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Sustainability
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Improvement and Exploitation in Energy Conservation and Engine Combustion
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Improvement and Exploitation in Energy Conservation and Engine Combustion

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: closed (23 October 2023) | Viewed by 3907

Special Issue Editors

Dr. Zhiqing Zhang

E-Mail Website
Guest Editor
School of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou 545006, China
Interests: renewable energy; energy efficiency; combustion; energy conservation; emission control; exhaust gas recirculation
Dr. Zibin Yin

E-Mail Website
Guest Editor
School of Marine Engineering, Jimei University, Xiamen 361021, China
Interests: marine engine; combustion; selective catalytic reduction; energy efficiency; diesel particulate filte
Dr. Dongli Tan

E-Mail Website
Guest Editor
Research Center of Guangxi Industry High-Quality Development, Guangxi University of Science and Technology, Liuzhou 545006, China
Interests: diesel engine; combustion; energy conversion; energy efficiency; diesel particulate filte; biodiesel

Special Issue Information

Dear Colleagues,

The low-carbon development and carbon emission reduction have been approved by all countries. This has become a new economic development model and is very important to the sustainable development of mankind. As a result, many clean combustion and energy conservation technologies, such as plasma-assisted combustion, porous media combustion, mild combustion, supercharging technology and chemical looping combustion have been developed in the past decades.

This Special Issue's primary objective is the deployment of engine combustion technology, renewable energy, energy conservation development, energy-saving technology improvement, increased access to energy, and the mitigation of climate change. Sustainable development is made possible by using sustainable energy and ensuring access to affordable, reliable, sustainable, and modern energy for citizens. Nowadays, the improvements in energy conservation, microscale combustion and engine combustion technologies are attracting more and more attention from researchers all over the world.

To promote communication between researchers, we invite investigators to contribute original research articles as well as review articles that will stimulate the continuing efforts to understand the mechanisms, production, and controls related to energy conservation and engine combustion technologies in engine power systems.

  • Performance comparison, evaluation and optimization of engine power systems
  • Renewable energy systems, modeling, and optimization
  • Energy from combustion and power generation
  • Energy-saving, economic evaluation, and material integration in combustion processes
  • Numerical simulation, modeling, and optimization of engines
  • Improvement of new energy technology
  • Hydrogen energy production and utilization
  • Fuel and biofuel processing and production technology
  • New energy and advanced energy-saving technologies

Dr. Zhiqing Zhang
Dr. Zibin Yin
Dr. Dongli Tan
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. Sustainability 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 2400 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

  • diesel engine
  • renewable energy conversion and utilization
  • energy saving
  • renewable energy
  • system optimization
  • energy efficiency
  • supercharging technology
  • chemical looping combustion
  • clean combustion
  • power system
  • microscale combustion

Published Papers (2 papers)

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Research

23 pages, 7394 KiB  
Article
Study on Multi-Objective Optimization of Power System Parameters of Battery Electric Vehicles
by Jie Hu, Wentong Cao, Feng Jiang, Lingling Hu, Qian Chen, Weiguang Zheng and Junming Zhou
Sustainability 2023, 15(10), 8219; https://doi.org/10.3390/su15108219 - 18 May 2023
Cited by 5 | Viewed by 1708
Abstract
The optimization of power parameters is the key to the design of pure electric vehicles. Reasonable matching of the relationship between various parameters can effectively reduce energy consumption and achieve energy sustainability. In this paper, several vehicle performance indexes such as maximum vehicle [...] Read more.
The optimization of power parameters is the key to the design of pure electric vehicles. Reasonable matching of the relationship between various parameters can effectively reduce energy consumption and achieve energy sustainability. In this paper, several vehicle performance indexes such as maximum vehicle speed, acceleration time and power consumption per 100 km were used as optimization target vectors, and transmission ratio was used as optimization variable to establish the optimization problem of parameter matching. Then, the feasible domain of the transmission ratio was obtained by taking the lowest performance index of the vehicle as the constraint condition. In the feasible domain, the multi-objective genetic algorithm is used to solve the optimization problem. The Pareto optimal solution set is obtained for fixed ratio transmission and two-gear transmission, which is used as an alternative solution set. The final parameter-matching scheme is determined by comparing the alternative scheme set of different motors comprehensively. The results show that the competition relationship between multiple optimizable indexes can be described effectively by solving the Pareto front. Specifically, the Pareto optimal solution set for the motor A + fixed transmission scheme is 1.33~1.85; the Pareto optimal solution set for the motor A + 2 transmission scheme is [1.72, 0.98]~[2.99, 1.57], and the Pareto optimal solution set for the motor B + 2 transmission scheme is [2.99, 1.40]~[2.99, 1.57]. The motor A + fixed transmission scheme does not require A clutch and does not require designing a shift algorithm. Therefore, after comprehensive consideration, the motor A + fixed transmission ratio transmission scheme is set as the final scheme. Full article
(This article belongs to the Special Issue Improvement and Exploitation in Energy Conservation and Engine Combustion)
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20 pages, 106734 KiB  
Article
An Energy Management Strategy for Fuel-Cell Hybrid Commercial Vehicles Based on Adaptive Model Prediction
by Enyong Xu, Mengcheng Ma, Weiguang Zheng and Qibai Huang
Sustainability 2023, 15(10), 7915; https://doi.org/10.3390/su15107915 - 11 May 2023
Cited by 3 | Viewed by 1574
Abstract
Fuel-cell hybrid electric vehicles have the advantages of zero pollution and high efficiency and are extensively applied in commerce. An energy management strategy (EMS) directly impacts the fuel consumption and performance. Moreover, model prediction control (MPC) is synchronous and has been a research [...] Read more.
Fuel-cell hybrid electric vehicles have the advantages of zero pollution and high efficiency and are extensively applied in commerce. An energy management strategy (EMS) directly impacts the fuel consumption and performance. Moreover, model prediction control (MPC) is synchronous and has been a research hotspot of EMS in recent years. The existing MPC’s low-speed prediction accuracy, which results in considerable instability in EMS allocation, is solved by the proposed energy management strategy based on adaptive model prediction. Dynamic programming (DP) is used as the solver, improved condition recognition and a radial basis neural network (RBFNN) are used as the speed predictor, and hydrogen consumption and the state of charge (SOC) are used as the objective function. According to the simulation results, using a 5 s speed prediction improves the forecast accuracy by 9.75%, and compared with employing a rule-based energy management strategy, this strategy reduces hydrogen consumption and the power cell fluctuation frequency by 3.50%. Full article
(This article belongs to the Special Issue Improvement and Exploitation in Energy Conservation and Engine Combustion)
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