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Energies
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Reliable and Safe Electric Vehicle Powertrain Design and Optimization
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Reliable and Safe Electric Vehicle Powertrain Design and Optimization

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

Deadline for manuscript submissions: closed (31 December 2024) | Viewed by 5269

Special Issue Editors

Dr. Sajib Chakraborty

E-Mail Website
Guest Editor
MOBI-EPOWERS Research Group, ETEC Department, Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Brussels, Belgium
Interests: design for reliability; lifetime testing; condition monitoring and predictive health management of automotive converters; cloud-connected digital twin design and AI-based modeling of the powertrain components; situationally aware battery management systems (BMS)
Prof. Dr. Omar Hegazy

E-Mail Website
Guest Editor
Head of EPOWERS Research Group, ETEC Department & MOBI Research Centre, Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Brussels, Belgium
Interests: power electronics; electric machines; control systems; charging and energy management strategies; co-design optimization; electric vehicles; (plug-in) electric hybrid vehicles; optimization techniques; powertrain modelling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The European Commission's “Fit for 55” package has proposed 55% and 50% emission reduction targets for cars and vans (below 1990 levels), respectively, and a zero-emission target for 2035, which is crucial to achieve climate neutrality by 2050. These objectives necessitate a significant shift towards the electrification of powertrains. This Special Issue will show the pathway to achieving these ambitious goals by facilitating international research ideas, findings, and results from experts. The research published in this Special Issue will encompass the latest metaheuristic algorithms aimed at identifying the optimal trade-off analysis for powertrain design and component sizing and control parameter optimization (i.e., EMS, TMS, and ECO features), while taking into account enhancements to meet EV consumers’ expectations of range, comfort, and reliability. The topics of interest for this Special Issue include, but are not limited to, the following:

  • Correct component sizing for energy efficiency;
  • Optimal powertrain design, control, and ECO functionalities;
  • Optimal thermal and energy management control;
  • Physics-based and machine-learning-based powertrain design tool;
  • Streamlined X-in-the-Loop tests for powertrain;
  • Advanced E/E topologies for powertrain (i.e., multi-inverter, in-wheel propulsion, HV DC/DC, and integrated power electronics);
  • Ageing-aware energy efficient control and sizing;
  • Fault localization and fail-safe mode operation for reliable powertrain components;
  • Advanced optimization techniques related to powertrain;
  • Advanced measurement concepts for development and validation of EV/FCEVs;
  • Predictive health management of powertrain components;
  • Fuel cell powertrains design, sizing and control;
  • User-immersive powertrain control for autonomous shuttles and cars;
  • User-centric powertrain control.

Dr. Sajib Chakraborty
Prof. Dr. Omar Hegazy
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. 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.

Keywords

  • efficient EV
  • optimization
  • safety and reliability
  • EV design tool
  • user-centric design

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Published Papers (4 papers)

