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Intelligent Technologies and Processes for Advanced Nuclear Power and Energy...
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Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering

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

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 29926

Special Issue Editors

Dr. Amir M. Fathollahi-Fard

E-Mail Website
Guest Editor
Peter B. Gustavson School of Business, University of Victoria, P.O. Box 1700, Victoria, BC V8P5C2, Canada
Interests: supply chain management; healthcare systems; sustainable logistics and production management; optimization algorithms; heuristics; metaheuristics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Vigen H. Arakelian

E-Mail Website
Guest Editor
Head of the research team «Mecaproce», Institut National des Sciences Appliquées (INSA) 20 av. des Buttes de Coesmes, CS 70839, F-35708 Rennes, France
Interests: design, kinematics and dynamics of mechanical systems; robot hands and the mechanics of manipulation; industrial robotic innovation; (4) mechatronic approaches to the design of robot manipulators; dynamic balancing and synthesis of high-speed machines; rehabilitation engineering, prosthetics and orthotics; numerical simulation and optimization of mechanisms using ADAMS software
Special Issues, Collections and Topics in MDPI journals
Dr. Zhiwu Li

E-Mail Website
Guest Editor
Institute of Systems Engineering, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macao
Interests: petri net theory and application; supervisory control of discrete event systems; workflow analysis; system reconfiguration; game theory; production scheduling and planning; data and process mining
Special Issues, Collections and Topics in MDPI journals
Dr. Zixian Zhang

E-Mail Website
Guest Editor
Department of Mechanical Science, Tokyo Institute of Technology, Tokyo 101-0021, Japan
Interests: reconstruction of CAD models from triangular surface mesh; product optimal design; advanced manufacturing technology;networked manufacturing.
Special Issues, Collections and Topics in MDPI journals
Dr. Guangdong Tian

E-Mail Website
Guest Editor
School of Mechanical-Electrical and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
Interests: remanufacturing and green manufacturing; green logistics and transportation; intelligent inspection and automotive repair
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Nuclear power equipment is a national name card which plays an important role in the nuclear power supply of the new generation of onshore nuclear power plants, submarine aircraft carriers, marine development, deep space exploration and other major national projects. From the designation to decommissioning of nuclear power equipment, lifecycle digital and intelligent technologies implement a visual and flexible analysis mode and integrate information on the whole process to supply systematic engineering service in design, manufacturing, operation and management. Because of the numerous subsystems, complex working conditions and lengthy service period of advanced nuclear power equipment, how to realize its lifecycle digital and intelligent technologies is a daunting task. This has recently motivated researchers to explore new lifecycle digital and intelligent technologies of advanced nuclear power equipment.

The objective of this Special Issue is to present the latest advances and developments dedicated to the lifecycle digital and intelligent technologies for advanced nuclear power equipment, such as digital collaborative design, multidisciplinary design optimization and autonomous decision making, intelligent and sustainable nuclear manufacturing, predictive maintenance and autonomous diagnostics.

Topics of interest for this Special Issue include, but are not limited to, the following:

  • Digital collaborative design and manufacturing in the nuclear power industry;
  • Multidisciplinary design optimization and autonomous decision making for nuclear power equipment;
  • Modular technologies for nuclear engineering;
  • The whole lifecycle model system of nuclear power equipment;
  • Intelligent nuclear manufacturing with digital twin;
  • Four-dimensional digital construction schedule management in the nuclear power industry;
  • Visual simulation technologies in start-up commissioning of nuclear systems;
  • Sustainable nuclear manufacturing using data-driven approaches;
  • Predictive maintenance for long-term operation of nuclear power equipment;
  • Autonomous diagnostics and prognostics for nuclear power equipment;
  • Information integration and cognitive system in nuclear power scenarios;
  • Quality control and traceability of state co-evolution for nuclear power equipment;

Domain knowledge coupling association and deep mining based on data space in the nuclear power industry.

