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: 15 September 2024 | Viewed by 5324

Special Issue Editors


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Guest Editor
College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China
Interests: green manufacturing; sustainable management and technology; field synergy analysis; biodiesel combustion in diesel engine; after-treatment system of automotive systems; multidisciplinary design optimization; intelligent information fusion; active control and signal processing
Special Issues, Collections and Topics in MDPI journals
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

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Keywords

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

Published Papers (4 papers)

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Research

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://0-doi-org.brum.beds.ac.uk/10.3390/pr11072036 - 07 Jul 2023
Cited by 2 | Viewed by 760
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)
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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://0-doi-org.brum.beds.ac.uk/10.3390/pr11061756 - 09 Jun 2023
Viewed by 1694
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)
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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://0-doi-org.brum.beds.ac.uk/10.3390/pr11051416 - 06 May 2023
Cited by 2 | Viewed by 1255
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)
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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://0-doi-org.brum.beds.ac.uk/10.3390/pr11041089 - 04 Apr 2023
Cited by 1 | Viewed by 997
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)
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