• 한국자동차공학회논문집
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• 제23권6호
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• pp.591-600
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• 2015

The efficiency of a powertrain system of hybrid vehicle is highly dependent on the design and control of the hybrid powertrain system. In other words, the optimal design of the powertrain systems is coupled with optimal control of the powertrain system. Therefore, the solution of an optimal design problem for hybrid vehicles is computationally and timely very expensive. For example, dynamic programming, which is a recursive optimization method, is usually used to evaluate the best fuel economy of certain hybrid vehicle design, and, thus, the evaluation takes tens of minutes to several hours. This research aims to accelerate the speed of efficiency evaluation of hybrid vehicles. We suggest a mathematical treat and a methodological treat to reduce the computational load. The mathematical treat is that the dynamics of system is discretized with sparse sampling time without loss of energy balance. The methodological treat is that the efficiency of the hybrid vehicle is inferred by characteristic loss evaluation that is computationally inexpensive. With the suggested methodology, evaluating a design candidate of hybrid powertrain system is taken few minutes, which was taken several hours when dynamic programming is used.

• 에너지공학
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• 제19권2호
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• pp.92-102
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• 2010

플러그인 하이브리드 전기자동차(Plug-in Hybrid Electric Vehicle, PHEV)는 하이브리드 전기자동차(Hybrid Electric Vehicle, HEV)의 일종으로, 배터리 용량을 HEV보다 더욱 증대시키고 배터리의 충전을 전력망으로부터 할 수 있도록 한 자동차이며, 순수 배터리 전기자동차(Plug-in Battery Electric Vehicle, PBEV)는 전력망으로부터 전기를 배터리에 충전하여 저장하고 배터리에 저장된 전기만을 이용하여 운전가능한 자동차이다. 최근에 PHEV와 PBEV에 대한 관심과 개발이 전세계적으로 급속하게 증가하고 있다. 그러므로 이들 전력망 충전식 전기자동차가 전력망의 전력수요에 미치는 영향을 검토하는 것이 중요하다. 본 논문에서는 이들 PHEV와 PBEV 자동차의 보급으로 전력망의 전력수요, 이산화탄소 배출량과 차량구매자의 관점에서 운전비용에 미치는 영향을 분석하였다. 2020년경에 차량보급이 10%정도로 이루어질 것을 가정하여 영향을 분석하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권10호
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• pp.3955-3971
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• 2020

Due to the significant increase in the use of autonomous car technology, it is essential to integrate this technology with high-precision digital map data containing more precise and accurate roadway information, as compared to existing conventional map resources, to ensure the safety of self-driving operations. While existing map technologies may assist vehicles in identifying their locations via Global Positioning System, it is however difficult to update the environmental changes of roadways in these maps. Roadway vision algorithms can be useful for building autonomous vehicles that can avoid accidents and detect real-time location changes. We incorporate a hybrid architectural design that combines unsupervised classification of vision data with supervised joint fusion classification to achieve a better noise-resistant algorithm. We identify, via a deep learning approach, an intelligent hybrid fusion algorithm for fusing multimodal vision feature data for roadway classifications and characterize its improvement in accuracy over unsupervised identifications using image processing and supervised vision classifiers. We analyzed over 93,000 vision frame data collected from a test vehicle in real roadways. The performance indicators of the proposed hybrid fusion algorithm are successfully evaluated for the generation of roadway digital maps for autonomous vehicles, with a recall of 0.94, precision of 0.96, and accuracy of 0.92.

• Journal of Communications and Networks
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• 제14권6호
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• pp.672-681
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• 2012

A potential breakthrough of the electrification of the vehicle fleet will incur a steep rise in the load on the electrical power grid. To avoid huge grid investments, coordinated charging of those vehicles is a must. In this paper, we assess algorithms to schedule charging of plug-in (hybrid) electric vehicles as to minimize the additional peak load they might cause. We first introduce two approaches, one based on a classical optimization approach using quadratic programming, and a second one, market based coordination, which is a multi-agent system that uses bidding on a virtual market to reach an equilibrium price that matches demand and supply. We benchmark these two methods against each other, as well as to a baseline scenario of uncontrolled charging. Our simulation results covering a residential area with 63 households show that controlled charging reduces peak load, load variability, and deviations from the nominal grid voltage.

• 한국전자통신학회논문지
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• 제9권1호
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• pp.91-96
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• 2014

최근 양산되고 있는 하이브리드 전기자동차에 비해서 연비를 좀 더 개선하기 위한 플러그인 하이브리드 전기자동차(Plug-in Hybrid Electric Vehicle)에 대한 연구가 활발히 진행되고 있다. 이 논문에서는 플러그인 하이브리드 전기자동차를 위한 고효율의 탑재형 충전기(on-board charger)에 대해서 연구한다. 탑재형 충전기는 2상 인터리브드 PFC 회로와 LLC 공진형 컨버터로 구성된다. LLC 공진형 컨버터의 새로운 설계절차를 본 논문에서 제안한다. 이는 매우 쉽고 강력한 방법이다. 위에서 언급한 내용을 확인하기 위해서 LLC 공진형 컨버터를 설계하고 PSIM 툴을 이용하여 테스트한다.