Dr. Amir M. Fathollahi-Fard
Prof. Dr. Vigen H. Arakelian
Dr. Zhiwu Li
Dr. Zixian Zhang
Prof. Dr. Guangdong Tian
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

  • lifecycle management
  • sustainability
  • quality control
  • intellgent systems
  • nuclear manufacturing

Published Papers (15 papers)

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Editorial

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3 pages, 186 KiB  
Editorial
Editorial for Special Issue on “Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering”
by Amir M. Fathollahi-Fard, Vigen H. Arakelian, Zhiwu Li, Zixian Zhang and Guangdong Tian
Processes 2023, 11(2), 449; https://doi.org/10.3390/pr11020449 - 2 Feb 2023
Viewed by 892
Abstract
This Special Issue, entitled “Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering”, was organized by the journal Processes as a way to collect original research articles on the latest developments in intelligent technologies and processes for advanced nuclear power and [...] Read more.
This Special Issue, entitled “Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering”, was organized by the journal Processes as a way to collect original research articles on the latest developments in intelligent technologies and processes for advanced nuclear power and energy systems [...] Full article
(This article belongs to the Special Issue Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering)

Research

Jump to: Editorial

15 pages, 1802 KiB  
Article
Energy Storage Charging Pile Management Based on Internet of Things Technology for Electric Vehicles
by Zhaiyan Li, Xuliang Wu, Shen Zhang, Long Min, Yan Feng, Zhouming Hang and Liqiu Shi
Processes 2023, 11(5), 1561; https://doi.org/10.3390/pr11051561 - 19 May 2023
Cited by 1 | Viewed by 2157
Abstract
The traditional charging pile management system usually only focuses on the basic charging function, which has problems such as single system function, poor user experience, and inconvenient management. In this paper, the battery energy storage technology is applied to the traditional EV (electric [...] Read more.
The traditional charging pile management system usually only focuses on the basic charging function, which has problems such as single system function, poor user experience, and inconvenient management. In this paper, the battery energy storage technology is applied to the traditional EV (electric vehicle) charging piles to build a new EV charging pile with integrated charging, discharging, and storage; Multisim software is used to build an EV charging model in order to simulate the charge control guidance module. On this basis, combined with the research of new technologies such as the Internet of Things, cloud computing, embedded systems, mobile Internet, and big data, new design and construction methods of the energy storage charging pile management system for EV are explored. Moreover, K-Means clustering analysis method is used to analyze the charging habit. The functions such as energy storage, user management, equipment management, transaction management, and big data analysis can be implemented in this system. The simulation results of this paper show that: (1) Enough output power can be provided to meet the design and use requirements of the energy-storage charging pile; (2) the control guidance circuit can meet the requirements of the charging pile; (3) during the switching process of charging pile connection state, the voltage state changes smoothly. It can provide a new method and technical path for the design of electric vehicle charging pile management system, which can effectively reduce the system’s operation and maintenance costs and provide more friendly and convenient charging services. Full article
(This article belongs to the Special Issue Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering)
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15 pages, 2336 KiB  
Article
An Improved MOEA/D Algorithm for the Solution of the Multi-Objective Optimal Power Flow Problem
by Zhitao Wu, Hao Liu, Jian Zhao and Zhiwu Li
Processes 2023, 11(2), 337; https://doi.org/10.3390/pr11020337 - 20 Jan 2023
Cited by 2 | Viewed by 1472
Abstract
The optimal power flow (OPF) is an important tool for the secure and economic operation of the power system. It attracts many researchers to pay close attention. Many algorithms are used to solve the OPF problem. The decomposition-based multi-objective algorithm (MOEA/D) is one [...] Read more.
