• Title/Summary/Keyword: EV driving data

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Development of Urban Driving Cycle for Performance Evaluation of Electric Vehicles Part II: Verification of Driving Cycle (전기자동차 성능평가를 위한 도심 주행 모드 개발 Part II: 주행 모드 검증)

  • Jeong, Nak-Tak;Yang, Seong-Mo;Kim, Kwang-Seup;Choi, Su-Bin;Wang, Maosen;You, Sehoon;Kim, Hyunsoo;Suh, Myung-Won
    • Transactions of the Korean Society of Automotive Engineers
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    • v.23 no.2
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    • pp.161-168
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    • 2015
  • Recently, due to various environmental problems such as global warming, increases of international oil prices, exhaustion of resource, a paradigm of world automobile market is rapidly changing from conventional vehicles using internal combustion engine to eco-friendly vehicles using electric power such as EV, HEV, PHEV and FCEV. Generally, in order to measure fuel consumption and pollutant emissions of cars, chassis dynamometer tests are performed on various driving cycles before actual driving test. There are many driving cycles for performance evaluation of conventional vehicles. However, there is a lack of researches on driving cycle for EV. In this study, the urban driving cycle for performance evaluation of electric vehicles was developed. This study is composed of two parts. In the part 1, the urban driving cycle 'GUDC-EV(Gwacheon-city Urban Driving Cycle for Electric Vehicles)' was developed by using driving data, which were obtained through actual driving experiment, and statistic analysis with chronological table. In this paper part 2, in order to verify the developed driving cycle GUDC-EV, virtual EV platforms were configured and simulations were performed with actual driving data using In addition, simulation results were compared with existing driving cycles such as FTP-72, NEDC and Japan 10-15.

EV Battery State Estimation using Real-time Driving Data from Various Routes (전기차 주행 데이터에 의한 경로별 배터리 상태 추정)

  • Yang, Seungmoo;Kim, Dong-Wan;Kim, Eel-Hwan
    • The Transactions of the Korean Institute of Power Electronics
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    • v.24 no.3
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    • pp.139-146
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    • 2019
  • As the number of electric vehicles (EVs) in Jejudo Island increases, the secondary use of EV batteries is becoming increasingly mandatory not only in reducing greenhouse gas emissions but also in promoting resource conservation. For the secondary use of EV batteries, their capacity and performance at the end of automotive service should be evaluated properly. In this study, the battery state information from the on-board diagnostics or OBD2 port was acquired in real time while driving three distinct routes in Jejudo Island, and then the battery operating characteristics were assessed with the driving routes. The route with higher altitude led to higher current output, i.e., higher C-rate, which would reportedly deteriorate state of health (SOH) faster. In addition, the SOH obtained from the battery management system (BMS) of a 2017 Kia Soul EV with a mileage of 55,000 km was 100.2%, which was unexpectedly high. This finding was confirmed by the SOH estimation based on the ratio of the current integral to the change in state of charge. The SOH larger than 100% can be attributed to the rated capacity that was lower than the nominal capacity in EV application. Therefore, considering the driving environment and understanding the SOH estimation process will be beneficial and necessary in evaluating the capacity and performance of retired batteries for post-vehicle applications.

Development of Urban Driving Cycle for Performance Evaluation of Electric Vehicles Part I : Development of Driving Cycle (전기 자동차 성능 평가를 위한 도심 주행 모드 개발 Part I : 주행 모드 개발)

  • Yang, Seong-Mo;Jeong, Nak-Tak;Kim, Kwang-Seup;Choi, Su-Bin;Wang, Maosen;Kim, Hyun-Soo;Suh, Myung-Won
    • Transactions of the Korean Society of Automotive Engineers
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    • v.22 no.7
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    • pp.117-126
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    • 2014
  • Recently, due to various environmental problems such as global warming, increasing of international oil prices and exhaustion of resource, a paradigm of world automobile market is rapidly changing from vehicles using internal combustion engine to eco-friendly vehicles using electric power such as EV (Electric Vehicle), HEV (Hybrid Electric Vehicle), PHEV (Plug-in Hybrid electric Vehicle) and FCEV (Fuel Cell Electric Vehicle). There are many driving cycles for performance evaluation of conventional vehicles. However there is a lack of researches on driving cycle for EV. This study is composed of part 1 and part 2. In this paper part 1, in order to develop urban driving cycle for performance evaluation of electric vehicles, Gwacheon-city patrol route of police patrol car was selected. Actual driving test was performed using EV. The driving data such as velocity, time, GPS information etc. were recorded. GUDC-EV (Gwacheon-city Urban Driving Cycle for Electric Vehicles) including road gradient was developed through the results of analyzing recorded data. Reliability of the driving cycle development method was substantiated through comparison of electricity performance. In the second part of this study, the developed driving cycle was compared to simulation result of the existing urban driving cycle. Verification of the developed driving cycle for EV performance evaluation was described.

EV battery's real-time driving data acquisition and comparison by route (전기차 배터리의 실시간 주행 데이터 취득과 주행경로별 비교)

  • Yang, Seungmoo;Kim, Eel-Hwan
    • Proceedings of the KIPE Conference
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    • 2018.07a
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    • pp.489-490
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    • 2018
  • As the number of electric vehicles (EV) increases, there is an increasing interest in the post-vehicle application of the EV batteries. For the second use application of EV batteries, the state of health (SOH) at the end of automotive service has to be evaluated differently from the automotive perspective. It will be helpful to consider the driving conditions of EVs in understanding the performance deterioration trend of the battery. In this paper, we acquired the battery status information in real time during driving and compared the characteristics by the driving routes. The SOH from the BMS can be rescaled to percentage ratio to give a more general idea about the performance degradation.

