Jaewoong Choi

Unified Chassis Control for the Improvement of Agility, Maneuverability, and Lateral Stability

This paper describes a unified chassis control (UCC) strategy for improving agility, maneuverability, and vehicle lateral stability by the integration of active front steering (AFS) and electronic stability control (ESC). The proposed UCC system consists of a supervisor, a control algorithm, and a coordinator. The supervisor determines the target yaw rate and velocity based on control modes that consist of no-control, agility-control, maneuverability-control, and lateral-stability-control modes. These control modes can be determined using indices that are dimensionless numbers to monitor a current driving situation. To achieve the target yaw rate and velocity, the control algorithm determines the desired yaw moment and longitudinal force, respectively. The desired yaw moment and longitudinal force can be generated by the coordination of the AFS and ESC systems. To consider a performance limit of the ESC system and tires, the coordination is designed using the Karush-Kuhn-Tucker (KKT) condition in an optimal manner. Closed-loop simulations with a driver-vehicle-controller system were conducted to investigate the performance of the proposed control strategy using the CarSim vehicle dynamics software and the UCC controller, which was coded using MATLAB/Simulink. Based on our simulation results, we show that the proposed UCC control algorithm improves vehicle motion with respect to agility, maneuverability, and lateral stability, compared with conventional ESC.

Coordinated Control of Hybrid 4WD Vehicles for Enhanced Maneuverability and Lateral Stability

This paper presents a method for coordinated control of hybrid four-wheel drive (4WD) vehicles (H4Vs), which consists of a front internal combustion engine and independent motor-driven rear wheels. H4Vs are equipped with electronic stability control (ESC), active front steering (AFS), and 4WD. For maneuverability and lateral stability, a yaw moment controller is designed. After generating a control yaw moment with a direct yaw moment control, it is distributed with ESC, AFS, and 4WD. Several actuator configurations of ESC, AFS, and 4WD are presented in the framework of the weighted pseudo-inverse based control allocation. Simulation-based tuning is proposed to improve the performance of the yaw moment distribution. Simulations show that the proposed method is effective for the coordinated control of H4Vs for enhanced maneuverability and lateral stability.

Environment-Detection-and-Mapping Algorithm for Autonomous Driving in Rural or Off-Road Environment

This paper presents an environment-detection-and-mapping algorithm for autonomous driving that is provided in real time and for both rural and off-road environments. Environment-detection-and-mapping algorithms have been designed to consist of two parts: (1) lane, pedestrian-crossing, and speed-bump detection algorithms using cameras and (2) obstacle detection algorithm using LIDARs. The lane detection algorithm returns lane positions using one camera and the vision module “VisLab Embedded Lane Detector (VELD),” and the pedestrian-crossing and speed-bump detection algorithms return the position of pedestrian crossings and speed bumps. The obstacle detection algorithm organizes data from LIDARs and generates a local obstacle position map. The designed algorithms have been implemented on a passenger car using six LIDARs, three cameras, and real-time devices, including personal computers (PCs). Vehicle tests have been conducted, and test results have shown that the vehicle can reach the desired goal with the proposed algorithm.

Development of supervisory control strategy for optimized fuel consumption of the compound hybrid excavator

This paper describes a hybrid supervisory control strategy for fuel optimization of a compound hybrid excavator that incorporates an engine-assist motor, an electric swing motor and a super capacitor in the original drive train. The main features of the compound hybrid excavator are that the electrically-propelled swing motor increases the number of energy paths and also incurs many constraints related to the power balance of the hybrid drive train. The dynamic programming technique has been applied to the constrained nonlinear fuel optimization problem over representative excavation cycles. Then, by imitating the behaviour of the dynamic programming optimization scheme, a rule-based controller has been designed. The rule-based controller determines the diesel engine set speed and the engine-assist motor power to operate the engine in an efficient region and to minimize the energy loss in the hybrid drive train. The performance of the rule-based controller has been compared to that of the thermostat controller, which determines the energy distribution, only based on the state of charge of the applied super capacitor. Simulation results indicate that the compound hybrid excavator can improve overall fuel efficiency by about 20% compared to the conventional excavator for representative excavation cycles, and the proposed rule-based controller further enhances the fuel economy by about 2–3% compared to the simple thermostat controller.

Coordinated Control of Motor-Driven Power Steering Torque Overlay and Differential Braking for Emergency Driving Support

This paper describes a coordinated control of motor-driven power steering (MDPS) torque overlay and differential braking for emergency driving support (EDS). The coordinated control algorithm is designed to assist drivers to overcome hazardous situations. Electrically controllable MDPS and brake system are used as actuators, and a radar and a camera are used as a sensor system. Using environmental and vehicle information obtained from the sensor system, a risk of collision and drivers intention are determined, and a collision avoidance trajectory is generated, incorporating the drivers intention. Based on the generated collision avoidance trajectory, the MDPS overlay torque is determined to assist the drivers speed of response, and differential braking is determined to maximize the minimum vehicle-to-vehicle distance to avoid collision. The performance of the proposed algorithm has been investigated via computer simulations and real-time (RT) human-in-the-loop simulations. The simulation studies show that the controlled vehicle can secure additional vehicle-to-vehicle distance in severe lane change maneuvering for collision avoidance. The success rate of collision avoidance has been investigated for eight test drivers using the human-in-the-loop simulations. It has been shown that most of the test drivers can benefit from the proposed support system.