The optimal power flow (OPF) is an important tool for the secure and economic operation of the power system. It attracts many researchers to pay close attention. Many algorithms are used to solve the OPF problem. The decomposition-based multi-objective algorithm (MOEA/D) is one of them. However, the effectiveness of the algorithm decreases as the size of the power system increases. Therefore, an improved MOEA/D (IMOEA/D) is proposed in this paper to solve the OPF problem. The main goal of IMOEA/D is to speed up the convergence of the algorithm and increase species diversity. To achieve this goal, three improvement strategies are introduced. Firstly, the competition strategy between the barnacle optimization algorithm and differential evolution algorithm is adopted to overcome the reduced species diversity. Secondly, an adaptive mutation strategy is employed to enhance species diversity at the latter stage of iteration. Finally, the selective candidate with similarity selection is used to balance the exploration and exploitation capabilities of the proposed algorithm. Simulation experiments are performed on IEEE 30-bus and IEEE 57-bus test systems. The obtained results show that the above three measures can effectively improve the diversity of the population, and also demonstrate the competitiveness and effectiveness of the proposed algorithm for the OPF problem. Full article
(This article belongs to the Special Issue Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering)
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13 pages, 2907 KiB  
Article
Green Manufacturing-Oriented Polyetheretherketone Additive Manufacturing and Dry Milling Post-Processing Process Research
by Hao Zhou, Xiang Cheng, Xiuli Jiang, Guangming Zheng, Junfeng Zhang, Yang Li, Mingze Tang and Fulin Lv
Processes 2022, 10(12), 2561; https://doi.org/10.3390/pr10122561 - 1 Dec 2022
Cited by 3 | Viewed by 1541
Abstract
The application of polyetheretherketone (PEEK) in additive manufacturing (AM) can effectively reduce material and energy waste in the manufacturing process and help achieve lightweight parts. As a result, AM PEEK is considered an emerging technology in line with green manufacturing concepts. However, 3D-printed [...] Read more.
The application of polyetheretherketone (PEEK) in additive manufacturing (AM) can effectively reduce material and energy waste in the manufacturing process and help achieve lightweight parts. As a result, AM PEEK is considered an emerging technology in line with green manufacturing concepts. However, 3D-printed PEEK parts often suffer from low mechanical strength and poor surface quality due to the immaturity of the manufacturing process. Therefore, this research investigates the feasibility of improving the surface quality of 3D-printed parts by dry milling post-processing. Meanwhile, the mechanical strength of the parts is improved by optimizing the printing process parameters, and the effects of mechanical strength on milling quality are investigated. The novelty of this research is to design experiments based on the anisotropy of 3D-printed parts. For the first time, the delamination of the milling post-processing surface of 3D-printed PEEK parts is investigated. The results show that the milled surfaces of 3D-printed PEEK parts are prone to delamination problems. The printing direction has a significant effect on the quality of milling post-processing, whereas the milling directions have little effect on milling post-processing quality. The delamination problem can be significantly improved by a side milling process where the specimen is printed at 90° and then milled. Milling surface delamination is caused by the poor mechanical strength (internal bonding) of 3D-printed PEEK parts. By improving the mechanical strength of 3D-printed PEEK parts, the delamination of its milled surfaces can be significantly improved. Full article
(This article belongs to the Special Issue Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering)
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13 pages, 1265 KiB  
Article
Digital Technology and Innovative Technology to Promote the Professional Development of Digital Media Based on Green Energy under COVID-19
by Qianqian Xu, Bing Zheng, Hongmi Zhou, Jingfan Chen, Zhifeng Zhang and Xueping Wu
Processes 2022, 10(10), 1915; https://doi.org/10.3390/pr10101915 - 21 Sep 2022
Cited by 1 | Viewed by 1201
Abstract
Taking as an example the practical teaching of the design of children’s solar-energy-based ultraviolet disinfection products, we analyzed the practical activities in four stages of teaching—case background, research methods, product design, and practical results—in the practical teaching mode based on solar green energy. [...] Read more.
