Article
Engineering, Electrical & Electronic
Shiyao Zhou, Ziqiang Chen, Deyang Huang, Tiantian Lin
Summary: This study introduces an EMS design and optimization method for PHEVs, which has improved energy efficiency by 1.6%-2.5% and extended the energy storage system's lifespan by 159%-203% through the use of HESS and optimized EMS.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2021)
Article
Engineering, Electrical & Electronic
Yuyan Liu, Zhongping Yang, Xiaobo Wu, Donglei Sha, Fei Lin, Xiaochun Fang
Summary: This article proposes an adaptive energy management framework for stationary energy storage systems (ESS) using a battery-supercapacitor hybrid ESS. The advantages of this stationary hybrid ESS are demonstrated through an example. The proposed power distribution strategy solves the adaptability issue of two energy storage media to the load variation of rail transportation power systems, delaying battery degradation. Simulation and experimental results show that the proposed energy management strategy outperforms conventional strategies in terms of energy conservation rate, voltage stabilization rate, and battery current.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2022)
Article
Energy & Fuels
Yijie Zhang, Qimeng Xue, Diju Gao, Weifeng Shi, Wanneng Yu
Summary: Compared with ground power systems, the intermittent and random fluctuation of ship load power demand poses challenges to the energy management system of ship power systems. To address this issue, a hybrid energy storage system and a two-level model predictive control strategy are proposed to optimize fuel economy and power distribution.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Engineering, Electrical & Electronic
Seneke Chamith Chandrarathna, Seong-Yeon Moon, Jong-Wook Lee
Summary: This article presents a power management system (PMS) for hybrid energy harvesting from multiple multitype sources. The proposed approach features a simple architecture for hybrid energy harvesting, a backup power controller for recycling surplus energy, and an efficient boost-buck conversion mode for tracking multiple sources. The PMS operates under four modes and improves efficiency using auxiliary output paths and two storage nodes. The integrated circuit (IC) part of the PMS is fabricated in a 180 nm process, achieving high tracking efficiency and an end-to-end efficiency of up to 92.5%. Energy harvesting from multiple sources significantly extends the output power range.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
Article
Chemistry, Physical
Zhichao Fu, Qihong Chen, Liyan Zhang, Haoran Zhang, Zhihua Deng
Summary: An energy management strategy for fuel cell hybrid power system based on ADHDP was proposed to reduce hydrogen consumption and enhance dynamic performance. Hardware-in-the-loop simulation demonstrated its good performance under real operating conditions, showing better fuel economy and dynamic performance compared to other algorithms.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2021)
Article
Chemistry, Analytical
Ming Ye, Jing Chen, Xu Li, Kai Ma, Yonggang Liu
Summary: A new energy management control strategy based on V2X communication was proposed to dynamically adjust engine and motor power output for vehicle speed prediction. The study utilized deep learning algorithm to model vehicle speed prediction and validated the proposed strategy with a plug-in hybrid vehicle model simulation, showing improvements in vehicle energy economy and reduced CO2 emissions.
Article
Thermodynamics
Junhui Meng, Nuo Ma, Fanmin Meng, Xiaohui Zhang, Li Liu
Summary: This paper studies a hybrid energy system for a multi-lobes hybrid air vehicle (HAV), which uses solar cells, fuel cells, and lithium batteries as energy sources. By establishing a rule-based power-following management strategy, different energy subsystems can be better managed to achieve optimal flight performance for HAV.
Article
Thermodynamics
Shuangqi Li, Chenghong Gu, Pengfei Zhao, Shuang Cheng
Summary: The study designs a novel propulsion system topology and power distribution algorithm for light manned electric aircraft, verified on the Alpha Electro prototype aircraft, demonstrating the ability to dynamically meet power requirements and protect the fuel cell effectively while reducing hydrogen consumption by 7.63% compared to fuel cell electric aircraft.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Energy & Fuels
Yuan Zhou, Jiangjiang Wang, Fuxiang Dong, Yanbo Qin, Zherui Ma, Yanpeng Ma, Jianqiang Li
Summary: This paper proposes a novel operational strategy for CCHP systems by analyzing system flexibility and evaluating design and operational performance using a flexibility index. A multi-objective optimization model is constructed to improve the economic performance and flexibility of the system.
