https://scholar.dgist.ac.kr/handle/20.500.11750/58892 2026-04-04T13:58:02Z https://scholar.dgist.ac.kr/handle/20.500.11750/59957 Title: Physically Informed Sideslip Angle Estimation for Electric Vehicles Using Lateral Tire Force Sensors and a GPR-UKF Observer Author(s): Nam, Kanghyun; Wang, Yafei; Fujimoto, Hiroshi Abstract: This article presents a nonlinear sideslip angle estimation framework that directly incorporates lateral tire force measurements into an observer structure. To address the limitations of conventional approaches that rely on tire models and slip angle approximations, a physically grounded tire model is developed that features load-dependent cornering stiffness, relaxation dynamics, and time-varying parameter adaptation. Cornering stiffness is estimated via a regression-based method using only measurable signals, and a Gaussian process regression (GPR) model is introduced to estimate the front-rear cornering stiffness. The resulting estimates are integrated into an unscented Kalman filter (UKF) observer for robust sideslip angle estimation under nonlinear and transient conditions. The framework is experimentally validated using a full-scale vehicle equipped with in-wheel motors (IWMs) and lateral tire force sensors. Results confirm that the proposed UKF-based observer achieves accurate and stable sideslip angle estimation during aggressive maneuvers and across varying road surfaces. This approach enables high-fidelity, real-time state estimation for advanced driver-assistance and automated driving applications. 2026-02-28T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/59327 Title: Road Environment Aware Control Framework for Steering Feel Generation in Steer-by-Wire Systems Author(s): Cheon, Dasol; Nam, Kanghyun; Oh, Sehoon Abstract: In steer-by-wire (SBW) systems, where the steering wheel and the tire are not physically connected, the steering feel is artificially generated regardless of road conditions. Typically, SBW systems generate steering feel based on steering angle to steering torque models to provide specific reaction torques in response to the driver's steering input. However, since the steering wheel is not mechanically connected to the tire, the driver cannot feel the road surface condition. This article proposes a novel control algorithm framework that can extract and transfer road surface information while still following the desired steering feel model. The steering feel generation control and road wheel control are integrated to achieve this goal. Specifically, we propose a reference steering model (RSM) for steering feel generation and bilateral control (BiC) for integrated steering wheel and road wheel control. This allows us to reflect the road surface condition without changing the steering feel model or identifying the road surface parameters. We validate the effectiveness of our proposed control through experiments using an SBW test vehicle. 2025-12-31T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/58940 Title: Tire Vertical Force Estimation Method using Suspension Deformation and Stochastic Road Model in Vehicle Suspension System Author(s): Cheon, Dasol; Choi, Wonhyeok; Nam, Kanghyun; Oh, Sehoon Abstract: Tire vertical force is an important factor in the vehicle system because the tire vertical force directly affects the longitudinal force such as the driving force and the braking force, and the lateral force caused by steering motion. Therefore, estimating the tire vertical force is an essential issue. In this study, we propose a tire vertical force observer(TVFOB) using the measurable acceleration sensor and the suspension deformation sensor in a vehicle. The observer set a tire radius as a state, and the derivative of the tire radius is assumed as stochastic white Gaussian noise. A quarter car model is used to verify the performance of the algorithm The proposed algorithm is evaluated through the simulation by using Matlab Simulink and Carmaker. 2022-11-02T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/58899 Title: 전기자동차용 듀얼 모터구동 EVT 시스템의 강인한 구동제어 Author(s): 서영훈; 남강현; 천다솔; 권태우 2020-11-18T15:00:00Z