Title: Look-forward longitudinal dynamic modelling for a series-parallel hybrid electric vehicle

Authors: Mojtaba Shams Zahraei, Seyed Ali Jazayeri, Mahdi Shahbakhti, Mohammad Sharifirad

Addresses: Department of Mechanical Engineering, K.N. Toosi University of Technology, Tehran, Iran. ' Department of Mechanical Engineering, K.N. Toosi University of Technology, Tehran, Iran. ' University of Alberta, Edmonton, Alberta, Canada. ' Iran Heavy Diesel Engine Mfg. Co., Tehran, Iran

Abstract: In this research all components which affect the longitudinal dynamics of a typical series-parallel hybrid electric vehicle have been modelled in MATLAB/SIMULINK1. A look-forward model is developed by coupling an experimentally identified and verified mean value engine model together with longitudinal vehicle dynamic. This model consists of sub-models for power split planetary gear set, permanent magnet synchronous motor/generator with the local controllers, and energy storage system. An energy management strategy has been defined to control the complete model in all vehicle operation modes: pure electric, hybrid, power boost, regenerative braking and engine on/off transient mode. The energy management strategy has been implemented to optimise engine operating conditions. A fuzzy-logic auto-driver model is used to compare the performance of a simulated hybrid vehicle with that of a conventional powertrain in the ECE driving cycle. The simulation results indicate a 40% improvement in fuel economy by converting the conventional vehicle into a series-parallel hybrid vehicle.

Keywords: control strategy; dynamic modelling; hybrid electric vehicles; look-forward models; series-parallel HEVs; hybrid vehicles; longitudinal dynamics; vehicle dynamics; energy management; vehicle control; fuzzy logic; simulation; fuel economy.

DOI: 10.1504/IJEHV.2008.022261

International Journal of Electric and Hybrid Vehicles, 2008 Vol.1 No.4, pp.342 - 363

Available online: 24 Dec 2008

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