• Korea Trade Review
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• v.46 no.2
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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.

• Proceedings of the KIEE Conference
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• 1992.07a
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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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• v.1 no.1
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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.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.6
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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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• v.13 no.2
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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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• v.53 no.2
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• pp.164-173
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• 2015

This study aims to design energy supply systems from various energy sources for transportation sectors and comparatively analyze the life cycle cost of different scenario-based systems. For components of the proposed energy supply system, we consider a typical oil refinery, byproduct hydrogen system, renewable energy source (RES)-based electric generation system and existing electricity grid. We also include three types of vehicles in transportation sector such as internal combustion engine vehicle (ICEV), electric vehicle (EV), fuel cell vehicle (FCV). We then develop various energy supply scenarios which consist of such components and evaluate the economic performance of different systems from the viewpoint of life cycle cost. Finally we illustrate the applicability of the proposed framework by conducting the design problem of energy supply systems of Jeju, Korea. As the results of life cycle cost analysis, EV fueled by electricity from grid is the most economically feasible. In addition, we identify key parameters to contribute the total life cycle cost such as fuel cost, vehicle cost, infra cost and maintenance cost using sensitivity analysis.

• Transactions of the Korean hydrogen and new energy society
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• v.28 no.6
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• pp.642-648
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• 2017

The use of fossil is causing enviromental all over the world. So hydrogen energy is attracting attention as one of the alternative. The government announced that 30% of the air pollution is because of the Internal Combustion Engine Vehicle. In addition, they plans to reduce Internal Combustion Engine Vehicles by 2030 and increase (electric vehicles, EV) or (fuel cell vehicle, FCV). The FCV is evaluated as a next-generation green car because it has a long driving distance and short charging time. However, the hydrogen industry is not able to expand due to the lack of refueling infrastrucutre. This paper predicts the site of hydrogen refueling stations for the expansion of the hydrogen industry and proposes a method to supply hydrogen multi energy filling stations.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.114-117
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• 2001

In the Electric Vehicle(EV) driving system, the Battery Management System(BMS) is very important and an essential equipment. Particularly, BMS monitors the State of Charge(SOC), voltage, current, and temperature of the battery modules when Electric Vehicle is in the state of motoring or charging. Major roles of BMS are like these the first, estimation of State of Charge(SOC), the second, detection of the unbalance of the voltage between battery modules, the third, control of the available limit of the voltage and temperature of batteries by monitoring the batteries status during motoring or charging. In this research, We have focused on estimating SOC of battery according to the status of Electric Vehicle and the BMS operation algorithm. The result for algorithm of SOC estimation is presented. It have been modified, compensated, and verified by means of the experiment.

• Journal of the Korean Society for Railway
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• v.17 no.2
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• pp.94-99
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• 2014

Recently, trends in new transportation system development have been primarily focused on sustainable and ecofriendly mobility solutions. The personal rapid transit (PRT) system has been considered a promising candidate in this category; its competitiveness is being improved through convergence with cutting-edge electric vehicle (EV) technologies. However, battery-powered vehicles pose difficult technical challenges in attempts to achieve reliable and efficient operation. In this study, a design approach for a solar-power assisted PRT system is presented with small-scale demonstrations aimed at circumventing challenges facing its adoption, as well as helping speed the transition to electric-powered ground transportation. From the results, it is expected that flexible photovoltaic (PV) cells will be able to supply 11% of the power required by the service equipment installed in a prototype vehicle. In particular, flexible photovoltaic (PV) cells are advantageous in terms of cost, weight, and design considerations. Most importantly, the cells' flexibility and attach-ability are expected to give them great potential for extended application in various areas.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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• pp.179-185
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• 2014

Average temperature and temperature uniformity in a battery cell are the important criteria of the thermal management of the battery pack for hybrid electric vehicles and electric vehicles (HEVs and EVs) because high power with large size cell is used for the battery pack. Thus, liquid cooling system is generally applied for the HEV/EV battery pack. The liquid cooling system is made of multiple cooling plates with coolant flow paths. The cooling plates are inserted between the battery cells to reject the heat from batteries to coolant. In this study, the cooling plate with U-shaped coolant flow paths is considered to evaluate the effects of coolant flow condition on the cooling performance of the system. The counter flow and parallel flow set up is compared and the effect of flow rate is evaluated using CFD tool (FLUENT). The number of counter-flows and flow rate are changed and the effect on the cooling performance including average temperature, differential temperature, and standard deviation of temperature are investigated. The results show that the parallel flow has better cooling performance compared with counter flow and it is also found that the coolant flow rate should be chosen with the consideration of trade-off between the cooling performance and pressure drop.