• 한국정보전자통신기술학회논문지
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• 제14권6호
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• pp.452-460
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• 2021

전 세계적으로 전기차 시장이 확대됨에 따라 성능 및 안전성의 문제를 보완한 친환경적인 전기차가 계속 출시되고 시장이 더욱 커지고 있다. 하지만 전기차의 경우 충전의 불편함, 감전과 같은 안전 문제, 여러 전장부품들의 연동으로 인한 EMI(Electromagnetic interference) 문제는 전기차에서 해결해야 하는 문제이다. 무선전력전송 기술을 이용하면 전기차 충전에 대한 불편함 해소와 고전류, 고전압을 직접 다루지 않아 안전성의 문제를 해결할 수 있으나 EMI 저감을 위한 설계가 이루어지지 않는다면 오작동을 일으켜 더 큰 문제를 일으킬 수 있다. 본 논문은 전기차 무선전력전송 핵심 전장 부품인 무선충전컨트롤모듈에서 발생할 수 있는 EMI를 저감시키기 위한 전원무결성과 신호무결성을 갖는 전기차 무선전력전송 무선충전컨트롤모듈 EMI 저감 설계하였다. 전원부분에서 발생할 수 있는 공진, 임피던스 등의 문제와 신호 부분에서 발생할 수 있는 고속통신간의 신호왜곡의 문제를 시뮬레이션을 통해 EMI 저감 설계하였다.따라서 전원무결성과 신호무결성을 갖는 EMI 저감 설계를 통해 전기차 무선전력전송 무선충전컨트롤모듈 800 MHz ~ 1 GHz 대역과 1.5 GHz에서 각각 10 dBu V/m, 15 dBu V/m이 저감되는 것을 확인하였다.

• Journal of Power Electronics
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• 제16권4호
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• pp.1355-1366
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• 2016

In the present paper, a speed control algorithm with fast response characteristics is proposed to reduce the shift shock of medium/large-sized electric vehicles equipped with a two-speed AMT. Shift shocks, which are closely related with to the vehicles' ride comfort, occur due to the difference between the speed of the motor shaft and the load shaft when the gear is engaged. The proposed speed control method for shift shock reduction can quickly synchronize speeds occurring due to differences in the gear ratios during speed shifts in AMT systems by speed command feed-forward compensation and a state feedback controller. As a result, efficient shift results without any shift shock can be obtained. The proposed speed control method was applied to a 9 m- long medium- sized electric bus to demonstrate the validity through a simulated analysis and experiments.

• Journal of Electrical Engineering and Technology
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• 제13권2호
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• pp.580-590
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• 2018

Active distribution system (ADS) considering distributed generation (DG) and electric vehicle (EV) is an effective way to cut carbon emission and improve system benefits. ADS is an evolving, complex and uncertain system, thus comprehensive model and effective optimization algorithms are needed. Battery swapping station (BSS) for EV service is an essential type of flexible load (FL). This paper establishes ADS planning model considering BSS firstly for the minimization of total cost including feeder investment, operation and maintenance, net loss and carbon tax. Meanwhile, immune binary firefly algorithm (IBFA) is proposed to optimize ADS planning. Firefly algorithm (FA) is a novel intelligent algorithm with simple structure and good convergence. By involving biological immune system into FA, IBFA adjusts antibody population scale to increase diversity and global search capability. To validate proposed algorithm, IBFA is compared with particle swarm optimization (PSO) algorithm on IEEE 39-bus system. The results prove that IBFA performs better than PSO in global search and convergence in ADS planning.

• International Journal of Automotive Technology
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• 제4권2호
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• pp.87-94
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• 2003

Recent advancements of permanent magnet (PM) materials and solid-state devices have contributed to a substantial performance improvement of permanent magnet machines. Owing to the rare-earth PMs, these motors have higher efficiency, power factor, output power per mass and volume, and better dynamic performance than induction motors without sacrificing reliability. Not surprisingly, they are continuously receiving serious considerations for a variety of automotive and propulsion applications. An electric vehicle (EV) requires a high-effficient propulsion system having a wide operating range and a capability of generating a high peak torque for short durations. The improvement of torque-speed performance for these systems is consequently very important, and researches in various aspects are therefore being actively pursued. A great emphasis has been placed on the efficiency and optimal utilization of PM machines. This requires attention to many aspects related to the machine design and overall performance. In this respect, the prediction of iron losses is particularly indispensable and challenging, especially for drives with a deep field-weakening range. The objective of this paper is to present iron loss estimations of a PM motor over a wide speed range. As aforementioned, in EV applications core losses can be significant during high-speed operation and it is imperative to evaluate these losses accurately and take them into consideration during the motor design stage. In this investigation, the losses are predicted by using an analytical model and a 2D time-stepped finite element method (FEM). The results from different analytical approaches are compared with the FEM computations. The validity of each model is then evaluated by these comparisons.

