Article
Engineering, Electrical & Electronic
Brian S. Gu, Tharindu Dharmakeerthi, Seho Kim, Michael J. O'Sullivan, Grant A. Covic
Summary: This article proposes a reduced ferrite inductive power transfer system for electric vehicle charging, which uses ferrite-based soft magnetic composites to reduce system cost and improve mechanical robustness. The optimized system reduces ferrite volume by 63% and exhibits minimal deterioration in terms of coupling reduction and magnetic field leakage.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
Article
Computer Science, Information Systems
Jannik Schaefer, Johann Walter Kolar
Summary: This paper presents an isolated three-port DC/DC converter topology for energy distribution grid of electric vehicles, with simplicity in control and circuit complexity, achieving high efficiency and power density for charging EVs.
Article
Engineering, Multidisciplinary
Utsav Sharma, Bhim Singh
Summary: This article investigates the application of neural network-assisted deadbeat predictive current control in onboard charger for an e-rickshaw. By introducing a multistep charging scheme, the electricity consumption efficiency of the charger is improved under wide load conditions. The article presents the topology of the grid-connected charger and the working principles of its two stages.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Siqi Li, Sizhao Lu, Chunting Chris Mi
Summary: This article introduces the latest electric vehicle charging technologies utilizing wide bandgap devices, focusing on the applications of WBG devices in improving efficiency and power density, reducing costs, and introducing a performance evaluation index for wireless chargers.
PROCEEDINGS OF THE IEEE
(2021)
Article
Energy & Fuels
Shahab Afshar, Zachary K. Pecenak, Masoud Barati, Vahid Disfani
Summary: The advancement of fixed charging stations has facilitated the charging of electric vehicles in urban areas, while the construction is limited by budget and infrastructure constraints. Mobile charging stations can serve as a supplementary charging technology to address challenges such as long charging times and inconvenient locations, allowing for rapid expansion of charging infrastructure.
Article
Energy & Fuels
Yaseen Alwesabi, Farzad Avishan, Ihsan Yanikoglu, Zhaocai Liu, Yong Wang
Summary: This study aims to address the limitations of battery electric buses (BEBs) in terms of charging time and driving range by utilizing dynamic wireless charging (DWC) technology, and to improve their application in public bus systems. The research analyzes the benefits of joint planning of charging infrastructure and fleet scheduling in a bus network based on Binghamton University using robust planning models.
Article
Computer Science, Information Systems
Arman Fathollahi, Sayed Yaser Derakhshandeh, Ali Ghiasian, Mohammad A. S. Masoum
Summary: This paper presents a long-term stochastic scenario-based mathematical model for allocating and sizing dynamic wireless charging (DWC) infrastructures for electric vehicles (EVs), taking into account EV location-routing, power distribution system losses, and transportation network traffic. Simulation results show that using location-routing problem can save up to 45% of the total cost of the DWC system, and demonstrate the advantage of DWC technology in reducing the size of vehicle batteries.
Article
Green & Sustainable Science & Technology
Kristian Sevdari, Lisa Calearo, Bjorn Harald Bakken, Peter Bach Andersen, Mattia Marinelli
Summary: In this study, the researchers propose, test, and validate a method for investigating EV onboard chargers via the OBDII port. They present the charging efficiency and reactive power characteristics of 38 different EV models and find that smart charging through current modulation can increase global charging energy demand. They also observe that some EV models violate power factor limits for the low-voltage grid. The projections show an improvement in charging efficiency by 2030 and saturation by 2035. The results highlight the importance of improving charging technology and legislation based on other technological experiences.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2023)
Article
Engineering, Electrical & Electronic
Teng Long, Qing-Shan Jia, Gongming Wang, Yu Yang
Summary: This paper presents an efficient and scalable real-time scheduling method for handling the charging demands of plug-in electric vehicles (PEV), demonstrating through simulations that the proposed method provides high computation efficiency and scalability while reducing operating costs for charging stations. Compared to existing methods, it outperforms in terms of charging policy search capabilities and performance guarantee.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Article
Thermodynamics
Jean-Michel Clairand, Mario Gonzalez-Rodriguez, Rajesh Kumar, Shashank Vyas, Guillermo Escriva-Escriva
Summary: This study proposes an optimal siting and sizing approach for an electric taxi charging station, considering transportation and power system needs, with particular attention to taxi drivers' requirements. Network modeling and sensitivity analysis are used to explore interest points and uncertainties in traffic flow in Quito, the capital of Ecuador.
