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이주인(Jooin Lee),이형철(Hyeongcheol Lee) 한국자동차공학회 2019 한국자동차공학회 부문종합 학술대회 Vol.2019 No.5
Recently, the technologies for reducing fuel consumption and greenhouse gas emission have attracted much attention at automobile industry. Especially in urban areas where traffic volume is concentrated, environmental problems are more serious and important. With this situation the `Intelligent Transportation System(ITS)` has been developed to collect traffic information and provide it to vehicle and drivers. The traffic information collected at ITS can applied to the vehicle controller to effectively reduce fuel consumption. This Paper proposes path finding algorithm for determining the path, which minimizes fuel consumption, using vehicle model and traffic information. This fuel-optimal route decision algorithm estimates travel-time and travel-fuel-consumption and uses `Dynamic Programming(DP)` for optimization. The cost function used in DP is designed to minimize the fuel consumption used throughout the path. The fuel-optimal route decision algorithm is verified using AIMSUN intersection model that reflects the actual traffic environment.
교차로 형상 정보를 반영한 연비 최적 속도 프로파일 결정 알고리즘
이주인(Jooin Lee),허남(Nam Heo),윤희수(Heesu Youn),이형철(Hyeongcheol Lee) 한국자동차공학회 2017 한국자동차공학회 부문종합 학술대회 Vol.2017 No.5
This paper presents the method for determining the speed profile to minimize fuel consumption using information on the intersection structure. Numerous previous papers have suggested that fuel consumption can be minimized by driving at constant speed. The driving pattern in urban area have frequent deceleration, acceleration, and idling that make unnecessary fuel consumption and carbon emissions. An individual vehicle moving along the urban street are difficult to drive at constant speed because of a lot of obstructions consisting of traffic light, queue, and intersection structure. Fuel consumption is greatly influenced by road curve, and acceleration characteristic. Therefore, optimal speed profile can be computed using intersection structure information, vehicle dynamics model. This algorithm simulated on several intersections with various shape and various traffic environments. The simulation environment is developed by microscopic traffic simulation tool and the proposed algorithm is realized by using Python. Simulations show that the information about intersection and traffic condition provides benefits in terms of fuel economy.
수소연료전지 버스의 비선형 모델 예측 제어를 활용한 실시간 동력 분배 제어 알고리즘
이승연(Seungyeon Lee),이주인(Jooin Lee),임종원(Jongwon Lim),이형철(Hyeongcheol Lee) 한국자동차공학회 2023 한국자동차공학회 학술대회 및 전시회 Vol.2023 No.11
In this paper, power distribution control algorithm for fuel cell electric bus was developed. Power distribution control algorithm is developed by using Gradient based Model Predictive Control(GRAMPC). Algorithm considered vehicle’s system characteristics like fuel cell, battery, motor and vehicle dynamics. Cost function is developed with considering battery’s State-of-charge and consumption ratio of fuel cell. GRAMPC can execute nonlinear model predictive control algorithm with real-time environment. Driving scenario is developed including real world traffic condition by using SUMO and Autonomie. Algorithms is validated in real-time simulation environment with dSPACE RCP-HIL simulator.
이동 지평선 추정기를 활용한 전기 차량의 구동 모터 고장 진단 알고리즘
이현창(Hyunchang Lee),이주인(Jooin Lee),김재영(Jaeyoung Kim),이형철(Hyeongcheol Lee) 한국자동차공학회 2024 한국자동차공학회 부문종합 학술대회 Vol.2024 No.6
Recently, research on electric vehicles has been actively conducted due to environmental pollution problems. Permanent magnet synchronous motors (PMSM) are mainly used as traction motors for electric vehicles. Fail safe for the PMSM of traction system is essential to ensure the stability and reliability of the vehicle. In this paper, modeling of an electric vehicle traction system was performed, and a state observer was designed to diagnose inter turn short circuit (ITSC) fault, which mainly occurs among PMSM actuator faults. Nonlinear Moving Horizon Estimation was used as the state observer, and the fault diagnosis algorithm was verified in a simulation environment for the proposed state observer.
확장형 칼만 필터를 활용한 자율주행 전기차의 통합 고장 진단 알고리즘
이현창(Hyunchang Lee),이주인(Jooin Lee),이형철(Hyeongcheol Lee) 한국자동차공학회 2023 한국자동차공학회 학술대회 및 전시회 Vol.2023 No.11
It is important to obtain an accurate sensor value because an autonomous vehicle controls by processing various information through a sensor. If a sensor value problem occurs due to a sensor failure, it can cause a serious performance degradation problem. To prevent this deterioration problem, sensor failures are diagnosed and model-based fault detection and diagnosis algorithms are utilized as a method. In previous studies, a generalized observer method using extended kalman filter(EKF) was used as a model-based fault diagnosis method, but the computational amount increased as the number of diagnostic subjects increased. In this paper, a new method for the reduction number of extended kalman filter(EKF) was investigated. The proposed method designs the extended kalman filter(EKF) by integrating the lower system dynamics of the vehicle with vehicle dynamics.
