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Battery Technologies for Electric Vehicles from Materials to Management
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Battery Technologies for Electric Vehicles from Materials to Management

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "E: Electric Vehicles".

Deadline for manuscript submissions: closed (30 March 2023) | Viewed by 12706

Special Issue Editor

Dr. Balakumar Balasingam

E-Mail Website
Guest Editor
Department of Electrical & Computer Engineering, University of Windsor, 401 Sunset Avenue, Windsor, ON N9B 3P4, Canada
Interests: signal processing; machine learning; information fusion; battery management systems; human system automation; target tracking
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Rechargeable Li-ion batteries have emerged as leading candidates for energy storage in transportation electrification. However, the cost reduction in Li-ion batteries has shown a stabilizing trend in the recent years, threatening the growth of electric vehicle adoption. Continued and rapid drop in battery prices is crucial to accelerate transportation electrification and the replacement of internal compulsion engines. This Special Issue is dedicated to reporting advances in battery materials, battery manufacturing technologies, battery management, battery reuse, and battery recycling technologies that contribute to the safety, performance, reliability, and cost reduction in rechargeable Li-ion battery systems.

Topics of interest include but are not limited to:

  • Equivalent circuit model approaches to battery management systems;
  • Battery system identification approaches;
  • Approaches to battery state of charge and state of health modeling;
  • Battery thermal management;
  • Novel battery charging solutions;
  • Cell balancing strategies;
  • Challenges faced in battery reuse applications;
  • Challenges in Li-ion battery recycling;
  • Performance analysis of battery management system algorithms.

Dr. Balakumar Balasingam
Guest Editor

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. Energies is an international peer-reviewed open access semimonthly 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 2600 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.

Published Papers (5 papers)

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Research

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14 pages, 4493 KiB  
Article
A Study on Capacity and State of Charge Estimation of VRFB Systems Using Cumulated Charge and Electrolyte Volume under Rebalancing Conditions
by Hyeonhong Jung and Seongjun Lee
Energies 2023, 16(5), 2478; https://0-doi-org.brum.beds.ac.uk/10.3390/en16052478 - 05 Mar 2023
Cited by 1 | Viewed by 1765
Abstract
Extensive research has been conducted on energy storage systems (ESSs) for efficient power use to mitigate the problems of environmental pollution and resource depletion. Various batteries such as lead-acid batteries, lithium batteries, and vanadium redox flow batteries (VRFBs), which have longer life spans [...] Read more.
Extensive research has been conducted on energy storage systems (ESSs) for efficient power use to mitigate the problems of environmental pollution and resource depletion. Various batteries such as lead-acid batteries, lithium batteries, and vanadium redox flow batteries (VRFBs), which have longer life spans and better fire safety, have been actively researched. However, VRFBs undergo capacity reduction due to electrolyte crossover. Additionally, research on the capacity and state of charge (SOC) estimation for efficient energy management, safety, and life span management of VRFBs has been performed; however, the results of short-term experimental conditions with little change in capacity are presented without considering the rebalancing process of the electrolyte. Therefore, herein we propose a method for estimating the capacity of a VRFB using the cumulative charge and electrolyte volume amount under long-term cycle conditions, including rebalancing. The main point of the estimation method is to design a capacity estimation equation in the form of a power function with the measured cumulative charge of the battery as a variable and to update the initial capacity value applied to the estimation equation with the amount of electrolyte measured at the time of rebalancing. Additionally, the performance verification results of the SOC estimation algorithm using the capacity estimation model were presented using the long-term charge/discharge cycle test data of a 10 W-class single cell. Full article
(This article belongs to the Special Issue Battery Technologies for Electric Vehicles from Materials to Management)
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18 pages, 4393 KiB  
Article
Two-Phase Modeling and Simulations of a Polymer Electrolyte Membrane Water Electrolyzer Considering Key Morphological and Geometrical Features in Porous Transport Layers
by Hassan Salihi and Hyunchul Ju
Energies 2023, 16(2), 766; https://0-doi-org.brum.beds.ac.uk/10.3390/en16020766 - 09 Jan 2023
Viewed by 1767
Abstract
Polymer electrolyte membrane (PEM) electrolysis has a promising future for large-scale hydrogen production. As PEM electrolysis technology develops, larger operating current densities are required. In order to increase current density, more water should be available at the reaction sites. Moreover, the removal rate [...] Read more.
Polymer electrolyte membrane (PEM) electrolysis has a promising future for large-scale hydrogen production. As PEM electrolysis technology develops, larger operating current densities are required. In order to increase current density, more water should be available at the reaction sites. Moreover, the removal rate of oxygen and hydrogen needs to be effectively improved. This, in turn, necessitates a better understanding of the main mass transport and electrochemical processes. On the anode side, mass transport is particularly crucial because water must be supplied to the catalyst layer (CL) while, at the same time, oxygen bubbles must be eliminated in a parallel flow from the reaction sites into the flow channels. Hence, simulating the two-phase bubbly flow across the cell thickness is necessary to predict PEM electrolysis performance more accurately as a function of the operating current density. This study provides a systematic understanding of how morphological and geometrical features contribute to the polarization curve and performance characteristics of a PEM electrolysis cell. Hence, a multi-phase PEM electrolysis model has been implemented using MATLAB R2022a. Polarization curves have been calibrated against experimental data and then assessed to provide a fundamental understanding of the relationship between the two-phase flow and cell performance. Full article
(This article belongs to the Special Issue Battery Technologies for Electric Vehicles from Materials to Management)
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26 pages, 4677 KiB  
Article
Robust Approach to Battery Equivalent-Circuit-Model Parameter Extraction Using Electrochemical Impedance Spectroscopy
by Marzia Abaspour, Krishna R. Pattipati, Behnam Shahrrava and Balakumar Balasingam
Energies 2022, 15(23), 9251; https://0-doi-org.brum.beds.ac.uk/10.3390/en15239251 - 06 Dec 2022
Cited by 3 | Viewed by 3104
Abstract
Electrochemical impedance spectroscopy (EIS) is a well-established method of battery analysis, where the response of a battery to either a voltage or current excitation signal spanning a wide frequency spectrum is measured and analyzed. State-of-the-art EIS analysis is limited to high-precision measurement systems [...] Read more.
Electrochemical impedance spectroscopy (EIS) is a well-established method of battery analysis, where the response of a battery to either a voltage or current excitation signal spanning a wide frequency spectrum is measured and analyzed. State-of-the-art EIS analysis is limited to high-precision measurement systems within laboratory environments. In order to be relevant in practical applications, EIS analysis needs to be carried out with low-cost sensors, which suffer from high levels of measurement noise. This article presents an approach to estimate the equivalent circuit model (ECM) parameters of a Li-Ion battery pack based on EIS measurements in the presence of high levels of noise. The proposed algorithm consists of a fast Fourier transform, feature extraction, curve fitting, and least-squares estimation. The results of the proposed parameter-estimation algorithm are compared to that of recent work for objective performance comparison. The error analysis of the proposed approach, in comparison to the existing approach, demonstrated significant improvement in parameter estimation accuracy in low signal-to-noise ratio (SNR) regions. Results show that the proposed algorithm significantly outperforms the previous method under high-measurement-noise scenarios without requiring a significant increase in computational resources. Full article
(This article belongs to the Special Issue Battery Technologies for Electric Vehicles from Materials to Management)
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23 pages, 3705 KiB  
Article
Tabular Open Circuit Voltage Modelling of Li-Ion Batteries for Robust SOC Estimation
by Sneha Sundaresan, Bharath Chandra Devabattini, Pradeep Kumar, Krishna R. Pattipati and Balakumar Balasingam
Energies 2022, 15(23), 9142; https://0-doi-org.brum.beds.ac.uk/10.3390/en15239142 - 02 Dec 2022
Cited by 14 | Viewed by 1893
Abstract
Battery management systems depend on open circuit voltage (OCV) characterization for state of charge (SOC) estimation in real time. The traditional approach to OCV-SOC characterization involves collecting OCV-SOC data from sample battery cells and then fitting a polynomial model to this data. The [...] Read more.
Battery management systems depend on open circuit voltage (OCV) characterization for state of charge (SOC) estimation in real time. The traditional approach to OCV-SOC characterization involves collecting OCV-SOC data from sample battery cells and then fitting a polynomial model to this data. The parameters of these polynomial models are known as the OCV-parameters, or OCV-SOC parameters, in battery management systems and are used for real-time SOC estimation. Even though traditional OCV-SOC characterization approaches are able to abstract the OCV-SOC behavior of a battery in a few parameters, these parameters are only applicable in high precision computing systems. However, many practical battery applications do not have access to high-precision computing resources. The typical approach in a low-precision system is to round the OCV-parameters. This paper highlights the perils of rounding the OCV parameters and proposes an alternative OCV-SOC table. First, several existing OCV-SOC parameters are compared in terms of their expected system requirements and accuracy losses due to rounding. Then, a systematic optimization-based approach is introduced to create an OCV-SOC table that is robust to rounding. A formal performance evaluation metric is introduced to measure the robustness of the resulting OCV-SOC table. It is shown that the OCV-SOC table obtained through the proposed optimization approach outperforms the traditional parametric OCV-SOC models with respect to rounding. Full article
(This article belongs to the Special Issue Battery Technologies for Electric Vehicles from Materials to Management)
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Review

