Cutting-Edge EMS Technologies for EVs and HEVs: Recent Developments and Future Directions

Energy Management Strategies (EMS) are critical for optimizing energy utilization, improving performance, and reducing environmental impact in Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs). This study aims to address the growing complexities in EMS development by introducing a novel classification framework that organizes existing methodologies into rule-based, optimization-based, and intelligent transportation system (ITS)-based approaches. The research systematically explores the influence of advanced powertrain architectures and charging technologies on EMS objectives. Recent advancements, such as the integration of machine learning, predictive controls, and multi-objective optimization, are analyzed to highlight their contributions to addressing challenges in modern electrified transportation systems. Key findings demonstrate the importance of emerging trends like vehicle-to-everything (V2X) communication and renewable energy integration in enhancing EMS capabilities. The study concludes by emphasizing the necessity of adaptive and innovative solutions to meet the increasing demands of energy-efficient and sustainable transportation. This work provides a comprehensive and objective representation of current advancements, offering insights to guide future research and practical applications in the field.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3582527
Citations
2
Primary Topic
Wireless Power Transfer Systems
Type
article
Field-Weighted Citation Impact
1.46
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article

Cutting-Edge EMS Technologies for EVs and HEVs: Recent Developments and Future Directions

Yashar Farajpour
2 citations
IEEE Access
Wireless Power Transfer Systems
1.46
article

Cutting-Edge EMS Technologies for EVs and HEVs: Recent Developments and Future Directions

Yashar Farajpour
article en
2 citations

Abstract

Energy Management Strategies (EMS) are critical for optimizing energy utilization, improving performance, and reducing environmental impact in Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs). This study aims to address the growing complexities in EMS development by introducing a novel classification framework that organizes existing methodologies into rule-based, optimization-based, and intelligent transportation system (ITS)-based approaches. The research systematically explores the influence of advanced powertrain architectures and charging technologies on EMS objectives. Recent advancements, such as the integration of machine learning, predictive controls, and multi-objective optimization, are analyzed to highlight their contributions to addressing challenges in modern electrified transportation systems. Key findings demonstrate the importance of emerging trends like vehicle-to-everything (V2X) communication and renewable energy integration in enhancing EMS capabilities. The study concludes by emphasizing the necessity of adaptive and innovative solutions to meet the increasing demands of energy-efficient and sustainable transportation. This work provides a comprehensive and objective representation of current advancements, offering insights to guide future research and practical applications in the field.

IEEE AccessVol. 13
Université du Québec à Trois-Rivières (CA), Carleton University (CA)
Industry, innovation and infrastructure
Openalex Percentile: Top 17%
Wireless Power Transfer Systems
1.46
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