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Development of Intelligent Electric Vehicles and Smart Transportation—2nd Edition

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

Deadline for manuscript submissions: 10 November 2025 | Viewed by 1044

Special Issue Editors


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Guest Editor
Undergraduate Program of Vehicle and Energy Engineering, National Taiwan Normal University, Taipei 10610, Taiwan
Interests: intelligent control; optimal energy management; vehicle system dynamics; hybrid and electric vehicles
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Undergraduate Program of Vehicle and Energy Engineering, National Taiwan Normal University, Taipei, 10610, Taiwan
Interests: solar power; maximum power point tracking algorithm; rail vehicle auxiliary power system; power quality
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Due to stringent environmental policies and global warming, the technology using green energy sources, which are employed in advanced vehicles, and smart transportation technology have become essential. For intelligent electric vehicles, which differ from internal combustion engine vehicles, traction motors and green energy systems (such as batteries and fuel cells) cause vehicles to produce zero (or few) pollutants, and they also have low-vibration, low-noise, and energy-saving characteristics. Moreover, multiple energy sources or power sources, such as fuel cell/battery vehicles and engine/motor hybrid electric vehicles, maximize output performance while minimizing the inherent drawbacks of single power (or energy) sources. Therefore, proper intelligent control and energy management are crucial considerations. Moreover, with the intelligent control of vehicle dynamics, steering, brakes and chassis, vehicles can be operated more efficiently and stably. Using the signals from sensors and actuators, vehicles must respond rapidly to maintain optimal conditions. Besides the outstanding performance of a single vehicle, intelligent transportation systems (ITSs) have recently attracted increasing research attention due to improved communication and information technologies. By establishing proper infrastructures and implementing rapid information exchange between vehicles and users, traffic management and vehicle supervision can be conducted. Therefore, a highly efficient traffic network can be established. This Special Issue will consider high-quality research and review papers that address the theoretical and application aspects of intelligent vehicles and smart transportation systems. Specific topics of interest for this Special Issue include, but are not limited to, the following topics:

  • Electric vehicles and hybrid vehicles;
  • Green energy sources and hybrid powertrains;
  • Key components of electric vehicles;
  • Intelligent vehicle control and energy management;
  • Control of vehicle dynamics and steering;
  • Intelligent vehicle systems design and control;
  • Applications of neural and fuzzy control systems;
  • Vehicle modeling and performance evaluation;
  • Information and communication system;
  • Real-time simulations and hardware-in-the-loop systems;
  • X-by-wire control;
  • Advanced driver assistance systems;
  • Autonomous vehicle systems;
  • Smart traffic management;
  • Intelligent transportation systems;
  • Human interface and safety enhancement;
  • Sensor and actuator technology;
  • Transportation policy and traffic planning.

Prof. Dr. Yi-Hsuan Hung
Dr. Hwa-Dong Liu
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

  • electric vehicles
  • hybrid vehicles
  • intelligent vehicle systems
  • intelligent transportation
  • autonomous vehicle

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Related Special Issue

Published Papers (2 papers)

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Research

42 pages, 5715 KiB  
Article
Development and Fuel Economy Optimization of Series–Parallel Hybrid Powertrain for Van-Style VW Crafter Vehicle
by Ahmed Nabil Farouk Abdelbaky, Aminu Babangida, Abdullahi Bala Kunya and Péter Tamás Szemes
Energies 2025, 18(14), 3688; https://doi.org/10.3390/en18143688 - 12 Jul 2025
Viewed by 341
Abstract
The presence of toxic gas emissions from conventional vehicles is worrisome globally. Over the past few years, there has been a broad adoption of electric vehicles (EVs) to reduce energy usage and mitigate environmental emissions. The EVs are characterized by limited range, cost, [...] Read more.
The presence of toxic gas emissions from conventional vehicles is worrisome globally. Over the past few years, there has been a broad adoption of electric vehicles (EVs) to reduce energy usage and mitigate environmental emissions. The EVs are characterized by limited range, cost, and short range. This prompts the need for hybrid electric vehicles (HEVs). This study describes the conversion of a 2022 Volkswagen Crafter (VW) 35 TDI 340 delivery van from a conventional diesel powertrain into a hybrid electric vehicle (HEV) augmented with synchronous electrical machines (motor and generator) and a BMW i3 60 Ah battery pack. A downsized 1.5 L diesel engine and an electric motor–generator unit are integrated via a planetary power split device supported by a high-voltage lithium-ion battery. A MATLAB (R2024b) Simulink model of the hybrid system is developed, and its speed tracking PID controller is optimized using genetic algorithm (GA) and particle swarm optimization (PSO) methods. The simulation results show significant efficiency gains: for example, average fuel consumption falls from 9.952 to 7.014 L/100 km (a 29.5% saving) and CO2 emissions drop from 260.8 to 186.0 g/km (a 74.8 g reduction), while the vehicle range on a 75 L tank grows by ~40.7% (from 785.7 to 1105.5 km). The optimized series–parallel powertrain design significantly improves urban driving economy and reduces emissions without compromising performance. Full article
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46 pages, 9390 KiB  
Article
Multi-Objective Optimization of Distributed Generation Placement in Electric Bus Transit Systems Integrated with Flash Charging Station Using Enhanced Multi-Objective Grey Wolf Optimization Technique and Consensus-Based Decision Support
by Yuttana Kongjeen, Pongsuk Pilalum, Saksit Deeum, Kittiwong Suthamno, Thongchai Klayklueng, Supapradit Marsong, Ritthichai Ratchapan, Krittidet Buayai, Kaan Kerdchuen, Wutthichai Sa-nga-ngam and Krischonme Bhumkittipich
Energies 2025, 18(14), 3638; https://doi.org/10.3390/en18143638 - 9 Jul 2025
Viewed by 410
Abstract
This study presents a comprehensive multi-objective optimization framework for optimal placement and sizing of distributed generation (DG) units in electric bus (E-bus) transit systems integrated with a high-power flash charging infrastructure. An enhanced Multi-Objective Grey Wolf Optimizer (MOGWO), utilizing Euclidean distance-based Pareto ranking, [...] Read more.
This study presents a comprehensive multi-objective optimization framework for optimal placement and sizing of distributed generation (DG) units in electric bus (E-bus) transit systems integrated with a high-power flash charging infrastructure. An enhanced Multi-Objective Grey Wolf Optimizer (MOGWO), utilizing Euclidean distance-based Pareto ranking, is developed to minimize power loss, voltage deviation, and voltage violations. The framework incorporates realistic E-bus operation characteristics, including a 31-stop, 62 km route, 600 kW pantograph flash chargers, and dynamic load profiles over a 90 min simulation period. Statistical evaluation on IEEE 33-bus and 69-bus distribution networks demonstrates that MOGWO consistently outperforms MOPSO and NSGA-II across all DG deployment scenarios. In the three-DG configuration, MOGWO achieved minimum power losses of 0.0279 MW and 0.0179 MW, and voltage deviations of 0.1313 and 0.1362 in the 33-bus and 69-bus systems, respectively, while eliminating voltage violations. The proposed method also demonstrated superior solution quality with low variance and faster convergence, requiring under 7 h of computation on average. A five-method compromise solution strategy, including TOPSIS and Lp-metric, enabled transparent and robust decision-making. The findings confirm the proposed framework’s effectiveness and scalability for enhancing distribution system performance under the demands of electric transit electrification and smart grid integration. Full article
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