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32 pages, 2156 KiB  
Review
Electric Vehicle Charging Modes, Technologies and Applications of Smart Charging
by Afaq Ahmad, Muhammad Khalid, Zahid Ullah, Naveed Ahmad, Mohammad Aljaidi, Faheem Ahmed Malik and Umar Manzoor
Energies 2022, 15(24), 9471; https://0-doi-org.brum.beds.ac.uk/10.3390/en15249471 - 14 Dec 2022
Cited by 6 | Viewed by 3514
Abstract
The rise of the intelligent, local charging facilitation and environmentally friendly aspects of electric vehicles (EVs) has grabbed the attention of many end-users. However, there are still numerous challenges faced by researchers trying to put EVs into competition with internal combustion engine vehicles [...] Read more.
The rise of the intelligent, local charging facilitation and environmentally friendly aspects of electric vehicles (EVs) has grabbed the attention of many end-users. However, there are still numerous challenges faced by researchers trying to put EVs into competition with internal combustion engine vehicles (ICEVs). The major challenge in EVs is quick recharging and the selection of an optimal charging station. In this paper, we present the most recent research on EV charging management systems and their role in smart cities. EV charging can be done either in parking mode or on-the-move mode. This review work is novel due to many factors, such as that it focuses on discussing centralized and distributed charging management techniques supported by a communication framework for the selection of an appropriate charging station (CS). Similarly, the selection of CS is evaluated on the basis of battery charging as well as battery swapping services. This review also covered plug-in charging technologies including residential, public and ultra-fast charging technologies and also discusses the major components and architecture of EVs involved in charging. In a comprehensive and detailed manner, the applications and challenges in different charging modes, CS selection, and future work have been discussed. This is the first attempt of its kind, we did not find a survey on the charging hierarchy of EVs, their architecture, or their applications in smart cities. Full article
(This article belongs to the Special Issue Battery Technologies for Electric Vehicles from Materials to Management)
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