Article
Thermodynamics
Kai Gao, Pan Luo, Jin Xie, Bin Chen, Yue Wu, Ronghua Du
Summary: This paper proposes an improved energy management strategy for plug-in hybrid electric vehicles (PHEVs) by integrating driving intention and LIDAR data to achieve accurate speed prediction and optimize energy management in real-time.
Article
Engineering, Chemical
Dapai Shi, Shipeng Li, Kangjie Liu, Yun Wang, Ruijun Liu, Junjie Guo
Summary: Under the dual-carbon goal, research on energy conservation and emission reduction of new energy vehicles has once again become a hot topic. This study proposes an adaptive energy management strategy for plug-in hybrid electric vehicles (PHEVs) to improve fuel economy based on intelligent prediction of driving cycles. Simulation results show that the proposed strategy achieves a 9.85% higher fuel saving rate compared to the rule-based strategy and a 5.30% higher rate compared to the ECMS strategy without prediction, further enhancing the fuel saving potential of PHEVs.
Article
Thermodynamics
Yonggang Liu, Bin Huang, Yang Yang, Zhenzhen Lei, Yuanjian Zhang, Zheng Chen
Summary: This paper investigates a hierarchical energy management control strategy for autonomous plug-in hybrid electric vehicles in vehicle-following environment. The strategy includes an upper layer controller with grey neural network and fuzzy adaptive control algorithm, and a lower layer controller with genetic algorithm and fuzzy logic algorithm, to predict speed, plan target speed, and optimize energy consumption, achieving 95.43% optimality compared to dynamic programming results.
Article
Green & Sustainable Science & Technology
Z. Chen, Y. Liu, M. Ye, Y. Zhang, G. Li
Summary: Hybrid electric vehicles use a combination of fuel and electric power as power supply to improve fuel economy, requiring a well-designed energy management strategy to cope with the complexity of power distribution. Equivalent consumption minimisation strategy, with the use of an equivalent factor, is a promising technique for achieving real-time fuel economy optimisation and is classified based on its dependence on either online computation or offline pre-computation.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(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
Mathematics
Harshit Mohan, Gopal Agrawal, Vibhu Jately, Abhishek Sharma, Brian Azzopardi
Summary: To reduce pollution and energy consumption, electric vehicles (EVs) are gaining more attention in the automotive industry. High efficiency, compactness, lightweight, low cost, and easy recyclability are desired in the electric motors used in EVs. Various motor control strategies and sensorless speed control techniques are employed to achieve better dynamic performance and increased reliability.
Article
Thermodynamics
Desiree Alcazar-Garcia, Jose Luis Romeral Martinez
Summary: This paper presents an adaptive and high-accuracy methodology that utilizes genetic algorithms to accelerate the design and implementation of ecological vehicles in smart cities. The methodology maximizes vehicle range with minimal computational effort and provides predictive information on cost, volume, and weight. The reliability and precision of the model have been verified using commercially available vehicles.
Article
Automation & Control Systems
Xiaohui Hou, Junzhi Zhang, Yuan Ji, Weilong Liu, Chengkun He
Summary: This paper presents a novel autonomous drift controller for a distributed drive electric vehicle, which uses control channel recombination and fuzzy-integral sliding-mode control to achieve stable drifting. The controller's performance with fast response and strong robustness was validated through bench testing.
Article
Energy & Fuels
Hongwen He, Yiwen Shou, Jian Song
Summary: Plug-in hybrid electric vehicles (PHEVs) play a significant role in urban public transportation systems due to their potential for energy saving and emission reduction. However, current energy management strategies rarely consider the transient characteristics of the engine, leading to extra fuel consumption. In this study, an optimization approach is proposed to improve energy management considering engine transient characteristics for PHEVs. The results show a significant reduction in extra fuel consumption and an improvement in fuel economy.
Article
Engineering, Mechanical
Tao Deng, Ke Zhao, Haoyuan Yu
Summary: The paper proposes an Adaptive Equivalent Consumption Minimization Strategy (A-ECMS) to reduce emissions of PHEV by considering catalyst temperature, while only slightly increasing fuel consumption.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING
(2022)
Article
Thermodynamics
Lingxiong Guo, Xudong Zhang, Yuan Zou, Ningyuan Guo, Jianwei Li, Guodong Du
Summary: This paper proposes an EMS based on MPC to minimize fuel cost, electricity usage and battery ageing through a speed predictor and SOC reference generator, achieving desirable performance as shown in simulation results.
