Application of genetic algorithm for simultaneous optimisation of HEV component sizing and control strategy. (30th August 2006)

• Record Type: Journal Article
• Authors: Montazeri-Gh, Morteza; Poursamad, Amir
• Is Part Of: International journal of alternative propulsion. Volume 1:Number 1(2006)
• Page Start: 63
• Page End: 78
• Publication Date: 2006-08-30
• Subjects: optimisation -- genetic algorithms -- component sizes -- control strategy -- hybrid electric vehicles -- HEV control -- alternative propulsion -- fuel consumption -- emissions reduction -- simulation; Propulsion systems -- Periodicals; Fuel switching -- Periodicals; Hybrid power systems -- Periodicals; Renewable energy sources -- Periodicals; 629.2293
• Languages: English
• ISSNs: 1471-0234

Abstract

This paper describes a methodological approach for the simultaneous optimisation of Hybrid Electric Vehicle (HEV) component sizing and control strategy using Genetic Algorithm (GA). In this approach, using a parallel HEV configuration and an Electric Assist Control Strategy (EACS), the optimisation problem is formulated. The whole set of sizing and control variables is then encoded as the chromosomes. The multi-objective target is also defined to minimise the Fuel Consumption (FC) and emissions. In addition, the PNGV performance requirements are considered as constraints. Finally, to evaluate the objective function, three driving cycles, ECE-EUDC, FTP and TEH-CAR, are employed. The simulation results obtained in this study show that the approach is effective, resulting in improvement of the objective value and FC.