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The smart EV charging system based on the big data analysis of the power consumption patterns

  • Kang, Hun-Cheol;Kang, Ki-Beom;Ahn, Hyun-kwon;Lee, Seong-Hyun;Ahn, Tae-Hyo;Jwa, Jeong-Woo
    • International Journal of Internet, Broadcasting and Communication
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    • v.9 no.2
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    • pp.1-10
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    • 2017
  • The high costs of electric vehicle supply equipment (EVSE) and installation are currently a stumbling block to the proliferation of electric vehicles (EVs). The cost-effective solutions are needed to support the expansion of charging infrastructure. In this paper, we develope EV charging system based on the big data analysis of the power consumption patterns. The developed EV charging system is consisted of the smart EV outlet, gateways, powergates, the big data management system, and mobile applications. The smart EV outlet is designed to low costs of equipment and installation by replacing the existing 220V outlet. We can connect the smart EV outlet to household appliances. Z-wave technology is used in the smart EV outlet to provide the EV power usage to users using Apps. The smart EV outlet provides 220V EV charging and therefore, we can restore vehicle driving range during overnight and work hours.

Mechanical Assessments Development of Through The EV-Relay's Impurse Prediciton (EV Relay의 충격량 예측을 통한 기계적 시험법 개발)

  • Kim, Eung-Nam;Park, Guk-Nam;Ryu, Hang-Su;Park, Hong-Tae
    • Proceedings of the KIEE Conference
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    • 2011.07a
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    • pp.868-869
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    • 2011
  • Domestic Foreign automaker's are focused on the high-efficiency, low emission cars development. On the way, the hybrid car is the first priority. Hybrid electric vehicle battery pack configurations, EV Relay one of the key components of the engine driving, to assist in the drive motor to supply electrical energy to the battery is a device for opening and closing of the output device. EV Relay determine the longevity and the replacement cycle, The EV Relay environmental conditions and duty cycle considering the reliability tests are essential requirements of many automotive companies to respond to RFQ, this test is essential. This paper using Maxwell Software for Prediction of the Ev Relay impulse, the theoretical data to obtain the impulse to develop methods for mechanical testing after to take advantage of it.

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A study on the Large High Speed Press Plunger Structure and Dynamic Bottom Dead Center Displacement (대형 고속프레스 플런저 구조와 동적 하사점 변위량에 대한 연구)

  • Seung-Soo Kim;Chun-Kyu Lee
    • Design & Manufacturing
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    • v.16 no.4
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    • pp.40-45
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    • 2022
  • The EV electric vehicle market is growing rapidly worldwide. An electric vehicle means a vehicle that uses energy charged through an electricity source as power. The precision of the press is important to mass-produce the drive motor, which is a key component of the electric vehicle. The size of the driving motor is increasing, and The size of the mold is also growing. In this study, the precision of large high-speed presses for mass production of driving motors was measured. A study was conducted on the measurement method of press and the analysis of measurement data. A drive motor is a component that transmits power by converting electrical energy into kinetic energy. EV driven motors have key material properties to improve efficiency. The material properties are the thickness of the material. As a method for improving performance, use a 0.2mm thin steel sheet. Mold is also becoming larger. As the mold grows, the size of the high-speed press for mass production of the driving motor is also increasing. Also, the precision of the press is the most important because it uses a thin iron plate material. So the importance of large press precision is being emphasized. In this study, the effect of large high-speed press structure on precision was verified

Self-Driving and Safety Security Response : Convergence Strategies in the Semiconductor and Electronic Vehicle Industries

  • Dae-Sung Seo
    • 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.

Development of a Battery Model for Electric Vehicle Virtual Platform (전기 자동차 가상 플랫폼용 배터리 모델 개발 및 검증)

  • Kim, Sunwoo;Jo, Jongmin;Han, Jaeyoung;Kim, Sung-Soo;Cha, Hanju;Yu, Sangseok
    • Transactions of the Korean Society of Automotive Engineers
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    • v.23 no.5
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    • pp.486-493
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    • 2015
  • In this paper, a battery model for electric vehicle virtual platform was developed. A battery model consisted of a battery cell model and battery thermal management system. A battery cell model was developed based on Randles equivalent circuit model. Circuit parameters in the form of 3D map data was obtained by charge-discharge experiment of Li-Polymer battery in various temperature condition. The developed battery cell model was experimentally verified by comparing voltages. Thermal management system model was also developed using heat generator, heat transfer and convection model, and cooling fan. For verification of the developed battery model in vehicle level, the integrated battery model was applied in to EV(electric vehicle) virtual platform, and virtual driving simulation using UDDS velocity profile was conducted. The accuracy of the developed battery model has been verified by comparing the simulation results from EV platform with the experimental data.

Smart EVs Charging Scheme for Load Leveling Considering ToU Price and Actual Data

  • Kim, Jun-Hyeok;Kim, Chul-Hwan
    • Journal of Electrical Engineering and Technology
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    • v.12 no.1
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    • pp.1-10
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    • 2017
  • With the current global need for eco-friendly energies, the large scale use of Electric Vehicles (EVs) is predicted. However, the need to frequently charge EVs to an electrical power system involves risks such as rapid increase of demand power. Therefore, in this paper, we propose a practical smart EV charging scheme considering a Time-of-Use (ToU) price to prevent the rapid increase of demand power and provide load leveling function. For a more practical analysis, we conduct simulations based on the actual distribution system and driving patterns in the Republic of Korea. Results show that the proposed method provides a proper load leveling function while preventing a rapid increase of demand power of the system.