• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1674-1688
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• 2019

As environmental pollution and fossil fuel energy problems from fuel vehicle have occurred, the interest of electric vehicle(EV) has increased. EV industry and energy industry have grown dynamically in these days. It is expected that the next generation of primary transportation will be EV, and it is necessary to prepare EV infra and efficient energy management such as EV communication protocol, EV charge station, and smart grid. Those EV and energy industry fields are now on growth. Also, the study and development of them are now in progress. In this paper, distributed charge signal processing software for smart slow and quick EV charge is proposed and designed for dealing with EV charge demand. The software consists of smart slow and quick EV charge schedule engine and EV charge power distribution core. The software is designed to support two charge station types. One is normal EV charge station and the other is bus garage EV charge station. Both two types collect the data from EV charge stations, and then analyze the collected data. The software suggests optimized EV charge schedule and deliveries EV charge power distribution information to power switchboard system, and the designed software is implemented on embedded system. It is expected that the software provides efficient EV charge schedule.

• Proceedings of the KIPE Conference
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• 2016.07a
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• pp.345-346
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• 2016

The grid-connected energy storage systems, which could increase the reliability, efficiency, and cleanliness of the grid is presently restricted by the high cost of batteries. This problems could be solved by batteries retired from automotive services. These batteries can provide a low-cost system for energy storage and other applications such as residential applications and renewable energy integration. This paper gives an overview of technical requirements for the re-use of the electric vehicle batteries in energy storage systems.Firstly, the motivation of research is introduced. Secondly, the technologies needed for the re-use of the battery are introduced such asidentification of the battery characteristics, grading of the aged batteries, identification of the state-of-charge and state-of-health of the battery and suitable power electronic converter topologies. In addition the control strategy to maximize the battery lifespan and bypass the faulty batteries is presented and one-stop solution to implement the above mentioned technologies are also given.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.2
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• pp.155-162
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• 2009

In walking guide robot, a guide vehicle detects an obstacle distribution in the walking space using range sensors, and generates a 3D grid map to map the obstacle information and the tactile display. And the obstacle information is transferred to a blind pedestrian using tactile feedback. Based on the obstacle information a user plans a walking route and controls the guide vehicle. The algorithm for 3D detection of an obstacle distribution and the method of mapping the generated obstacle map and the tactile display device are proposed in this paper. The experiment for the 3D detection of an obstacle distribution using ultrasonic sensors is performed and estimated. The experimental system consisted of ultrasonic sensors and control system. In the experiment, the detection of fixed obstacles on the ground, the moving obstacle, and the detection of down-step are performed. The performance for the 3D detection of an obstacle distribution and space mapping is verified through the experiment.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.662-671
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• 2012

Plug-in hybrid electric vehicles (PHEVs) will be widely used in future transportation systems to reduce oil fuel consumption. Therefore, the electrical energy demand will be increased due to the charging of a large number of vehicles. Without intelligent control strategies, the charging process can easily overload the electricity grid at peak hours. In this paper, we consider a smart charging and discharging process for multiple PHEVs in a building's garage to optimize the energy consumption profile of the building. We formulate a centralized optimization problem in which the building controller or planner aims to minimize the square Euclidean distance between the instantaneous energy demand and the average demand of the building by controlling the charging and discharging schedules of PHEVs (or 'users'). The PHEVs' batteries will be charged during low-demand periods and discharged during high-demand periods in order to reduce the peak load of the building. In a decentralized system, we design an energy cost-sharing model and apply a non-cooperative approach to formulate an energy charging and discharging scheduling game, in which the players are the users, their strategies are the battery charging and discharging schedules, and the utility function of each user is defined as the negative total energy payment to the building. Based on the game theory setup, we also propose a distributed algorithm in which each PHEV independently selects its best strategy to maximize the utility function. The PHEVs update the building planner with their energy charging and discharging schedules. We also show that the PHEV owners will have an incentive to participate in the energy charging and discharging game. Simulation results verify that the proposed distributed algorithm will minimize the peak load and the total energy cost simultaneously.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.6
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• pp.14-22
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• 2014

An autonomous vehicle requires a technology of generating maps by recognizing surrounding environment. The recognition of the vehicle's environment can be achieved by using distance information from a 2D laser scanner and color information from a camera. Such sensor information is used to generate 2D or 3D maps. A 2D map is used mostly for generating routs, because it contains information only about a section. In contrast, a 3D map involves height values also, and therefore can be used not only for generating routs but also for finding out vehicle accessible space. Nevertheless, an autonomous vehicle using 3D maps has difficulty in recognizing environment in real time. Accordingly, this paper proposes the technology for generating 2D maps that guarantee real-time recognition. The proposed technology uses only the color information obtained by removing height values from 3D maps generated based on the fusion of 2D laser scanner and camera data.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2001.10a
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• pp.202-206
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• 2001

