Article
Engineering, Electrical & Electronic
Junhui Liu, Lei Feng, Zhiwu Li
Summary: This article introduces a new method that considers road conditions, particularly grade angle, as design variables for reducing energy consumption of ground vehicles. By modeling speed trajectories of vehicles on the road as a Markov chain, the optimal road grade profile designed using dynamic programming is shown to save up to 22% energy compared to a flat road for simulated speed trajectories.
IET INTELLIGENT TRANSPORT SYSTEMS
(2021)
Article
Computer Science, Information Systems
Yousra Abdul Alsahib S. Aldeen, Mustafa Musa Jaber, Mohammed Hasan Ali, Sura Khalil Abd, Ahmed Alkhayyat, R. Q. Malik
Summary: Environmentally friendly and sustainable transportation options have been developed to tackle pollution and fuel shortages. However, there are still obstacles to overcome before green transportation goals can be fully achieved. A research study focuses on electric vehicle-centric approach and proposes using IoT-CC to improve EVCS location selection.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Energy & Fuels
Bingkun Song, Udaya Madawala, Craig Baguley
Summary: This paper proposes an optimal planning strategy for car parks deploying reconfigurable electric vehicle chargers (REVCs). The strategy involves optimizing the power rating, number, and configuration of REVCs, as well as the operation plan for the EV car park. A case study shows that the proposed strategy significantly reduces total cost while meeting charging demands.
Article
Energy & Fuels
Morteza Azimi Nasab, Mohammad Zand, Amir Ali Dashtaki, Mostafa Azimi Nasab, Sanjeevikumar Padmanaban, Frede Blaabjerg, Q. Juan C. Vasquez
Summary: This article addresses the issue of uncertainty in the use of new energies by solving the flexibility planning of electric vehicle charging and discharging with the help of the CPLEX solver. It aims to coordinate with wind and solar production and compensate for the uncertainty of these resources. The results show that considering uncertainties can reduce costs through optimal planning for electric vehicles, which is also profitable for the operator.
Article
Energy & Fuels
Weiwei Xin, Enyong Xu, Weiguang Zheng, Haibo Feng, Jirong Qin
Summary: This paper proposes an energy management framework based on model predictive control for fuel cell commercial vehicles. By introducing vehicle mass as a variable parameter, a vehicle mass identification model is established and evaluated the influence of variable algorithm parameters. The study also discusses the effects of mass varying on vehicle performance and evaluates the performance for different drive cycles on different loaded situations.
Article
Green & Sustainable Science & Technology
Jacid Montoya-Torres, Ortzi Akizu-Gardoki, Maider Iturrondobeitia
Summary: This study aims to determine the environmentally optimal time to replace a petrol car and quantify the impact of different substitution scenarios on greenhouse gas emissions. The results show that choosing an electric car as a substitute can lead to environmental benefits in a relatively short period of time. Additionally, using a cleaner energy mix can significantly reduce the replacement time.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Thermodynamics
Zhiguang Hua, Tianhong Wang, Xianglong Li, Dongdong Zhao, Yuanlin Wang, Manfeng Dou
Summary: This research introduces a multi-objective comprehensive optimization power distribution strategy specifically designed for a hybrid electric vehicle that utilizes both fuel cell and battery technology. The strategy focuses on optimizing the operational cost and service life of the fuel cell stack, as well as the energy storage system's lifetime loss and state of charge (SOC) fluctuation. Furthermore, the research aims to enhance fuel efficiency by optimizing the hydrogen consumption of the system. The proposed strategy has been validated using hardware-in-the-loop (HIL) bench, showing advantages over other benchmark power distribution strategies.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Computer Science, Artificial Intelligence
Zhenzhong Wang, Kai Ye, Min Jiang, Junfeng Yao, Neal N. Xiong, Gary G. Yen
Summary: This study proposes a framework to reuse knee points in a new environment to address the Dynamic Vehicle Routing Problem based on Hybrid Charging Strategy. Reusing knee points helps generate a better initial population and brings convenience to decision makers.
