A novel energy-efficiency optimization approach based on driving patterns styles and experimental tests for electric vehicles

Juan Diego Valladolid, Diego Patino, Giambattista Gruosso, Carlos Adrián Correa-Flórez, José Vuelvas, Fabricio Espinoza

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

This article proposes an energy-efficiency strategy based on the optimization of driving patterns for an electric vehicle (EV). The EV studied in this paper is a commercial vehicle only driven by a traction motor. The motor drives the front wheels indirectly through the differential drive. The electrical inverter model and the power-train efficiency are established by lookup tables determined by power tests in a dynamometric bank. The optimization problem is focused on maximizing energyefficiency between the wheel power and battery pack, not only to maintain but also to improve its value by modifying the state of charge (SOC). The solution is found by means of a Particle Swarm Optimization (PSO) algorithm. The optimizer simulation results validate the increasing efficiency with the speed setpoint variations, and also show that the battery SOC is improved. The best results are obtained when the speed variation is between 5% and 6%.

Original languageEnglish
Article number1199
JournalElectronics (Switzerland)
Volume10
Issue number10
DOIs
StatePublished - 2 May 2021

Bibliographical note

Funding Information:
Funding: D. Patino wants to thank Pontificia Universidad Javeriana and the project No. 8660.

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • Electrical vehicle
  • Energy management
  • Optimization of driving patterns
  • Particle swarm optimization algorithm
  • System efficiency

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