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Special Issue "Dynamics Modeling, Control, and Eco-Driving of Heavy Equipment & Machinery for Eco-Friendly Environments"
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electrical and Autonomous Vehicles".
Deadline for manuscript submissions: 15 September 2023 | Viewed by 104
Special Issue Editors
Interests: vehicle system dynamics; lightweight design of automotive components
Special Issues, Collections and Topics in MDPI journals
Special Issue in Sustainability: Recent Advances in Sustainability Development for Autonomous Systems
Special Issue in Actuators: Modeling, Dynamics, Intelligent Control, and Fault Diagnosis of Vehicle Systems
Topics: Safety of Lithium-ion Batteries
Interests: CAD/CAE/CAx; virtual design and manufacture; design for MC; design optimization; product innovation; R&D management
Special Issue Information
Heavy equipment, or heavy machinery, refers to heavy-duty vehicles. These vehicles are frequently used for construction, lifting, landscaping, digging, road paving, forestry, etc., and consume extensive amounts of energy. Research on the dynamics modeling, control and environmental friendliness of heavy machinery is thus critical to reduce their energy consumption and develop a more ecofriendly, less energy-intensive vehicle model. Recently, a large number of methods, including machine learning methods, have been applied for the dynamics modeling, control and development of heavy equipment and machinery for ecofriendly environments.
In this Special Issue, we will analyze how an accurate dynamics model can be developed for ecofriendly safety and control applications to improve heavy equipment’ overall efficiency, aiming to present high-quality research detailing recent progress in the development of safe, energy-saving control technologies.
We welcome original papers on topics including, but not limited to, the following:
- Machine learning methods for modeling and control;
- Machine learning methods for eco-driving and energy saving applications;
- Multibody system methods for dynamics modeling and analysis;
- Other effective methods for modeling, control and energy saving applications;
- Health monitoring and management of heavy equipment and machinery;
- Fault diagnosis and prognosis of heavy equipment and machinery;
- Comfort and performance of heavy equipment and machinery;
- Passive and active safety control of heavy equipment and machinery.
Dr. Yongjun Pan
Prof. Dr. Liang Hou
Prof. Dr. Zhixiong Li
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. Electronics 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 2000 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.
- machine learning methods for modeling and control
- energy saving
- heavy equipment and machinery