Loss Minimization Algorithm Based Strategy for EV Hybrid Energy Storage System Optimization

This work proposes an energy management strategy that optimizes an objective function evaluating losses and energy consumption in a hybrid energy storage system of an electric vehicle. This strategy is based on a loss minimization algorithm that iterates the objective function evaluated for the reference signals. Furthermore, supercapacitor voltage and temperature protection measures were implemented to avoid penalizing situations. The proposed strategy is validated by simulation using the electric vehicle model provided by the IEEE 2024 VTS Motor Vehicles Challenge (MVC). The results show that the strategy can improve the overall power distribution performance. Moreover, this proposal obtained the best final score among the 44 presented in MVC.

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Published
2024-10-07
DOI
https://doi.org/10.1109/vppc63154.2024.10755374
Primary Topic
Electric Vehicles and Infrastructure
Type
article
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article

Loss Minimization Algorithm Based Strategy for EV Hybrid Energy Storage System Optimization

Facundo Aguilera, Manuel Javier Vidal Cué, A. Medina
Electric Vehicles and Infrastructure
article

Loss Minimization Algorithm Based Strategy for EV Hybrid Energy Storage System Optimization

Facundo Aguilera, Manuel Javier Vidal Cué, A. Medina
article en

Abstract

This work proposes an energy management strategy that optimizes an objective function evaluating losses and energy consumption in a hybrid energy storage system of an electric vehicle. This strategy is based on a loss minimization algorithm that iterates the objective function evaluated for the reference signals. Furthermore, supercapacitor voltage and temperature protection measures were implemented to avoid penalizing situations. The proposed strategy is validated by simulation using the electric vehicle model provided by the IEEE 2024 VTS Motor Vehicles Challenge (MVC). The results show that the strategy can improve the overall power distribution performance. Moreover, this proposal obtained the best final score among the 44 presented in MVC.

Consejo Nacional de Investigaciones Científicas y Técnicas (AR)
Affordable and clean energy
Openalex Percentile: Top 81%
Electric Vehicles and Infrastructure
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