Green Energy and Intelligent Transportation最新文献

{"title":"Multi-scale analysis and hierarchical optimization design of a 2D twill woven composite front firewall for electric vehicles","authors":"Junfei Yan ,&nbsp;Jian Song ,&nbsp;Bengang Yi ,&nbsp;Yi Quan ,&nbsp;Cheng Xu ,&nbsp;Wenyuan Gong ,&nbsp;Zhaojun Du ,&nbsp;Tengyong Liu ,&nbsp;Changchun Xie ,&nbsp;Darong Liang ,&nbsp;Zihao Pu ,&nbsp;Zhexuan Dong","doi":"10.1016/j.geits.2025.100251","DOIUrl":"10.1016/j.geits.2025.100251","url":null,"abstract":"<div><div>In high-performance electric sports vehicles, the application of woven composite materials with the purpose of lightweight has become an inevitable choice. It is considerably difference between traditional metal materials and composites for the lightweight design strategy of electric vehicle structures, due to the multi-scale and anisotropic characteristics of fiber reinforced composites. Nevertheless, most of scholars are focus on the meso-scale mechanical responses of woven composites, and few studies are involved in their multi-scale mechanical behaviors and hierarchical design strategy of composite structures in electric vehicles. In this work, a multi-scale analysis strategy was proposed to investigate mechanical behaviors of composite front firewall. Subsequently, a hierarchical optimization strategy with the objective of lightweight design of composite front firewall was carried out. Finally, a reasonable layout scheme of composite front firewall was quantitatively obtained. The maximum errors between the predicted and theoretical/experimental results in terms of equivalent engineering constants of fiber yarns and 2D twill woven composites (2DTWCs) were 8.8 ​GPa and 7%, respectively. It indicates that the multi-scale models can be used to evaluate the mechanical properties of 2DTWCs. Additionally, the total weight of optimized composite front firewall was reduced by 36% in comparison with the reference, and simultaneously the total stiffness was improved by 26%. Hence, it is an effective strategy to design lightweight composite structures of electric vehicles. We hope the proposed multi-scale and hierarchical design strategy could promote the further development of composite structures in high-performance electric sports vehicles.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 2","pages":"Article 100251"},"PeriodicalIF":0.0,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143508507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Power supply for the projectile-borne electromechanical system: A review","authors":"Da Yu ,&nbsp;Xiangyu Han ,&nbsp;Wenrui Wang ,&nbsp;He Zhang ,&nbsp;Peixun Xiong ,&nbsp;Keren Dai","doi":"10.1016/j.geits.2025.100256","DOIUrl":"10.1016/j.geits.2025.100256","url":null,"abstract":"<div><div>Wide-area battlefields, smart ammunition, and precision damage are the new directions of modern warfare, while munition-borne electric systems serve as “decision-makers” for smart ammunition. As the primary energy supplier for the entire system, munition-borne power sources hold a veto power position. The complexity of the application environment for munition-borne power sources involves enduring high overloads, high centrifugal forces, ballistic aerothermal effects, variations in ballistic airflow fields, central blast impacts, complex disturbances in indefinite postures, and even the influence of complex ionized media. These factors represent weak links in research on the entire munition-borne electric system. Therefore, nations around the world attach great importance to developing munition-borne power sources and conducting research on various related aspects, such as technological innovation, digital simulation, and testing techniques. This paper elaborates on the existing technologies and scientific issues facing munition-borne power sources, comparing and analyzing the advantages and disadvantages of liquid reserve batteries, solid-state thermoelectric batteries, and supercapacitors as energy sources for modern warfare systems. It also discusses current technological developments and future challenges. To address the insufficient environmental and spatial adaptability of munition-borne power sources, this paper proposes a design approach that couples excitation with integrated packaging. Specifically, although the diversity of ammunition platforms leads to differences in power source requirements, common problems faced by munition-borne electric systems in modern battlefield environments include extreme impact mechanics, low-temperature rapid activation requirements, and structural size limitations. This paper comprehensively discusses the extreme mechanical environments of ammunition platforms, failure mechanisms and protection methods under high-impact conditions for munition-borne power sources, low-temperature rapid activation, and miniaturization design and proposes protective design concepts such as elastic skeleton structures and high-pressure sealed secondary packaging. Additionally, these findings suggest the use of capillary microarray structures with electrode membranes to increase infiltration rates and further improve the activation rate of munition-borne power sources. Lastly, this paper outlines future directions for the development of munition-borne electrical system power sources, primarily from the perspectives of non-reserve primary batteries, non-bottle-breaking reserve batteries, new system batteries, and the advantages of battery-supercapacitor composite energy, providing a reference for the design of munition-borne electrical system power sources used in diversified weapon system platforms.