Sistemas híbridos de armazenamento de energia aplicados à veículos elétricos: uma revisão da literatura

Abstract

This work aims to organize and analyze the literature on hybrid energy storage systems (HESS) composed of batteries and supercapacitors applied to electric vehicles. Methodologically, a systematic review (2020-2025) was conducted in the ScienceDirect, Scopus, and Web of Science databases, with access via CAPES. The Methodi Ordinati was employed for article ranking (temporal weight = 10), and the PRISMA flowchart was used for screening. The initial search returned 176 records; after duplicate removal and scope filtering, 33 articles were included in the qualitative analysis. The results and discussion indicate that: (i) equivalent circuit models for batteries and RC models for supercapacitors are predominant and sufficient for energy and aging studies; (ii) semi-active and fully active topologies outperform passive ones in terms of efficiency and battery stress mitigation; (iii) strategies based on predictive control models, demand forecasting, and learning-based approaches (e.g., deep and reinforcement learning) tend to outperform heuristic methods by reducing losses, attenuating current peaks, and stabilizing the DC bus; and (iv) validations using standardized driving cycles and hardware-in-the-loop setups reinforce efficiency gains and lifetime extension. It is concluded that the combination of appropriate modeling, topological selection, and predictive control strategies is decisive for enhancing performance and durability of energy storage in electric vehicles, while research gaps remain in long-term field testing, thermal integration, and cost–benefit evaluation among different topologies.