• 한국기계가공학회지
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• 제18권7호
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• pp.29-35
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• 2019

In this paper, the component loss models of the electric vehicle(EV) and the internal combustion engine vehicle(ICEV) are developed to analyze the losses and efficiencies of these two types of vehicles. The EV powertrain efficiency decreases as the vehicle velocity increases over most of the vehicle velocity range because the battery efficiency decreases. Especially, the EV powertrain efficiency decreases significantly when the battery SOC is low. But the ICEV powertrain efficiency increases as the vehicle velocity increases. This is because the efficiencies of both the transmission and engine increases.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.866-867
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• 2011

As part of the green growth, The Green Car has attracted wide attention. Types of the Green Car are Electric Vehicle, Plug-in Hybrid Electric Vehicle, Hybrid Electric Vehicle, Fuel Cell Vehicle and Clean Diesel Vehicle. Of these, The electric vehicle is equipped with the BDU(Battery Disconnecting Unit). BDU is supplying stable battery power and blocking it to protect electrical system of the electric vehicle. The BDU consists of electric components such as current sensor, fuse and pre-charge resistor. These must pass Voltage withstand test, Salt mist test, Thermal shock test, Vibration test and Short-circuit test commonly to verify reliability of the electric components. In addition, The current sensor should be verified whether normal operation. The breaking capacity of fuse should be verified. The durability of pre-charge resistor should be verified by supplying battery power and blocking it repeatedly. The reliability of BDU as well as the electric vehicle is secured by verifying the reliability of electric components. In addition, It will contribute to the acceleration and promotion of Green Car Technology.

• 한국멀티미디어학회논문지
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• 제24권9호
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• pp.1203-1210
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• 2021

In this paper, we developed the inspection system of electric vehicle pouch battery using image processing. Line scan cameras are used for acquiring the all parts of the pouch battery, and several steps of image processing for extracting significant dimensions(User Required Position) of the battery. In image processing, edge lines, node points, dimension lines, etc. were extracted using Preprocessor, Square Edge Detection, and Size Detection algorithms. This is used to measure the dimensions of the location requested by the user on the pouch battery. For verification of the inspection system, the dimensions of three pouch batteries produced in the same process were measured, and the mean and standard deviation were obtained to confirm the precision.

• Journal of Electrical Engineering and Technology
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• 제8권6호
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• pp.1431-1438
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• 2013

A pack-level battery hardware-in-the-loop simulation (B-HILS) platform is implemented. It consists of dynamic vehicle models using PSAT and multiple control interfaces including real-time 3D driving and GPS mode. In real-time 3D driving mode, user can drive a virtual vehicle using actual drive equipment such as steering wheel and accelerator to generate the cycle profile of the battery. In GPS mode, actual road traffic and terrain effects can be simulated using GPS data while the trajectory is displayed on Google map. In the latter part of the paper, several performance tests of an actual lithium-polymer battery pack are carried out utilizing the developed system. All experiments are conducted as parts of actual development process of a commercial battery pack adopting 2nd generation Prius as a target vehicle model. Through the experiments, the low temperature performance and fuel efficiency of the battery are quantitatively investigated in comparison with the original nickel-metal hydride (NiMH) pack of the Prius.

• 전력전자학회논문지
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• 제9권4호
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• pp.319-325
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• 2004

무공해 자동차를 만들기 위해 중요한 요소로서는 주행거리와 알맞은 가격이다. 니켈-수소 배터리와 같은 향상된 배터리의 개발은 부분적으로 문제를 해결할 수 있으며, 또 하나의 효과적인 방법은 배터리 관리 시스템이나. 니켈-수소 배터리와 배터리 ECU는 주행거리, 가속도, 등판능력과 같은 무공해 자동차의 성능에 영향을 미치는 중요한 구성품이다. 예컨대 운행 중 쉽게 발생하는 단락, 과방전, 과충전은 배터리와 관계되는 가장 큰 문제점이기 때문에 전용의 HEV용 배터리 ECU의 개발은 필수적이다. 본 논문에서는 배터리 전류적산 및 전압에 기초한 HEV용 SOC 알고리즘을 제안하고 배터리 ECU를 설계 및 해석하였으며, 시험을 통해 타당성을 검증하였다.

