• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.6
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• pp.467-473
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• 2001

BMS(Battery Management System) in EV system(Electric Vehicle) senses voltage, temperature and the charging or discharging current of batteries. The main roles of BMS are to estimate SOC(State OF Charge) of batteries and optimally monitor them according to the operation state of EV system which is motoring mode or charging mode. In this paper, we propose the proper algorithm about BMS's roles and operation which is suitable to EV system and illustrate validity and effectiveness through the experiments which were performed in the condition of Vehicle road test and charging test.

• International journal of advanced smart convergence
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• v.11 no.3
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• pp.206-214
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• 2022

Automobile manufacturers in each country are spurring the development of electric vehicles that use electric energy, an eco-friendly energy, as a futuristic vehicle. Electric vehicles have the advantage of no harmful gas or environmental pollution and low noise. Unlike automobiles using existing internal combustion engines using fossil fuels, electric vehicles use the electricity of batteries to cause rotational motion of motors. In the electric vehicle driven by the motor, it is indispensable to develop a controller for controlling the motor. One of the areas where automobile manufacturers are concentrating is the development of small electric vehicles as a personal transportation means. Small electric vehicles such as electric motorcycles, one-seat electric vehicles and two-seat electric vehicles are expanding the market as a means of operating throughout the city. In the domestic road conditions with many hills, it is effective to have a separate transmission system for small electric vehicles to drive smoothly. In this study, we propose a new type of continuously variable transmission(CVT) system to ensure that small electric vehicles can be driven smoothly in hilly domestic terrain. The proposed CVT system is equipped with a basic disk and a rotational disk in the driving pulley and the driven pulley, respectively, and is applied with a sloping spline to rotate the rotational disk. To commercialize the proposed CVT system, an experimental device was developed to examine the power transmission efficiency and the configuration of the CVT system was proposed.

• Journal of Institute of Convergence Technology
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• v.11 no.1
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• pp.19-23
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• 2021

These days, sales of battery electric vehicles have been rapidly increasing due to the strict CO₂ regulations. However, since it take too long to measure the energy economy of electric vehicles, it has been required to improve the procedure of energy economy measurement. In order to improve this problem, the present study analyzed the battery charge/discharge pattern according to the changes in battery SOC (state of charge). In general, the energy economy test is started with a battery SOC charged to 100 %. However, it was identified that when the battery is fully charged, it can actually be charged over the 100 % (e.g., 100.5 %). This can induce errors in the energy economy measurement. Therefore, the present study recommend to start the test at SOC 99.9 %. The regenerative braking was partly restricted for the SOC over 90 %. This made it difficult to estimate the overall energy economy of the electric vehicle. However, it was identified that there was no change in the battery charge/discharge characteristics under the SOC 90 %. Therefore, the energy economy test can be shortened by predicting the overall energy economy through a short mileage test.

• Journal of Power Electronics
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• v.14 no.5
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• pp.1038-1046
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• 2014

Lithium-ion batteries are widely used in hybrid and pure electric vehicles. State-of-charge (SOC) estimation is a fundamental issue in vehicle power train control and battery management systems. This study proposes a novel model-based SOC estimation method that applies closed-loop state observer theory and a comprehensive battery model. The state-space model of lithium-ion battery is developed based on a three-order resistor-capacitor equivalent circuit model. The least square algorithm is used to identify model parameters. A multi-state closed-loop state observer is designed to predict the open-circuit voltage (OCV) of a battery based on the battery state-space model. Battery SOC can then be estimated based on the corresponding relationship between battery OCV and SOC. Finally, practical driving tests that use two types of typical driving cycle are performed to verify the proposed SOC estimation method. Test results prove that the proposed estimation method is reasonably accurate and exhibits accuracy in estimating SOC within 2% under different driving cycles.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.307-311
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• 2004

In this study, a novel hybrid vehicle is proposed. The vehicle has a flywheel-engine hybrid system. Flywheels are more effective as energy charge systems than electric batteries in a respect of output power density. However, transmissions to effectively drive flywheels are very complex systems such as CVTs (Continuously Variable Transmissions). In the proposed hybrid vehicle, Constant Pressure System is employed, which is hydraulic power transmission. Using Constant Pressure Systems, hydraulic CVTs are easily realized with variable displacement pumps/motors. In this paper, firstly, the proposed flywheel hybrid vehicle making use of Constant Pressure System is described. Secondly, fuel consumption characteristics of the flywheel hybrid vehicle are experimentally examined with the stationary test facility, which employs a flywheel as a load emulating vehicle inertia. Finally, the experimental results and discussions are described. Fuel consumption of 26km/L is expected for 10 mode driving schedule with vehicle mass of 1500kg.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.385-391
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• 2023