SWARM AND EVOLUTIONARY COMPUTATION
(2022)
Article
Environmental Studies
Filip Mandys
Summary: The UK has a significant automobile market, with a growing share of alternative fuel vehicles (AFVs). However, there is limited research on the price determinants of conventional vehicles (CVs) and AFVs. This paper uses a hedonic pricing model and a comprehensive dataset from 2008 to 2019 to estimate the factors influencing automobile prices. The results show that performance and size are key drivers of prices, with a stronger effect as prices increase. Engine power and weight have significant impacts on prices, with a one standard deviation increase leading to a 16.9% and 14.7% price increase respectively. AFVs are more sensitive to changes in car characteristics compared to CVs.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2023)
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
Energy & Fuels
Reza Fachrizal, Mahmoud Shepero, Magnus aberg, Joakim Munkhammar
Summary: The integration of PV systems and EVs in the built environment has brought new technical challenges, which can be minimized through optimal sizing and operation. This study presents an optimal sizing framework based on self-consumption-sufficiency balance (SCSB) score and explores the potential enhancement through smart charging schemes.
Article
Automation & Control Systems
Yan Ma, Cheng Li, Siyu Wang
Summary: This paper proposes a multi-objective predictive energy management strategy based on model predictive control, which achieves efficient power allocation between the fuel cell and lithium-ion battery, improves fuel utilization, and avoids fuel cell degradation.
Article
Computer Science, Information Systems
Manuel Gomez-Gonzalez, Marcos Tostado-Veliz, Manuel Valverde, Francisco Jurado
Summary: This study developed a novel optimization methodology for analyzing the effect of using retired batteries from electric vehicles in domestic photovoltaic installations. It found that using these second-purpose batteries in smart homes can reduce total cost by 15% and increase self-consumption rates by 20%.
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
Green & Sustainable Science & Technology
Haochen Xu, Niaona Zhang, Zonghao Li, Zichang Zhuo, Ye Zhang, Yilei Zhang, Haitao Ding
Summary: This research introduces an energy-conserving speed planning approach using reinforcement learning for autonomous electric vehicles. By leveraging vehicle-to-vehicle and vehicle-to-infrastructure communication, real-time data is obtained to optimize driving behavior and minimize energy consumption. The evaluation results demonstrate the efficacy of the algorithm in reducing energy consumption while considering safety.
Article
Engineering, Civil
Cong-Zhi Liu, Liang Li, Jia-Wang Yong, Fahad Muhammad, Shuo Cheng
Summary: A novel finite frequency H-infinity observer-based method is proposed in this study to address the disturbances in the practical application of advanced driver assistant system (ADAS). By analyzing Radar tracking characteristics and establishing an H-infinity observer, the design criterion of the finite frequency H-infinity observer is established using the linear matrix inequality (LMI) based on H-infinity theory and Kalman-Yakubovic-Popov (KYP) lemma. Two real-world experiments are presented to demonstrate the effectiveness of the proposed method.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Engineering, Mechanical
Wei Yue, Cong-zhi Liu, Liang Li, Xiang Chen, Fahad Muhammad
Summary: This work focuses on designing a fractional-order H-infinity observer and applying it to SOC estimation for a lithium-ion battery pack system. The method includes establishing a fractional order equivalent circuit model, proposing a SOC estimation method based on the observer, and verifying its effectiveness through experimental results.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING
(2021)
Article
Engineering, Mechanical
Jintao Zhao, Shuo Cheng, Liang Li, Mingcong Li, Zhihuang Zhang
Summary: This paper proposes a novel model-free controller based on reinforcement learning for active steering system with unknown parameters. The controller effectively tackles the challenges brought by uncertainties in vehicle steering systems, by establishing an agent network and designing environment rewards.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING
(2021)
Article
Computer Science, Interdisciplinary Applications
Liang Li, Jianye Zhou, Yuewen Jiang, Biqing Huang
Summary: Source identification in networks is a challenging task, and the study introduces a novel Source Identification Graph Convolutional Network (SIGN) framework to address this issue effectively. Extensive experiments on diverse datasets demonstrate the strong performances of the proposed algorithms, especially under large infection sizes.
