• International Journal of Internet, Broadcasting and Communication
• /
• 제9권1호
• /
• pp.1-8
• /
• 2017

Nowadays many articles describe the controlling models for four rotor flying vehicle. Basic approaches to the problem of these articles are mathematical expressions describing dynamics of the models of the vehicle and PID control for manipulating the object in 3 dimensional space. Design of control systems is usually started by careful consideration of its mathematical model description. We present a detailed mathematical model for a quad rotor. This paper first considers simulation of quadcopter control based on full state feedback technique with linearization in MATLAB environment and shows the results of the simulations. Finally will be shown experimental results of the state feedback control implemented in real model.

• 제어로봇시스템학회논문지
• /
• 제21권3호
• /
• pp.210-216
• /
• 2015

This paper proposes a method to determine vehicle driving state using the driving characteristics index. This index is a quantitative value to classify the driving state of a vehicle with its velocity and heading angle in that instant. It can classify driving state into straight driving, lane changing driving and curve driving in real time. In addition, the number of positional information is movably set up by designed region of interest. The proposed index is expressed on the stable driving states. Each driving state has characteristic tendency, and is compared with index distributional areas. The proposed method is verified by the actual driving experiment on the KATECH proving ground.

• 전기학회논문지
• /
• 제57권5호
• /
• pp.839-844
• /
• 2008

A novel state of health estimation method for hybrid electric vehicle lithium battery using sliding mode observer has been presented. A simple R-C circuit method has been used for the lithium battery modeling for the reduced calculation time and system resources due to the simple matrix operations. The modeling errors of simple model are compensated by the sliding mode observer. The design methodology for state of health estimation using dual sliding mode observer has been presented in step by step. The structure of the proposed system is simple and easy to implement, but it shows robust control property against modeling errors and temperature variations. The convergence of proposed observer system has been proved by the Lyapunov inequality equation and the performance of system has been verified by the sequence of urban dynamometer driving schedule test. The test results show the proposed observer system has superior tracking performance with reduced calculation time under the real driving environments.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권12호
• /
• pp.5842-5861
• /
• 2019

A current autonomous vehicle determines its driving strategy by considering only external factors (Pedestrians, road conditions, etc.) without considering the interior condition of the vehicle. To solve the problem, this paper proposes "An Optimal Driving Support Strategy(ODSS) based on an Genetic Algorithm for Autonomous Vehicles" which determines the optimal strategy of an autonomous vehicle by analyzing not only the external factors, but also the internal factors of the vehicle(consumable conditions, RPM levels etc.). The proposed ODSS consists of 4 modules. The first module is a Data Communication Module (DCM) which converts CAN, FlexRay, and HSCAN messages of vehicles into WAVE messages and sends the converted messages to the Cloud and receives the analyzed result from the Cloud using V2X. The second module is a Data Management Module (DMM) that classifies the converted WAVE messages and stores the classified messages in a road state table, a sensor message table, and a vehicle state table. The third module is a Data Analysis Module (DAM) which learns a genetic algorithm using sensor data from vehicles stored in the cloud and determines the optimal driving strategy of an autonomous vehicle. The fourth module is a Data Visualization Module (DVM) which displays the optimal driving strategy and the current driving conditions on a vehicle monitor. This paper compared the DCM with existing vehicle gateways and the DAM with the MLP and RF neural network models to validate the ODSS. In the experiment, the DCM improved a loss rate approximately by 5%, compared with existing vehicle gateways. In addition, because the DAM improved computation time by 40% and 20% separately, compared with the MLP and RF, it determined RPM, speed, steering angle and lane changes faster than them.

• 한국생산제조학회지
• /
• 제23권1호
• /
• pp.7-14
• /
• 2014

The core of the automotive industry's strategy to handle the climate change can be explained as the development and distribution of the vehicles with high fuel efficiencies and low emission. Clean Diesel, hydrogen fuel cell, electric, and especially hybrid power-train vehicles have been actively studied. This paper dynamically analyzes the performance of a hybrid system's five driving modes. The research subject consists of one engine, two electric motors, two simple planetary gears, and one compound planetary gears with five clutches. To define the steady state equation of the system, interaction formulas of five driving modes are introduced with motion variables and torque variables. These formulas are then used to analyze the speeds, torques, and power flows of each mode.

