Article
Computer Science, Information Systems
V. Manoj Kumar, Bharatiraja Chokkalingam, Lucian Mihet-Popa
Summary: This study proposes a scheduling system for EV charging using the optimization strategy of Chaotic Harris Hawks optimization (CHHO), which reduces the charging time and distance traveled by EVs. The CHHO-based system outperforms other algorithms in terms of energy utilization, travel time, and EV station utilization.
Article
Automation & Control Systems
Mostafa Mahfouz, Reza Iravani
Summary: This article presents a supervisory controller for operating an electric vehicle fast charging station in autonomous mode when the supply grid is unavailable. The controller is based on the supervisory control theory and ensures seamless transition between different modes of operation.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Chemistry, Multidisciplinary
Andrija Petrusic, Aleksandar Janjic
Summary: This article introduces a multicriteria methodology for scheduling a hybrid EV charging station, incorporating renewable energy sources and battery storage to mitigate grid stress, and solving the problem using a genetic algorithm optimization procedure.
APPLIED SCIENCES-BASEL
(2021)
Article
Construction & Building Technology
Shuohan Liu, Xu Xia, Yue Cao, Qiang Ni, Xu Zhang, Lexi Xu
Summary: Electric Vehicles (EVs) are more environmentally friendly than traditional internal combustion vehicles (ICVs), but they have longer charging times. This paper proposes an Urgency First Charging (UFC) scheduling policy based on charging urgency, which is shown through simulations to improve user experience and shorten overall EV trip durations.
SUSTAINABLE CITIES AND SOCIETY
(2021)
Review
Thermodynamics
Dingsong Cui, Zhenpo Wang, Peng Liu, Shuo Wang, David G. Dorrell, Xiaohui Li, Weipeng Zhan
Summary: This paper provides a comprehensive overview of the operation optimization approaches for EV battery swapping and charging stations. It analyzes the mathematical methods used in the process and examines the current operation mode and optimization objectives. The paper also discusses the merits and drawbacks of previous studies and suggests future research opportunities.
Article
Environmental Studies
Tai-Yu Ma, Simin Xie
Summary: A new online vehicle-charging assignment model is proposed to reduce charging delays in electrified shared mobility services, showing promising results in minimizing charging operation time with an efficiency optimization approach.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2021)
Article
Chemistry, Multidisciplinary
Hojun Jin, Sangkeum Lee, Sarvar Hussain Nengroo, Dongsoo Har
Summary: This study proposes a power management scheme for interdependent microgrid and electric vehicle fleets, assisted by a novel charging/discharging scheduling algorithm. The scheme maximizes the utilization of electric vehicle charging/discharging while minimizing operating costs through multi-objective optimization. It also establishes a more economical and energy-efficient PV-based charging station.
APPLIED SCIENCES-BASEL
(2022)
Article
Automation & Control Systems
Liangliang Hao, Jiangliang Jin, Yunjian Xu
Summary: This article studies the problem of online pricing and charging scheduling for a public electric vehicle (EV) charging station under stochastic electricity prices and renewable generation. A novel scheme called laxity differentiated pricing (LDP) is proposed to balance electricity cost and opportunity cost, and a model-free soft actor critic (SAC) algorithm is used to reduce the action dimensionality. Numerical results show that the proposed approach outperforms alternative methods with various pricing and charging schemes.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Information Systems
Ashish Kumar Karmaker, Md. Alamgir Hossain, Hemanshu Roy Pota, Ahmet Onen, Jaesung Jung
Summary: This paper presents an energy management algorithm that considers techno-economic and environmental factors for a hybrid solar and biogas-based electric vehicle charging station. The proposed algorithm, designed for a 20-kW charging station, utilizes a fuzzy inference system in MATLAB SIMULINK to optimize real-time charging costs and renewable energy utilization by managing power generation, EV power demand, charging periods, and existing charging rates. The results demonstrate a 74.67% reduction in energy costs compared to existing flat rate tariffs, with lower charging costs on weekdays and weekends. The integration of hybrid renewables also leads to a significant decrease in greenhouse gas emissions, making the project profitable with short payback periods for charging station owners.