• Journal of Platform Technology
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• 제11권2호
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• pp.54-65
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• 2023

전기자동차에 사용되는 배터리는 전기자동차의 특성상 정격용량이 매우 커다란 배터리이다. 전기자동차를 장기간 운행하거나 교통사고로 전기자동차가 폐차되게 되면 전기자동차용 배터리는 폐배터리가 된다. 폐차되는 차량이더라도 전기자동차용 폐배터리에 남아 있는 용량은 다른 용도로 사용하기에 충분하다. 자동차용 폐배터리는 매우 고가이기때문에 재활용 및 재사용이 필요하지만 재활용 및 재사용을 위한 폐배터리 성능등급 측정기준이 부족한 문제가 있었다. 폐배터리의 잔존용량을 측정하는 방법으로 가장 안정적이고 신뢰할 수 있는 방법은 완전 충·방전을 이용하여 배터리의 잔존용량을 측정하는 것이다. 하지만 이러한 완전 충·방전에 방식에 의한 검사 방법은 배터리의 용량에 따라 다르지만 검사하는데 하루 이상이 걸리는 단점을 가지고 있으며 많은 사람들이 이러한 문제를 해결하기 위하여 많은 노력을 하고 있다. 본 논문에서는 전기자동차 배터리에 대한 검사 시간을 줄일 수 있는 방법으로 셀간 전압 편차를 활용한 전기자동차 배터리 잔존용량 분석 기법을 연구 분석하였다. 이를 위하여 완전 충·방전 기반의 용량 측정시스템을 구성하고 코나 폐배터리를 이용하여 실험데이터를 수집하였고 배터리 팩을 구성하고 있는 배터리 셀간 전압 편차와 잔존용량과의 상관관계를 분석하여 배터리 검사에 활용할 수 있는지를 검증하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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• pp.669-671
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• 2000

Vehicle electric power system, which consists of two major components; an alternator and a battery, supplies electric power to vehicle electric and electronic systems. In recent years, bigger power supply is required for the rapid demand of the number of vehicle electric and electronic systems. It is important that vehicle power system should be analyzed exactly. For the simulation of vehicle electric power system, appropriate component model of vehicle electric power system should be chosen. In this paper, a simplified and accurate battery model is developed to obtain the battery parameters, and a Variable Alternator Terminal Voltage Model is introduced to described an alternator. The case study shows that simulation results using the suggested models are well agreed with the experiments.

• Journal of Electrical Engineering and Technology
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• 제13권2호
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• pp.742-751
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• 2018

Electric vehicles (EV) are emerging as the future transportation vehicle reflecting their potential safe environmental advantages. Vehicle to Grid (V2G) system describes the hybrid system in which the EV can communicate with the utility grid and the energy flows with insignificant effect between the utility grid and the EV. The paper presents an optimal power control and energy management strategy for Plug-In Electric Vehicle (PEV) charging stations using Wind-PV-FC-Battery renewable energy sources. The energy management optimization is structured and solved using Multi-Objective Particle Swarm Optimization (MOPSO) to determine and distribute at each time step the charging power among all accessible vehicles. The Model-Based Predictive (MPC) control strategy is used to plan PEV charging energy to increase the utilization of the wind, the FC and solar energy, decrease power taken from the power grid, and fulfil the charging power requirement of all vehicles. Desired features for EV battery chargers such as the near unity power factor with negligible harmonics for the ac source, well-regulated charging current for the battery, maximum output power, high efficiency, and high reliability are fully confirmed by the proposed solution.

• Journal of Electrical Engineering and Technology
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• 제8권4호
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• pp.920-929
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• 2013

Within the project 'e performance' supported by the German Ministry of Education and Research (BMBF) an electric vehicle, powered by two lithium-ion battery packs of different capacity and voltage has been developed. The required Energy Management System (EMS) in this system controls the current flows of both packs independently by means of two individual dc-dc converters. It acts as an intermediary between energy storage (battery management systems-BMS) and the drivetrain controller on the vehicle control unit (VCU) as well as the on-board charger. This paper describes the most important tasks of the EMS and its interfaces to the BMS and the VCU. To validate the algorithms before integrating them into the vehicle prototype, a detailed Matlab / Simulink-model was created in the project. Test procedures and results from the simulation as well as experiences and comparisons from the real car are presented at the end.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.560-562
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• 1998

A new approach to developing battery SOC indicator for electric vehicle is discussed in this paper. One of the most difficult problems associated with the development of electric vehicle is the battery indicator which reliably informs the state of charge(SOC) of the battery to the driver. And the condition to be satisfied with SOC indicator installed on the electric vehicle is that it should be used under frequently variable load. A new method to determining SOC using neural networks(NN) is proposed to satify the condition. The training data of NN are obtained by using mathematical model of lead-acid battery, and calculating discharge currents and terminal voltages while battery discharges with constant current. The 3-layered NN with back propagation algorithm is used Simulation results show that the proposed method is appropriate as SOC indicator of the battery.