Title: Optimal gain scheduling control strategy for parallel HEV based on traffic conditions

Authors: Amir Poursamad

Addresses: Department of Mechanical Engineering, Iran University of Science and Technology, Narmak, Tehran, 16844, Iran.

Abstract: This paper presents gain scheduling of control strategy for parallel hybrid electric vehicles, based on traffic conditions. Electric assist control strategy (EACS) is employed, with different parameters for different traffic conditions. The parameters of the EACS are optimised and scheduled for different traffic conditions of the TEH-CAR driving cycle. TEH-CAR is a driving cycle which is developed, based on the experimental data collected from the real traffic conditions in the city of Tehran. The objective of the optimisation is to minimise the fuel consumption and emissions over the driving cycle, while enhancing or maintaining the driving performance characteristics of the vehicle. A genetic algorithm (GA) is used to solve the optimisation problem, and the constraints are handled by using penalty functions. The results from the computer simulation show the effectiveness of the approach and reduction in fuel consumption and emissions, while ensuring that the vehicle performance is not sacrificed.

Keywords: control strategy; gain scheduling; genetic algorithms; GAs; hybrid electric vehicles; optimisation; traffic conditions; optimal control; parallel HEV; fuel consumption; emissions; vehicle performance.

DOI: 10.1504/IJEHV.2008.019898

International Journal of Electric and Hybrid Vehicles, 2008 Vol.1 No.3, pp.221 - 237

Published online: 14 Aug 2008 *

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