Article
Automation & Control Systems
Mao Tan, Zhuocen Dai, Yongxin Su, Caixue Chen, Ling Wang, Jie Chen
Summary: With the increase in the number of electric vehicles, battery swapping is seen as promising due to its short waiting time. However, it is challenging to achieve efficient scheduling in a large scale battery swap station due to the uncertainty of the power grid and EV behavior. To address this, a new bi-level scheduling model is proposed, combining deep reinforcement learning for optimal power allocation and MILP subproblems for battery dispatching. Experimental results show excellent performance and cost reduction, benefiting both the battery swap station and the power grid in peak shaving and valley filling.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Engineering, Electrical & Electronic
Sajad Esmailirad, Ali Ghiasian, Abdorreza Rabiee
Summary: The recent trend in plug-in electric vehicles involves investing in public charging stations to allow for battery charging and potentially generate profits. Various scheduling algorithms are used to optimize the use of resources at the charging stations and cater to different customer requirements. A comprehensive model for maximizing profits at multi-service charging stations is introduced, along with a mixed-integer linear programming problem for scheduling vehicle charging and discharging. Simulation results show increased profit and reduced vehicle delay with an increase in battery swapping requests.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Engineering, Civil
Tianyang Zhang, Xi Chen, Bin Wu, Mehmet Dedeoglu, Junshan Zhang, Ljiljana Trajkovic
Summary: This paper focuses on the interactions between electric vehicle fleets and charging stations/battery swapping stations, developing a stochastic model and deriving revenue boundaries through simulations. The findings are valuable for future studies in public transportation.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Computer Science, Information Systems
Linfeng Liu, Houqian Zhang, Jiagao Wu
Summary: In this paper, the strategies of selecting the local-optimal SEVs for IEVs and rescheduling their travel routes are investigated, and a distributed Reciprocal Charging Mechanism (RCM) is proposed. Both mechanism analysis and simulation results demonstrate the performance superiority of RCM. Specifically, with the proposed reciprocal charging mechanism, IEVs can be charged by SEVs in a charging-station-absent zone, and the electric energy consumption can be approximatively minimized.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Green & Sustainable Science & Technology
Ruisheng Wang, Zhong Chen, Qiang Xing, Ziqi Zhang, Tian Zhang
Summary: This article proposes a modified rainbow-based deep reinforcement learning strategy to optimize the scheduling of charging stations, aiming to improve operating efficiency and economic benefits. By considering the interaction among electric vehicles, charging stations, and distribution networks, a comprehensive information perception model is constructed to extract the required environmental state. The results show that the proposed method effectively reduces operating costs and improves new energy consumption.
Article
Computer Science, Artificial Intelligence
Jaume Jordan, Pasqual Marti, Javier Palanca, Vicente Julian, Vicente Botti
Summary: With the increasing sales of electric vehicles, there is a significant lack of infrastructure to support charging, especially in interurban environments. To minimize the economic costs of installing sufficient charging points, this paper proposes using an evolutionary approach to calculate the most suitable locations for electric charging stations in interurban environments.
Article
Computer Science, Hardware & Architecture
Chia-Wei Chang, Yi-Bing Lin, Jyh-Cheng Chen
Summary: This paper explores the relationship between energy efficiency and data accuracy for IoT devices, using the example of PM2.5 application. Two reporting mechanisms, based on timer and threshold, were proposed and experimental results showed that the threshold-based reporting achieved over 37% more energy saving compared to the timer-based reporting when accuracies were the same.
MOBILE NETWORKS & APPLICATIONS
(2022)
Editorial Material
Automation & Control Systems
Patrick Siarry, Arun Kumar Sangaiah, Yi-Bing Lin, Shiwen Mao, Marek R. Ogiela
Summary: The convergence of cognitive data science methods and models with IoT and big data systems has brought challenges to industrial systems that need to be addressed. Cognitive science will enhance the fluidity of analytics and improve IoT systems through data science techniques, impacting the future IoT networking systems.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Chemistry, Analytical
Wen-Liang Chen, Yi-Bing Lin, Ted C. -Y. Chang, Yan-Ren Lin
Summary: Acute Coronary Syndrome (ACS) and other heart emergencies require immediate identification in ambulances, but traditional approaches may lead to treatment delays. The proposed solution, AMBtalk, uses the AllCheck(R) IoT device for early ACS identification, reducing treatment time and improving patient survival rates. The device outperforms existing cardiovascular IoT solutions and has been recognized with the 17th Taiwan Innovators Award for its excellent performance.