Article
Automation & Control Systems
Shu Liu, Hongyu You, Yan Liu, Wanfu Feng, Shuo Fu
Summary: This article proposes an optimal control method for a wind-solar storage complement device designed using power prediction. By establishing simulation models and utilizing a wavelet packet neural network to build a power prediction model, a MPPT optimal control strategy that combines the hysteresis loop comparison-based P&O algorithm and the improved firefly algorithm is introduced. It ensures the dynamic tracking ability, speed, and optimization capability of both single and multiple peaks.
Article
Energy & Fuels
Zhichao Fu, Qihong Chen, Liyan Zhang, Jing Fan, Haoran Zhang, Zhihua Deng
Summary: The study proposed a Grey-Markov chain power prediction energy management strategy for fuel cell power generation systems, which can accurately predict load power in advance and reduce hydrogen consumption in the system.
Article
Thermodynamics
Jiayi Hu, Jianqiu Li, Zunyan Hu, Liangfei Xu, Minggao Ouyang
Summary: This study introduces a novel dual-engine system with the incorporation of dynamic programming algorithm for energy management, achieving lower fuel consumption compared to conventional hybrid systems.
Article
Energy & Fuels
Muhammed Resit Corapsiz, Hakan Kahveci
Summary: This paper proposes a new energy management strategy for electric vehicles with battery/supercapacitor hybrid energy storage systems, achieving optimized load management and demonstrating promising results in experiments.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Article
Green & Sustainable Science & Technology
Hoai-An Trinh, Hoai Vu Anh Truong, Minh Duc Pham, Tri Cuong Do, Hong-Hee Lee, Kyoung Kwan Ahn
Summary: Using renewable energy is a new trend to reduce fossil fuel consumption and greenhouse gas emissions. This paper proposes an innovative energy management strategy to improve power distribution accuracy and enhance the performance of a fuel cell in a hybrid power system.
INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING-GREEN TECHNOLOGY
(2023)
Article
Green & Sustainable Science & Technology
Lin Hu, Qingtao Tian, Changfu Zou, Jing Huang, Yao Ye, Xianhui Wu
Summary: This paper proposes an energy distribution optimization method and an improved topology for hybrid energy storage system in electric vehicles. Through experiments and simulations, it is shown that the proposed method effectively reduces battery degradation and energy loss, providing future research directions.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Engineering, Electrical & Electronic
Jikai Wang, Meng Xu, Guangpu Zhao, Zonghai Chen
Summary: In this article, a novel 3-D LiDAR SLAM method is proposed, which combines feature-based fast scan matching, distribution-based keyframe matching, and loop closure. The proposed mechanisms effectively improve the performance of the LiDAR SLAM system and demonstrate competitive performance compared to state-of-the-art methods. The source code will be made open to serve as a new baseline for the robotic community.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Civil
Jiaqiang Tian, Xinghua Liu, Chaobo Chen, Gaoxi Xiao, Yujie Wang, Yu Kang, Peng Wang
Summary: In this study, a battery pack inconsistency evaluation method based on an improved GMM and feature fusion approach is proposed. The method accurately estimates battery parameters and quantifies inconsistency using the standard deviation coefficient approach.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Hao Zhao, Jikai Wang, Zonghai Chen, Shiqi Lin, Peng Bao
Summary: The paper proposes a novel data augmentation scheme called SRK-Augment, which utilizes self-deformation data and class activation map to achieve region-level removal and improve the generalization of deep learning models.
NEURAL PROCESSING LETTERS
(2023)
Review
Chemistry, Multidisciplinary
Longfei Han, Li Wang, Zonghai Chen, Yongchun Kan, Yuan Hu, Hao Zhang, Xiangming He
Summary: Lithium-ion batteries, known for their portability, high energy density, and reusability, are widely used but they can leak, burn, or explode under extreme conditions. Researchers propose using solid electrolytes to improve the safety of lithium-ion batteries, but even polymer electrolytes can decompose and burn. Furthermore, the uneven charge distribution on the lithium metal anode leads to the formation of lithium dendrites, causing potential short circuits and thermal runaway. This review summarizes the thermal runaway mechanism, discusses battery abuse test standards, reviews recent works on high-safety polymer electrolytes, and considers solution strategies for lithium anode problems in polymer batteries, aiming to prospect the development of safe polymer solid lithium batteries.
