An Optimization Strategy Applied to Identify the Optimal Powertrain Configurations for Efficient Electric Vehicles

The recent transition to electric motors has initiated a real effervescence of the literature on EV. It is now established that adding transmissions to electric motors or combining multiple motors increases their efficiency. However, the literature offers no real comparison, or establishes the configuration that provides the best efficiency. Thus, defining the influence of the powertrain design on EV efficiency remains an open challenge. This paper optimizes five single-motor (SM) and dual-motor (DM) designs to compare their efficiency. The paper also proposes a two-level optimization based on a modified version of a particle swarm optimizer. The results show that, with efficiency gains of more than 11.5% under highway conditions, a two-speed SM design offers improvements over any single-speed SM layout. However, with gains of more than 4.5% and 12% for urban and highway conditions, respectively, a DM combined with planetary gear train can provide efficiency increases superior to the response of any SM architecture. A comparison of the optimization algorithms shows that the proposed modification reduced the calculation times by 62% as compared to the original version.