Article
Computer Science, Information Systems
Li Yan, Haiying Shen, Liuwang Kang, Juanjuan Zhao, Zhe Zhang, Chengzhong Xu
Summary: This paper introduces a mobile wireless charger guidance system, MobiCharger, which determines the number and optimal routes of serving Mobile Energy Disseminators (MEDs). By studying a metropolitan-scale vehicle mobility dataset, the authors discovered patterns of EV's routine and density changes. Through combining EV's current trajectories and routines, and employing multi-objective optimization and reinforcement learning methods, they achieved offline and online deployment adjustment of MEDs. Experimental results show that MobiCharger significantly increases the State-of-Charge and number of charges for all EVs compared to previous methods.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Thermodynamics
WanJun Yin, Xuan Qin
Summary: This paper proposes a method to solve the optimal scheduling problem of large-scale electric vehicles connected to the grid. By considering multiple factors and using a high-confidence wind power scenario, the collaborative optimization of coal-fired power generation, wind power generation, and electric vehicles is achieved.
Article
Construction & Building Technology
Hossien Faraji, Reza Hemmati
Summary: This paper integrates DC fast charging (DCFC) stations into the distribution network (DN) and designs DCFC stations equipped with charging devices (CDs) at different rated powers to support electric vehicles (EVs) charging. A central control system (CCS) is designed for each DCFC to manage its local controllers. Distributed energy storage (DES) is also used to increase the charging speed and improve the DN operation. The proposed strategies effectively improve the DN performance and accurately control the charging process in the EVs, as demonstrated by nonlinear simulations using MATLAB-SIMULINK.
SUSTAINABLE CITIES AND SOCIETY
(2023)
Review
Business
Ishtiak Mahmud, Mohtarima Begum Medha, M. Hasanuzzaman
Summary: Global primary energy supply relies heavily on fossil fuels, which are limited in supply and have negative environmental impacts. The popularity of electric vehicles is rapidly increasing due to various factors, leading to the need for governments to support their adoption. However, the rapid growth of electric vehicles is presenting challenges for the existing power system.
RESEARCH IN TRANSPORTATION BUSINESS AND MANAGEMENT
(2023)
Article
Economics
Marcin Jacek Klos, Grzegorz Sierpinski
Summary: The rapid growth of cities and transport systems has led to specific problems, particularly pollution and noise caused by individual transport in urban areas. Transitioning towards green solutions can help alleviate the negative effects of traditional combustion engines. However, the lack of charging stations poses a considerable limitation to the adoption of electric vehicles in cities. This article proposes a GIS-based method for siting charging stations in urban areas, considering their distances and pedestrian accessibility. The results, demonstrated through a case study in Katowice, Poland, show that increasing the number of stations significantly expands the coverage area, confirming the effectiveness of the method for planning charging station distribution. Moreover, the method allows for adaptation to the city budget, which is an important factor.
JOURNAL OF TRANSPORT GEOGRAPHY
(2023)
Article
Chemistry, Physical
Alireza Goshtasbi, Tulga Ersal
JOURNAL OF POWER SOURCES
(2020)
Article
Transportation
Yifan Weng, Rasoul Salehi, Xinyi Ge, Denise Rizzo, Matthew P. Castanier, Scott Heim, Tulga Ersal
Summary: Motivated by military applications, this study focuses on connected platoons of ground vehicles with different sizes and presents a model-free approach to optimize the platoon's speed in order to balance fuel economy and mobility. The results demonstrate that the proposed method can achieve this balance in a model-free manner despite gear shift deadzones.
JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Behavioral Sciences
Chen Li, Yue Tang, Yingshi Zheng, Paramsothy Jayakumar, Tulga Ersal
Summary: This paper extends a prior human operator model to predict human steering performance in path-following scenarios of unmanned ground vehicles (UGVs) with varying speed. The proposed model successfully captures human steering behavior under the effect of accelerations/decelerations, time delays, and varying speed. Human subject experiments validate the model's performance.