Article
Computer Science, Information Systems
Ling-Yan Zhang, Hung-Cheng Lin, Kun-Ru Wu, Yi-Bing Lin, Yu-Chee Tseng
Summary: This article investigates an object identification system using multiple distributed cameras and IoT devices, proposing a method to merge detection results for locating, identifying, and tracking target objects. The FusionTalk system integrates data fusion techniques with an IoT device management platform, offering flexibility and modularity in surveillance settings. Experimental evaluation shows an identification accuracy above 95% with a low failure probability in pairing IoT devices with video objects.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Automation & Control Systems
Whai-En Chen, Yi-Bing Lin, Li-Xian Chen
Summary: This article presents a new method using artificial intelligence and Internet of Things technology to detect and mitigate the issue of piglet crushing on pig farms. The method improves piglet scream detection accuracy and automatically activates sow alert devices in emergency situations.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Chemistry, Analytical
Yi-Bing Lin, Sheng-Lin Chou
Summary: This paper introduces a platform called SpecTalk that automatically generates code to align IoT applications with TAICS specifications, including various types of tests. Through experiments in smart campus constructions, the feasibility and effectiveness of SpecTalk were demonstrated.
Article
Chemistry, Analytical
Yun-Wei Lin, Yi-Bing Lin, Ted C. -Y. Chang, Bo-Xun Lu
Summary: Smart agriculture utilizes IoT technologies and smart sensors to support farming intelligence. This study proposes SensorTalk3, a combination of machine learning models, to calibrate EC sensors at edge devices. It introduces a dual-sensor detection solution to determine when recalibration is needed.
Article
Computer Science, Artificial Intelligence
Yun-Wei Lin, Yuh-Hwan Liu, Yi-Bing Lin, Jian-Chang Hong
Summary: In order to improve accuracy in new fields, we propose FenceTalk, a moving object detection system that automatically selects suspicious images not successfully detected by Yolo model using SSIM measure, reducing labor cost for data selection. FenceTalk can effectively update background image, reducing misjudgment and selecting optimal threshold images, reaching over 99% recall when combined with Yolo and SSIM.
Article
Computer Science, Information Systems
Lijun Wei, Yuhan Yang, Jing Wu, Chengnian Long, Yi-Bing Lin
Summary: Social Internet of Things (SIoT), as an emerging paradigm, applies social networking aspects to IoT, allowing objects to establish social relationships without human intervention and enhance interaction efficiency. However, trust remains a crucial issue in SIoT development. Existing literature predominantly focuses on unidirectional solutions, evaluating the trust of service providers solely based on the needs of service requesters. This study proposes a bidirectional trust model and an explicit approach to address the service delegation issue, considering the context of SIoT services or tasks.
Article
Computer Science, Information Systems
Yun-Wei Lin, Yi-Bing Lin, Hui-Nien Hung
Summary: The article introduces the CalibrationTalk mechanism to address the important issue of sensor failure detection and calibration in IoT applications, using smart agriculture as an example. Through measurements and analytical modeling, a method for detecting sensor failures within a specific time frame is proposed, enabling automatic calibration of sensors to resolve inaccuracies caused by aging.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Yi-Bing Lin, Chien-Chao Tseng, Ming-Hung Wang
Summary: Network slicing is vital for 5G mobile networks to meet diverse service requirements, and our research demonstrates the impact of transport network slicing on IoT and MBB applications. Different applications require different Committed Information Rate (CIR) ratios to ensure optimal performance.
Article
Computer Science, Information Systems
Yi-Bing Lin, Sheng-Kai Tseng, Ta-Hsien Hsu, Chuntei David Tseng
Summary: Passive building design in Orchid House utilizes smart controller HouseTalk to effectively control the passive mechanisms and optimize thermal control using non-thermodynamic cycle systems and low energy-consumption equipment. This enhances air quality, improves cooling effect, and reduces energy consumption in the house. HouseTalk scenario maintains oxygen concentration between 18% and 21%, and can effectively reduce carbon dioxide concentrations by 53%, demonstrating the potential of enhancing indoor air quality.
Article
Computer Science, Information Systems
Yi-Bing Lin, Helin Luo, Chen-Chi Liao, Yu-Fen Huang
Summary: Glove Puppetry, a traditional art form in Chinese societies, has been innovated by advances in information technology such as smart gloves and smartphones. PuppetTalk is an Internet of Things application platform that allows users to control puppet robots through multiple IoT devices simultaneously with high control accuracy.
Article
Computer Science, Information Systems
Yi-Bing Lin, Tai-Hsiang Yen, Chien-Ju Hung
INTERNATIONAL JOURNAL OF SENSOR NETWORKS
(2020)
Article
Computer Science, Information Systems
Yi-Chih Kao, Jui-Chun Liu, Yi-Quan Ke, Shi-Chun Tsai, Yi-Bing Lin