ADVANCED FUNCTIONAL MATERIALS
(2023)
Article
Automation & Control Systems
Yujie Wang, Guanghui Zhao
Summary: This paper compares four typical fractional-order models for lithium-ion batteries and employs the Runge Kutta optimizer algorithm for model parameter identification. The accuracy for predicting terminal voltage and the time required for parameter identification under different dynamic conditions are compared. The fitted results of the model impedance spectrum and the model parameter values are discussed. This paper provides guidance on modeling and parameter identification for lithium-ion batteries by analyzing different fractional-order models and introducing impedance spectroscopy.
CONTROL ENGINEERING PRACTICE
(2023)
Article
Engineering, Electrical & Electronic
Hongyan Yuan, Zhendong Sun, Yujie Wang, Zonghai Chen
Summary: This study proposes a deep reinforcement learning controller (FO-DDPG) based on fusion optimization and a control optimization strategy based on net power optimization to address the coordination problem in the flow control of air and hydrogen in a proton exchange membrane fuel cell system. The experimental results demonstrate that the undecoupled FO-DDPG algorithm has a faster dynamic response and more stable static performance compared to other control algorithms.
WORLD ELECTRIC VEHICLE JOURNAL
(2023)
Article
Electrochemistry
Ruilong Xu, Yujie Wang, Zonghai Chen
Summary: This paper proposes a data-driven approach for battery aging mechanism analysis and degradation pathway prediction. The dominant aging modes and critical aging factors affecting battery capacity decay are determined through statistical analysis methods. A data-driven multi-factor coupled battery aging mechanism prediction model is developed using the Transformer network and regression-based data enhancement. Experimental results show that the proposed approach achieves satisfactory performances under different aging conditions.
Article
Energy & Fuels
Li Wang, Zonghai Chen, Yan Liu, Yuan Li, Hao Zhang, Xiangming He
Summary: The safety concerns of lithium-ion batteries (LIBs) have hindered their widespread application in electric vehicles and stationary energy storage. Solid-state lithium batteries with nonflammable electrolytes have been proposed as a potential solution for better safety. However, the safety of solid-state lithium metal batteries (SS-LMBs) remains uncertain. This review summarizes recent investigations on the safety concerns of SS-LMBs and provides a systematic analysis and discussion.
Article
Automation & Control Systems
Yujie Wang, Kaiquan Li, Pei Peng, Zonghai Chen
Summary: In this study, multiple candidate health indicators are extracted from the peaks and valleys of the partial incremental capacity curves and screened first. The deep belief network is fine-tuned using particle swarm optimization and compared with three classical deep networks in terms of error and time consumption. Three datasets of LiFePO4 cells under different discharge depths are used to verify the proposed framework. The experimental results show that the presented framework is feasible and the prediction error can be minimized to less than 2%.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Automation & Control Systems
Zhenkun Zhu, Jikai Wang, Meng Xu, Zonghai Chen
Summary: Image matching task and SLAM systems both rely on feature points for pixel association. This article proposes a training strategy based on the operating mode of SLAM systems, which enables the feature extraction network to better adapt to SLAM for pose estimation and mapping. The proposed method shows improved performance on both the matching task and integrated SLAM system, and can be easily applied to other image matching networks, narrowing the gaps between matching tasks and SLAM systems.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Xingchen Zhang, Yujie Wang, Zonghai Chen
Summary: Lithium-ion batteries and their control technologies are crucial for electric and intelligent transportation. Dynamic thermal management is an important technology for intelligent battery management systems. This article proposes a distributed control-oriented electro-thermal coupling model and improved parameter identification methods based on it. A state of charge (SoC)-modified core temperature estimation method is also proposed. Experimental results show high accuracy and robustness of the proposed methods.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)
Article
Chemistry, Physical
Yujie Wang, Kangfan Xie, Yanfei Zhu, Kai Tong, Mingyu Zhang, Feixiang Wu
Summary: Microcubic FeF3@C composite, synthesized through the Prussian blue microcubes, shows stable and ultralong lifespan as the cathode of lithium batteries. The capacity rising of as-prepared FeF3 cathodes within initial cycles is attributed to the compact carbon shell and stable cathode solid electrolyte interphase.
