Open AccessFuzzy gear shifting control optimisation to improve vehicle performance, fuel consumption and engine emissions
Author(s) -
Eckert Jony Javorski,
Santiciolli Fabio M.,
Yamashita Rodrigo Y.,
Corrêa Fernanda C.,
Silva Ludmila C.A.,
Dedini Franco G.
Publication year - 2019
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2018.6272
Subject(s) - fuel efficiency , automotive engineering , fuzzy logic , matlab , acceleration , engineering , control theory (sociology) , fuzzy control system , reduction (mathematics) , crank , computer science , control (management) , mathematics , physics , mechanical engineering , geometry , cylinder , artificial intelligence , classical mechanics , operating system
This study presents a multiobjective optimisation applied to the gear shifting fuzzy control of a vehicle equipped with an automated manual transmission (AMT), aiming to improve acceleration performance and reduce engine fuel consumption and emissions. An Adaptive‐Weight Genetic Algorithm was employed to find optimum fuzzy membership functions, according to the input and output ranges, and also optimum control rules with their respective weights. The vehicle behaviour is represented by longitudinal dynamics simulations developed in Simulink/Matlab ™ interface, associated with the ADVISOR ™ fuel converter block, that provides the engine emissions and fuel consumption. These simulations were based on the FTP‐75 emissions test procedure, that considers cold and hot phases of the driving cycle evaluating the engine transient operation as a function of the catalyst efficiency during the warm‐up period. The optimum fuzzy control with the best trade‐off among the optimisation criteria presented 19.72% fuel saving associated with 12.90% hydrocarbon, 29.20% carbon monoxide and 17.02% nitrogen oxides emissions reduction and an acceleration performance improvement when compared to a standard gear shifting procedure for a manual controlled gearbox. Moreover, the optimised fuzzy gear shifting control, improves the relationship between fuel consumption and emissions significantly, when compared to another optimum AMT control based on speed limits only.