Chinese Electric Vehicle Brands’ Strategic Entry into the European Market

Yuan Feng HONG KONG ACADEMY OF SOCIAL SCIENCES 2024 Journal of Social Science Development Research Vol.1 No.2

This article examines the entry of Chinese EV brands into the European market, emphasizing the significance of Europe's strong environmental policies and consumer demand for sustainable transport. It discusses the strategic approaches of companies like Geely, Lynk & Co, MG, and Polestar, highlighting their tailored market strategies, challenges, and opportunities amidst stringent regulations and diverse consumer behaviors. The focus is on how these brands adapt and position themselves within the competitive landscape, aiming to capitalize on Europe’s shift towards electric mobility.

Distributed Target Localization with Inaccurate Collaborative Sensors in Multipath Environments

( Yuan Feng ),( Qinsiwei Yan ),( Po-hsuan Tseng ),( Ganlin Hao ),( Nan Wu ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.5

Location-aware networks are of great importance for both civil lives and military applications. Methods based on line-of-sight (LOS) measurements suffer sever performance loss in harsh environments such as indoor scenarios, where sensors can receive both LOS and non-line-of-sight (NLOS) measurements. In this paper, we propose a data association (DA) process based on the expectation maximization (EM) algorithm, which enables us to exploit multipath components (MPCs). By setting the mapping relationship between the measurements and scatters as a latent variable, coefficients of the Gaussian mixture model are estimated. Moreover, considering the misalignment of sensor position, we propose a space-alternating generalized expectation maximization (SAGE)-based algorithms to jointly update the target localization and sensor position information. A two dimensional (2-D) circularly symmetric Gaussian distribution is employed to approximate the probability density function of the sensor's position uncertainty via the minimization of the Kullback-Leibler divergence (KLD), which enables us to calculate the expectation step with low computational complexity. Moreover, a distributed implementation is derived based on the average consensus method to improve the scalability of the proposed algorithm. Simulation results demonstrate that the proposed centralized and distributed algorithms can perform close to the Monte Carlo-based method with much lower communication overhead and computational complexity.

CNN-based damage identification method of tied-arch bridge using spatial-spectral information

Yuanfeng Duan,Qianyi Chen,Hongmei Zhang,Chung Bang Yun,Sikai Wu,Qi Zhu 국제구조공학회 2019 Smart Structures and Systems, An International Jou Vol.23 No.5

In the structural health monitoring field, damage detection has been commonly carried out based on the structural model and the engineering features related to the model. However, the extracted features are often subjected to various errors, which makes the pattern recognition for damage detection still challenging. In this study, an automated damage identification method is presented for hanger cables in a tied-arch bridge using a convolutional neural network (CNN). Raw measurement data for Fourier amplitude spectra (FAS) of acceleration responses are used without a complex data pre-processing for modal identification. A CNN is a kind of deep neural network that typically consists of convolution, pooling, and fully-connected layers. A numerical simulation study was performed for multiple damage detection in the hangers using ambient wind vibration data on the bridge deck. The results show that the current CNN using FAS data performs better under various damage states than the CNN using time-history data and the traditional neural network using FAS. Robustness of the present CNN has been proven under various observational noise levels and wind speeds.

Influence of some key factors on material damping of steel beams

Yuanfeng Wang,Yuhua Pan,Jie Wen,Li Su,Shengqi Mei 국제구조공학회 2014 Structural Engineering and Mechanics, An Int'l Jou Vol.49 No.3

Material damping affects the dynamic behaviors of engineering structures considerably, but up to till now little research is maintained on influence factors of material damping. Based on the damping-stress function of steel, the material damping of steel beams is obtained by calculating the stress distribution of the beams with an analytical method. Some key influence factors of the material damping, such as boundary condition, amplitude and frequency of excitation, load position as well as the cross-sectional dimension of a steel beam are analyzed respectively. The calculated results show that even in elastic scope, material damping does not remain constant but varies with these influence factors. Although boundary condition affects material damping to some extent, such influence can be neglected when the maximum stress amplitude of the beam is less than the fatigue limit of steel. Exciting frequency, load position and cross-section dimension have great effects on the material damping of the beam which maintain the similar changing trend under different boundary conditions respectively.

