Resumen de Gear shifting multi-objective optimization to improve vehicle performance, fuel consumption, and engine emissions
Jony Javorski Eckert, Fabio Mazzariol Santiciolli, Elvis Bertoti, Eduardo dos Santos Costa, Fernanda Cristina Corrêa, Ludmila Corrêa de Alkmin e Silva, Franco Giusepe Dedini
In the present work, the Adaptive-Weight Genetic Algorithm was employed in order to determine the gear shifting strategies that allow an automobile to work in the best compromise among fuel consumption, engine emissions, and vehicle performance. For the assessment of each of the three objective functions, a simulation model based on engine data and on the well-established equations of the longitudinal dynamics was developed. The driving cycle chosen for the calculations was the FTP-75, which takes into account both cold and hot starts, meaning that the transient operation during the warm-up of the catalyst is also considered.