Article
Automation & Control Systems
Eunjeong Hyeon, Youngki Kim, Tulga Ersal, Anna Stefanopoulou
Summary: This paper investigates temporal correlations in human driving behavior and proposes a new prediction method to improve speed forecasting accuracy. The results show that the new method significantly improves energy saving compared to conventional speed predictors.
JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME
(2022)
Article
Engineering, Electrical & Electronic
James Dallas, Michael P. Cole, Paramsothy Jayakumar, Tulga Ersal
Summary: A novel single-level adaptive trajectory planner and tracking controller has been developed for off-road autonomous vehicles, featuring a neural network deformable terrain terramechanics model. By estimating terrain parameters online, the adaptive controller implemented within model predictive control improves vehicle safety and performance.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Thermodynamics
Chunan Huang, Rasoul Salehi, Anna G. Stefanopoulou, Tulga Ersal
Summary: This study extends our understanding of the trade-offs among fuel economy, driving aggressiveness, and emissions in connected automated diesel-powered vehicles through experiments. Results show that the flexible leader following policy has potential in reducing fuel consumption and tailpipe emissions.
INTERNATIONAL JOURNAL OF ENGINE RESEARCH
(2023)
Article
Automation & Control Systems
Sicong Guo, Yuzhang Liu, Yingshi Zheng, Tulga Ersal
Summary: This study presents a model-free framework to address the challenge of achieving high-fidelity closed-loop integration on engineering testbeds accessible remotely over a network. By expanding the framework with two design parameters, the delay compensation performance is improved, as demonstrated through simulation and experimental validation.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Behavioral Sciences
Chen Li, Michael Cole, Paramsothy Jayakumar, Tulga Ersal
Summary: This study extends a human steering model to capture human behavior in haptic shared control of autonomy-enabled UGVs. Human subject tests were conducted to collect data, and the ACT-R architecture and two-point steering model were used to predict steering angles. A torque conversion module was developed to enable haptic shared control. The model predicts the best shared control performance in terms of average lane keeping error (ALKE).
Article
Automation & Control Systems
John Wurts, Jeffrey L. Stein, Tulga Ersal
Summary: Model predictive control (MPC) is a control strategy that can account for future response and complex control objectives. This study investigates the computational cost of solving nonlinear MPC problems and provides a framework for designing nonlinear MPC architectures compatible with real-time performance.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2022)
Article
Engineering, Civil
Eunjeong Hyeon, Tulga Ersal, Youngki Kim, Anna G. Stefanopoulou
Summary: Accurate prediction of the preceding vehicle's trajectory is crucial in car-following scenarios to minimize energy consumption of automated vehicles. This study presents a novel design strategy for data-driven vehicle speed predictors to improve energy efficiency in following connected and automated vehicles. The proposed loss function, based on weighted-mean-squared error, effectively reduces the energy consumption of an electric vehicle compared to conventional loss functions.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Proceedings Paper
Automation & Control Systems
Congkai Shen, Siyuan Yu, Tulga Ersal
Summary: This paper introduces a novel three-phase global path planning framework that combines D* Lite, RRT*, and local path optimization algorithms for nonholonomic autonomous off-road navigation on 3D terrains. Through simulation experiments and performance comparisons, the study finds that the new framework offers higher path quality and success rate.
Proceedings Paper
Automation & Control Systems
Siyuan Yu, Congkai Shen, Tulga Ersal
Summary: A novel model predictive formulation is introduced for autonomous vehicles to plan and execute collision-free and dynamically feasible maneuvers on 3D terrains. By constructing a vehicle model that considers terrain topology and using a single layer nonlinear model predictive control framework, the control inputs are optimized for steering rate and longitudinal acceleration. The new algorithm successfully navigates the vehicle to the target on varying slopes terrain, outperforming conventional methods in simulation.
Article
Computer Science, Information Systems
John Wurts, Jeffrey L. Stein, Tulga Ersal
Summary: This article presents a new formulation of collision imminent steering to extend the capability to curved roads, allowing for aggressive lane change maneuvers at high speeds through a drivable tube concept. Numerical simulation results showcase inside and outside lane changes, as well as single and double lane maneuvers on curved roads in a shorter distance than braking alone.