도심 내 교차로 환경에서 연비 최적 경로 결정 알고리즘
윤경섭(Kyungsup Yoon),이주인(Jooin Lee),김경준(Kyungjun Kim),이형철(Hyeongcheol Lee) 한국자동차공학회 2018 한국자동차공학회 부문종합 학술대회 Vol.2018 No.6
Recently, global warming, environmental pollution, and fuel shortages have become major worldwide problems. To solve these problems, the rapid development of Mobile Internet, Smart Devices and Intelligent Transportation Systems(ITS) has been made and it makes it possible to predict and increase information about current driving conditions. The fuel-optimal route decision is one of several tools that attempt to address this problem by minimizing network-wide vehicle fuel consumption and emission levels. The fuel-optimal route decision algorithm selects the most environmentally friendly route. In this paper, we study how to determine fuel optimal route using A* algorithm. This algorithm uses a heuristic of the remaining cost at each time step in order to reduce the computation. Therefore, it is possible to operate faster than Dijkstra’s routing algorithm, which is widely used. In the previous study, fuel optimal route was determined by using traffic volume. However, in this study, we considered the speed variation to compare and verify fuel optimal route decision algorithm.
ADAS의 실험 및 검증을 위한 통합 평가 시나리오 연구
나원빈(Wonbin Na),이주인(Jooin Lee),박창우(Changwoo Park),이형철(Hyeongcheol Lee) 한국자동차공학회 2016 한국자동차공학회 부문종합 학술대회 Vol.2016 No.5
Recently, the ADAS (Advanced Driver Assistance System) vehicle is actively developed. The evaluation criteria and test method were created to validate the reliability of the system. The ADAS vehicle have to cope with the emergent situation. Since the real ADAS vehicle is integration of many performances of DAS systems, there might be unexpected situations or malfunctions that is not detected by each scenario test. Euro NCAP and ISO decisively offer many test scenarios for each criterions and conditions. In this paper, we studied the newly developed integrated scenario for testing ADAS using ‘PreScan’. The scenario that can evaluate at least two ADAS systems at the same time using virtual environments-based method. This paper offered the integrated test scenario about ACC (Adaptive Cruise Control) and AEB (Autonomous Emergency Braking) systems.
실시간 교통 상황 정보 추정을 통한 속도 계획 알고리즘 개발
허남(Nam Heo),이주인(Jooin Lee),윤희수(Heesu Youn),이형철(Hyeongcheol Lee) 한국자동차공학회 2017 한국자동차공학회 부문종합 학술대회 Vol.2017 No.5
This paper proposes speed-planning algorithm to minimize fuel consumption by estimating traffic condition. There are many researcher undergoing strategies to reduce fuel consumption and emission on highway and arterial road. Excessive acceleration, deceleration and Idling generate unnecessary fuel consumption and emission. There are many cause of making frequent speed change in urban road like traffic light or queue. To reduce fuel consumption at the intersection, it is important to estimate traffic light and traffic conditions. Vehicles driving through urban intersection can compute optimal speed by estimating Queue clearance time and signal changing time. In this study, we present algorithm providing speed-planning with estimated traffic condition at intersection. This algorithm is simulated by microscopic traffic simulation model (Aimsun).
Track-to-Track 센서 퓨전 방법을 이용한 고장 검출 알고리즘
김경준(Kyungjun Kim),이주인(Jooin Lee),이형철(Hyeongcheol Lee) 한국자동차공학회 2018 한국자동차공학회 부문종합 학술대회 Vol.2018 No.6
Recently, in the automotive industry, one of the most important mainstream is the intelligent vehicle. The intelligent vehicle acquires the information of the vehicle and its environments such as lane and a preceding vehicle. Then it provides convenience to the driver by using ADAS (Advanced Driver Assistance System) controller, for instance, LKA (Lane Keeping Assist), SCC (Smart Cruise Control), and FCA (Forward Collision-Avoidance Assist). It is important to get accurate sensing data of the vehicle and the environment. ISO26262 (“Road Vehicles- Functional safety”) is defined to address possible hazards of S/W and H/W for Automotive Electric/Electronic Systems. This paper deals with the FDI (Fault Detection and Isolation) algorithm to figure out the sensor faults of ADAS sensors and In-Vehicle Sensors such as IMU and Wheel Speed Sensors. Since it is hard to secure hardware redundancies of ADAS sensors, it creates underlying states of ADAS sensors and compares it with the outputs of the EKF composed of In-vehicle sensors. As the ADAS sensors, Front Camera, Left Camera, and Right Camera were selected.