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 5","pages":"Article 100256"},"PeriodicalIF":16.4,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145010154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Economic dispatch in microgrid with battery storage system using wild geese algorithm","authors":"Vimal Tiwari ,&nbsp;Hari Mohan Dubey ,&nbsp;Manjaree Pandit ,&nbsp;Surender Reddy Salkuti","doi":"10.1016/j.geits.2025.100263","DOIUrl":"10.1016/j.geits.2025.100263","url":null,"abstract":"<div><div>The development of microgrid systems forces to integration of various distributed generators (DG) and battery energy storage (BES) systems. The integration of a BES system in MG provides several benefits such as fast response, short-term power supply, improved power quality, ancillary service, and arbitrage. The system constraints as power balance and the assets constraints as power limit of different DGs, energy, and charge/discharge power limit of BES increase the complexity of the original problem. Therefore, to tackle such a problem an efficient, robust, and strong optimization algorithm is required. In this paper, a recently developed optimization method known as the wild geese algorithm (WGA) has been applied to solve the problem. The WGA is a population-based metaheuristic approach inspired by the different aspects of the living behavior of wild geese. This algorithm has developed with the inspiration of different phases of wild geese's lives, such as their evolution, well-organized and coordinated long-distance group migration, and fatality. The WGA has tested on the MG problem and the obtained simulation results are validated by comparison of results obtained from the other methods. The result shows the WGA is efficiently able to handle the MG operational problem with numerous constraints and shows the potential to produce a high-quality solution in terms of cost reduction. The incorporation of BES reduces operating costs for MG's off-grid and on-grid operational modes by 5.91% and 8.62%, respectively. Further, the analysis for off-grid mode under different seasonality, reduction in the operational cost by 4.47%, 9.28%, 6.37%, and 7.22% was measured in the summer, autumn, winter, and spring seasons, respectively, with the integration of BES. Additionally, the integration of BES in on-grid mode results in a decrease in operating costs by 7.15%, 12.54%, 7.56%, and 11.07% in the summer, autumn, winter, and spring, respectively.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 5","pages":"Article 100263"},"PeriodicalIF":16.4,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144913804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding spatial–temporal attributes influencing electric vehicle's charging stations utilization: A multi-city study","authors":"Boniphace Kutela ,&nbsp;Abdallah Kinero ,&nbsp;Hellen Shita ,&nbsp;Subasish Das ,&nbsp;Cuthbert Ruseruka ,&nbsp;Tumlumbe Juliana Chengula ,&nbsp;Norris Novat","doi":"10.1016/j.geits.2025.100255","DOIUrl":"10.1016/j.geits.2025.100255","url":null,"abstract":"<div><div>Electric vehicles (EVs) are gaining popularity across the globe. Various initiatives are being implemented to ensure that most of the operating vehicles on public roadways are EVs by 2050. Such initiatives include the construction of charging stations to improve EV charging accessibility. The utilization of the charging stations has not been explored to a great extent, despite its importance in future installations in various cities. This study evaluated the EV station utilization across eleven cities in three countries: the United States, Canada, and Scotland. The Negative Binomial (NB) regression model was applied to understand the influence of the spatial–temporal factors on the daily utilization of EV charging stations. In addition to the overall analysis, country-specific analyses were also performed. It was revealed that there is a great variation in daily EV utilization across the cities in different countries and within the country. In fact, only stations in Crieff, Scotland, showed lower predicted daily utilization, while cities in the United States had over two times predicted daily utilization compared to stations in Aberfeldy, Scotland. Furthermore, the longer the station has been in service, the higher the daily utilization, although there was significant variation across cities. Further, the day of the week and months of the year depicted consistent utilization patterns for Scotland and the United States but showed mixed findings for Canada. The study findings can help planners and policymakers improve the allocation of EV charging stations.