As the use of electric vehicles has increased to minimize carbon emissions, the analyzing the state and performance of lithium-ion batteries that is instrumental in electric vehicles have been important. Comprehensive analysis using not only the voltage, current and temperature of the battery pack, which can affect the condition and performance of the battery, but also the driving data and charging pattern data of the electric vehicle is required. Therefore, a thorough analysis is imperative, utilizing electric vehicle operation data, charging pattern data, as well as battery pack voltage, current, and temperature data, which collectively influence the condition and performance of the battery. Therefore, collection and preprocessing of battery data collected from electric vehicles, collection and preprocessing of data on driver driving habits in addition to simple battery data, detailed design and modification of artificial intelligence algorithm based on the analyzed influencing factors, and A battery analysis and evaluation model was designed. In this paper, we gathered operational data and battery data from real-time electric buses. These data sets were then utilized to train a Random Forest algorithm. Furthermore, a comprehensive assessment of battery status, operation, and charging patterns was conducted using the explainable Artificial Intelligence (XAI) algorithm. The study identified crucial influencing factors on battery status, including rapid acceleration, rapid deceleration, sudden stops in driving patterns, the number of drives per day in the charging and discharging pattern, daily accumulated Depth of Discharge (DOD), cell voltage differences during discharge, maximum cell temperature, and minimum cell temperature. These factors were confirmed to significantly impact the battery condition. Based on the identified influencing factors, a battery analysis and evaluation model was designed and assessed using the Random Forest algorithm. The results contribute to the understanding of battery health and lay the foundation for effective battery management in electric vehicles.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.168-169
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• 2022

As the electric vehicle market has grown rapidly, the battery market has grown exponentially. Due to the gap between the generation speed of quality control technology and battery mass production speed for batteries mounted on electric vehicles, many durability problems have arisen for batteries. Most accidents are caused by electrical factors, but there is no technology to quickly inspect them. In this paper, we are going to propose a quick analysis of battery cell defects using the GAN model.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.5
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• pp.138-144
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• 2012

Recent environmental issues such as exhaust gas and greenhouse effect make the agricultural machinery market takes into account the hybrid and electric propulsion technology used in automotive engineering. Generally the agricultural machinery, particularly an agricultural tractor, needs large load capacity and long continuous operating time comparing with conventional vehicles. In case of a pure electric tractor, it is necessary for considering large capacity batteries and long charging time. Therefore we take an AER extended PHEV (All Electric Range extended Plug-in Hybrid Electric Vehicle) power transmission system in developing an electric tractor in this study. First we propose a PHEV powertrain structure in order to substitute the conventional diesel engine equipped tractor. And we performed the road tests using a conventional mechanical tractor with various load conditions, which were classified and statistically treated real agricultural works. The test results were analysed with respect to the power characteristics of the power source. Finally using the test result, we designed two-stepped reduction gear ratios in the proposed an electric tractor powertrain for carrying out typical agricultural works.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.292-294
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• 2011

전기자동차에 대한 연구가 진행됨에 따라 동력원으로 사용되는 대용량 리튬-폴리머 배터리의 운용과 관리에 대한 관심이 증가하고 있다. 다중 셀로 구성된 대용량 리튬-폴리머 배터리는 물리적 화학적 특성에 따라 충전시 셀간 전압 격차가 발생하게 된다. 셀간 전압차는 배터리 용량, 수명, 안정성에 부정적 영향을 주게 된다. 기존 연구들은 각 셀의 특성을 고려하지 않고 충전 결과를 바탕으로 동일한 밸런싱 방법을 적용시킴으로 효율성을 떨어트린다. 본 논문에서는 진화 신경망 기반의 지능형 셀 밸런싱 시스템을 제안한다. 배터리의 특성을 진화 신경망을 통해 학습시킴으로 각 셀 충전시 저항의 크기를 결정한다. 이를 통해 각 셀 특성을 고려한 사전 셀 밸런싱을 수행하였다. 제안하는 방법의 유용성을 입증하기 위해 카이스트 온라인 전기자동차에 장착 예정인 배터리 관리 시스템 기반 시뮬레이션을 수행하여 효과적인 셀 밸런싱이 가능함을 보였다.

• Proceedings of the KIEE Conference
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• 1999.11d
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• pp.968-970
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• 1999

The trend of increasing of portable electric devices and demand for global environmental conservation have demands the development of high energy density rechargeable batteries. Lithium polymer battery has excellent theoretical energy density and energy conversion efficiency. Lithium polymer battery, included solid polymer electrolyte(SPE), can be viewed as a system suitable for wide applications from thin film batteries for microelectronics to electric vehicle batteries. The purpose of this paper is to research and development of flyash anode for lithium polymer battery. We investigated AC impedance response and charge/discharge characteristics of flyash/SPE/Li cells. The radius of semicircle associated with the interfacial resistance of flyash/SPE/Li cell increased very slowly during discharge process from 3.11V to 0.478V. And then the cell resistance was decreased at discharge process from 10% SOC to 0% SOC. Also, The radius of semicircle associated with the interfacial resistance of flyash/SPE/Li cell decreasing very slowly during charge process. And then the cell resistance was increased after 20th discharge precess. The discharge capacity based on flyash of 1st and 20th cycles was 276mAh/g and 143mAh/g.