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Vehicles
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Advanced Storage Systems for Electric Mobility
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Advanced Storage Systems for Electric Mobility

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

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 48144

Special Issue Editor

Dr. Teresa Donateo

E-Mail Website
Guest Editor
Department of Engineering for Innovation, University of Salento, 73100 Lecce, LE, Italy
Interests: fluid machinery; energy systems; power generation; automotive and aircraft
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Electrified vehicles (EVs) are rapidly becoming a part of the modern air, road, and water transportation system, but their diffusion in the market is still negatively affected by technical, environmental, and economic issues, especially in the case of battery electric vehicles (BEVs) and fuel cell systems.

In the case of BEVs, the energy storage system is usually a secondary (rechargeable) battery, but hybrid electric storage systems (HESSs), mainly consisting of a battery coupled with supercapacitors, are also considered in the literature. In the case of fuel cell power systems, the storage systems depend on the kind of converter and powertrain, and usually consist of a fuel tank to feed a fuel cell, either directly or through a reformer. However, fuel cells are not able to follow the dynamic power request of a vehicle, so they are usually combined with an electric storage system in a series hybrid electric configuration. Moreover, the need to overcome today’s limits on energy density for both batteries and hydrogen storage is particularly felt in the aircraft field, where weight is a critical issue. 

In this context, this Special Issue aims to be an open platform to share knowledge about advanced storage systems for BEVs and FCVs. It particularly seeks review papers and original contributions describing either experimental or numerical investigations, with emphasis on the expected advantages in terms of range, cost, and environmental issues with a life-cycle assessment (LCA) approach (i.e., “from start to finish” of the storage systems) in all field of transportation.

Dr. Teresa Donateo
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. Vehicles is an international peer-reviewed open access quarterly 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

  • batteries
  • hydrogen
  • supercapacitors
  • HESSs
  • BEVs
  • FCVs
  • LCA

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Published Papers (6 papers)

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Editorial

Jump to: Research, Review

4 pages, 164 KiB  
Editorial
Advanced Storage Systems for Electric Mobility
by Teresa Donateo
Vehicles 2024, 6(3), 1661-1664; https://doi.org/10.3390/vehicles6030079 - 19 Sep 2024
Viewed by 757
Abstract
Electrified vehicles (EVs) are increasingly integrated into modern air, road, and water transportation systems [...] Full article
(This article belongs to the Special Issue Advanced Storage Systems for Electric Mobility)

