Intelligent approach for parallel HEV control strategy based on driving cycles

Abstract

This article describes a methodological approach for the intelligent control of parallel hybrid electric vehicle (HEV) by the inclusion of the concept of driving cycles. In this approach, a fuzzy logic controller is designed to manage the internal combustion engine to work in the vicinity of its optimal condition instantaneously. In addition, based on the definition of microtrip, several driving patterns are classified that represent the congested to highway traffic conditions. The driving cycle and traffic conditions are then incorporated in an optimisation process to tune the fuzzy membership function parameters. In this study, the optimisation process is formulated to minimise the HEV fuel consumption (FC) and emissions as well as the satisfaction of the driving performance constraints. Finally, optimisation results are provided for three different driving cycles including ECE-EUDC, FTP and TEH-CAR. TEH-CAR is a driving cycle that is developed based on the experimental data collected from the real traffic condition in the city of Tehran. The results from the computer simulation show the effectiveness of the approach and reduction in FC and emissions while ensuring that the vehicle performance is not sacrificed.