Article
Ergonomics
Ruikun Luo, Yifan Weng, Yifan Wang, Paramsothy Jayakumar, Mark J. Brudnak, Victor Paul, Vishnu R. Desaraju, Jeffrey L. Stein, Tulga Ersal, X. Jessie Yang
Summary: This study presents a haptic shared control scheme that adapts to human operator's workload, eyes on road and input torque in real time. The experiments conducted with 24 participants show that the adaptive haptic control scheme results in lower workload, higher trust in autonomy, better driving task performance and smaller control effort.
ACCIDENT ANALYSIS AND PREVENTION
(2021)
Article
Electrochemistry
Alireza Goshtasbi, Benjamin L. Pence, Jixin Chen, Michael A. DeBolt, Chunmei Wang, James R. Waldecker, Shinichi Hirano, Tulga Ersal
JOURNAL OF THE ELECTROCHEMICAL SOCIETY
(2020)
Article
Energy & Fuels
Shitong Fang, Houfan Du, Tao Yan, Keyu Chen, Zhiyuan Li, Xiaoqing Ma, Zhihui Lai, Shengxi Zhou
Summary: This paper proposes a new type of nonlinear VIV energy harvester (ANVEH) that compensates for the decrease in peak energy output at low wind speeds by introducing an auxiliary structure. Theoretical and experimental results show that ANVEH performs better than traditional nonlinear VIV energy harvesters under various system parameter variations.
Article
Energy & Fuels
Wei Jiang, Shuo Zhang, Teng Wang, Yufei Zhang, Aimin Sha, Jingjing Xiao, Dongdong Yuan
Summary: A standardized method was developed to evaluate the availability of solar energy resources in road areas, which combined the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). By analyzing critical factors and using a multi-indicator evaluation method, the method accurately evaluated the utilization of solar energy resources and guided the optimal location selection for road photovoltaic (PV) projects. The results provided guidance for the application of road PV projects and site selection for route corridors worldwide, promoting the integration of transportation and energy.
Article
Energy & Fuels
Chang Liu, Jacob A. Wrubel, Elliot Padgett, Guido Bender
Summary: The study investigates the effects of coating defects on the performance of the anode porous transport layer (PTL) in water electrolyzers. The results show that an increasing fraction of uncoated regions on the PTL leads to decreased cell performance, with continuous uncoated regions having a more severe impact compared to multiple thin uncoated strips.
Article
Energy & Fuels
Marcos Tostado-Veliz, Xiaolong Jin, Rohit Bhakar, Francisco Jurado
Summary: In this paper, a coordinated charging price mechanism for clusters of parking lots is proposed. The research shows that enabling vehicle-to-grid characteristics can bring significant economic benefits for users and the cluster coordinator, and vehicle-to-grid impacts noticeably on the risk-averse character of the uncertainty-aware strategies. The developed pricing mechanism can reduce the cost for users, avoiding to directly translate the energy cost to charging points.
Article
Energy & Fuels
Duan Kang
Summary: Building an energy superpower is a key strategy for China and a long-term goal for other countries. This study proposes an evaluation system and index for measuring energy superpower, and finds that China has significantly improved its ranking over the past 21 years, surpassing other countries.
Article
Energy & Fuels
Fucheng Deng, Yifei Wang, Xiaosen Li, Gang Li, Yi Wang, Bin Huang
Summary: This study investigated the synergistic blockage mechanism of sand and hydrate in gravel filling layer and the evolution of permeability in the layer. Experimental models and modified permeability models were established to analyze the effects of sand particles and hydrate formation on permeability. The study provided valuable insights for the safe and efficient exploitation of hydrate reservoirs.
Article
Energy & Fuels
Hao Wang, Xiwen Chen, Natan Vital, Edward Duffy, Abolfazl Razi
Summary: This study proposes a HVAC energy optimization model based on deep reinforcement learning algorithm. It achieves 37% energy savings and ensures thermal comfort for open office buildings. The model has a low complexity, uses a few controllable factors, and has a short training time with good generalizability.
Article
Energy & Fuels
Moyue Cong, Yongzhuo Gao, Weidong Wang, Long He, Xiwang Mao, Yi Long, Wei Dong
Summary: This study introduces a multi-strategy ultra-wideband energy harvesting device that achieves high power output without the need for external power input. By utilizing asymmetry, stagger array, magnetic coupling, and nonlinearity strategies, the device maintains a stable output voltage and high power density output at non-resonant frequencies. Temperature and humidity monitoring are performed using Bluetooth sensors to adaptively assess the device.