• 무역학회지
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• 제46권2호
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• pp.193-212
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• 2021

This study investigates the structural relationship among 11 latent factors that potentially influence the intention of Chinese consumers to purchase electrical vehicles (EV) by applying the MGB and TAM models, both based on well-established socio-psychological theories. For this research, we conducted an online survey using a Chinese platform collecting 287 valid responses to our questionnaire. The analysis reveals that 10 out of the 12 hypotheses were adopted while 2 were rejected. Specifically, it was found that EC (environment concern) and PEV (perceived environment value) had a positive effect on the PEU (perceived environmental usefulness) of electric vehicles. In addition, ATT (attitude), PAE (positive anticipated emotion), and PBC (perceived behavior control) were confirmed to have a significant positive relationship with DES (desire) for EV purchase. At the same time, the results of the analysis show a statistically significant relationship between PEU, ATT as well as PI (purchase intention). This study further analyzed and presented the results of the moderating effects of gender, based on the adopted relationship hypotheses. This study is novel in that it is the first attempt in the literature to apply both the MGB model and the TAM simultaneously to predict EV purchasing behavior.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.27-30
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• 1992

In this paper, we report the research activities of the technical committee of Electric Vehicle (EV). Recently, environmental pollution has become a world-wide problem. As a practical step to solve this problem, it is sincerely hoped that EVs will become widely used. Here in, we wish to describe an Electric Vehicle research facility with the objectives of developing motor propulsion technology, energy storage technology, control system, battery charging systems, and etc.

• Journal of international Conference on Electrical Machines and Systems
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• 제1권1호
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• pp.114-120
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• 2012

Eco-driving technique for electric vehicles (EVs) is investigated in this paper. Many findings on EVs have been reported; however, they did not deal with eco-driving from the viewpoint of theoretical study. The authors have developed an energy-saving driving technique - the so-called "eco-driving" technique based on dynamic programming (DP). Optimal speed profile of an EV, which minimizes the amount of total energy consumption, was determined under fixed origin and destination, running time, and track conditions. DP algorithm can deal with such complicated conditions and can also derive the optimal solution. Using the proposed method, simulations were run for some cases. In particular, the author ran simulations for the case of a gradient road with a traffic signal. The optimization model was solved with MATLAB.

• 전력전자학회논문지
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• 제27권6호
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• pp.455-463
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• 2022

This study proposes a receiving pad identification coil for wireless charging of electric vehicles. The proposed coil identifies the shape of the receiving pad through magnetic coupling with the receiving pad. Therefore, the shape of the coil is designed to show the different magnetic properties of each receiving pad. The accuracy of this design is verified through finite element method simulation. Furthermore, the operation method of the secondary pad identification circuit is described, and the appropriate magnitude and length of the pulse voltage applied to this circuit for receiving pad identification are derived through simulation. The performance of the proposed identification coil set is verified by the experimental results.

• International journal of advanced smart convergence
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• 제13권2호
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• pp.25-34
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• 2024

The paper investigates how the semiconductor and electric vehicle industries are addressing safety and security concerns in the era of autonomous driving, emphasizing the prioritization of safety over security for market competitiveness. Collaboration between these sectors is deemed essential for maintaining competitiveness and value. The research suggests solutions such as advanced autonomous driving technologies and enhanced battery safety measures, with the integration of AI chips playing a pivotal role. However, challenges persist, including the limitations of big data and potential errors in semiconductor-related issues. Legacy automotive manufacturers are transitioning towards software-driven cars, leveraging artificial intelligence to mitigate risks associated with safety and security. Conflicting safety expectations and security concerns can lead to accidents, underscoring the continuous need for safety improvements. We analyzed the expansion of electric vehicles as a means to enhance safety within a framework of converging security concerns, with AI chips being instrumental in this process. Ultimately, the paper advocates for informed safety and security decisions to drive technological advancements in electric vehicles, ensuring significant strides in safety innovation.

• Korean Chemical Engineering Research
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• 제53권2호
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• pp.164-173
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• 2015

본 연구에서는 다양한 도로운송부문용 에너지 공급 시스템을 구축하고 각 시나리오의 최적 비용을 비교분석하였다. 에너지 공급 시스템의 구성요소로써 기존의 정유공정, 부생수소 시스템, 신재생 에너지 자원 기반의 전력 생산공정, 전력운송을 위한 전력망을 설정하였으며, 내연기관자동차, 전기자동차, 연료전지자동차 등 세 가지의 도로운송부문용 자동차를 포함하였다. 이러한 구성요소를 포함한 다양한 에너지 공급 시스템 시나리오를 기반으로 최적 생애주기비용을 규명할 수 있는 에너지 시스템 평가모델을 개발하였다. 본 연구에서 개발한 최적화 모델을 제주도 지역에 적용함으로써 모델의 성능을 검증하였고 또한 제주도 지역의 에너지 시스템 구축에 관한 다양한 시나리오의 경제성을 분석하였다. 제주도 도로운송부문용 에너지 공급 시스템의 생애주기비용 분석 결과, 전력망을 이용하여 전기를 공급하는 전기자동차 시나리오가 상대적으로 가장 높은 경제성을 보였으며, 신재생 에너지 자원을 이용하여 수소를 공급하는 연료전지자동차 시나리오가 가장 낮은 경제성을 보였다. 또한 연료비용, 차량비용, 인프라비용, 유지비용 등 주요 비용 관련 변수들에 관한 민감도분석을 수행함으로써 생애주기비용의 변화에 주요한 구성요소들을 규명하였다.