Article
Thermodynamics
Zhicheng Zhou, Yaojie Lv, Jian Qu, Qin Sun, Dmitrii Grachev
Summary: This study developed a hybrid oscillating heat pipe using CNT nanofluids for cooling electric vehicle batteries, demonstrating improved heat transfer performance and reduced battery pack temperature.
APPLIED THERMAL ENGINEERING
(2021)
Review
Energy & Fuels
Andhy M. Fathoni, Nandy Putra, T. M. Indra Mahlia
Summary: Heat pipes are widely used in the thermal management systems of electric vehicle batteries to control the working temperature and reduce the risk of thermal runaway. Besides traditional heat pipes, hybrid thermal management systems based on heat pipes are also worth exploring and researching.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Guoju Dang, Maohui Zhang, Fanqi Min, Yixiao Zhang, Banglin Zhang, Quansheng Zhang, Jiulin Wang, Yongning Zhou, Wen Liu, Jingying Xie, Samuel S. Mao
Summary: Electrification plays a crucial role in the transformation of the global vehicle industry. This study developed a hybrid-electric heavy-duty truck battery system based on LTO batteries, which are uniquely suitable for high-rate fast charging and discharging. Field operation tests showed that the LTO battery system performed as expected, resulting in 54.9% fuel savings compared to conventional diesel-powered trucks of the same size.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Lingcong Guo, Pan Hu, Hong Wei
Summary: A dedicated energy storage system suitable for hybrid electric vehicles, called the hybrid supercapacitor-based energy storage system, has been proposed. This system combines the advantages of supercapacitor materials and lithium-ion battery materials, providing low cost, long life cycle, high safety, wide working temperature range, high power density, and high energy density. The developed supercapacitor battery pack and hybrid electric vehicle with this system demonstrated significant performance improvements.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Z. J. Zhang, R. T. Ji, Y. Wang, M. Chang, X. P. Ma, J. Sha, D. L. Mao
Summary: This study investigates the heat and mass transfer in solar powered UAV under extreme conditions, exploring the effects of flight velocity, attitude, day and night on energy management. An improved energy management strategy is proposed to enhance efficiency and results show strengthened heat transfer and controlled battery temperature with the improved structure. The findings provide valuable insights for optimal global energy management design.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Energy & Fuels
Akif Demircali, Selim Koroglu
Summary: This study proposes a Jaya-based modular energy management system to optimize power sharing between the battery and ultracapacitor in electric vehicles. Experimental results show that compared to the rule-based method, this approach significantly reduces total loss and battery current.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Review
Green & Sustainable Science & Technology
Nur Ayeesha Qisteena Muzir, Md Rayid Hasan Mojumder, Md Hasanuzzaman, Jeyraj Selvaraj
Summary: The article thoroughly reviews the challenges of promoting electric vehicles in Malaysia and proposes potential solutions and suggestions. This review can serve as a valuable reference for policymakers in formulating strategic policies to achieve sustainable electric vehicle transportation goals.
Article
Energy & Fuels
R. Saravanan, O. Sobhana, M. Lakshmanan, P. Arulkumar
Summary: This manuscript proposes a hybrid technique, called JSO-RSA method, for the energy management of a battery-based FC electric vehicle system. The method aims to minimize the equivalent consumption by controlling the operational mode, state machine, and dynamic power factor. The proposed method demonstrates high efficiency (90.2%) and low operating cost ($568) compared to existing methods.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Pier Giuseppe Anselma, Phillip Kollmeyer, Jeremy Lempert, Ziyu Zhao, Giovanni Belingardi, Ali Emadi
Summary: This paper presents an optimal, multi-objective battery state-of-health (SOH) sensitive off-line HEV control approach based on dynamic programming, which is experimentally validated for prediction capability of battery lifetime. By improving the battery ageing model accuracy, the approach allows for downsizing the battery pack by 35% without impacting battery lifetime and with just a 1.1% increase in fuel consumption. Adopting this control approach could lead to significant cost, weight, and CO2 emissions reductions in battery packs for HEVs.
Article
Thermodynamics
Zexing Wang, Hongwen He, Jiankun Peng, Weiqi Chen, Changcheng Wu, Yi Fan, Jiaxuan Zhou
Summary: Research on deep reinforcement learning-based energy management strategies for hybrid electric vehicles is rapidly developing. This study designs four DRL-based EMSs for HEVs with a multiobjective optimization reward function that considers battery health. The performance of these EMSs is intensively studied under nine driving cycles, and the SAC-based EMS achieves the lowest fuel consumption and highest battery health. This paper provides a theoretical basis for the parametric and driving cycle study of DRL-based EMSs.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Thermodynamics
Tabbi Wilberforce, Afaaq Anser, Jangam Aishwarya Swamy, Richard Opoku
Summary: This study aims to develop a hybrid energy storage system (HESS) comprising battery and supercapacitor cells for a commercial Hybrid Electric Vehicle model (Hyundai Sonata) and evaluate its impact on battery health and vehicle performance. Different configurations of the energy storage devices are discussed, with a semi-active configuration used in simulations and testing. The addition of the supercapacitor stabilizes the battery's working status, reducing peak current and improving battery state of charge and temperature. However, there is a slight increase in fuel consumption due to losses in the supercapacitor system. A parametric study suggests that using 2 supercapacitor modules provides optimal results for battery behavior.
Article
Energy & Fuels
Weihan Li, Han Cui, Thomas Nemeth, Jonathan Jansen, Cem Uenluebayir, Zhongbao Wei, Lei Zhang, Zhenpo Wang, Jiageng Ruan, Haifeng Dai, Xuezhe Wei, Dirk Uwe Sauer
Summary: This paper introduces an energy management strategy based on deep reinforcement learning for a hybrid battery system in electric vehicles, which aims to minimize energy loss and enhance safety levels. The proposed strategy shows superiority in reducing computation time and energy loss, highlighting its potential in future energy management systems.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Automation & Control Systems
Jun Xu, Xuesong Mei, Haitao Wang, Junping Wang
Summary: A hybrid self-heating method (HSHM) for batteries used at low temperatures is proposed, featuring low cost, high temperature rise rate, and low energy loss. Experimental results show that HSHM heats batteries faster with less energy consumption, improving performance by 1.3 times compared to traditional methods.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Chemistry, Physical
Shibo Wang, Hui Wang, Min Chang, Jiakuan Xu, Jiuzhou Wang, Xueying Yang, Junqiang Bai
Summary: This study proposes a lightweight and portable directional heat transfer structure for battery heat dissipation in UAVs. Experimental results show that this structure can significantly reduce the maximum temperature in the battery and extend the cruise time of UAVs. The findings provide guidance for designing efficient battery cooling devices for UAVs.
JOURNAL OF POWER SOURCES
(2023)
Article
Green & Sustainable Science & Technology
Xiao Xu, Weihao Hu, Wen Liu, Yuefang Du, Qi Huang, Zhe Chen
Summary: This paper proposes a novel concept of an on-grid hybrid hydrogen refueling and battery swapping station powered by wind energy. It introduces a hybrid stochastic/distributionally robust optimization method to handle different uncertainties for the energy management problem. The overall objective is to minimize the total operational cost while considering the battery swapping station overstock punishment.
JOURNAL OF CLEANER PRODUCTION
(2022)
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.