JOURNAL OF BIOMEDICAL INFORMATICS
(2021)
Article
Engineering, Mechanical
Qiong Wu, Shuo Cheng, Liang Li, Fan Yang, Li Jun Meng, Zhi Xian Fan, Hua Wei Liang
Summary: This paper proposes a fuzzy-inference-based reinforcement learning approach for autonomous overtaking decision making in automated vehicles, considering various factors such as vehicle safety, driving comfort, and vehicle efficiency, and validating the effectiveness of the method on a simulation platform.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING
(2022)
Article
Engineering, Mechanical
Shuo Cheng, Ming-ming Mei, Shi-yong Guo, Liang Li, Cong-zhi Liu, Xiang Chen, Xiu-heng Wu
Summary: The study introduces an adaptive sliding-mode control algorithm to optimize tire slip speed of the automated vehicle, along with a traction control system and TBW coupling strategy based on the logic threshold method to respond to the optimum slip speed curve.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING
(2021)
Article
Engineering, Multidisciplinary
Huang ChangYao, Li Liang, Fang ShengNan, Cheng Shuo, Chen Zheng
Summary: PHEVs offer great potential in energy savings by combining engine and electric motor advantages. Fuel economy performance is influenced by driving conditions and lane selection, with lane selection strategies needing to consider energy consumption costs. Intelligent connected vehicles can improve energy performance by incorporating environmental information from V2X and sensors, as demonstrated in a neural network-based method for predicting vehicle status and energy consumption in different lanes.
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
(2021)
Article
Automation & Control Systems
Shuo Cheng, Liang Li, Xiang Chen, Jian Wu, Hong-da Wang
Summary: The article proposes a vehicle automated steering controller based on model predictive control (MPC) approach, which improves control performance, ensures control accuracy, and strong robustness.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Engineering, Electrical & Electronic
Lingtao Wei, Xiangyu Wang, Liang Li, Zhixian Fan, Ruzhen Dou, Jingui Lin
Summary: This study proposes a model predictive control (MPC) method based on the Takagi-Sugeno (T-S) fuzzy model to realize yaw stability control (YSC) in the nonlinear region. The results show that the proposed strategy has similar performance in the vehicle stable region with linear MPC, and it is able to suppress the instability of the vehicle in the nonlinear region, with an acceptable computation burden.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Engineering, Mechanical
Qiuyue Du, Chenxi Zhu, Quantong Li, Bin Tian, Liang Li
Summary: The article introduces a new four-wheel active steering control strategy, which utilizes the MPC algorithm for path tracking control, designs an estimator based on UKF theory and low-cost sensors, and combines it with the LQR optimal controller to achieve optimized control of front and rear steering. Simulation results demonstrate that this method performs well in lateral control stability and path tracking accuracy.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING
(2022)
Article
Automation & Control Systems
Shuo Cheng, Liang Li, Cong-Zhi Liu, Xiuheng Wu, Sheng-Nan Fang, Jia-Wang Yong
Summary: This article proposes a novel robust linear matrix inequality (LMI)-based H-infinite feedback algorithm for vehicle dynamics stability control, which is robust against vehicle parametric uncertainties.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Zheng Zhu, Yang Tian, Xiangyu Wang, Liang Li, Xuegong Luan, Yipeng Gao
Summary: A fusion predictive control method based on uncertain algorithm is proposed to address the parameter sensitivity issue in traditional deadbeat current control of permanent magnet synchronous motor (PMSM), integrating forward linear prediction (FLP) and deadbeat prediction (DP) to improve current response speed. The uncertain controller adjusts the reliability of FLP and DP in real time through uncertainty measurement, while a flux observer is designed to dynamically adjust flux parameters for current loop satisfaction. Simulation and experimental results demonstrate a reduction in system parameter sensitivity and an improvement in current loop dynamic performance (up to 12.56%).
