Energy Management Strategy of Hybrid Electric Vehicles

A special issue of Vehicles (ISSN 2624-8921).

Deadline for manuscript submissions: 15 May 2026 | Viewed by 243

Special Issue Editors


E-Mail Website
Guest Editor
School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, China
Interests: power transmission of new energy vehicles

E-Mail Website
Guest Editor
School of Mechanical Engineering, Yanshan University, Qinhuangdao 066004, China
Interests: powertrain of new energy vehicles

Special Issue Information

Dear Colleagues,

With the accelerating green transformation of the automotive industry, energy management strategies for hybrid electric vehicles (HEVs) have emerged as a critical research domain for enhancing energy efficiency and reducing emissions. This Special Issue focuses on recent advances and practical applications in HEV energy management, encompassing rule-based methods, optimization algorithms, intelligent control techniques—including machine learning and deep learning—and cooperative approaches enabled by vehicle-to-everything (V2X) connectivity. It examines the adaptability of these strategies under diverse and dynamic driving conditions, their potential for maximizing fuel economy and emission reduction, and the challenges associated with real-world implementation. By addressing both theoretical innovation and engineering feasibility, this collection aims to advance the development of intelligent, efficient energy management systems and to provide timely, high-impact solutions for the evolving automotive industry.

Dr. Weiwei Yang
Dr. Yang Tian
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Vehicles is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • energy management strategy
  • battery life optimization
  • real-time power distribution
  • intelligent control technology
  • vehicle–road–cloud collaboration
  • multi-objective optimization

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

25 pages, 4962 KB  
Article
A Methodological Framework for Inferring Energy-Related Operating States from Limited OBD Data: A Single-Trip Case Study of a PHEV
by Michal Loman, Branislav Šarkan, Arkadiusz Małek, Jacek Caban, Beata Martyna-Syroka and Katarzyna Piotrowska
Vehicles 2025, 7(4), 165; https://doi.org/10.3390/vehicles7040165 - 17 Dec 2025
Abstract
This paper presents a methodological framework for inferring energy-related operating states of plug-in hybrid electric vehicles (PHEVs) under conditions of limited and incomplete on-board diagnostic (OBD) data. The proposed approach is illustrated using a single short real-world urban trip recorded for one PHEV [...] Read more.
This paper presents a methodological framework for inferring energy-related operating states of plug-in hybrid electric vehicles (PHEVs) under conditions of limited and incomplete on-board diagnostic (OBD) data. The proposed approach is illustrated using a single short real-world urban trip recorded for one PHEV operating in electric mode. Unsupervised clustering based on k-means is applied in progressively expanded state spaces (3D–5D) to decompose the driving process into physically interpretable operating states, despite the absence of direct measurements of key variables such as regenerative braking power. Cluster validity indices, per-cluster silhouette values, temporal segmentation, and robustness checks are employed to support the interpretability and internal consistency of the results. The study demonstrates that even a single, non-representative OBD time series contains sufficient internal structure to recover meaningful energy-related information when appropriate state-space decomposition is applied. While no statistical generalization is intended, the results highlight the potential of the proposed framework for analyzing real-world vehicle operation under constrained data availability. Full article
(This article belongs to the Special Issue Energy Management Strategy of Hybrid Electric Vehicles)
Show Figures

Figure 1

Back to TopTop