Efficient Design Methodology of an All-Electric Vehicle Powertrain using Multi-Objective Genetic Optimization Algorithm IFP Energies Novelles

Format:

Conference/Event

Author/Creator:

Abdelli, Abdelli, author.

Contributor:

Benlamine, Raouf

Le Berr, Fabrice

Conference Name:

SAE 2013 World Congress & Exhibition (2013-04-16 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2013

Summary:

This paper presents a methodology to design the powertrain of an electrical vehicle (EV) in an optimal way. The electric vehicle optimal design is carried out using multiobjective genetic optimization algorithm. The developed methodology is based on the coupling of a genetic algorithm with powertrain component models. It allows determining the drive train components specifications for imposed vehicle performances, taking into account the dynamic model of the vehicle and all the components interactions. In this way, the components can be sized taking into account the whole system behavior in an optimal global design. The developed methodology is performed on the European driving cycle (NEDC) to estimate energy consumption gains but also powertrain mass reduction in comparison with a classical step-by-step methodology. This optimal procedure is notably important to increase electric vehicle range or reduce battery size and thus electric vehicle cost

Notes:

Vendor supplied data

Publisher Number:

2013-01-1758

Access Restriction:

Restricted for use by site license