Anomaly detection of isolating switch based on single shot multibox detector and improved frame differencing

Yuanfeng Duan,Qi Zhu,Hongmei Zhang,Wei Wei,Chung Bang Yun 국제구조공학회 2021 Smart Structures and Systems, An International Jou Vol.28 No.6

High-voltage isolating switches play a paramount role in ensuring the safety of power supply systems. However, their exposure to outdoor environmental conditions may cause serious physical defects, which may result in great risk to power supply systems and society. Image processing-based methods have been used for anomaly detection. However, their accuracy is affected by numerous uncertainties due to manually extracted features, which makes the anomaly detection of isolating switches still challenging. In this paper, a vision-based anomaly detection method for isolating switches, which uses the rotational angle of the switch system for more accurate and direct anomaly detection with the help of deep learning (DL) and image processing methods (Single Shot Multibox Detector (SSD), improved frame differencing method, and Hough transform), is proposed. The SSD is a deep learning method for object classification and localization. In addition, an improved frame differencing method is introduced for better feature extraction and a hough transform method is adopted for rotational angle calculation. A number of experiments are conducted for anomaly detection of single and multiple switches using video frames. The results of the experiments demonstrate that the SSD outperforms the You-Only-Look-Once network. The effectiveness and robustness of the proposed method have been proven under various conditions, such as different illumination and camera locations using 96 videos from the experiments.

Abnormal Behavior Recognition Based on Spatio-temporal Context

Yuanfeng Yang,Lin Li,Zhaobin Liu,Gang Liu 한국정보처리학회 2020 Journal of information processing systems Vol.16 No.3

This paper presents a new approach for detecting abnormal behaviors in complex surveillance scenes whereanomalies are subtle and difficult to distinguish due to the intricate correlations among multiple objects’behaviors. Specifically, a cascaded probabilistic topic model was put forward for learning the spatial contextof local behavior and the temporal context of global behavior in two different stages. In the first stage of topicmodeling, unlike the existing approaches using either optical flows or complete trajectories, spatio-temporalcorrelations between the trajectory fragments in video clips were modeled by the latent Dirichlet allocation(LDA) topic model based on Markov random fields to obtain the spatial context of local behavior in each videoclip. The local behavior topic categories were then obtained by exploiting the spectral clustering algorithm. Based on the construction of a dictionary through the process of local behavior topic clustering, the secondphase of the LDA topic model learns the correlations of global behaviors and temporal context. In particular,an abnormal behavior recognition method was developed based on the learned spatio-temporal context ofbehaviors. The specific identification method adopts a top-down strategy and consists of two stages: anomalyrecognition of video clip and anomalous behavior recognition within each video clip. Evaluation was performedusing the validity of spatio-temporal context learning for local behavior topics and abnormal behaviorrecognition. Furthermore, the performance of the proposed approach in abnormal behavior recognitionimproved effectively and significantly in complex surveillance scenes.

Design formulas for vibration control of sagged cables using passive MR dampers

Yuanfeng Duan,Yi-Qing Ni,Hongmei Zhang,Billie F. Jr. Spencer,Jan-Ming Ko,Shenghao Dong 국제구조공학회 2019 Smart Structures and Systems, An International Jou Vol.23 No.6

In this paper, a method for analyzing the damping performance of stay cables incorporating magnetorheological (MR) dampers in the passive control mode is developed taking into account the cable sag and inclination, the damper coefficient, stiffness and mass, and the stiffness of damper support. Both numerical and asymptotic solutions are obtained from complex modal analysis. With the asymptotic solution, analytical formulas that evaluate the equivalent damping ratio of the sagged cable-damper system in consideration of all the above parameters are derived. The main thrust of the present study is to develop an general design formula and a universal curve for the optimal design of MR dampers for adjustable passive control of sagged cables. Two sag-affecting coefficients are derived to reflect the effects of cable sag on the maximum attainable damping ratio and the optimal damper coefficient. For the cable configurations commonly used in cable-stayed bridges, the sag-affecting coefficients are directly expressed in terms of the sag-extensibility parameter to facilitate the control design. A case study on adjustable passive vibration control of the longest cable (536 m) on Stonecutters Bridge is carried out to demonstrate the influence of the sag for the damper design, and to figure out the necessity of adjustability of damper coefficients for achieving maximum damping ratio for different vibration modes.