Research

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30 pages, 8550 KiB  
Communication
Evaluation of Electric Vehicle Performance Characteristics for Adaptive Supervisory Self-Learning-Based SR Motor Energy Management Controller under Real-Time Driving Conditions
by Pemmareddy Saiteja, Bragadeshwaran Ashok and Dharmik Upadhyay
Vehicles 2024, 6(1), 509-538; https://doi.org/10.3390/vehicles6010023 - 8 Mar 2024
Viewed by 2349
Abstract
The performance of an electric vehicle (EV) notably depends on an energy management controller. This study developed several energy management controllers (EMCs) to optimize the efficiency of EVs in real-time driving conditions. Also, this study employed an innovative methodology to create EMCs, efficiency [...] Read more.
The performance of an electric vehicle (EV) notably depends on an energy management controller. This study developed several energy management controllers (EMCs) to optimize the efficiency of EVs in real-time driving conditions. Also, this study employed an innovative methodology to create EMCs, efficiency maps, and real-time driving cycles under actual driving conditions. The various EMCs such as PID, intelligent, hybrid, and supervisory controllers are designed using MATLAB/Simulink and examined under real-time conditions. In this instance, a mathematical model of an EV with a switched reluctance (SR) motor is developed to optimize energy consumption using different energy management controllers. Further, an inventive experimental approach is employed to generate efficiency maps for the SR motor and above-mentioned controllers. Then, the generated efficiency maps are integrated into a model-in-loop (MIL)-based EV test platform to analyze the performance under real-time conditions. Additionally, to verify EV model, a real-time driving cycle (DC) has been developed, encompassing various road conditions such as highway, urban, and rural. Subsequently, the developed models are included into an MIL-based EV test platform to optimize the performance of the electric motor and battery consumption in real-time conditions. The results indicate that the proposed supervisory controller (59.1%) has a lower EOT SOC drop compared to the PID (3.6%), intelligent (21.5%), and hybrid (44.9%) controllers. Also, the suggested controller achieves minimal energy consumption (44.67 Wh/km) and enhances energy recovery (−58.28 Wh) under different real-time conditions. Therefore, it will enhance the driving range and battery discharge characteristics of EVs across various real-time driving conditions. Full article
(This article belongs to the Special Issue Advanced Storage Systems for Electric Mobility)
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17 pages, 5998 KiB  
Article
Battery Pack and Underbody: Integration in the Structure Design for Battery Electric Vehicles—Challenges and Solutions
by Giovanni Belingardi and Alessandro Scattina
Vehicles 2023, 5(2), 498-514; https://doi.org/10.3390/vehicles5020028 - 23 Apr 2023
Cited by 13 | Viewed by 15840
Abstract
The evolution toward electric vehicle nowadays appears to be the main stream in the automotive and transportation industry. In this paper, our attention is focused on the architectural modifications that should be introduced into the car body to give a proper location to [...] Read more.
The evolution toward electric vehicle nowadays appears to be the main stream in the automotive and transportation industry. In this paper, our attention is focused on the architectural modifications that should be introduced into the car body to give a proper location to the battery pack. The required battery pack is a big, heavy, and expensive component to be located, managed, climatized, maintained, and protected. This paper develops some engineering analyses and shows sketches of some possible solutions that could be adopted. The possible consequences on the position of the vehicle center of gravity, which in turn could affect the vehicle drivability, lead to locate the battery housing below the passenger compartment floor. This solution is also one of the most interesting from the point of view of the battery pack protection in case of a lateral impact and for easy serviceability and maintenance. The integration of the battery pack’s housing structure and the vehicle floor leads to a sort of sandwich structure that could have beneficial effects on the body’s stiffness (both torsional and bending). This paper also proposes some considerations that are related to the impact protection of the battery pack, with particular reference to the side impacts against a fixed obstacle, such as a pole, which are demonstrated to be the most critical. By means of some FE simulation results, the relevance of the interplay among the different parts of the vehicle side structure and battery case structure is pointed out. Full article
(This article belongs to the Special Issue Advanced Storage Systems for Electric Mobility)
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22 pages, 7549 KiB  
Article
Assessment of Battery–Supercapacitor Topologies of an Electric Vehicle under Real Driving Conditions
by Michele Pipicelli, Bernardo Sessa, Francesco De Nola, Alfredo Gimelli and Gabriele Di Blasio
Vehicles 2023, 5(2), 424-445; https://doi.org/10.3390/vehicles5020024 - 5 Apr 2023
Cited by 10 | Viewed by 3782
Abstract
Road transport is shifting towards electrified vehicle solutions to achieve the Conference of the Parties of the United Nations Framework Convention on Climate Change (COP27) carbon neutrality target. According to life cycle assessment analyses, battery production and disposal phases suffer a not-negligible environmental [...] Read more.
Road transport is shifting towards electrified vehicle solutions to achieve the Conference of the Parties of the United Nations Framework Convention on Climate Change (COP27) carbon neutrality target. According to life cycle assessment analyses, battery production and disposal phases suffer a not-negligible environmental impact to be mitigated with new recycling processes, battery technology, and life-extending techniques. The foundation of this study consists of combining the assessment of vehicle efficiency and battery ageing by applying supercapacitor technology with different topologies to more conventional battery modules. The method employed here consists of analysing different hybrid energy storage system (HESS) topologies for light-duty vehicle applications over a wide range of operating conditions, including real driving cycles. A battery electric vehicle (BEV) has been modelled and validated for this aim, and the reference energy storage system was hybridised with a supercapacitor. Two HESSs with passive and semi-active topologies have been analysed and compared, and an empirical ageing model has been implemented. A rule-based control strategy has been used for the semi-active topology to manage the power split between the battery and supercapacitor. The results demonstrate that the HESS reduced the battery pack root mean square current by up to 45%, slightly improving the battery ageing. The semi-active topology performed sensibly better than the passive one, especially for small supercapacitor sizes, at the expense of more complex control strategies. Full article
(This article belongs to the Special Issue Advanced Storage Systems for Electric Mobility)
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17 pages, 3961 KiB  
Article
Analysis of Kinetic Energy Recovery Systems in Electric Vehicles
by Carlos Armenta-Déu and Hernán Cortés
Vehicles 2023, 5(2), 387-403; https://doi.org/10.3390/vehicles5020022 - 29 Mar 2023
Cited by 8 | Viewed by 11786
Abstract
The recovery of kinetic energy (KER) in electric vehicles was analyzed and characterized. Two main systems were studied: the use of regenerative brakes, and the conversion of potential energy. The paper shows that potential energy is a potential source of kinetic energy recovery [...] Read more.
The recovery of kinetic energy (KER) in electric vehicles was analyzed and characterized. Two main systems were studied: the use of regenerative brakes, and the conversion of potential energy. The paper shows that potential energy is a potential source of kinetic energy recovery with higher efficiency than the traditional system of regenerative brakes. The study compared the rate of KER in both cases for a BMWi3 electric vehicle operating under specific driving conditions; the results of the analysis showed that potential energy conversion can recover up to 88.2%, while the maximum efficiency attained with the regenerative brake system was 60.1%. The study concluded that in driving situations with sudden and frequent changes of vehicle speed due to traffic conditions, such as in urban routes, the use of regenerative brakes was shown to be the best option for KER; however, in intercity routes, driving conditions favored the use of potential energy as a priority system for KER. Full article
(This article belongs to the Special Issue Advanced Storage Systems for Electric Mobility)
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Review

