• Title/Summary/Keyword: Small electric vehicle

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Design and Performance Evaluation of Two-Layered Microwave Absorbers(Dielectric/Magnetic) for Wide Oblique Incidence Angles Used for ITS (ITS용 2층형 전파 흡수체(유전체/자성체) 설계 및 경사 입사 흡수 특성 해석)

  • Kim, Jae-Woong;Kim, Sung-Soo
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.18 no.11
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    • pp.1217-1223
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    • 2007
  • Advanced microwave absorbers for wide oblique incidence angles are required in many applications including wireless communication or vehicle identification in ITS(Intelligent Transport System) where 5.8 GHz DSRC(Dedicated Short Range Communication) system is applied. In this study, two-layered microwave absorber(with a laminate structure of dielectric/magnetic composites) has been designed for the achievement of low reflection coefficient over wide incidence angles at 5.8 GHz. Iron flake particles are used as the filler in the absorbing layer, and the magnetic composite sheet exhibits high magnetic loss due to ferromagnetic resonance in gigahertz frequencies. The surface layer of low dielectric constant containing small amount of carbon black is used as the impedance transformer. On the basis of transmission line theory, the reflection loss has been calculated for the two-layer structure with variation of incident angles for both TE(Transverse Electric) and TM(Transverse Magnetic) polarizations. At the optimum thickness of the composite layers, a low value of reflection loss(less than -10 dB) has been predicted for wide incidence angles up to $55^{\circ}$ which is in good agreement with the measured value determined by free-space measurement.

Electrode bonding method and characteristic of high density rechargeable battery using induction heating system (유도 가열 접합 시스템을 이용한 대용량 이차전지 전극의 접합 방법 및 특성)

  • Kim, Eun-Min;Kim, Shin-Hyo;Hong, Won-Hee;Cho, Dae-Kweon
    • Journal of Advanced Marine Engineering and Technology
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    • v.38 no.6
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    • pp.688-697
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    • 2014
  • In this study, electrode bonding technology needed for high density of rechargeable battery is studied, which is recently researched for electric vehicle, the small leisure vessel. For the alternative overcoming the limit of stacking amount able to be stacked by conventional ultrasonic welding, the low temperature bonding method, eligible for minimum of degeneration of chemical activator on the electrode surface which is generated by thermal effect as well as the increase of conductivity and tension strength caused by electrode bonding using filler metal, not using conventional direct heating on the electrode material method, is studied. Specifically to say, recently used more generally the ultrasonic welding and spot welding method are not usable for satisfying stable electric conductivity and bonding strength when much electrode is stacking bonded. If the electrical power is unreasonably increased for the welding, due to the effect of welding temperature, deformation of electrode and activating material degeneration are caused, and after the last packaging, decline of electrical output and generating heat cause to reduce stability of battery. Therefore, in this study, induction heating system bonding method using high frequency heating and differentiated electrode method using filler metal pre-treatment of hot dipping are introduced.

Smart Battery System of Lithium ion Batteries (리튬이온전지의 Smart Battery System)

  • Kim Hyun-Soo;Moon Seong-In;Yun Mun-Soo;Ko Beyng-Hi;Park Sang-Kun;Shin Dong-O;Yoo Seong-Mo;Lee Seung-Ho
    • Journal of the Korean Electrochemical Society
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    • v.4 no.3
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    • pp.132-137
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    • 2001
  • Recently, the demand for notebook PC with lithium ion batteries has steadily increased and consumers require them to adopt a SBP(smart battery pack) able to predict the remaining capacity and the run time of batteries precisely. The SBP is composed of a protection If, by which safety of lithium ion batteries is maintained against overcharge, overdischarge and overcurrent, and a smart IC, which calculates the remaining capacity and the remaining run time. The protection IC shut abmormal current down by using overcharge/overdischarge FET. A SBS(smart battery system) is composed of a system host, a smart battery and a smart battery charger. The smart ICs for SBP will be required to provide a low cost, low current consumption and small size. There will need to develop a microcomputer control type IC and an optimum algorism which is able to predict the residual capacity and the residual run time precisely. SBS will apply to many kinds of industry fields such as an electric bicycle, an electric vehicle, a load levelling and a military.

A Review on 3D Structure Formation, Analysis and Performance Prediction Technique for All-solid-state Electrode and Battery (3차원 전고체 전극 구조체 형성, 분석 및 성능 예측 기술 동향)

  • Park, Joonam;Jin, Dahee;Kim, Dohwan;Bae, Kyung Taek;Lee, Kang Taek;Lee, Yong Min
    • Journal of the Korean Electrochemical Society
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    • v.22 no.4
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    • pp.139-147
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    • 2019
  • Lithium-ion battery (LiB) with high energy density and efficiency has been utilized for the electric vehicle (EV) and energy storage system (ESS) as well as portable devices. However, as explosion accidents have frequently happened till lately, all-solid-state lithium secondary battery (ALSB) began to get in a spotlight because it can secure a very high safety and energy density by substituting flammable organic liquid electrolyte to nonflammable inorganic solid electrolyte. In spite of ALSB's certain merits, it has shown much poorer performance of cells than one of LiB due to some challenges, which have been small or never dealt with in the LiB system. Hence, although plenty of studies made progress to solve them, an approach about design of all-solid-state electrode (ASSE) has been limited on account of difficulty of ALSB's experiments. That is why the virtual 3D structure of an all-solid-state electrode has to be built and used for the prediction of cell performance. In this study, we elucidate how to form the 3D ASSE structure and what to be needed for the simulation of characteristics on ALSB. Furthermore, the ultimate orientation of 3D modeling and simulation for the study of ALSB are briefly suggested.

Development of deep learning network based low-quality image enhancement techniques for improving foreign object detection performance (이물 객체 탐지 성능 개선을 위한 딥러닝 네트워크 기반 저품질 영상 개선 기법 개발)

  • Ki-Yeol Eom;Byeong-Seok Min
    • Journal of Internet Computing and Services
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    • v.25 no.1
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    • pp.99-107
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    • 2024
  • Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.