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 5","pages":"Article 100255"},"PeriodicalIF":16.4,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144902445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on vertical strategy for left turn at signal-free T-shaped intersections based on multi-layer reinforcement learning methods","authors":"Xuemei Chen,&nbsp;Jia Wu,&nbsp;Jiachen Hao,&nbsp;Yixuan Yang","doi":"10.1016/j.geits.2025.100261","DOIUrl":"10.1016/j.geits.2025.100261","url":null,"abstract":"<div><div>The task of executing left turns at signal-free T-shaped intersections without protective signals poses a critical challenge in the realm of autonomous driving. Conventional rule-based approaches tend to be excessively cautious, rendering them inadequate for effectively managing driving tasks within unpredictable T-shaped intersection environments. In the case of complex traffic scenarios, a single model is less effective in convergence and has a lower pass rate and poorer safety. Thus, this study introduces a multi-layer reinforcement learning model, employing D3QN (Dueling Double DQN) and TD3 (Twin Delayed Deep Deterministic policy gradient algorithm) for advanced behavioral decision-making and vertical acceleration planning, respectively. In our experimental investigation, we designed four simulation scenarios based on the driving behavior of the Carla simulator to replicate real-world driving conditions. Verification and test simulation outcomes substantiate that, in comparison to other single-trained reinforcement learning models, the multi-layer reinforcement learning model proposed in this study attains the highest success rate. Specifically, the pass rate in the verification scenario, consistent with the training conditions, achieves an impressive 99.5%. Furthermore, the pass rate in the comprehensive test scenario reaches 89.6%. These experiments unequivocally demonstrate the considerable enhancement in T-shaped intersections pass rates achieved by the proposed method while ensuring both traffic efficiency and safety.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 5","pages":"Article 100261"},"PeriodicalIF":16.4,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144913805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lithium-ion battery remaining useful life prediction based on data-driven and particle filter fusion model","authors":"Chunling Wu ,&nbsp;Chenfeng Xu ,&nbsp;Liding Wang ,&nbsp;Juncheng Fu ,&nbsp;Jinhao Meng","doi":"10.1016/j.geits.2025.100267","DOIUrl":"10.1016/j.geits.2025.100267","url":null,"abstract":"<div><div>To improve the accuracy and stability of battery remaining useful life (RUL) prediction for lithium-ion batteries, this paper proposes a new convolutional neural network-gated recurrent unit-particle filter (CNN-GRU-PF) fusion prediction model. First, the battery capacity series is decomposed and reconstructed by complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm and Pearson correlation coefficient method, which reduces the influence of noise on RUL prediction. Then, the capacity is predicted by CNN-GRU, and the CNN-GRU prediction value is used as the observation value of PF, and the prediction error of CNN-GRU is corrected by the state prediction ability of PF. A moving window is used to iteratively update the training set, and the PF optimization value is added to the CNN-GRU training set, forming an iterative training and dynamic updating between them, which improves the long-term prediction performance of CNN-GRU. To verify the effectiveness of proposed method, CNN-GRU-PF model is applied to predict the battery's RUL. The experiments show that CNN-GRU-PF improves the prediction accuracy of battery B5 by 87.27%, 82.88%, and 55.43% respectively compared with GRU, PF and GRU-PF, and also achieves significant improvement for other batteries. The new model is an effective RUL prediction method with good accuracy and robustness.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 5","pages":"Article 100267"},"PeriodicalIF":16.4,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145010152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of an analytical model to evaluate the effect of the ported shroud on centrifugal compressors","authors":"Carlo Cravero ,&nbsp;Philippe Joe Leutcha ,&nbsp;Davide Marsano","doi":"10.1016/j.geits.2024.100249","DOIUrl":"10.1016/j.geits.2024.100249","url":null,"abstract":"<div><div>Extending the operational range of centrifugal compressors is strategically vital for turbocharging internal combustion engines, particularly in enhancing efficiency and expanding operational capabilities. This extension is crucial for reducing environmental impact by enabling engines to perform more efficiently under a wider range of conditions. In the transition from conventional thermal reciprocating engines, fuel cells, especially proton exchange membrane fuel cells (PEMFCs), are emerging as strong alternatives. In automotive applications, PEMFCs often require turbocharging to supply compressed air to the cathode system of the fuel cell stack. This integration is essential for utilizing the heat from the fuel cell's waste products, thereby improving overall system efficiency. Ongoing research and development in radial turbomachinery are critical for optimizing the performance of these propulsion systems. Specifically, adapting turbocharger designs to meet the unique requirements of fuel cell systems and extending their operational range are essential tasks. Using a simplified CFD model, the impact of a ported shroud on compressor performance and range extension has been investigated. Flow structure analysis identified that the primary role of the ported shroud is to modify the relative flow angle on the rotor at the highest span channel. Additionally, a simplified analytical model was developed to quantify the effectiveness of different ported shroud geometries on the compressor by examining changes in tangential velocity after mixing with the flow from the cavity.