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Modeling and Simulation of Electric Vehicle, Hybrid Electric Vehicle, and Intelligent Vehicle Dynamics

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

Deadline for manuscript submissions: closed (16 November 2024) | Viewed by 3550

Special Issue Editors

Dr. Pu Gao

E-Mail Website
Guest Editor
School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
Interests: vehicle dynamics
Dr. Shida Nie

E-Mail Website
Guest Editor
School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
Interests: intelligent electric vehicles; eco-driving; vehicle dynamic control
Dr. Yue Wang

E-Mail Website
Guest Editor
School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, China
Interests: intelligent electric vehicles; eco-driving; speed planning; energy management; integrated control

Special Issue Information

Dear Colleagues,

During the last decade, electric vehicles, hybrid electric vehicles, and intelligent vehicles have been hotspots in the development of land transportation. Effective dynamic modeling, simulation, and analysis are key to improving vehicle dynamic characteristics and transportation efficiency.

This Special Issue calls for papers that explore the dynamic modeling, simulation, and analysis of electric vehicles, hybrid electric vehicles, and intelligent vehicles in complex driving scenarios. It aims to present original research papers as well as review articles providing new highlights and a summary of the current and emerging problems of generalized electric vehicle, hybrid electric vehicle, and intelligent vehicle dynamics. We invite authors from all fields of science that fall under the broader umbrella of electric vehicles, hybrid electric vehicles, and intelligent vehicles, including but not limited to the following:

  1. All aspects of induction electric vehicle, hybrid electric vehicle, and intelligent vehicle dynamics.
  2. Modeling, simulation, and analysis of electric vehicles, hybrid electric vehicles, and intelligent vehicles.
  3. Electric motor/generator technologies for electric vehicles, hybrid electric vehicles, and intelligent vehicles.
  4. Energy management, speed planning, eco-driving control, and dynamic control (in the field of intelligent electric vehicles).
  5. Novel applications of electric vehicles, hybrid electric vehicles, and intelligent vehicles.
  6. Vehicles for safety-critical applications.
  7. Online and offline condition monitoring techniques of vehicles.
  8. Optimal design methodologies of vehicles.

Dr. Pu Gao
Dr. Shida Nie
Dr. Yue Wang
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 electric vehicles
  • intelligent vehicles
  • modeling
  • simulation
  • analysis
  • electric motor/generator
  • energy management

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Published Papers (2 papers)

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Research

24 pages, 7525 KiB  
Article
Optimal EMS Design for a 4-MW-Class Hydrogen Tugboat: A Comparative Analysis Using DP-Based Performance Evaluation
by Seonghyeon Hwang, Changhyeong Lee, Juyeol Ryu, Jongwoong Lim, Sohmyung Chung and Sungho Park
Energies 2024, 17(13), 3146; https://doi.org/10.3390/en17133146 - 26 Jun 2024
Cited by 3 | Viewed by 1399
Abstract
In the current trend of hydrogen fuel cell-powered ships, batteries are used together with fuel cells to overcome the limitations of fuel cell technology. However, performance differences arise depending on fuel cell and battery configurations, load profiles, and energy management system (EMS) algorithms. [...] Read more.
In the current trend of hydrogen fuel cell-powered ships, batteries are used together with fuel cells to overcome the limitations of fuel cell technology. However, performance differences arise depending on fuel cell and battery configurations, load profiles, and energy management system (EMS) algorithms. We designed four hybrid controllers to optimize EMS algorithms for achieving maximum performance based on target profiles and hardware. The selected EMS is based on a State Machine, an Equivalent Consumption Minimization Strategy (ECMS), Economic Model Predictive Control (EMPC), and Dynamic Programming (DP). We used DP to evaluate the optimal design state and fuel efficiency of each controller. To evaluate controller performance, we obtained a 4-MW-class tug load profile as a reference and performed simulations based on Nedstack’s fuel cells and a lithium-ion battery model. The constraints were set according to the description of each equipment manual, and the optimal controller was derived based on the amount of hydrogen consumed by each EMS under the condition of completely tracking the load profile. As a result of simulating the hybrid fuel cell–battery system by applying the load profile of the tugboat, we found that the 4-MW EMPC, which requires more state variables and control inputs, is the most fuel-efficient controller. Full article
(This article belongs to the Special Issue Modeling and Simulation of Electric Vehicle, Hybrid Electric Vehicle, and Intelligent Vehicle Dynamics)
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20 pages, 1829 KiB  
Article
Dynamics of a Rail Vehicle in Transition Curve above Critical Velocity with Focus on Hunting Motion Considering the Review of History of the Stability Studies
by Krzysztof Zboinski and Milena Golofit-Stawinska
Energies 2024, 17(4), 967; https://doi.org/10.3390/en17040967 - 19 Feb 2024
Cited by 2 | Viewed by 1525
Abstract
The most general purpose of the current paper is to trace and discuss the history and state of the art of studies on vehicle motion (dynamics) in a transition curve above the critical velocity, with the aim of potentially increasing the circle of [...] Read more.
The most general purpose of the current paper is to trace and discuss the history and state of the art of studies on vehicle motion (dynamics) in a transition curve above the critical velocity, with the aim of potentially increasing the circle of researchers involved in studying this issue and strengthening the will of the authors to continue their studies. This general goal is achieved in two ways: first, through a profiled literature analysis, showing the historical progress and current state of the research; and second, through reference to the history of stability studies as an example of selected studies’ development. In addition, this work has two more specific goals. Together, they consist of collecting the literature in a related field in one place and analyzing it on site to accomplish the review. Both specific goals are attained by dividing the literature into two corresponding parts. In the first part, the current issues of rail vehicle stability are analyzed and divided into four problems. The second part includes works that deal with the subject of the motion and dynamics of a rail vehicle on a transition curve section. Here, the works are divided into five groups and discussed. They are put in order from the closest to the furthest from this paper’s main subject; however, the last group includes the most recent references. In addition, information on the authors’ approach to the problem is provided, including the methods and models used, as well as example results. Based on the analysis of the literature and the state of the art, a summary of the analysis is presented at this paper’s end. It highlights the small number of works on the subject of interest, and based on the review of stability studies, it seeks to encourage present and potential authors to study this field and share their results with society. Full article
(This article belongs to the Special Issue Modeling and Simulation of Electric Vehicle, Hybrid Electric Vehicle, and Intelligent Vehicle Dynamics)
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