Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.1
2.8
Journals
Processes
Special Issues
Green Manufacturing and Low-Carbon Application of the Power Batteries
share announcement

Green Manufacturing and Low-Carbon Application of the Power Batteries

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: 25 November 2025 | Viewed by 10939

Special Issue Editors

Prof. Dr. Jiaqiang E

grade E-Mail Website
Guest Editor
College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China
Interests: combustion & micro-combustion; biodiesel combustion; micro-thermophotovoltaic power generators; after-treatment system of automotive systems; battery thermal management system
Special Issues, Collections and Topics in MDPI journals
Dr. Bin Zhang

E-Mail Website
Guest Editor
School of Electrical and Information Engineering, Hunan Institute of Engineering, Xiangtan 411104, China
Interests: after-treatment system of automotive systems; battery thermal management systems; clean combustion of engines; utilization of renewable energy

Special Issue Information

Dear Colleagues,

There are many waste emissions and fault problems in the process of manufacturing and application of the power battery.

Minimum waste emissions and long service life are desirable in the manufacturing and use of power batteries. Many waste emissions and fault problems will reduce the service efficiency and life of power batteries. Green manufacturing and low-carbon application are very important to energy, environment and sustainable ecological development. However, green manufacturing and low-carbon application of power batteries still represent serious challenges for academic researchers and industrial engineers.

This Special Issue is dedicated to the most recent advances in research on the green manufacturing and low-carbon application of power batteries. We invite scientists and investigators to contribute original research and review articles which address the topics of the special issue.

Potential topics include, but are not limited to:

  • Green manufacturing assessment of power batteries;
  • Green manufacturing strategies for power batteries;
  • Green manufacturing operation models for power batteries;
  • Life-cycle assessment of power batteries;
  • Countermeasure analysis of power batteries;
  • Cascade utilization of power batteries;
  • Thermal management technology of power batteries;
  • Carbon footprint evolution under green manufacturing and low-carbon application of power batteries;
  • Renewable materials for power batteries;
  • Systems modeling and simulation under green manufacturing and low-carbon application of power batteries.

Prof. Dr. Jiaqiang E
Dr. Bin Zhang
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. Processes is an international peer-reviewed open access monthly 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

  • green manufacturing
  • low-carbon technology
  • power battery
  • carbon footprint
  • life-cycle theory

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (5 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

15 pages, 2681 KiB  
Article
Simulation Study on Factors Affecting the Output Voltage of Extended-Range Electric Vehicle Power Batteries
by Xiaodong Wang, Bin Zhang, Jiaqiang E and Xidan Xiao
Processes 2024, 12(10), 2195; https://doi.org/10.3390/pr12102195 - 9 Oct 2024
Viewed by 1245
Abstract
The power battery configuration of an extended-range electric vehicle directly affects the overall performance of the vehicle. Optimization of the output voltage of the power battery can improve the overall power and economy of the vehicle to ensure its safe operation. Factors affecting [...] Read more.
The power battery configuration of an extended-range electric vehicle directly affects the overall performance of the vehicle. Optimization of the output voltage of the power battery can improve the overall power and economy of the vehicle to ensure its safe operation. Factors affecting the output voltage of power batteries under different operating conditions, such as nominal voltage and the number of series and parallel connections of the battery cells, have been studied. This study uses AVL Cruise to establish an overall model of an extended-range electric vehicle to simulate the output voltage characteristics under the different operating conditions of the NEDC (New European Driving Cycle), WLTC (World Light Vehicle Test Cycle) and CLTC (China Light Duty Vehicle Test Cycle). The influence of the output voltage of the power battery under different operating conditions is studied to ensure that the power battery can output energy with high efficiency. The operating conditions have an impact on the output voltage with an idle voltage fluctuation of the operating conditions. The nominal voltage variation and the number of series and parallel connections of the battery cells affect the frequency and time of breakdown. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Application of the Power Batteries)
►▼ Show Figures

Figure 1

18 pages, 3239 KiB  
Article
A Fast Density Peak Clustering Method for Power Data Security Detection Based on Local Outlier Factors
by Zhuo Lv, Li Di, Cen Chen, Bo Zhang and Nuannuan Li
Processes 2023, 11(7), 2036; https://doi.org/10.3390/pr11072036 - 7 Jul 2023
Cited by 4 | Viewed by 1395
Abstract
The basic work of power data research is anomaly detection. It is necessary to find a method suitable for processing current power system data. Research proposes an algorithm of fast density peak clustering with Local Outlier Factor (LOF). The algorithm has poor performance [...] Read more.
The basic work of power data research is anomaly detection. It is necessary to find a method suitable for processing current power system data. Research proposes an algorithm of fast density peak clustering with Local Outlier Factor (LOF). The algorithm has poor performance in processing datasets with irregular shapes and significant local density changes, and has the disadvantage of strong dependence on truncation distance. This study provides the decision rules for outliers incorporating the idea of LOF. The improved algorithm can fully consider the characteristics of power data and reduce the dependence on truncation distance. In anomaly detection based on the simulation of real power data, the classification accuracy of the improved CFSFDP algorithm is 4.87% higher than that of the traditional algorithm, and the accuracy rate is 97.41%. The missed and false detection rates of the LOF-CFSFDP algorithm are decreased by 2.23% and 2.64%, respectively, compared to the traditional algorithm, and it is ultimately able to reach rates of 1.26% and 1.33%. These results indicate that the algorithm proposed in this study can better describe the characteristics of power data, making the features of outliers and cluster center points more obvious. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Application of the Power Batteries)
►▼ Show Figures

