<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The paper presents the energy loss minimization of a hybrid energy storage system used in an electric vehicle, composed by a battery and a supercapacitor. The optimization is carried out by searching the optimal power sharing between the energy storage devices. The power sharing factor is defined as a discrete time variable, with constant values during each subdivision of the driving cycle. The elements of the optimal solution vector are the power sharing factors and the time instants that define the subdivisions. The particle swarm optimization algorithms have been validated using the Rastrigin test function, and three versions of the boundary behaviour have been compared in case of the constrained optimization. The algorithms have been tested for the energy loss minimization in case of a simple driving cycle, and their performance has been assessed by statistical analysis for different swarm sizes.</p>
</abstract>

The paper presents the energy loss minimization of a hybrid energy storage system used in an electric vehicle, composed by a battery and a supercapacitor. The optimization is carried out by searching the optimal power sharing between the energy storage devices. The power sharing factor is defined as a discrete time variable, with constant values during each subdivision of the driving cycle. The elements of the optimal solution vector are the power sharing factors and the time instants that define the subdivisions. The particle swarm optimization algorithms have been validated using the Rastrigin test function, and three versions of the boundary behaviour have been compared in case of the constrained optimization. The algorithms have been tested for the energy loss minimization in case of a simple driving cycle, and their performance has been assessed by statistical analysis for different swarm sizes.

Particle Swarm Optimization of a Hybrid Energy Storage System

Faculty of Electrical Engineering, Department of Electrical Machines and Drives

Sapientia-Hungarian University of Transylvania

Faculty of Technical and Human Sciences, Târgu Mureş, Department of Electrical Engineering

Acta Universitatis Sapientiae, Electrical and Mechanical Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Particle Swarm Optimization of a Hybrid Energy Storage System"}

The paper presents the energy loss minimization of a hybrid energy storage system used in an electric vehicle, composed by a battery and a supercapacitor. The...

Particle Swarm Optimization of a Hybrid Energy Storage System

Online veröffentlicht: 30. Dez. 2021

Seitenbereich: 82 - 100

Eingereicht: 15. Okt. 2021

Akzeptiert: 06. Dez. 2021

DOI: https://doi.org/10.2478/auseme-2021-0007

Schlüsselwörter
Particle swarm optimization, hybrid energy storage system, electric vehicle, constrained optimization

© 2021 János Ferencz et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Particle Swarm Optimization of a Hybrid Energy Storage System

Online veröffentlicht: 30. Dez. 2021

Seitenbereich: 82 - 100

Eingereicht: 15. Okt. 2021

Akzeptiert: 06. Dez. 2021

DOI: https://doi.org/10.2478/auseme-2021-0007

SchlüsselwörterParticle swarm optimization, hybrid energy storage system, electric vehicle, constrained optimization

© 2021 János Ferencz et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Particle swarm optimization, hybrid energy storage system, electric vehicle, constrained optimization