Article
Engineering, Civil
Lipeng Zhang, Xin Liu, Shuaishuai Liu, Minghan Chen
Summary: This study investigates the online self-seeking traction control based on the dual-mode coupling drive system (DMCS) for electric vehicles. It proposes a new traction control strategy and verifies its feasibility and superiority in improving vehicle dynamics performance through simulation and testing.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Economics
M. Amine Masmoudi, Leandro C. Coelho, Emrah Demir
Summary: This paper investigates the problem of designing refuse vehicle routes for commercial waste collection and proposes a Hybrid Threshold Acceptance algorithm to solve the problem. Extensive computational experiments confirm the good performance of the proposed algorithm and demonstrate the benefits of using hybrid electric refuse vehicles in terms of operational costs and total distance traveled.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Energy & Fuels
Tao Deng, Peng Tang, JunLin Luo
Summary: A novel real-time energy management strategy for PHEVs based on equivalence factor dynamic optimization method is proposed in this paper, which weakens the influence of future driving cycle to the control accuracy and improves computation efficiency.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Green & Sustainable Science & Technology
Zhenyu Jia, Ning Wei, Jiawei Yin, Xiaoyang Zhao, Lin Wu, Yanjie Zhang, Jianfei Peng, Ting Wang, Zhiwen Yang, Qijun Zhang, Hongjun Mao
Summary: Green Light Optimized Speed Advisory (GLOSA) is a rapidly expanding technology for intelligent transportation worldwide. However, little research has been done on the energy consumption, pollutant emissions, and driving behavior changes of plug-in hybrid vehicles (PHEVs) before and after GLOSA implementation. In this study, we quantitatively analyze the environmental and energy benefits of PHEVs after GLOSA application using real-road driving cycles and chassis dynamometer tests. The results show that GLOSA significantly reduces engine starts and throttle openings, improves powertrain operating conditions, and leads to a reduction in energy consumption and pollutant emissions of PHEVs.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Engineering, Electrical & Electronic
Liang Li, Chao Yang, Yahui Zhang, Lipeng Zhang, Jian Song
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2015)
Article
Engineering, Mechanical
Lipeng Zhang, Wei Yu, Xun Zhao, Aihong Meng, Fahad Muhammad
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING
(2016)
Article
Engineering, Mechanical
Lipeng Zhang, Xiaohong Zhang, Zongqi Han, Junyun Chen, Jingchao Liu
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING
(2017)
Article
Engineering, Multidisciplinary
Zhang LiPeng, Qi BingNan, Zhang RunSheng, Liu JingChao, Wang LiQiang
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
(2016)
Article
Engineering, Multidisciplinary
Zhang LiPeng, Li Liang, Qi BingNan
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
(2018)
Article
Engineering, Mechanical
Lipeng Zhang, Silong Zhang, Wei Zhang
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING
(2019)
Article
Engineering, Mechanical
Lipeng Zhang, Zhaowen Pang, Sheng Wang, Silong Zhang, Xinmao Yuan
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING
(2020)
Article
Thermodynamics
LiPeng Zhang, Wei Liu, Bingnan Qi
Article
Engineering, Mechanical
Lipeng Zhang, Liuquan Yang, Xiaobin Guo, Xinmao Yuan
MECHANISM AND MACHINE THEORY
(2020)
Article
Engineering, Mechanical
Lipeng Zhang, Chenhui Ren, Xinmao Yuan, Wei Zhang
Summary: The use of regenerative suspension control can improve the vehicle dynamics control functions of unmanned ground vehicles, reduce discomfort when driving on rough roads, and extend the driving range of the vehicle.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING
(2021)
Article
Engineering, Mechanical
Lipeng Zhang, Wei Liu, Bingnan Qi
CHINESE JOURNAL OF MECHANICAL ENGINEERING
(2020)
Article
Engineering, Electrical & Electronic
Bingnan Qi, Liuquan Yang, Lipeng Zhang, Runsheng Zhang
Summary: The dual-mode coupling drive system for electric vehicles can switch automatically between centralized and distributed drive modes and realize two-speed gear shifting. Failure of the angle-displacement sensor in this system may greatly affect mode-switching quality, but an adaptive fault-tolerant control method has been proposed to address this issue effectively.
AUTOMOTIVE INNOVATION
(2021)
Article
Engineering, Mechanical
Zhang Lipeng, Guo Xiaobin, Yang Liuquan, Peng Yunao, Qi Bingnan
INTERNATIONAL JOURNAL OF VEHICLE DESIGN
(2020)
Proceedings Paper
Engineering, Multidisciplinary
Zhang Run Sheng, Li Liang, Zhang Si Long, Zhang Wei, Zhang Li Peng
PROCEEDINGS OF THE 2017 2ND INTERNATIONAL CONFERENCE ON MATERIALS SCIENCE, MACHINERY AND ENERGY ENGINEERING (MSMEE 2017)
(2017)
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.
