Comparison of Several Energy-Efficient Control Laws Using Energetic Macroscopic Representation for Electric Vehicles

Jean-Matthieu Bourgeot, Romain Leclerre and Emmanuel Delaleau ()
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Jean-Matthieu Bourgeot: ENI Brest, UMR CNRS 6027, IRDL, F-29 200 Brest, France
Romain Leclerre: ENI Brest, UMR CNRS 6027, IRDL, F-29 200 Brest, France
Emmanuel Delaleau: ENI Brest, UMR CNRS 6027, IRDL, F-29 200 Brest, France

Energies, 2024, vol. 17, issue 19, 1-29

Abstract: Energy transition and decarbonization present significant challenges to transportation. Electric machines, such as motors and generators, are increasingly replacing internal combustion engines to reduce greenhouse gas emissions. This study focuses on enhancing the energy efficiency of electric machines used in vehicles, which are predominantly powered by batteries with limited energy capacity. By investigating various control strategies, the aim is to minimize energy losses and improve overall vehicle performance. This research examines two types of electric motors: Permanent Magnet Synchronous Motor (PMSM) and Induction Motor (IM). Real-time loss measurements were conducted during simulated driving cycles, including acceleration, constant speed, and braking phases, to mimic typical driving behavior. The simulation utilized characteristics from commercial vehicles, specifically the Renault Zoé and Bombardier eCommander, to assess the controls under different configurations. This study employed the Energetic Macroscopic Representation (EMR) formalism to standardize the analysis across different motors and controls. The results demonstrate significant loss reductions. The controls investigated in this study effectively reduce energy losses in electric motors, supporting their applicability in the automotive industry.

Keywords: Energetic Macroscopic Representation; electrical motor control; flux management; reduction in losses (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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