On-going Projects
[한국연구재단] (역할: PI) 자가 학습 능력을 갖춘 적응형 통합 종방향 운전자 주행보조 시스템 개발 (23.09 ~ 26.02 )
[한국연구재단] (역할: 공동) 숙명여자대학교 현장연계 탄소중립 ESG 미래선도인재양성지원사업단 (22.03 ~ 25.12)
[한국타이어앤테크놀로지] (역할: PI) 후륜 조향 시스템 적용에 따른 타이어 성능 변화 연구 (25.03 ~)
[현대자동차] (역할: PI) 터레인TCS 제어 성능 고도화를 위한 차량의 구동축 토크(휠토크) 추정 로직 개발 (25.03 ~)
[현대자동차](역할: PI) 차량 거동 최적화를 위한 제동 디스크 온도 추정 및 영향도 분석 (25.06 ~)
[현대자동차] (역할: PI) 전기차의 전비/주행 안정성 향상을 위한 모터 활용 모터 활용 emABS로직 개발 (25.08 ~)
Completed Projects
[현대자동차] (역할: PI) 전기차의 전비/주행 안정성 향상을 위한 모터 활용 제동 제어 알고리즘 개발 (24.07~25.07)
[현대자동차] (역할: PI) 커브 도로에서 운전자 성향에 맞는 자동 감속을 위한 도로 곡률 기반 자율주행 플래닝 알고리즘 개발 (24.05~25.05)
[한국타이어앤테크놀로지] (역할: PI) 차량 통합 제어(ABS/VDC)에 따른 타이어 성능 변화 연구 (24.04 ~25.04)
[현대자동차] (역할: PI) 스마트회생시스템의 감속 느낌 개선을 위한 운전자 성향 기반 파라미터 자동 학습 알고리즘 개발 (23.04~24.04)
[현대자동차] (역할: 공동) 탑승자 이질감 저해요인을 고려한 인간운전자 드라이빙 패턴 모사 자율주행 AI-Agent 개발 (22.12~23.08)
Research Topics
I. Personalized Control of Autonomous Electrified Vehicle Systems (차량 개인화 제어)
We study vehicle control algorithms that adapt to individual driver preferences to enhance safety, comfort, and energy efficiency in autonomous electrified vehicles.
◎ Selected Topics
Online parameter adaptation-based personalized car-following control for intelligent regenerative braking systems
Real-time personalized control of longitudinal ADAS using a combined CNN-LSTM network and a robust feedback controller
II. Adaptive Control and Online Learning for Production Vehicles (양산차 적응형/학습 기반 제어)
This research focuses on maintaining control performance of production vehicles despite changes caused by temperature fluctuations, component aging, and mechanical variations.
◎ Selected Topics
Online adaptive identification of clutch friction characteristics to maintain drivability consistency in high-performance production vehicles
III. Safety and Dynamics Control for Electrified Vehicles (차량 동역학/도로 정보 기반 안전 제어)
This topic focuses on ensuring vehicle stability and passenger safety by designing dynamics control systems tailored for electric powertrains.
◎ Selected Topics
Regenerative braking control during cornering to enhance yaw stability, braking safety, and energy efficiency in low-cost production electric vehicles
Intelligent regenerative braking using road curvature and slope information to improve driver comfort during deceleration
IV. Optimal Control for Electrified Powetrains with Multiple Energy Sources (에너지/변속 최적 제어)
We develop optimal control strategies for electrified powertrains, including multi-source energy management and gear shift control, to enhance efficiency, ride comfort, and performance while satisfying constraints such as SOC limits and emission regulations.
◎ Selected Topics
Robust clutch-to-clutch shift control for dual-clutch transmission EVs to optimize jerk, shift time, and frictional energy losses
Optimal energy management strategies for hybrid vehicles under SOC, power, and emission constraints
V. AI-based Vehicle Control and Modeling (AI 기반 차량 제어 및 모델링)
We apply machine learning techniques, including deep neural networks and reinforcement learning, to develop intelligent control algorithms and vehicle models suitable for real-world uncertainties.
VI. Vehicle State and Parameter Estimation for Production Vehicles (양산차 상태/파라미터 추정)
We design estimation algorithms to infer key states and parameters from limited sensor data in production vehicles, enabling intelligent control and diagnostics.
◎ Selected Topics
Estimation of clutch torque and output shaft torque in driveline systems with stepped-ratio transmissions
Estimation of individual wheel drive torques and tire forces for all-wheel-drive production vehicles
State of charge (SOC) and state of health (SOH) estimation of batteries for automotive applications