Taking as an example the practical teaching of the design of children’s solar-energy-based ultraviolet disinfection products, we analyzed the practical activities in four stages of teaching—case background, research methods, product design, and practical results—in the practical teaching mode based on solar green energy. This paper presents and proposes a design solution for a solar-powered green energy-based multifunctional inductive UV disinfection product for children to provide additional services for school interventions and improve public health in primary and secondary schools. This new innovative design for a children’s disinfection product is based on solar green energy and enhances the graded disinfection strategy in schools, reducing the number of viruses and the potential risk of virus transmission in the educational environment. The proposed program aims to be project-oriented, combining green energy concepts with innovative educational concepts, classroom content with social prevention products, digital technology with innovative thinking, promoting the development of innovative and digital abilities of teachers and students, and promoting the development of practical teaching in digital media. The practical results show that the model has positive teaching effects, practical value for students, schools and society, cultivation of digital innovation ability of teachers and students, and reference significance for practical teaching. Full article
(This article belongs to the Special Issue Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering)
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17 pages, 3141 KiB  
Article
Development of an Improved Water Cycle Algorithm for Solving an Energy-Efficient Disassembly-Line Balancing Problem
by Xuesong Zhang, Jing Yuan, Xiaowen Chen, Xingqin Zhang, Changshu Zhan, Amir M. Fathollahi-Fard, Chao Wang, Zhiming Liu and Jie Wu
Processes 2022, 10(10), 1908; https://doi.org/10.3390/pr10101908 - 21 Sep 2022
Cited by 11 | Viewed by 1401
Abstract
Nowadays, there is a great deal of interest in the development of practical optimization models and intelligent solution algorithms for solving disassembly-line balancing problems. Based on the importance of energy efficiency of product disassembly and the trend for green remanufacturing, this paper develops [...] Read more.
Nowadays, there is a great deal of interest in the development of practical optimization models and intelligent solution algorithms for solving disassembly-line balancing problems. Based on the importance of energy efficiency of product disassembly and the trend for green remanufacturing, this paper develops a new optimization model for the energy-efficient disassembly-line balancing problem where the goal is to minimize the energy consumption generated during the disassembly-line operations. Since the proposed model is a complex optimization problem known as NP-hard, this study develops an improved metaheuristic algorithm based on the water cycle algorithm as a recently developed successful metaheuristic inspired by the natural water cycle phenomena of diversion, rainfall, confluence, and infiltration operations. A local search operator is added to the main algorithm to improve its performance. The proposed algorithm is validated by the exact solver and compared with other state-of-the-art and recent metaheuristic algorithms. A case study in a turbine reducer with different parameters is solved to show the applicability of this paper. Finally, our results confirm the high performance of the proposed improved water cycle algorithm and the efficiency of our sensitivity analyses during some sensitivity analyses. Full article
(This article belongs to the Special Issue Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering)
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25 pages, 5977 KiB  
Article
Adaptive Energy Management Strategy Based on Intelligent Prediction of Driving Cycle for Plug−In Hybrid Electric Vehicle
by Dapai Shi, Shipeng Li, Kangjie Liu, Yun Wang, Ruijun Liu and Junjie Guo
Processes 2022, 10(9), 1831; https://doi.org/10.3390/pr10091831 - 10 Sep 2022
Cited by 8 | Viewed by 1713
Abstract
Under the dual−carbon goal, the research on energy conservation and emission reduction of new energy vehicles has once again become a current hotspot, and plug−in hybrid electric vehicles (PHEVs) are the first to bear the brunt. In order to improve the fuel economy [...] Read more.