JOURNAL OF POWER SOURCES
(2023)
Article
Energy & Fuels
Ruilong Xu, Yujie Wang, Zonghai Chen
Summary: This paper proposes a hybrid battery health prediction method that combines Transformer and online correction models. It accurately predicts the battery health by establishing a nonlinear relationship between measured data and capacity decline. By considering multi-scale health features and reducing feature dimensions, this method achieves optimal prediction performance for batteries under different aging conditions.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Thermodynamics
Yong Cheng, Fukai Song, Lei Fu, Saishuai Dai, Zhiming Yuan, Atilla Incecik
Summary: This paper investigates the accessibility of wave energy absorption by a dual-pontoon floating breakwater integrated with hybrid-type wave energy converters (WECs) and proposes a hydraulic-pneumatic complementary energy extraction method. The performance of the system is validated through experiments and comparative analysis.
Article
Thermodynamics
Jing Gao, Chao Wang, Zhanwu Wang, Jin Lin, Runkai Zhang, Xin Wu, Guangyin Xu, Zhenfeng Wang
Summary: This study aims to establish a new integrated method for biomass cogeneration project site selection, with a focus on the application of the model in Henan Province. By integrating Geographic Information System and Multiple Criterion Decision Making methods, the study conducts site selection in two stages, providing a theoretical reference for the construction of biomass cogeneration projects.
Article
Thermodynamics
Mert Temiz, Ibrahim Dincer
Summary: The current study presents a hybrid small modular nuclear reactor and solar-based system for sustainable communities, integrating floating and bifacial photovoltaic arrays with a small modular reactor. The system efficiently generates power, hydrogen, ammonia, freshwater, and heat for residential, agricultural, and aquaculture facilities. Thermodynamic analysis shows high energy and exergy efficiencies, as well as large-scale ammonia production meeting the needs of metropolitan areas. The hybridization of nuclear and solar technologies offers advantages of reliability, environmental friendliness, and cost efficiency compared to renewable-alone and fossil-based systems.
Editorial Material
Thermodynamics
Wojciech Stanek, Wojciech Adamczyk
Article
Thermodynamics
Desheng Xu, Yanfeng Li, Tianmei Du, Hua Zhong, Youbo Huang, Lei Li, Xiangling Duanmu
Summary: This study investigates the optimization of hybrid mechanical-natural ventilation for smoke control in complex metro stations. The results show that atrium fires are more significantly impacted by outdoor temperature variations compared to concourse/platform fires. The gathered high-temperature smoke inside the atrium can reach up to 900 K under a 5 MW train fire energy release. The findings provide crucial engineering insights into integrating weather data and adaptable ventilation protocols for smoke prevention/mitigation.
Article
Thermodynamics
Da Guo, Heping Xie, Mingzhong Gao, Jianan Li, Zhiqiang He, Ling Chen, Cong Li, Le Zhao, Dingming Wang, Yiwei Zhang, Xin Fang, Guikang Liu, Zhongya Zhou, Lin Dai
Summary: This study proposes a new in-situ pressure-preserved coring tool and elaborates its pressure-preserving mechanism. The experimental and field test results demonstrate that this tool has a high pressure-preservation capability and can maintain a stable pressure in deep wells. This study provides a theoretical framework and design standards for the development of similar technologies.
Article
Thermodynamics
Aolin Lai, Qunwei Wang
Summary: This study assesses the impact of China's de-capacity policy on renewable energy development efficiency (REDE) using the Global-MSBM model and the difference-in-differences method. The findings indicate that the policy significantly enhances REDE, promoting technological advancements and marketization. Moreover, regions with stricter environmental regulations experience a higher impact.
