Kyungsuk Han
Hanyang University · 工学
研究室紹介
Professor Kyungsuk Han's research lab specializes in advanced vehicle dynamics control and intelligent driving systems, focusing on enhancing vehicle safety, stability, and autonomy through model-based control strategies. The lab develops sensorless and adaptive estimation techniques for critical vehicle states such as tire-road friction, wheel slip, and road surface conditions, enabling robust performance without relying on additional hardware. Key research directions include model predictive control, sliding mode control, and game-theoretic approaches for autonomous maneuvering, particularly in complex traffic environments. The lab also explores innovative powertrain architectures and control systems for electric and hybrid vehicles to optimize traction and energy efficiency.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15It is well known that both the tire-road friction coefficient and the absolute vehicle velocity are crucial factors for vehicle safety control systems. Therefore, numerous efforts have been made to resolve these problems, but none have presented satisfactory results in all cases. In this paper, cost-effective observers are designed based on an adaptive scheme and a recursive least squares algorithm without the addition of extra sensors on a production vehicle or modification of the vehicle contr
Using a special type of sliding mode controller, a new type of traction control system (TCS) for hybrid four-wheel drive vehicles is developed. This paper makes two major contributions. First, a new electric powertrain architecture with an in-wheel motor at the front wheels and a clutch on the rear of the transmission is proposed for maximum traction force. The in-wheel motors are controlled to cycle near the optimal slip point. Based on the cycling patterns of the front wheels, the desired whee
Real-time classification of road surface conditions is very important for the control of a vehicle properly within its handling limits. There have been numerous attempts to estimate the road surface conditions, but there is a plenty of room for improvement, since most of the estimation methods have some robustness issues in real-world applications. The method proposed in this paper utilizes the relationship between the road surface condition and the tire cornering stiffness. Since the tire corne
This paper presents a control method of an antilock brake system (ABS) for electric vehicles. For decades, serious efforts have been dedicated to designing a wheel slip-based ABS controller, but there are some inherent flaws. To realize a robust control system, the wheel slip and road friction information are generally required. Unfortunately, however, these parameters cannot be accurately measured in production vehicles. The method suggested in this paper is aimed at solving these problems by e
This paper presents the lane-merging strategy for self-driving cars in dense traffic using the Stackelberg game approach. From the perspective of the self-driving car, in order to make sufficient space to merge into the next lane, a self-driving car should interact with the vehicles in the next lane. In heavy traffic, where the possible actions of the vehicle are pretty limited, it is possible to conjecture the driving intentions of the vehicles from their behaviors. For example, by observing th
This paper proposes a new control strategy to improve vehicle cornering performance in a model predictive control framework. The most distinguishing feature of the proposed method is that the natural handling characteristics of the production vehicle is exploited to reduce the complexity of the conventional control methods. For safety's sake, most production vehicles are built to exhibit an understeer handling characteristics to some extent. By monitoring how much the vehicle is biased into the
This paper presents an adaptive individual brake torque estimation method based on the characteristic of front-to-rear brake force distribution ratio. Most previous studies on tire force estimation have assumed that brake torques can be calculated out of brake pressure and given fixed brake gains. However, brake gains are proportional to brake pad friction coefficients, which are influenced significantly by operating or weather conditions. In this paper, it is assumed that the pad friction coeff
This paper addresses the hierarchical optimization of speed and gearshift control for battery electric vehicles using short-range traffic information. To achieve greater electric motor efficiency, a multi-speed transmission is employed, whose control involves discrete-valued gearshift signals. To overcome the computational difficulties in solving the integrated speed-and-gearshift optimal control problem that involves both continuous and discrete-valued optimization variables, we propose a hiera
This paper considers the optimization of multispeed transmission configuration and gearshift schedule for battery electric vehicles. Although only a single reduction gear is commonly utilized in commercial battery electric vehicles, further improvements in energy savings can be achieved by employing a multi-speed transmission as has been already shown in existing literature. In this paper, we propose an approach to co-optimization of transmission design (number of gears and gear ratios) and of g
With the emergence of vehicle-communication technologies, many researchers have strongly focused their interest in vehicle energy-efficiency control using this connectivity. For instance, the exploitation of preview traffic enables the vehicle to plan its speed and position trajectories given a prediction horizon so that energy consumption is minimized. To handle the strong uncertainties in the traffic model in the future, a constrained controller is generally employed in the existing researches