• Journal of Electrical Engineering and Technology
• /
• 제12권5호
• /
• pp.1851-1863
• /
• 2017

Interior permanent magnet synchronous motor (IPMSM) is most commonly used in the automotive industry as a traction motor for electric vehicle (EV). In electric vehicle, the torque output rapidly changes according to the operation of the accelerator and the braking of the driver. The transient torques are thus generated very frequently in accordance with the variable speed control of the driver. Therefore, in this paper, a method for improving the torque response in the transient states of IPMSM is proposed. In order to complement the disadvantages of the conventional PI current controller in the field oriented control (FOC), the finite-state model predictive current control and 2D-LUT is applied to improve the torque response at the torque transient period. Simulation and experiment results are given to verify the reliability of the proposed method.

• International Journal of Naval Architecture and Ocean Engineering
• /
• 제7권5호
• /
• pp.817-832
• /
• 2015

This paper presents a state feedback based backstepping control algorithm to address the trajectory tracking problem of an underactuated Unmanned Surface Vessel (USV) in the horizontal plane. A nonlinear three Degree of Freedom (DOF) underactuated dynamic model for USV is considered, and trajectory tracking controller that can track both curve trajectory and straight line trajectory with high accuracy is designed as the well known Persistent Exciting (PE) conditions of yaw velocity is completely relaxed in our study. The proposed controller has further been enriched by incorporating an integral action additionally for enhancing the steady state performance and control precision of the USV trajectory tracking control system. Global stability of the overall system is proved by Lyapunov theory and Barbalat's Lemma, and then simulation experiments are carried out to demonstrate the effectiveness of the controller designed.

• 한국추진공학회지
• /
• 제24권3호
• /
• pp.71-80
• /
• 2020

발사체 분석을 위한 CFD 소프트웨어인 LVAFoam을 개발하기 앞서 발사체의 연소기, 터보 펌프 및 외부유동의 시뮬레이션에 사용된 해외의 인하우스 CFD 소프트웨어 및 상용 CFD 소프트웨어에 대한 조사를 수행하였다. 인하우스 소프트웨어로는 NASA, 미시시피 주립대학, DLR, Bertin Technologies & CNES, CERFACS 및 JAXA의 솔버들과, 상용 소프트웨어로는 FLUENT, CFX, Adavance/FrontFlow/red, GASP, CRUNCH CFD, CFD-ACE+, FINE^TM/Turbo, STAR-CCM+ 의 솔버들을 정리하였다. 발사체 분석을 위한 각 소프트웨어의 계산 사례가 제시되었으며, 개발된 LVAFoam이 간략하게 소개되었다.

• Journal of Mechanical Science and Technology
• /
• 제16권10호
• /
• pp.1287-1295
• /
• 2002

In this work, the fuel economy of a parallel hybrid electric vehicle is investigated. A vehicle control algorithm which yields operating points where operational cost of HEV is minimal is suggested. The operational cost of HEV is decided considering both the cost of fossil fuel consumed by an engine and the cost of electricity consumed by an electric motor. A procedure for obtaining the operating points of minimal fuel consumption is introduced. Simulations are carried out for 3 variations of HEV and the results are compared to the fuel economy of a conventional vehicle in order to investigate the effect of hybridization. Simulation results show that HEV with the vehicle control algorithm suggested in this work has a fuel economy 45% better than the conventional vehicle if braking energy is recuperated fully by regeneration and idling of the engine is eliminated. The vehicle modification is also investigated to obtain the target fuel economy set in PNGV program.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.160.3-160
• /
• 2001

The objective of this research is to monitor and control the vehicle motion in order to remove out the existing safety risk based upon the human-machine cooperative vehicle control. A new control method is proposed to control the steering wheel of the vehicle to keep the lane. Desired angle of the steering wheel to control the vehicle motion could be calculated based upon vehicle dynamics, current and estimated pose of the vehicle every sample steps. The vehicle pose and the road curvature were calculated by geometrically fusing sensor data from camera image, tachometer and steering wheel encoder though the Perception Net, where not only the state variables, but also the corresponding uncertainties were propagated in ...