Under the dual−carbon goal, the research on energy conservation and emission reduction of new energy vehicles has once again become a current hotspot, and plug−in hybrid electric vehicles (PHEVs) are the first to bear the brunt. In order to improve the fuel economy of PHEV, an adaptive energy management strategy is designed on the basis of the intelligent prediction of driving cycles. Firstly, according to the vehicle dynamics model, the optimal control objective function of PHEV is established, and the relationship between vehicle fuel consumption and driving cycle is analyzed. Secondly, the initial weights and threshold of the backpropagation (BP) neural network are optimized using the particle swarm optimization (PSO) algorithm, and a PSO−BP neural network vehicle velocity prediction controller is established. Thirdly, combined with the approximate equivalent consumption minimization strategy (ECMS) algorithm to calculate the optimal initial equivalent factor in the prediction time domain, the fast−planning SOC and PI control are introduced to determine the optimal equivalent factor sequence, and the optimal torque distribution ratio of the engine and motor is calculated. Lastly, three different energy management strategies are simulated and verified under six China light−duty vehicle test cycle−passenger car (6*CLTC−P) driving cycles. Simulation results show that the established velocity prediction model has good prediction accuracy, and the proposed adaptive energy management strategy based on prediction is 9.85% higher than the rule−based strategy in terms of fuel saving rate and 5.30% higher than the ECMS strategy without prediction, which further improves the fuel saving potential of PHEV. Full article
(This article belongs to the Special Issue Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering)
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15 pages, 3142 KiB  
Article
Multi-Resource Computing Offload Strategy for Energy Consumption Optimization in Mobile Edge Computing
by Zhe Wei, Xuebin Yu and Lei Zou
Processes 2022, 10(9), 1762; https://doi.org/10.3390/pr10091762 - 2 Sep 2022
Cited by 4 | Viewed by 1470
Abstract
The energy consumption optimization of edge devices in the mobile edge computing environment is mainly based on computational offload strategy. Most of the current common computing offload strategies only consider a single computing resource and do not comprehensively consider different kinds of computing [...] Read more.
The energy consumption optimization of edge devices in the mobile edge computing environment is mainly based on computational offload strategy. Most of the current common computing offload strategies only consider a single computing resource and do not comprehensively consider different kinds of computing resources in mobile edge computing environments, which cannot fully reduce the energy consumption of edge devices under the condition of ensuring response time constraints. To solve this problem, a multi-resource computing unloading energy consumption model is proposed in the mobile edge computing environment, and a new fitness calculation method for evaluating the energy consumption of edge devices is designed. Combined with the workflow management system, a multi-resource computing offloading particle swarm optimization task scheduling algorithm for energy consumption optimization in mobile edge computing is proposed. The algorithm can fully reduce the energy consumption of mobile terminals under the condition of considering the response time constraint. Experiments show that, compared with the existing four algorithms, the task scheduling algorithm corresponding to the new strategy has stable convergence and optimal fitness. Under the constraint of user response time, the energy consumption of edge devices in the task scheduling scheme is better than the other four unloading strategies. Full article
(This article belongs to the Special Issue Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering)
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17 pages, 5037 KiB  
Article
Voltage-Stabilizing Method of Permanent Magnet Generator for Agricultural Transport Vehicles
by Jianwei Ma, Liwei Shi and Amir-Mohammad Golmohammadi
Processes 2022, 10(9), 1726; https://doi.org/10.3390/pr10091726 - 31 Aug 2022
Cited by 6 | Viewed by 3238
Abstract
Permanent magnet generators have the advantages of simple structure, high reliability, high efficiency, and energy saving. It is suitable for agricultural transportation vehicles, but there are some troubles on voltage regulation. In order to realize the stable output of permanent magnet generator, a [...] Read more.