Article
Energy & Fuels
Tianshu Dong, Xiudong Duan, Yuanyuan Huang, Danji Huang, Yingdong Luo, Ziyu Liu, Xiaomeng Ai, Jiakun Fang, Chaolong Song
Summary: Electrochemical water splitting is crucial for hydrogen production, and improving the hydrogen separation rate from the electrode is essential for enhancing water electrolyzer performance. However, issues such as air bubble adhesion to the electrode plate hinder the process. Therefore, a methodology to investigate the two-phase flow within the electrolyzer is in high demand. This study proposes using a microfluidic system as a simulator for the electrolyzer and optimizing the two-phase flow by manipulating the micro-structure of the flow.
Article
Energy & Fuels
Shuo Han, Yifan Yuan, Mengjiao He, Ziwen Zhao, Beibei Xu, Diyi Chen, Jakub Jurasz
Summary: Giving full play to the flexibility of hydropower and integrating more variable renewable energy is of great significance for accelerating the transformation of China's power energy system. This study proposes a novel day-ahead scheduling model that considers the flexibility limited by irregular vibration zones (VZs) and the probability of flexibility shortage in a hydropower-variable renewable energy hybrid generation system. The model is applied to a real hydropower station and effectively improves the flexibility supply capacity of hydropower, especially during heavy load demand in flood season.
Article
Energy & Fuels
Zhen Wang, Kangqi Fan, Shizhong Zhao, Shuxin Wu, Xuan Zhang, Kangjia Zhai, Zhiqi Li, Hua He
Summary: This study developed a high-performance rotary energy harvester (AI-REH) inspired by archery, which efficiently accumulates and releases ultralow-frequency vibration energy. By utilizing a magnetic coupling strategy and an accumulator spring, the AI-REH achieves significantly accelerated rotor speeds and enhanced electric outputs.
Article
Energy & Fuels
Yi Yang, Qianyi Xing, Kang Wang, Caihong Li, Jianzhou Wang, Xiaojia Huang
Summary: In this study, a novel hybrid Quantile Regression (QR) model is proposed for Probabilistic Load Forecasting (PLF). The model integrates causal dilated convolution, residual connection, and Bidirectional Long Short-Term Memory (BiLSTM) for multi-scale feature extraction. In addition, a Combined Probabilistic Load Forecasting System (CPLFS) is proposed to overcome the inherent flaws of relying on a single model. Simulation results show that the hybrid QR outperforms traditional models and CPLFS exceeds the best benchmarks in terms of prediction accuracy and stability.
Article
Energy & Fuels
Wen-Jiang Zou, Young-Bae Kim, Seunghun Jung
Summary: This paper proposes a dynamic prediction model for capacity fade in vanadium redox flow batteries (VRFBs). The model accurately predicts changes in electrolyte volume and capacity fade, enhancing the competitiveness of VRFBs in energy storage applications.
Article
Energy & Fuels
Yuechao Ma, Shengtie Wang, Guangchen Liu, Guizhen Tian, Jianwei Zhang, Ruiming Liu
Summary: This paper focuses on the balance of state of charge (SOC) among multiple battery energy storage units (MBESUs) and bus voltage balance in an islanded bipolar DC microgrid. A SOC automatic balancing strategy is proposed considering the energy flow relationship and utilizing the adaptive virtual resistance algorithm. The simulation results demonstrate the effectiveness of the proposed strategy in achieving SOC balancing and decreasing bus voltage unbalance.
Article
Energy & Fuels
Raad Z. Homod, Basil Sh. Munahi, Hayder Ibrahim Mohammed, Musatafa Abbas Abbood Albadr, Aissa Abderrahmane, Jasim M. Mahdi, Mohamed Bechir Ben Hamida, Bilal Naji Alhasnawi, A. S. Albahri, Hussein Togun, Umar F. Alqsair, Zaher Mundher Yaseen
Summary: In this study, the control problem of the multiple-boiler system (MBS) is formulated as a dynamic Markov decision process and a deep clustering reinforcement learning approach is applied to obtain the optimal control policy. The proposed strategy, based on bang-bang action, shows superior response and achieves more than 32% energy saving compared to conventional fixed parameter controllers under dynamic indoor/outdoor actual conditions.