Title: Intelligent power management of plug-in hybrid electric vehicles, part I: real-time optimum SOC trajectory builder

Authors: Mahyar Vajedi; Maryyeh Chehrehsaz; Nasser L. Azad

Addresses: Systems Design Engineering, University of Waterloo, ON N2L 3G1, Canada ' Systems Design Engineering, University of Waterloo, ON N2L 3G1, Canada ' Systems Design Engineering, University of Waterloo, ON N2L 3G1, Canada

Abstract: Offering better fuel economy and lower emissions than conventional vehicles, plug-in hybrid electric vehicles (PHEVs) are promising near-term options for high efficiency, 'sustainable' transportation. It has recently been found that these efficiency benefits can be further improved with access to upcoming trip and driving conditions. This study is organised into two parts: in part I, upcoming trip data is used to find the optimal SOC trajectory of our PHEV model that will help minimise the total cost of electricity and fossil fuel. In part II, the optimum SOC trajectory is applied within the real-time controller to optimally distribute propulsion power between two energy sources. Autonomie was used to develop and implement a high fidelity PHEV model. The optimal SOC trajectory which has been found by real-time optimisation technique is in close agreement with the global optimum solution of Dynamic Programming. Moreover, the real-time technique is much less computationally expensive.

Keywords: intelligent power management; real-time control; PHEV; plug-in HEVs; hybrid electric vehicles; hybrid vehicles; trip information preview; controller design; fuel economy; dynamic programming; trip preview; battery state of charge; SOC trajectory.

DOI: 10.1504/IJEHV.2014.062807

International Journal of Electric and Hybrid Vehicles, 2014 Vol.6 No.1, pp.46 - 67

Received: 03 Oct 2013
Accepted: 19 Dec 2013
Published online: 18 Jun 2014 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article