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49 pages, 5066 KiB  
Review
Artificial Intelligence Approaches for Advanced Battery Management System in Electric Vehicle Applications: A Statistical Analysis towards Future Research Opportunities
by M. S. Hossain Lipu, Md. Sazal Miah, Taskin Jamal, Tuhibur Rahman, Shaheer Ansari, Md. Siddikur Rahman, Ratil H. Ashique, A. S. M. Shihavuddin and Mohammed Nazmus Shakib
Vehicles 2024, 6(1), 22-70; https://doi.org/10.3390/vehicles6010002 - 25 Dec 2023
Cited by 10 | Viewed by 12348
Abstract
In order to reduce carbon emissions and address global environmental concerns, the automobile industry has focused a great deal of attention on electric vehicles, or EVs. However, the performance and health of batteries can deteriorate over time, which can have a negative impact [...] Read more.
In order to reduce carbon emissions and address global environmental concerns, the automobile industry has focused a great deal of attention on electric vehicles, or EVs. However, the performance and health of batteries can deteriorate over time, which can have a negative impact on the effectiveness of EVs. In order to improve the safety and reliability and efficiently optimize the performance of EVs, artificial intelligence (AI) approaches have received massive consideration in precise battery health diagnostics, fault analysis and thermal management. Therefore, this study analyzes and evaluates the role of AI approaches in enhancing the battery management system (BMS) in EVs. In line with that, an in-depth statistical analysis is carried out based on 78 highly relevant publications from 2014 to 2023 found in the Scopus database. The statistical analysis evaluates essential parameters such as current research trends, keyword evaluation, publishers, research classification, nation analysis, authorship, and collaboration. Moreover, state-of-the-art AI approaches are critically discussed with regard to targets, contributions, advantages, and disadvantages. Additionally, several significant problems and issues, as well as a number of crucial directives and recommendations, are provided for potential future development. The statistical analysis can guide future researchers in developing emerging BMS technology for sustainable operation and management in EVs. Full article
(This article belongs to the Special Issue Advanced Storage Systems for Electric Mobility)
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