Permanent magnet generators have the advantages of simple structure, high reliability, high efficiency, and energy saving. It is suitable for agricultural transportation vehicles, but there are some troubles on voltage regulation. In order to realize the stable output of permanent magnet generator, a kind of voltage-stabilizing method to ensure the average output voltage stability is proposed: by controlling the degree of clipping. First, the voltage regulation principle of permanent magnet generator is analyzed, mathematical model of permanent magnet generators in synchronous rotation coordinate system is built, and on this basis, the voltage-stabilizing circuit is designed. Second, the voltage-stabilizing circuit model of permanent magnet generator is created, the simulation analysis of reference point voltage and the output voltage under different speed and load is carried out, and the average value of output voltage is calculated according to the simulation curve taking advantage of the calculus principle. Third, the voltage-stabilizing circuit is made and tested. By comparing the simulation results with the experimental results, it is proved that the voltage-stabilizing circuit is suitable for the working characteristics of permanent magnet generator, the selected parameters of component are reasonable, and the simulation results are accurate and reliable. The circuit has excellent voltage-stabilizing performance. It provides a convenient and reliable method for the design and development of voltage-stabilizing circuit and promote the application of permanent magnet generator on agricultural transport vehicles. Full article
(This article belongs to the Special Issue Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering)
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21 pages, 13620 KiB  
Article
Parameter Matching and Performance Analysis of a Master-Slave Electro-Hydraulic Hybrid Electric Vehicle
by Qingxiao Jia, Hongxin Zhang, Yanjun Zhang, Jian Yang and Jie Wu
Processes 2022, 10(8), 1664; https://doi.org/10.3390/pr10081664 - 22 Aug 2022
Cited by 10 | Viewed by 1970
Abstract
To improve the battery state of charge (SOC) of the electric vehicle (EV), this paper proposes a master–slave electro-hydraulic hybrid electric vehicle (MSEH-HEV). The MSEH-HEV uses a planetary row as the core transmission component to realize the interconversion between mechanical energy, hydraulic energy [...] Read more.
To improve the battery state of charge (SOC) of the electric vehicle (EV), this paper proposes a master–slave electro-hydraulic hybrid electric vehicle (MSEH-HEV). The MSEH-HEV uses a planetary row as the core transmission component to realize the interconversion between mechanical energy, hydraulic energy and electrical energy. Meanwhile, this paper introduces the six working modes in vehicle operation, matches the parameters of key components to the requirements of the vehicle’s performance and designs a rule-based control strategy to dominate the energy distribution and the operating mode switching. The research uses AMESim and Simulink to perform a co-simulation of the MSEH-HEV, and the superiority of MSEH-HEV is testified by comparing it with an AMESim licensed EV. The simulation results show that in the Economic Commission for Europe (ECE) and the Extra Urban Driving Cycle (EUDC), the MSEH-HEV has a 15% reduction in battery consumption, and the motor peak torque is greatly reduced. Moreover, a fuzzy control strategy is designed to optimize the rule-based control strategy. Ultimately, the optimized strategy further reduces the motor torque while maintaining the battery SOC. In this paper, the applicable research consists of the necessary references for the design matching of future electro-hydraulic hybrid electricity systems. Full article
(This article belongs to the Special Issue Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering)
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19 pages, 4200 KiB  
Article
Evaluating the Performance of a Solar Distillation Technology in the Desalination of Brackish Waters
by Mahyar Shakerian, Mohsen Karrabi, Mohammad Gheibi, Amir M. Fathollahi-Fard and Mostafa Hajiaghaei-Keshteli
Processes 2022, 10(8), 1626; https://doi.org/10.3390/pr10081626 - 17 Aug 2022
Cited by 6 | Viewed by 1616
Abstract
Desalination is set to become a major source of drinking water in several Middle Eastern countries over the coming decades. Solar distillation is a simple power-independent method of water desalination, which can be carried out in active or passive modes. This study is [...] Read more.
Desalination is set to become a major source of drinking water in several Middle Eastern countries over the coming decades. Solar distillation is a simple power-independent method of water desalination, which can be carried out in active or passive modes. This study is among the first attempts to investigate the possibility of desalinating brackish groundwater resources under the threat of saltwater intrusion in the southern areas of Razavi Khorasan province in Iran. For this purpose, a pilot solar distillation unit was constructed to analyze the effects of the unit orientation, depth of the water pool, atmospheric conditions, input salinity, and flow continuity on the solar distillation performance. The results showed that the unit exhibited the highest efficiency when it had a 3 cm deep water pool. It was oriented facing southward while operating a continuous flow for at least 3 days under sunny weather conditions. It was found that among the studied parameters, the unit orientation and pool depth had the greatest impact on the water production performance for this type of water desalination system. Conversely, the water production efficiency was not very sensitive to the input salinity level. Overall, the solar distillation technology was able to reduce the salinity by 99.7% and the hardness by 94.7%. Full article
