Title: Application of the new SEUMRE global optimisation tool in high efficiency EV/PHEV/EREV electric mode operations

Authors: Adel Younis, Leon Zhou, Zuomin Dong

Addresses: Department of Mechanical Engineering, University of Victoria, P.O. Box 3035, STN CSC, Victoria, British Columbia, V8W 3P6, Canada. ' Department of Mechanical Engineering, University of Victoria, P.O. Box 3035, STN CSC, Victoria, British Columbia, V8W 3P6, Canada ' Department of Mechanical Engineering, University of Victoria, P.O. Box 3035, STN CSC, Victoria, British Columbia, V8W 3P6, Canada

Abstract: Electric vehicles (EV/HEV/PHEV/EREV) draw mechanical power or regenerate electric power using multiple electric motors and generators (M/Gs). To achieve optimal vehicles electrical/mechanical energy conversion efficiency and to prolong the pure electric range of these vehicles, the energy conversion efficiency is to be maximised against powertrain component operation parameters using high fidelity model and simulation. However, the energy conversion efficiency model using vehicle powertrain component model and simulation is complex and computationally intensive. An efficient global optimisation tool is needed to produce the optimal efficiency look-up surface for real-time control system implementation, or to search for the optimal operation parameters in real time. In this work, a new two-mode-plus EREV design is used. The optimal vehicle energy conversion efficiency under various powertrain component operation parameters are obtained using three alternative global optimisation tools, GA, PSO, and SEUMRE. Application of SEUMRE allow refined and more accurate vehicle energy conversion efficiency map being created for the optimal operation of the EV/PHEV/EREV. Optimal vehicle control schemes can then be generated in determining the speed and torque of the M/Gs of the vehicle without violating their physical constraints and achieving the overall maximum efficiency of the hybrid powertrain system.

Keywords: electric vehicles; plug-in HEVs; hybrid electric vehicles; PHEV; control strategy; global optimisation; electrical-mechanical energy conversion; energy efficiency; genetic algorithms; particle swarm optimisation; PSO; SEUMRE; optimal control; hybrid powertrains.

DOI: 10.1504/IJEHV.2011.042146

International Journal of Electric and Hybrid Vehicles, 2011 Vol.3 No.2, pp.176 - 190

Available online: 28 Aug 2011

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