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 2","pages":"Article 100249"},"PeriodicalIF":0.0,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143453133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Utilizing extended theory of planned behavior to evaluate consumers’ adoption intention of electric vehicles","authors":"Apurva Pamidimukkala ,&nbsp;Sharareh Kermanshachi ,&nbsp;Jay Michael Rosenberger ,&nbsp;Greg Hladik","doi":"10.1016/j.geits.2025.100258","DOIUrl":"10.1016/j.geits.2025.100258","url":null,"abstract":"<div><div>The growing apprehension regarding environmental issues is driving global economies to adopt alternative fuel technology to mitigate the release of greenhouse gases from vehicles. Electric vehicles (EVs) provide a practical and eco-friendly solution that can help transition to a sustainable transportation system with minimal emissions, therefore conserving the environment. This study employed the theory of planned behavior (TPB) and incorporated additional factors such as price value, moral norms, and policy incentives (monetary and non-monetary) to examine consumers' intention to adopt EVs. A survey was administered to prospective consumers in March 2023 in Texas and a total of 743 responses were collected. The analysis results revealed that attitudes, perceived behavior control, subjective norms, moral norms, price value, and monetary incentives positively and significantly influenced consumers' intentions to adopt EVs; however, it was also revealed that non-monetary incentives do not have a significant effect on consumers’ propensity to adopt EVs. Furthermore, the research findings from the moderation analysis indicate noteworthy differences in demographic factors along the consumer adoption intention.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 5","pages":"Article 100258"},"PeriodicalIF":16.4,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144913803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interpretable machine learning models for predicting Ebus battery consumption rates in cold climates with and without diesel auxiliary heating","authors":"Kareem Othman ,&nbsp;Diego Da Silva ,&nbsp;Amer Shalaby ,&nbsp;Baher Abdulhai","doi":"10.1016/j.geits.2024.100250","DOIUrl":"10.1016/j.geits.2024.100250","url":null,"abstract":"<div><div>The global shift towards sustainable and environmentally friendly transportation options has led to the increasing adoption of electric buses (Ebuses). To optimize the deployment and operational strategies of Ebuses, it is imperative to accurately predict their energy consumption under varying conditions, particularly in cold climates where battery life is typically degraded. The exploration of this aspect within the Canadian context has been limited. In addition, we have found that existing models in the literature perform poorly in the Canadian environment, giving rise to the need for new models using Canadian data. This paper focuses on the development, comparison, and evaluation of various data-driven models designed to predict the energy consumption of different Ebuses with different heating technologies under a wide range of climate conditions. We specifically use Canadian data as a good representative of cold climates in general. The results show that the performance of the different bus types varies substantially under the exact same conditions. In addition, tree-based family of models proves to be the most suitable approach for predicting the Ebus consumption rate. The results indicate that the Random Forest method emerges as the superior choice for predicting the energy consumption rate, with a resulting mean absolute error of 0.09–0.1 ​kWh/km observed across the different models. Furthermore, SHAP analysis shows that the main variables influencing the energy consumption rate depend on the type of heating system (using the battery for heating or using an auxiliary system that utilizes diesel for heating) adopted.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 2","pages":"Article 100250"},"PeriodicalIF":0.0,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143445084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Defects in lithium-ion batteries: From origins to safety risks","authors":"Wei Chen ,&nbsp;Xuebin Han ,&nbsp;Yue Pan ,&nbsp;Yuebo Yuan ,&nbsp;Xiangdong Kong ,&nbsp;Lishuo Liu ,&nbsp;Yukun Sun ,&nbsp;Weixiang Shen ,&nbsp;Rui Xiong","doi":"10.1016/j.geits.2024.100235","DOIUrl":"10.1016/j.geits.2024.100235","url":null,"abstract":"<div><div>Lithium-ion batteries are currently the most widely used energy storage devices due to their superior energy density, long lifespan, and high efficiency. However, the manufacturing defects, caused by production flaws and raw material impurities can accelerate battery degradation. In extreme cases, these defects may result in severe safety incidents, such as thermal runaway. Metal foreign matter is one of the main types of manufacturing defects, frequently causing internal short circuits in lithium-ion batteries. Among these, copper particles are the most common contaminants.</div><div>This paper addresses the safety risks posed by manufacturing defects in lithium-ion batteries, analyzes their classification and associated hazards, and reviews the research on metal foreign matter defects, with a focus on copper particle contamination. Furthermore, we summarize the detection methods to identify defective batteries and propose future research directions to address metal foreign matter defects.</div></div>","PeriodicalId":100596,"journal":{"name":"Green Energy and Intelligent Transportation","volume":"4 3","pages":"Article 100235"},"PeriodicalIF":0.0,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143891929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}