrical power sources and sinks. Charge-neutral simulations were run with conventional and hybrid models over WLTC and a local route which is created by collected in-city speed data. The hybrid and conventional vehicles were enabled to be compared with the developed method. Detailed comparison of ICE operations both between two vehicle models and two cycles was presented. Moreover, obtained results, including overall electrical system efficiencies, were compared over WLTC and the local route. Significant improvements both in consumption and CO2 values were concluded. It is also concluded that using the hybrid system in local route with higher proportion of in-city driving conditions caused higher improvements despite a slight decrease in overall electrical system efficiency. (C) 2021 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).

Automated summary

In this study, fuel consumption and CO2 maps were created using high-speed data acquisition and artificial neural networks. Hybrid and conventional vehicle models were compared on different routes, showing higher improvements with the hybrid system in urban conditions.