Figure 1

19 pages, 5709 KiB  
Article
The Modification of WO3 for Lithium Batteries with Nickel-Rich Ternary Cathode Materials
by Lipeng Xu, Chunjiang Bao, Haobing Zhou and Jun Li
Processes 2023, 11(6), 1756; https://doi.org/10.3390/pr11061756 - 9 Jun 2023
Cited by 4 | Viewed by 3196
Abstract
Nickel-rich ternary cathode materials (NRTCMs) have high energy density and a long cycle life, making them one of the cathode materials of LIB that are currently receiving much attention. However, it has shortcomings such as poor cycling performance (CP) and a high-capacity decay [...] Read more.
Nickel-rich ternary cathode materials (NRTCMs) have high energy density and a long cycle life, making them one of the cathode materials of LIB that are currently receiving much attention. However, it has shortcomings such as poor cycling performance (CP) and a high-capacity decay rate. Because of this, the study analyzed the modification effect of WO3 on NRTCM lithium batteries by preparing WO3-modified poly-crystal and single-crystal NCM622 materials under the existing conditions of better original cathode materials as reference samples. The results showed that in the morphology and structure testing, with the increase of WO3 addition, the c/a values of all NCM622-WO3 samples were greater than 4.95. In the analysis of cycling and rate performance (CRP), as W increased, the rate performance (RP) of the NCM622-W4.0 sample had a discharge specific capacity ratio of 86.2% at 10.0 C/1.0 C. In cyclic voltammetry testing, when the addition amount of WO3 was 1.0%, the polarization degree of SC-NCM622 sample was the weakest. In the AC impedance test, after six cycles, compared with the original sample, the Ret and R + Rct values of the NCM622-W sample modified with WO3 showed a significant downward trend. The above results prove that WO3 modification can lower the polarization of the material, effectively raising the CRP of the battery. It provides a reference path for the further progress of high capacity and stability ternary cathode materials. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Application of the Power Batteries)
►▼ Show Figures

Figure 1

16 pages, 2335 KiB  
Article
Optimization Strategy of the Electric Vehicle Power Battery Based on the Convex Optimization Algorithm
by Xuanxuan Wang, Wujun Ji and Yun Gao
Processes 2023, 11(5), 1416; https://doi.org/10.3390/pr11051416 - 6 May 2023
Cited by 6 | Viewed by 2305
Abstract
With the development of the electric vehicle industry, electric vehicles have provided more choices for people. However, the performance of electric vehicles needs improvement, which makes most consumers take a wait-and-see attitude. Therefore, finding a method that can effectively improve the performance of [...] Read more.
With the development of the electric vehicle industry, electric vehicles have provided more choices for people. However, the performance of electric vehicles needs improvement, which makes most consumers take a wait-and-see attitude. Therefore, finding a method that can effectively improve the performance of electric vehicles is of great significance. To improve the current performance of electric vehicles, a convex optimization algorithm is proposed to optimize the motor model and power battery parameters of electric vehicles, improving the overall performance of electric vehicles. The performance of the proposed convex optimization algorithm, dual loop DP optimization algorithm, and nonlinear optimization algorithm is compared. The results show that the hydrogen consumption of electric vehicles optimized by the convex optimization algorithm is 95.364 g. This consumption is lower than 98.165 g of the DCDP optimization algorithm and 105.236 g of the nonlinear optimization algorithm before optimization. It is also significantly better than the 125.59 g of electric vehicles before optimization. The calculation time of the convex optimization algorithm optimization is 4.9 s, which is lower than the DCDP optimization algorithm and nonlinear optimization algorithm. The above results indicate that convex optimization algorithms have better optimization performance. After optimizing the power battery using a convex optimization algorithm, the overall performance of electric vehicles is higher. Therefore, this method can effectively improve the performance of current electric vehicle power batteries, make new energy vehicles develop rapidly, and improve the increasingly serious environmental pollution and energy crisis in China. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Application of the Power Batteries)
►▼ Show Figures

Figure 1

22 pages, 6824 KiB  
Article
A Square Wave Alternating Current Preheating with High Applicability and Effectiveness of Preventing Lithium Plating
by Guanlin Liu, Zeping Zhang, Jinke Gong, Qiong Li, Yun Zhou and Hongfu Zou
Processes 2023, 11(4), 1089; https://doi.org/10.3390/pr11041089 - 4 Apr 2023
Cited by 5 | Viewed by 1800
Abstract
Alternating current preheating (ACP) of lithium-ion batteries has the advantage of a high heating rate while inhibiting lithium plating. Two strategies based on terminal voltage control and full battery impedance control were proposed to simplify the ACP implementation. However, such strategies either severely [...] Read more.
Alternating current preheating (ACP) of lithium-ion batteries has the advantage of a high heating rate while inhibiting lithium plating. Two strategies based on terminal voltage control and full battery impedance control were proposed to simplify the ACP implementation. However, such strategies either severely compromise the preheating rate or induce non-negligible lithium plating. To maximize the preheating rate while ensuring no lithium plating, an ACP method based on anode potential control is developed using a square wave alternating current. The operation boundaries of lithium plating prevention, in terms of frequency and maximum permissible current amplitude, are determined using the anode potential and impedance. Their effectiveness in preventing lithium plating is validated by repeating 800 cycles of preheating. By applying the operation boundaries, a temperature-adaptive preheating is found to be able to speed up the preheating rate with higher frequency, smaller temperature intervals and better thermal insulation. When the battery is preheated at a frequency of 400 Hz, with a temperature interval of 5 °C and a heat transfer coefficient of 5 Wm−2 K−1, the preheating rate can reach 6.61 °C/min, exceeding the method based on the terminal voltage control by 5.4%, and larger than that based on the full battery impedance control strategy by 41.8%. Full article
(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Application of the Power Batteries)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-5
Back to TopTop