• 전력전자학회논문지
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• 제22권1호
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• pp.75-81
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• 2017

This paper presents a design and parallel control strategy of 1.8 kW low-voltage DC-DC converter (LDC) for mild hybrid electric vehicles to improve their power density, system efficiency, and operation stability. Topology and control scheme are important on the LDC for mild hybrid electric vehicles to achieve high system efficiency and power density because of their very low voltage and large current in input and output terminals. Therefore, the optimal topological structure and control algorithm are examined, and a detailed design methodology for the power and control stages is presented. A working sample of 1.8 kW LDC is designed and implemented by applying the adopted topology and control strategy. Experimental results indicate 92.45% of the maximum efficiency and 560 W/l of power density.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2006년도 추계학술대회
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• pp.97-100
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• 2006

Accelerating ability is one of the most important performance of the vehicle. Unlike conventional internal combustion vehicles and power-assist hybrid vehicles, the maximized acceleration of dual mode hybrid vehicles is not simply. achieved by maximizing engine or motor torque Because of the dynamic stability of planetary gear, speeds and torques control of engine, motor 1 and motor 2 is essential and according to control value, acceleration performance is changed There are two control values which are velocity and torque for each component totalling six. These six values can be variables for an objective function. However, because three velocity variables can be regarded as only one variable speed ratio and the remaining three torque variables can be solved analytically, without complicated numerical algorithm the solution for the objective function can be obtained. This optimized solution shows the best performance possible to the specified dual mode system.

• International Journal of Automotive Technology
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• 제8권6호
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• pp.781-790
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• 2007

Hybrid electric vehicles(HEV) combined with more than one power sources have great potential to improve fuel economy and reduce pollutant emissions. The Integrated Starter Generator(ISG) HEV researched in this paper is a two energy sources vehicle, with a conventional internal combustion engine(ICE) and an energy storage system(batteries). In order to investigate the potential of diesel engine hybrid electric vehicles in fuel economy improvement and emissions reduction, a Dynamic Programming(DP) based supervisory controller is developed to allocate the power requirement between ICE and batteries with the objective of minimizing a weighted cost function over given drive cycles. A fuel-economy-only case and a fuel & emissions case can be achieved by changing specific weighting factors. The simulation results of the fuel-economy-only case show that there is a 45.1% fuel saving potential for this ISG HEV compared to a conventional transit bus. The test results present a 39.6% improvement in fuel economy which validates the simulation results. Compared to the fuel-economy-only case, the fuel & emissions case further reduces the pollutant emissions at a cost of 3.2% and 4.5% of fuel consumption with respect to the simulation and test result respectively.

• International Journal of Automotive Technology
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• 제8권5호
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• pp.651-658
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• 2007

This paper presents a new type of fuzzy logic-based power control strategy for fuel cell hybrid electric vehicles designed to improve their fuel economy while maintaining the battery's state of charge. Since fuel cell systems have inherent limitations, such as a slow response time and low fuel efficiency, especially in the low power region, a battery system is typically used to assist them. To maximize the advantages of this hybrid type of configuration, a power distribution control strategy is required for the two power sources: the fuel cell system and the battery system. The required fuel cell power is procured using fuzzy rules based on the vehicle driving status and the battery status. In order to show the validity and effectiveness of the proposed power control strategy, simulations are performed using a mid-size vehicle for three types of standard drive cycle. First, the fuzzy logic-based power control strategy is shown to improves the fuel economy compared with the static power control strategy. Second, the robustness of the proposed power control strategy is verified against several variations in system parameters.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2006년도 춘계학술대회
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• pp.539-542
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• 2006

Many researches about next generation vehicles are trending toward HEV which has better fuel economy than an internal-combustion engine. But existing HEV has some defects at specific running states(eg. highway running It is possible that dual-mode hybrid system overcomes that defects. Mode change parameter, ${\gamma}$ helps to analyse the mode changing of dual mode hybrid and is applied at a numerical analysis on testing the performance. There is an additional constraint when vehicles drive on engine mode. No power assistance of battery applies on engine mode. Because vehicles must be sustained by only engine power while vehicle drives on constant speed mode. At the conclusion of this paper, graphs show the ability of motors that satisfy the equilibrium of the lever system. Designers can roughly determine capacities of the motors, parameters of the lever system by this analysing method.