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Research

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17 pages, 4970 KiB  
Article
Multi-Objective Structural Optimization Design for Electric Excavator-Specific Battery Packs with Impact Resistance and Fatigue Endurance
by Zihang Li, Jiao Qin, Ming Zhao, Minmin Xu, Wei Huang and Fangming Wu
Energies 2025, 18(3), 669; https://doi.org/10.3390/en18030669 - 31 Jan 2025
Viewed by 464
Abstract
As the issue of energy scarcity becomes increasingly critical, the adoption of electric construction machinery emerges as a pivotal strategy to address the energy crisis. During the travel and operation of electric construction machinery, the machinery-specific battery packs are subjected to long-term mechanical [...] Read more.
As the issue of energy scarcity becomes increasingly critical, the adoption of electric construction machinery emerges as a pivotal strategy to address the energy crisis. During the travel and operation of electric construction machinery, the machinery-specific battery packs are subjected to long-term mechanical shocks and random vibration loads, leading to resonance and structural damage failure. To address the multi-objective optimization design issues of machinery-specific battery packs for electric construction machinery under the action of random vibration and impact loads and to enhance the fatigue life and reduce the mass of the battery pack, this paper conducts optimization design research on a newly developed battery pack for an electric excavator. Firstly, a finite element model of the battery pack is established to conduct simulation analyses on its impact resistance characteristics and fatigue life. Secondly, through a comprehensive contribution analysis method, key components are identified, with the thickness dimensions of the battery pack parts selected as design parameters. Finally, using maximum stress under mechanical shock conditions and first-order constraint mode as constraint conditions, mass minimization and fatigue life maximization are set as optimization objectives. The Box–Behnken experimental design is employed alongside a Kriging approximation model; subsequently, the NSGA-II algorithm is utilized for multi-objective optimization. The optimization results show that, while meeting the basic static and dynamic performance requirements, the mass of the optimized battery pack outer frame is reduced by 56.8 kg, a decrease of 5.75%. Concurrently, the optimized battery pack’s fatigue life has increased by 1,234,800 cycles, which is an enhancement factor of 1.65 compared to pre-optimization levels. These findings provide significant reference points for optimizing structural performance and achieving lightweight designs in electric excavator battery packs. Full article
(This article belongs to the Special Issue Reliable and Safe Electric Vehicle Powertrain Design and Optimization)
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29 pages, 4239 KiB  
Article
Early Design Stage Evaluation of All Electric Aircraft Power Systems Focusing on Long-Term Behavior
by Melanie Hoffmann, David Inkermann, Christoph Knieke, Fanke Zeng, Tobias Kopp, Michael Terörde and Michael Kurrat
Energies 2024, 17(18), 4653; https://doi.org/10.3390/en17184653 - 18 Sep 2024
Cited by 1 | Viewed by 1157
Abstract
In the aircraft industry, there is a shift towards more and all-electric power systems resulting in great research efforts on single components like batteries. At the same time there is an increasing need to investigate and evaluate the long-term behavior of the whole [...] Read more.
In the aircraft industry, there is a shift towards more and all-electric power systems resulting in great research efforts on single components like batteries. At the same time there is an increasing need to investigate and evaluate the long-term behavior of the whole electric power system to ensure safe and sustainable aircraft operation. Focusing on this challenge, the objective of this article is to propose a framework for electric power system assessment in the early design stages. In particular, the focus is on identifying and handling uncertainties regarding failure behavior and degradation, both on the component and system level. The evaluation of different power system topologies is based on the integration of Model-Based Systems Engineering and robust design methods. In this context, another central aspect is the definition of system and component requirements derived from the flight mission profile. SysML diagrams are used to define use cases and possible system topologies. Sensitivity of degradation effects are evaluated using robust design methods. The application of the framework and these methods is illustrated using a short-range aircraft with an all-electric power system. The results highlight the applicability of the framework to cope with the uncertainties that occur in the early design stages and point out fields of further research. Full article
(This article belongs to the Special Issue Reliable and Safe Electric Vehicle Powertrain Design and Optimization)
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24 pages, 8755 KiB  
Article
Modeling and Control of a Modular Multilevel Converter Based on a Battery Energy Storage System with Soft Arm State-of-Charge Balancing Control
by Yang Wang, Sajib Chakraborty, Thomas Geury and Omar Hegazy
Energies 2024, 17(3), 740; https://doi.org/10.3390/en17030740 - 4 Feb 2024
Viewed by 1701
Abstract
Modular multilevel converters (MMCs) with integrated battery energy storage systems (BESSs) are becoming crucial for modern power grids. This paper investigates the modeling and control of a grid-connected MMC-BESS, with a specific emphasis on state-of-charge (SoC) balancing. Compared to conventional hard arm SoC [...] Read more.
Modular multilevel converters (MMCs) with integrated battery energy storage systems (BESSs) are becoming crucial for modern power grids. This paper investigates the modeling and control of a grid-connected MMC-BESS, with a specific emphasis on state-of-charge (SoC) balancing. Compared to conventional hard arm SoC balancing control (HASBC), this paper proposes an alternative soft arm SoC balancing control (SASBC). The simulation results and analysis indicate the following: 1. SASBC provides superior performance in achieving SoC balance both between and within the arms, as compared to HASBC. 2. The MMC-BESS power fluctuates between phases, arms, and individual submodules to balance the SoC of batteries. After the accomplishment of SoC equalization, the power is equally distributed, and the circulating current is well eliminated. 3. MMC-BESS can operate in both the charging and discharging modes, and the total harmonic distortion (THD) of the output current is reduced from 6.80% to 1.13% after SoC balancing is achieved. 4. A robustness test shows the control system’s effective performance in handling component variations. Full article
(This article belongs to the Special Issue Reliable and Safe Electric Vehicle Powertrain Design and Optimization)
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Review

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24 pages, 5085 KiB  
Review
Energy Sources and Battery Thermal Energy Management Technologies for Electrical Vehicles: A Technical Comprehensive Review
by Sara El Afia, Antonio Cano, Paul Arévalo and Francisco Jurado
Energies 2024, 17(22), 5634; https://doi.org/10.3390/en17225634 - 11 Nov 2024
Viewed by 1193
Abstract
Electric vehicles are increasingly seen as a viable alternative to conventional combustion-engine vehicles, offering advantages such as lower emissions and enhanced energy efficiency. The critical role of batteries in EVs drives the need for high-performance, cost-effective, and safe solutions, where thermal management is [...] Read more.
Electric vehicles are increasingly seen as a viable alternative to conventional combustion-engine vehicles, offering advantages such as lower emissions and enhanced energy efficiency. The critical role of batteries in EVs drives the need for high-performance, cost-effective, and safe solutions, where thermal management is key to ensuring optimal performance and longevity. This study is motivated by the need to address the limitations of current battery thermal management systems (BTMS), particularly the effectiveness of cooling methods in maintaining safe operating temperatures. The hypothesis is that immersion cooling offers superior thermal regulation compared to the widely used indirect liquid cooling approach. Using MATLAB Simulink, this research investigates the dynamic thermal behaviour of three cooling systems, including air cooling, indirect liquid cooling, and immersion cooling, by comparing their performance with an uncooled battery. The results show that immersion cooling outperforms indirect liquid cooling in terms of temperature control and safety, providing a more efficient solution. These findings challenge the existing literature, positioning immersion cooling as the optimal BTMS. The main contribution of this paper lies in its comprehensive evaluation of cooling technologies and its validation of immersion cooling as a superior method for enhancing EV battery performance. Full article
(This article belongs to the Special Issue Reliable and Safe Electric Vehicle Powertrain Design and Optimization)
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