(This article belongs to the Special Issue Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering)
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22 pages, 9989 KiB  
Article
Optimal Control Strategy of Path Tracking and Braking Energy Recovery for New Energy Vehicles
by Bi Zhao, Ruijun Liu, Dapai Shi, Shipeng Li, Qingling Cai and Wencheng Shen
Processes 2022, 10(7), 1292; https://doi.org/10.3390/pr10071292 - 30 Jun 2022
Cited by 10 | Viewed by 2393
Abstract
In order to further improve the stability of path tracking control and fuel economy of new energy vehicles, an optimal control strategy of path tracking and braking energy recovery is proposed. First, a model predictive controller is designed based on the three-degrees of [...] Read more.
In order to further improve the stability of path tracking control and fuel economy of new energy vehicles, an optimal control strategy of path tracking and braking energy recovery is proposed. First, a model predictive controller is designed based on the three-degrees of freedom dynamics model of the vehicle according to the idea of hierarchical control, and a fuzzy yaw torque controller is established with the desired yaw velocity and side slip angle of the mass center as constraints. Second, at high-speed driving conditions, the executive layer of the component distributes the braking torque according to the braking energy recovery control strategy. Finally, the optimal control strategy of path tracking and braking energy recovery is verified by Carsim/Advisor/Simulink software under different driving speeds. The results show that the optimized control strategy can improve the tracking accuracy and driving stability of a vehicle with large curvature turning and further improve the fuel economy of new energy vehicles under the premise of meeting the control requirements. Full article
(This article belongs to the Special Issue Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering)
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20 pages, 4596 KiB  
Article
Study on Characteristics and Control Strategy of Diesel Particulate Filters Based on Engine Bench
by Hao Sun, Yingshuai Liu, Ning Li and Jianwei Tan
Processes 2022, 10(7), 1246; https://doi.org/10.3390/pr10071246 - 22 Jun 2022
Cited by 5 | Viewed by 3472
Abstract
The ignition temperature of a diesel oxidation catalyst (DOC) and the internal temperature-field distribution of the diesel particulate filter (DPF) during active regeneration are investigated during an engine bench test in this study. Based on the dropped to idle (DTI) test, a test [...] Read more.
The ignition temperature of a diesel oxidation catalyst (DOC) and the internal temperature-field distribution of the diesel particulate filter (DPF) during active regeneration are investigated during an engine bench test in this study. Based on the dropped to idle (DTI) test, a test method is developed to determine the safe regeneration temperature of the DPF. The results show that when the inlet temperature of the DOC is more than 240 °C, the DOC begins ignition and reaches the target temperature of 600 °C set for active regeneration of DPF; when the inlet exhaust temperature of the DOC is between 240 and 280 °C, a higher injection rate is required to reduce the secondary pollution of HC and thus make the DPF reach the set target temperature as soon as possible. The active regeneration process of the DPF is divided into three stages. During ignition, the temperature of the DPF inlet and outlet increases rapidly and successively. The internal and outlet temperatures of DPF during regeneration are approximately 50 °C higher than the inlet temperature. At the end of regeneration, the DPF inlet to outlet temperature drops rapidly. A feed-forward design and feedback algorithm are used to verify the change in the target regeneration temperature. The overshoot of the DPF control strategy was less than 3%, and the steady-state temperature control error was less than 20 °C. The results of this study provide a basis for the safe control of DPFs’ active regeneration temperatures. Full article
(This article belongs to the Special Issue Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering)
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18 pages, 2246 KiB  