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2021)
Article
Engineering, Electrical & Electronic
Jian Wu, Junda Zhang, Yang Tian, Liang Li
Summary: The study proposes an HMC steering torque control method based on MRAC to address disturbances and parameter uncertainties. Using an exponential decay function as a reference model, parameter adaptive laws are designed to improve robustness. The proposed control strategy demonstrates rapid convergence under disturbances and uncertainties introduced by HMC.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2021)
Article
Engineering, Civil
Cong-Zhi Liu, Liang Li, Xiang Chen, Jia-Wang Yong, Shuo Cheng, Hong-Lei Dong
Summary: In this study, a novel mixed H-2/H-infinity observer-based controller is proposed to address delayed measurements for real-time feedback control in advanced driver assistant system (ADAS). The controller enables object tracking and car-following, as well as attenuation of noises in the adaptive cruise control (ACC) system. The design criterion for the proposed controller is established based on linear matrix inequality (LMI) technique, demonstrating effectiveness through experiment scenarios.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Baiming Chen, Xiang Chen, Qiong Wu, Liang Li
Summary: This paper proposes an adaptive evaluation framework to efficiently evaluate autonomous vehicles in adversarial environments generated by deep reinforcement learning. By using ensemble models and nonparametric Bayesian methods to achieve diversity and cluster adversarial policies. Results show that the proposed method significantly degrades the performance of tested vehicles and can be used to infer weaknesses.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Mechanical
Xuanen Kan, Yanjun Lu, Fan Zhang, Weipeng Hu
Summary: A blade disk system is crucial for the energy conversion efficiency of turbomachinery, but differences between blades can result in localized vibration. This study develops an approximate symplectic method to simulate vibration localization in a mistuned bladed disk system and reveals the influences of initial positive pressure, contact angle, and surface roughness on the strength of vibration localization.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Zimeng Liu, Cheng Chang, Haodong Hu, Hui Ma, Kaigang Yuan, Xin Li, Xiaojian Zhao, Zhike Peng
Summary: Considering the calculation efficiency and accuracy of meshing characteristics of gear pair with tooth root crack fault, a parametric model of cracked spur gear is established by simplifying the crack propagation path. The LTCA method is used to calculate the time-varying meshing stiffness and transmission error, and the results are verified by finite element method. The study also proposes a crack area share index to measure the degree of crack fault and determines the application range of simplified crack propagation path.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Rongjian Sun, Conggan Ma, Nic Zhang, Chuyo Kaku, Yu Zhang, Qirui Hou
Summary: This paper proposes a novel forward calculation method (FCM) for calculating anisotropic material parameters (AMPs) of the motor stator assembly, considering structural discontinuities and composite material properties. The method is based on multi-scale theory and decouples the multi-scale equations to describe the equivalence and equivalence preconditions of AMPs of two scale models. The effectiveness of this method is verified by modal experiments.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Hao Zhang, Jiangcen Ke
Summary: This research introduces an intelligent scheduling system framework to optimize the ship lock schedule of the Three Gorges Hub. By analyzing navigational rules, operational characteristics, and existing problems, a mixed-integer nonlinear programming model is formulated with multiple objectives and constraints, and a hybrid intelligent algorithm is constructed for optimization.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Jingjing He, Xizhong Wu, Xuefei Guan
Summary: A sensitivity and reliability enhanced ultrasonic method has been developed in this study to monitor and predict stress loss in pre-stressed multi-layer structures. The method leverages the potential breathing effect of porous cushion materials in the structures to increase the sensitivity of the signal feature to stress loss. Experimental investigations show that the proposed method offers improved accuracy, reliability, and sensitivity to stress change.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Benyamin Hosseiny, Jalal Amini, Hossein Aghababaei