An optimization method for vibration suppression and energy dissipation of an axially moving string with hybrid nonclassical boundaries

Yuanfeng Wu,Enwei Chen,Neil S Ferguson,Yuteng He,Haozheng Wei,Yimin Lu 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.3

The axially moving string model is widely used in engineering applications and is of great significance in research. To suppress transverse vibration and facilitate energy dissipation of the axially moving string with nonclassical boundaries, a bi-objective optimization model and methodology are proposed for its boundary parameters’ design. First, an approximate numerical model for an axially moving string with a nonclassical boundary is established, which is based on the finite element method (FEM) and Newmark-beta method. Then, a biobjective model is proposed, including the average transverse vibration and the average system energy in a single traveling wave period, and a particle swarm optimization (BOPSO) algorithm is established for optimization. Finally, the proposed optimization model is applied in a numerical example, and the results are compared with NSGA-II, a multi-objective cuckoo search algorithm (MOCSA), and multi-objective flower pollination algorithm (MOFPA) to verify the feasibility of the proposed methodology.

Design formulas for vibration control of taut cables using passive MR dampers

Yuanfeng Duan,Yi-Qing Ni,Hongmei Zhang,Billie. F., Jr. Spencer,Jan-Ming Ko,Yi Fang 국제구조공학회 2019 Smart Structures and Systems, An International Jou Vol.23 No.6

Using magnetorheological (MR) dampers in multiswitch open-loop control mode has been shown to be cost-effective for cable vibration mitigation. In this paper, a method for analyzing the damping performance of taut cables incorporating MR dampers in open-loop control mode is developed considering the effects of damping coefficient, damper stiffness, damper mass, and stiffness of the damper support. Making use of a three-element model of MR dampers and complex modal analysis, both numerical and asymptotic solutions are obtained. An analytical expression is obtained from the asymptotic solution to evaluate the equivalent damping ratio of the cable-damper system in the open-loop control mode. The individual and combined effects of the damping coefficient, damper stiffness, damper mass and stiffness of damper support on vibration control effectiveness are investigated in detail. The main thrust of the present study is to derive a general formula explicitly relating the normalized system damping ratio and the normalized damper parameters in consideration of all concerned effects, which can be easily used for the design of MR dampers to achieve optimal open-loop vibration control of taut cables.

3D-monoclinic M–BTC MOF (M = Mn, Co, Ni) as highly efficient catalysts for chemical fixation of CO2 into cyclic carbonates

Yuanfeng Wu,Xianghai Song,Shuai Li,Jiahui Zhang,Xinghui Yang,Pengxin Shen,Lijing Gao,Ruiping Wei,Jin Zhang,Guomin Xiao 한국공업화학회 2018 Journal of Industrial and Engineering Chemistry Vol.58 No.-

[(CH3)2NH2][M3(BTC)(HCOO)4(H2O)].H2O (M–BTC, M = Mn, Ni, Co) were prepared under hydrothermal conditions and used as highly efficient catalysts for cycloaddition of CO2 with epichlorohydrin (ECH). The microstructure and physicochemical properties of the compounds were determined by PXRD, FT-IR, XPS, N2-adsorption, TG–DSC, NH3–TPD and CO2–TPD. 98.01% conversion of ECH and 96.05% selectivity to chloropropene carbonate was obtained over the Mn–BTC under the optimized reaction conditions (105 °C, 3.0 MPa, 9 h, 1.5 wt.% of ECH). Besides, the recyclability result exhibited the Mn–BTC compound can be utilized as least three times with a slight reduction in its catalytic ability. In addition, cycloaddition of CO2 with other epoxides and DFT calculation were also performed. The result exhibited the yield followed the order: ECH > 1, 2-epoxybutane > propene oxide > Allyl glycidyl ether, which was mainly determined by the energy of reaction.