Article
Thermodynamics
Mostafa Ghasemi, Hegazy Rezk
Summary: This study utilizes fuzzy modeling and optimization to enhance the performance of microbial fuel cells (MFCs). By simulating and analyzing experimental data sets, the ideal parameter values for increasing power density, COD elimination, and coulombic efficiency were determined. The results demonstrate that the fuzzy model and optimization methods can significantly improve the performance of MFCs.
Article
Thermodynamics
Zhang Ruan, Lianzhong Huang, Kai Wang, Ranqi Ma, Zhongyi Wang, Rui Zhang, Haoyang Zhao, Cong Wang
Summary: This paper proposes a grey box model for fuel consumption prediction of wing-diesel hybrid vessels based on feature construction. By using both parallel and series grey box modeling methods and six machine learning algorithms, twelve combinations of prediction models are established. A feature construction method based on the aerodynamic performance of the wing and the energy relationship of the hybrid system is introduced. The best combination is obtained by considering the root mean square error, and it shows improved accuracy compared to the white box model. The proposed grey box model can accurately predict the daily fuel consumption of wing-diesel hybrid vessels, contributing to operational optimization and the greenization and decarbonization of the shipping industry.
Article
Thermodynamics
Huayi Chang, Nico Heerink, Junbiao Zhang, Ke He
Summary: This study examines the interaction between off-farm employment decisions between couples and household clean energy consumption in rural China, and finds that two-paycheck households are more likely to consume clean energy. The off-farm employment of women is a key factor driving household clean energy consumption to a higher level, with wage-employed wives having a stronger influence on these decisions than self-employed ones.
Article
Thermodynamics
Hanguan Wen, Xiufeng Liu, Ming Yang, Bo Lei, Xu Cheng, Zhe Chen
Summary: Demand-side management is crucial to smart energy systems. This paper proposes a data-driven approach to understand the relationship between energy consumption patterns and household characteristics for better DSM services. The proposed method uses a clustering algorithm to generate optimal customer groups for DSM and a deep learning model for training. The model can predict the possibility of DSM membership for a given household. The results demonstrate the usefulness of weekly energy consumption data and household socio-demographic information for distinguishing consumer groups and the potential for targeted DSM strategies.
Article
Thermodynamics
Xinglan Hou, Xiuping Zhong, Shuaishuai Nie, Yafei Wang, Guigang Tu, Yingrui Ma, Kunyan Liu, Chen Chen
Summary: This study explores the feasibility of utilizing a multi-level horizontal branch well heat recovery system in the Qiabuqia geothermal field. The research systematically investigates the effects of various engineering parameters on production temperature, establishes mathematical models to describe their relationships, and evaluates the economic viability of the system. The findings demonstrate the significant economic feasibility of the multi-level branch well system.
Article
Thermodynamics
Longxin Zhang, Songtao Wang, Site Hu
Summary: This investigation reveals the influence of tip leakage flow on the modern transonic rotor and finds that the increase of tip clearance size leads to a decline in rotor performance. However, an optimal tip clearance size can extend the rotor's stall margin.
Article
Thermodynamics
Kristian Gjoka, Behzad Rismanchi, Robert H. Crawford
Summary: This paper proposes a framework for assessing the performance of 5GDHC systems and demonstrates it through a case study in a university campus in Melbourne, Australia. The results show that 5GDHC systems are a cost-effective and environmentally viable solution in mild climates, and their successful implementation in Australia can create new market opportunities and potential adoption in other countries with similar climatic conditions.
Article
Thermodynamics
Jianwei Li, Guotai Wang, Panpan Yang, Yongshuang Wen, Leian Zhang, Rujun Song, Chengwei Hou
Summary: This study proposes an orientation-adaptive electromagnetic energy harvester by introducing a rotatable bluff body, which allows for self-regulation to cater for changing wind flow direction. Experimental results show that the output power of the energy harvester can be greatly enhanced with increased rotatory inertia of the rotating bluff body, providing a promising solution for harnessing wind-induced vibration energy.