Summary: This paper presents a method for monitoring sub-second or sub-minute displacements using GBSAR signals, which employs spectral estimation to achieve multi-dimensional target detection. It improves the processing of MIMO radar data and enables high-resolution fast displacement monitoring from GBSAR signals.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Xianze Li, Hao Su, Ling Xiang, Qingtao Yao, Aijun Hu
Summary: This paper proposes a novel method for bearing fault identification, which can accurately identify faults with few samples under complex working conditions. The method is based on a Transformer meta-learning model, and the final result is determined by the weighted voting of multiple models.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Xiaomeng Li, Yi Wang, Guangyao Zhang, Baoping Tang, Yi Qin
Summary: Inspired by chaos fractal theory and slowly varying damage dynamics theory, this paper proposes a new health monitoring indicator for vibration signals of rotating machinery, which can effectively monitor the mechanical condition under both cyclo-stationary and variable operating conditions.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Hao Wang, Songye Zhu
Summary: This paper extends the latching mechanism to vibration control to improve energy dissipation efficiency. An innovative semi-active latched mass damper (LMD) is proposed, and different latching control strategies are tested and evaluated. The latching control can optimize the phase lag between control force and structural response, and provide an innovative solution to improve damper effectiveness and develop adaptive semi-active dampers.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Menghao Ping, Xinyu Jia, Costas Papadimitriou, Xu Han, Chao Jiang, Wang-Ji Yan
Summary: Identification of non-Gaussian processes is a challenging task in engineering problems. This article presents an improved orthogonal series expansion method to convert the identification of non-Gaussian processes into a finite number of non-Gaussian coefficients. The uncertainty of these coefficients is quantified using polynomial chaos expansion. The proposed method is applicable to both stationary and nonstationary non-Gaussian processes and has been validated through simulated data and real-world applications.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Lei Li, Wei Yang, Dongfa Li, Jianxin Han, Wenming Zhang
Summary: The frequency locking phenomenon induced by modal coupling can effectively overcome the dependence of peak frequency on driving strength in nonlinear resonant systems and improve the stability of peak frequency. This study proposes the double frequencies locking phenomenon in a three degrees of freedom (3-DOF) magnetic coupled resonant system driven by piezoelectricity. Experimental and theoretical investigations confirm the occurrence of first frequency locking and the subsequent switching to second frequency locking with the increase of driving force. Furthermore, a mass sensing scheme for double analytes is proposed based on the double frequencies locking phenomenon.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Kai Ma, Jingtao Du, Yang Liu, Ximing Chen
Summary: This study explores the feasibility of using nonlinear energy sinks (NES) as replacements for traditional linear tuned mass dampers (TMD) in practical engineering applications, specifically in diesel engine crankshafts. The results show that NES provides better vibration attenuation for the crankshaft compared to TMD under different operating conditions.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Wentao Xu, Li Cheng, Shuaihao Lei, Lei Yu, Weixuan Jiao
Summary: In this study, a high-precision hydraulic mechanical stand and a vertical mixed-flow pumping station device were used to conduct research on cavitation signals of mixed-flow pumps. By analyzing the water pressure pulsation signal, it was found that the power spectrum density method is more sensitive and capable of extracting characteristics compared to traditional time-frequency domain analysis. This has significant implications for the identification and prevention of cavitation in mixed-flow pump machinery.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Xiaodong Chen, Kang Tai, Huifeng Tan, Zhimin Xie
Summary: This paper addresses the issue of parasitic motion in microgripper jaws and its impact on clamping accuracy, and proposes a symmetrically stressed parallelogram mechanism as a solution. Through mechanical modeling and experimental validation, the effectiveness of this method is demonstrated.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
Article
Engineering, Mechanical
Zhifeng Shi, Gang Zhang, Jing Liu, Xinbin Li, Yajun Xu, Changfeng Yan
Summary: This study provides useful guidance for early bearing fault detection and diagnosis by investigating the effects of crack inclination and propagation direction on the vibration characteristics of bearings.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2024)