Article
Optimization Design and Injury Analysis of Driver’s Restraint System in Sedan Small Offset Collision
by Xiuju Yang, Jingjing Shi, Qianying Fu, Shanshan Pu, Zhixin Pan, Chunxiao Lian, Zhiyong Yin, Shengxiong Liu and Guixue Wang
Processes 2022, 10(5), 940; https://doi.org/10.3390/pr10050940 - 9 May 2022
Cited by 2 | Viewed by 1902
Abstract
A combination of airbag, seatbelt, and other restraint systems greatly reduces injury to drivers in small offset collisions. However, the airbag causes accidental injury to the driver in the deployment process. To maximize the protection effect of the restraint system on the driver, [...] Read more.
A combination of airbag, seatbelt, and other restraint systems greatly reduces injury to drivers in small offset collisions. However, the airbag causes accidental injury to the driver in the deployment process. To maximize the protection effect of the restraint system on the driver, this study proposes a pre-tensioned force-limiting seatbelt. A small offset collision accident with video information was simulated by using a Neon sedan and the THUMS (v.4.0.2) finite element model. The effectiveness of the accident model and the matching use of a pre-tensioned force-limiting seatbelt and airbag for driver protection were verified. To obtain the best parameter matching of protection effect, first, the seatbelt force-limiting A, pre-tensioned force B, pre-tensioned time C, airbag ignition time D, and mass flow coefficient E were selected as influencing factors, and orthogonal tests with different factor levels were designed. Then, the direct analysis method was applied to analyze the influence laws of each factor on driver dynamic response and injury. In addition, the radial basis function surrogate model was constructed by synthesizing each kind of critical injury value to the human body. Combined with NSGA-II multi-objective genetic algorithm, the structural performance parameters of the restraint system were optimized and matched. Results showed that the optimal protection matching parameters of the restraint system were 4933.5 N−2499.9 N−16 ms−15.3 ms−0.5 (A−B−C−D−E). Finally, the best matching parameters were input into the accident model for verification. After optimization, the WIC and Nij of drivers were reduced by 37.9% and 45.3%, respectively. The results show that the optimized restraint system can protect the driver the most. Full article
(This article belongs to the Special Issue Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering)
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21 pages, 7548 KiB  
Article
Power Parametric Optimization of an Electro-Hydraulic Integrated Drive System for Power-Carrying Vehicles Based on the Taguchi Method
by Hao Chen, Tiezhu Zhang, Hongxin Zhang, Guangdong Tian, Ruijun Liu, Jian Yang and Zhen Zhang
Processes 2022, 10(5), 867; https://doi.org/10.3390/pr10050867 - 27 Apr 2022
Cited by 14 | Viewed by 1948
Abstract
Focused on the troubles and defects introduced by the traditional single form of electric vehicle transmission, this paper proposes an electro-hydraulic power coupled electric vehicle based on the working principle of an electro-hydraulic power integrated drive system for light-duty cargo vehicles. The integration [...] Read more.
Focused on the troubles and defects introduced by the traditional single form of electric vehicle transmission, this paper proposes an electro-hydraulic power coupled electric vehicle based on the working principle of an electro-hydraulic power integrated drive system for light-duty cargo vehicles. The integration of the planetary row into the drive system allows the interconversion of mechanical, electrical, and hydraulic energy. By describing the system structure and composition, several working conditions during automobile driving are proposed, and the working principle of every circumstance is introduced. Simultaneously, the article determines the preliminary optimal ratio with the battery’s state of charge (SOC) as the constraint. Then, the orthogonal test matrix of electro-hydraulic ratios and speed thresholds for each operating condition is established according to Taguchi’s method. The impact of each optimized parameter on the motor torque and hydraulic torque as well as the SOC and the proportion of the effect is evaluated by the simulation to obtain the optimal solution. The simulation consequences show that the motor torque and hydraulic torque are reduced, and thus, the vehicle’s acceleration performance and energy recovery efficiency are improved. Full article
(This article belongs to the Special Issue Intelligent Technologies and Processes for Advanced Nuclear Power and Energy Engineering)
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