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Innovations in Vehicle Engines: Towards Low Carbon and Reduced Emissions

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "I2: Energy and Combustion Science".

Deadline for manuscript submissions: 15 July 2024 | Viewed by 628

Special Issue Editors


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Guest Editor
State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China
Interests: vehicle powertrain control; virtual sensors; after-treatment system control

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Guest Editor
College of Automotive Engineering, Jilin University, Changchun 130022, China
Interests: zero-carbon fuel engines; energy saving technology for automotive engines

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Guest Editor
College of Mathematics and Computer Science, Jilin Normal University, Siping 136000, China
Interests: vehicle powertrain control; mathematical modeling and control

Special Issue Information

Dear Colleagues,

This Special Issue aims to address the latest advancements and research in the field of vehicle engines, focusing on the performance, combustion processes and emission control in vehicle engines. This issue welcomes contributions that explore innovative approaches, both theoretical and practical, to enhance engine efficiency, reduce emissions and improve overall engine performance.

Internal combustion engines remain the mainstream power source for vehicles, especially in certain specific usage scenarios. More and more experts and scholars believe that a coexistence of multiple power sources will be a reasonable form for future transportation systems. Therefore, the goal of this Special Issue is to further enhance the performance of vehicle internal combustion engines, reduce their energy consumption and emissions, and contribute to sustainable energy and a green environment. With the rapid development of internal combustion engine technology, new combustion modes and a variety of alternative fuels have become the main focus of research. We hope to deeply explore the potential of each technology. Additionally, after-treatment systems have become indispensable parts of internal combustion engines. Identifying appropriate optimization and control methods is critical for emission performance. Hybrid engines, as a multi-power source system, have different requirements from traditional ICEs. Targeted design and optimization methods will significantly improve their performance. We encourage submissions that delve into advanced combustion techniques, emission reduction strategies and the integration of new technologies in engine design and operation.

The Special Issue covers a range of topics, including, but not limited to:

  • Advanced combustion modes;
  • Hybrid vehicle engines;
  • Emission control technologies and strategies;
  • After-treatment system control;
  • Zero-carbon fuel engines;
  • Innovations in engine designs;
  • Fault monitoring and diagnosis;
  • Calculation of the carbon footprint of ICEs;
  • Energy saving  technology of automotive power.

We look forward to receiving your contributions and advancing the field of vehicle engine technology through this Special Issue.

Dr. Yao Sun
Prof. Dr. Fangxi Xie
Prof. Dr. Jinghua Zhao
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

  • advanced combustion modes
  • hybrid vehicle engines
  • emission control technologies and strategies
  • after-treatment system control
  • zero-carbon fuel engines
  • innovations in engine designs
  • fault monitoring and diagnosis
  • calculation of the carbon footprint of ICEs
  • energy saving technology of automotive power

Published Papers (1 paper)

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Research

15 pages, 1120 KiB  
Article
Multi-Objective Optimization Strategy for Fuel Cell Hybrid Electric Trucks Based on Driving Patern Recognition
by Renzhi Lyu, Zhenpo Wang and Zhaosheng Zhang
Energies 2024, 17(6), 1334; https://doi.org/10.3390/en17061334 - 11 Mar 2024
Viewed by 463
Abstract
Fuel cell hybrid electric trucks have become a cutting-edge field in understanding urban traffic emissions due to their enormous potential in low-carbon areas. In order to improve the economy of fuel cell hybrid electric trucks and reduce the decline of fuel cell lifespan, [...] Read more.
Fuel cell hybrid electric trucks have become a cutting-edge field in understanding urban traffic emissions due to their enormous potential in low-carbon areas. In order to improve the economy of fuel cell hybrid electric trucks and reduce the decline of fuel cell lifespan, this paper proposes a multi-objective energy management strategy that optimizes weight coefficients. On the basis of establishing a fuel cell battery hybrid system model, three modes of uniform speed, acceleration, and deceleration were identified through clustering analysis of vehicle speed. Reinforcement learning algorithms were used to learn the corresponding weights for different modes, which reduced the decline in fuel cell life while improving the economic efficiency. The simulation results indicate that, under the conditions of no load, half load, and full load, the truck only sacrificed 0.9–5.6%, 1.7–2.6%, and 1.2–1.6% SOC, saving 5.7–6.45%, 5.9–6.67%, and 6.1–6.67% in lifespan loss, and reducing hydrogen consumption by 3.0–7.1%, 2.8–4.4%, and 1.0–3.0%, respectively. Full article
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