The global challenge to reduce emissions of polluting gases and greenhouse gases has forced
the development of alternatives to the traditional internal combustion engine vehicles, such
as electric or hybrid vehicles.
The electric powertrain are the most efficient for delivery trucks or urban buses, due to
acceleration and deceleration patterns make them inefficient for using internal combustion
engines. Despite this, its range and purchase cost are the main factors limiting the use of
electric vehicles in these applications.
Range and purchase cost of an electric vehicles are mainly related to the energy storage
system. Therefore, the optimum size of the battery pack should be considered as the design
goal of a vehicle when its application is known.
This paper presents a methodology to optimize the battery pack of an electric vehicle
according to a given route run in a target time. Therefore, it would be applicable to delivery
vehicles, buses and any vehicle whose route and travel time are known in advance. The
proposed methodology allows minimizing the energy consumption by determining the
optimal powertrain ratio for a given track, setting the travel time as an objective. A full
vehicle model and a multi-objective genetic algorithms are used for this matter.
