Study on the Selection of Electric Motor/Engine on the Performance of Hybrid Vehicles

Olivian Chiver (), Ioan Radu Sugar and Liviu Neamt
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Olivian Chiver: Electrical, Electronic and Computer Engineering Department, Technical University of Cluj-Napoca, Str. Dr. Victor Babeș Nr. 62A, 430083 Baia-Mare, Romania
Ioan Radu Sugar: Mechanical Engineering and Technological Management Department, Technical University of Cluj-Napoca, Str. Dr. Victor Babeș Nr. 62A, 430083 Baia-Mare, Romania
Liviu Neamt: Electrical, Electronic and Computer Engineering Department, Technical University of Cluj-Napoca, Str. Dr. Victor Babeș Nr. 62A, 430083 Baia-Mare, Romania

Energies, 2024, vol. 17, issue 14, 1-14

Abstract: Hybrid electric vehicles (HEVs) are perceived as a first step toward the future of sustainable transport. Of course, battery electric vehicles (EVs) are currently ideal for what is wanted in the future of transport. However, the lack of infrastructure for these vehicles makes many potential users choose hybrid vehicles. This paper presents an analysis of the influence of hybrid vehicle engines and electric motors on their performance. Three engines with slightly different power levels and similar characteristics were considered for the configured models. Additionally, two electric motors with very different power levels, but a very close maximum continuous torque were used in our models. One was an induction motor and the other was a permanent magnet synchronous motor. The ADVISOR software was used for vehicle configuration and simulation. Series and parallel hybrid vehicles were considered. The main dynamic performances and the fuel consumption rates of the two driving cycles were compared for the configured models. Three conventional models with the same engines used in HEVs were also simulated for reference. The results highlight that, in the case of HEVs, the choice of a combination engine/electric motor is crucial for obtaining the best compromise between a dynamic performance and a low fuel consumption and, implicitly, a low negative impact on the environment.

Keywords: ADVISOR software; electric motor/engine; hybrid vehicle; performance (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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