A three dimensional incompressible Navier-Stokes code based on the third derivative upwind is employed to simulate the flow around the underwater vehicle advancing on the calm water. Computations are carried out in the range of Froude numbers 0.4 to 0.7. The wave resistance, lift, moment and the pressure distribution on the body are calculated. Computations are performed in a rectangular grid system based on the Marker & Cell method. For validation, computation results are compared with existing experimental results.

• The Journal of Society for e-Business Studies
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• v.25 no.2
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• pp.1-14
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• 2020

ISO 15118 is an international standard that defines communication between electric vehicles and electric vehicle chargers. Plug & Charge (PnC) was also defined as a technology to automatically authenticate users when using charging services. PnC indicates automatic authentication technology where all processes such as electric vehicle user authentication, charging and billing are automatically processed. According to the standard, certificates for chargers and CPSs (Certificate Provisioning Services) should be under the V2G (Vehicle to Grid) Root certificate. In Korea, the utility company operates its own PKI (Public Key Infrastructure), making it difficult to provide chargers under the V2G Root Certificate. Therefore, a method that can be authenticated is necessary even when you have different Root Certificates. This paper proposes to apply cross-certificate technology to PnC authentication. Automatic authentication of Cross Certification is to issue a cross-certificate of the Root CA and include it in the certificate chain to proceed with automatic authentication, even if you have different Root certificates. Applying cross-certificate technology enables verification of certificates under other Root certificates. In this paper, the PnC automatic authentication and cross certificate automatic authentication is implemented, so as to proceed with proof of concept proving that both methods are available. Define development requirements, certificate profiles, and user authentication sequences, and implement and execute them accordingly. This experiment confirms that two automatic authentication are practicable, especially the scalability of automatic authentication using cross-certificate PnC.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.87-106
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• 2024

Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

• Proceedings of the KIPE Conference
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• 2013.11a
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• pp.83-84
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• 2013

최근 국내에서 진행중인 스마트 그리드(Smart Grid) 사업 분야에 속해 있는 스마트 운송(Smart Transportation) 사업의 하나로 전기차 운영이 핵심이 되어 진행이 되고 있다. 그러나 실제적으로 전기차를 원활히 운영하기 위해서는 극복해야 할 여러 문제가 있으며 대표적으로 주행 거리를 좌우하는 배터리 용량 문제와 고객이 어디서든 전기차를 사용하고 충전하는데 불편이 없을 만큼 충분한 충전 인프라 구축 문제가 있다. 충전 인프라는 현재, 완속 충전기와 급속 충전기로 구성되어 있으나 본 논문에서는 완속 충전기에 한정하여 서술하였고 인프라 구축에 있어 표준화 일환으로 미국자동차기술학회에서 제시하는 SAE-J1772 규격에 맞추어 개발한 자사의 완속 충전기에 2012년 독일과 미국의 자동차 업체 주도로 발표된 국제표준(ISO/IEC 15118, Vehicle-to-Grid Communication Interface) 기술 규격이며 향후 충전 인프라에 적용 예상이 되는 PLC 통신 방식을 적용한 완속 충전기 개발에 관하여 소개하도록 하였다.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.14-19
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• 2021

This paper presents LiDAR static obstacle map based vehicle dynamic state estimation algorithm for urban autonomous driving. In an autonomous driving, state estimation of host vehicle is important for accurate prediction of ego motion and perceived object. Therefore, in a situation in which noise exists in the control input of the vehicle, state estimation using sensor such as LiDAR and vision is required. However, it is difficult to obtain a measurement for the vehicle state because the recognition sensor of autonomous vehicle perceives including a dynamic object. The proposed algorithm consists of two parts. First, a Bayesian rule-based static obstacle map is constructed using continuous LiDAR point cloud input. Second, vehicle odometry during the time interval is calculated by matching the static obstacle map using Normal Distribution Transformation (NDT) method. And the velocity and yaw rate of vehicle are estimated based on the Extended Kalman Filter (EKF) using vehicle odometry as measurement. The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment, and is verified with data obtained from actual driving on urban roads. The test results show a more robust and accurate dynamic state estimation result when there is a bias in the chassis IMU sensor.