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Battery Management System in Electric and Hybrid Vehicles
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Battery Management System in Electric and Hybrid Vehicles

A special issue of World Electric Vehicle Journal (ISSN 2032-6653).

Deadline for manuscript submissions: 20 June 2025 | Viewed by 2215

Special Issue Editors

Dr. Yong Tian

E-Mail Website
Guest Editor
College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
Interests: battery state estimation; battery modeling and analysis; fault diagnosis; health assessment; measurement and control
Special Issues, Collections and Topics in MDPI journals
Dr. Penghua Li

E-Mail Website
Guest Editor
College of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
Interests: fault diagnosis; battery health management; states estimation; mechanism modeling; parameter identification
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid development of electric and hybrid vehicles has created a boom for lithium-ion batteries. However, lithium-ion batteries inherently have non-linear dynamic behaviours coupled with electrical, acoustic, and mechanical variations. Furthermore, their dynamic behaviors change with factors such as voltage, current, capacity, temperature, and vibration. These factors make it difficult to model and manage the lithium-ion batteries. Therefore, the intelligent battery management system is very crucial for the safe, reliable, and efficient operation of electric and hybrid vehicles. Although remarkable progress has been made in recent years, to control and manage the lithium-ion batteries accurately during their whole lifespan and practical conditions still remain open issues. This Special Issue focuses on the advanced battery management technologies that could potentially be used in electric and hybrid vehicles. Topics of interest include, but are not limited to, the following:

  • Battery state estimation and remaining useful life prediction;
  • Battery thermal analysis and management;
  • Battery charging strategy optimization;
  • Battery pack balance control;
  • Battery multi-physics field parameter monitoring.

Dr. Yong Tian
Dr. Penghua Li
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. World Electric Vehicle Journal 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 1400 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

  • battery management system
  • lithium-ion batteries
  • electric and hybrid vehicles
  • battery state estimation
  • battery charging control
  • battery parameter monitoring

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Published Papers (2 papers)

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Research

21 pages, 5179 KiB  
Article
LSTM-Based State-of-Charge Estimation and User Interface Development for Lithium-Ion Battery Management
by Abdellah Benallal, Nawal Cheggaga, Amine Hebib and Adrian Ilinca
World Electr. Veh. J. 2025, 16(3), 168; https://doi.org/10.3390/wevj16030168 - 13 Mar 2025
Viewed by 569
Abstract
State-of-charge (SOC) estimation is pivotal in optimizing lithium-ion battery management systems (BMSs), ensuring safety, performance, and longevity across various applications. This study introduces a novel SOC estimation framework that uniquely integrates Long Short-Term Memory (LSTM) neural networks with Hyperband-driven hyperparameter optimization, a combination [...] Read more.
State-of-charge (SOC) estimation is pivotal in optimizing lithium-ion battery management systems (BMSs), ensuring safety, performance, and longevity across various applications. This study introduces a novel SOC estimation framework that uniquely integrates Long Short-Term Memory (LSTM) neural networks with Hyperband-driven hyperparameter optimization, a combination not extensively explored in the literature. A comprehensive experimental dataset is created using data of LG 18650HG2 lithium-ion batteries subjected to diverse operational cycles and thermal conditions. The proposed framework demonstrates superior prediction accuracy, achieving a Mean Square Error (MSE) of 0.0023 and a Mean Absolute Error (MAE) of 0.0043, outperforming traditional estimation methods. The Hyperband optimization algorithm accelerates model training and enhances adaptability to varying operating conditions, making it scalable for diverse battery applications. Developing an intuitive, real-time user interface (UI) tailored for practical deployment bridges the gap between advanced SOC estimation techniques and user accessibility. Detailed residual and regression analyses confirm the proposed solution’s robustness, generalizability, and reliability. This work offers a scalable, accurate, and user-friendly SOC estimation solution for commercial BMSs, with future research aimed at extending the framework to other battery chemistries and hybrid energy systems. Full article
(This article belongs to the Special Issue Battery Management System in Electric and Hybrid Vehicles)
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18 pages, 4650 KiB  
Article
Integrating Battery Energy Storage Systems for Sustainable EV Charging Infrastructure
by Amanda Monteiro, A. V. M. L. Filho, N. K. L. Dantas, José Castro, Ayrlw Maynyson C. Arcanjo, Pedro A. C. Rosas, Pérolla Rodrigues, Augusto C. Venerando, Newmar Spader, Mohamed A. Mohamed, Adrian Ilinca and Manoel H. N. Marinho
World Electr. Veh. J. 2025, 16(3), 147; https://doi.org/10.3390/wevj16030147 - 4 Mar 2025
Viewed by 1328
Abstract
The transition to a low-carbon energy matrix has driven the electrification of vehicles (EVs), yet charging infrastructure—particularly fast direct current (DC) chargers—can negatively impact distribution networks. This study investigates the integration of Battery Energy Storage Systems (BESSs) with the power grid, focusing on [...] Read more.
The transition to a low-carbon energy matrix has driven the electrification of vehicles (EVs), yet charging infrastructure—particularly fast direct current (DC) chargers—can negatively impact distribution networks. This study investigates the integration of Battery Energy Storage Systems (BESSs) with the power grid, focusing on the E-Lounge project in Brazil as a strategy to mitigate these impacts. The results demonstrated a 21-fold increase in charging sessions and an energy consumption growth from 0.6 MWh to 10.36 MWh between June 2023 and March 2024. Compared to previous findings, which indicated the need for more robust systems, the integration of a 100 kW/138 kWh BESS with DC fast chargers (60 kW) and AC chargers (22 kW) proved effective in reducing peak demand, optimizing energy management, and enhancing grid stability. These findings confirm the critical role of BESSs in establishing a sustainable EV charging infrastructure, demonstrating improvements in power quality and the mitigation of grid impacts. The results presented in this study stem from a project approved under the Research and Development program of the Brazilian Electricity Regulatory Agency (ANEEL) through strategic call No. 022/2018. This initiative aimed to develop a modular EV charging infrastructure for fleet vehicles in Brazil, ensuring minimal impact on the distribution network. Full article
(This article belongs to the Special Issue Battery Management System in Electric and Hybrid Vehicles)
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