Lithium-ion SOC optimizer consumption using accelerated particle swarm optimization and temperature criterion

Juan D. Valladolid, Juan P. Ortiz, Felipe A. Berrezueta, Gina P. Novillo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Battery has a fundamental role in energy storage systems for hybrid electric vehicles (HEV), plug-in hybrid electric vehicles (PHEV), electric vehicles (EV) and nowadays in smart grids. The battery state of charge (SOC) behavior is affected by operating temperature reducing its supply capacity or energy storage, therefore, it has been considered important to establish a mathematical model from experimental data of a electric vehicle during route tests. This article presents a metaheuristic optimization method based on accelerated particle swarm optimization (APSO) for SOC maximization during Lithium-ion (Li-ion) batteries charge and discharge states. The proposed optimization model reach to satisfy the balance between: current, temperature and time for the battery to supply the required amount of energy, minimizing the SOC reduction, subject to system specific restrictions. Simulation results show an improvement in the SOC without sacrificing the energy supply of the battery, which demonstrates the potential of the optimization technique in the EV.

Original languageEnglish
Title of host publication2019 AEIT International Conference of Electrical and Electronic Technologies for Automotive, AEIT AUTOMOTIVE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9788887237436
ISBN (Print)9788887237436
DOIs
StatePublished - Jul 2019
Event2019 AEIT International Conference of Electrical and Electronic Technologies for Automotive, AEIT AUTOMOTIVE 2019 - Turin, Italy
Duration: 2 Jul 20194 Jul 2019

Publication series

Name2019 AEIT International Conference of Electrical and Electronic Technologies for Automotive, AEIT AUTOMOTIVE 2019

Conference

Conference2019 AEIT International Conference of Electrical and Electronic Technologies for Automotive, AEIT AUTOMOTIVE 2019
CountryItaly
CityTurin
Period2/07/194/07/19

Keywords

  • APSO algortihm
  • Electric vehicle
  • Li-ion battery
  • Optimization
  • State of charge (SOC)

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