Emergency driving support algorithm with steering torque overlay and differential braking

This paper presents an emergency driving support (EDS) algorithm which supports the driver to avoid collision using motor driven power steering (MDPS) and electronic stability control (ESC). If driver tries to avoid rear-end collision using steering input, the EDS system is activated and supports the driver to have appropriate steering angle and controls the ESC if vehicle needs large yaw rate. The EDS algorithm consists of 4 parts: risk monitoring, driver monitoring, decision and control. In risk monitoring process, risk index is derived using information of preceding vehicle. In driver monitoring process, drivers intention in emergency situation is estimated. In decision process, from the derived indices, the control policies are determined. Finally, in control process, the control inputs of actuators are determined. The performance of proposed algorithm has been investigated via computer simulation conducted to vehicle dynamic software CARSIM and Matlab/Simulink.

Computer vision at the hyundai autonomous challenge

As interest on autonomous vehicles is growing worldwide, different approaches, based on different perception technologies and concepts, are being followed. This paper exposes the importance of the use of vision technology in most of these approaches, and presents the experience of the SNUCLE autonomous vehicle which successfully completed the Hyundai Autonomous Challenge in November 2010.

Development of Power Management Strategies for a Compound Hybrid Excavator

: 패널티 함수 s : 변환효율 Key Words : Compound Hybrid Excavator(복합형 하이브리드 굴삭기), Power Management Strategy(동력 제어 전략), ECMS Strategy(실시간 최적 제어 기법) 초록: 본 논문은 복합형 하이브리드 굴삭기를 위한 동력전달계 제어기법에 대하여 기술하였다. 하이브리드 굴삭기는 기존 굴삭기의 동력전달계를 하이브리드화 하여 연비향상 및 배출가스 저감을 목표로 개발되고 있다. 특히 복합형 하이브리드 굴삭기는 유압시스템의 일부를 전기시스템으로 대체하여 낮은 유압효율로 인한 에너지 손실을 줄일 수 있도록 구성되어 있다. 해당 굴삭기의 하이브리드 동력 제어기는 동력전달계의 동력 흐름을 관리하여 굴삭기의 연비를 향상 시키고, 슈퍼 커패시터의 충전량을 적절한 범위에서 유지하며, 기존 굴삭기에 준하는 성능을 유지하여야 한다. 이를 위하여 본 논문에서는 슈퍼 캐패시터의 충전량 기반의 서모스탯(Thermostat)형 제어기와 실시간 최적해를 이용한 ECMS제어기를 설계하였으며 시뮬레이션을 통하여 그 성능을 검증하였다. 시뮬레이션 결과, 하이브리드 굴삭기의 연비가 대략 20% 이상 향상될 것으로 기대되며, 특히 등가 연료 개념을 이용한ECMS제어기의 성능이 서모스탯(Thermostat)형 제어기에 비해 연비 및 슈퍼 커패시터 충전량 관리 측면에서 보다 향상된 것을 확인하였다. Abstract: This paper presents the power management strategies for a compound hybrid excavator. The compound hybrid excavator has been replaced the hydraulic swing motor to the electric swing motor. This excavator requires a proper control algorithm to regulate the energy flow between the mechanical coupling and the electric devices. The controller should improve fuel economy and maintain the super capacitor voltage within a proper range. A thermostat controller and ECMS controller are designed such that these objectives can be achieved. The thermostat controller regulates the power of the engine-assist motor on the basis of the super capacitor voltage, and the ECMS controller determines it using the real-time fuel minimization strategy based on the concept of equivalent fuel. Simulation results showed that by using the hybrid excavator, the fuel economy becomes about 20% higher than that obtained using the conventional excavator and that the ECMS controller outperforms the thermostat controller.

Lateral Disturbance Compensation Using Motor Driven Power Steering

This paper deals with lateral disturbance compensation algorithm for an application to a Motor Driven Power Steering (MDPS) based driving assistant system. The lateral disturbance such as wind force and load from bank angle reduces the driver refinement and increases the possibility of an accident. In order to reduce the maneuvering effort of the driver in the disturbing situation, the lateral disturbance compensation algorithm has been proposed. The characteristics of the compensation system including a human driver model and the steering system have been mathematically analyzed. The control strategy using the motor overlay torque as a control input which improves the human steering behavior under the lateral disturbance has been proposed. A numerical simulation of the proposed algorithm has been conducted by full vehicle model and lateral driver model which represents steering behavior of human driver. The human torque and lateral deviation under the lateral disturbance are confirmed to be reduced by the simulation results.

Integrated Risk Management System for Intelligent Vehicle

This paper presents an Integrated Risk Management System (IRMS), which is designed to integrate longitudinal and lateral collision avoidance systems. Indices representing longitudinal and lateral collision risks are designed. From the designed indices, an integrated control strategy is designed. A collision avoidance algorithm is designed to assist the driver in avoiding collisions by using a vehicle-driver-controller integrated linear model. The performance of the proposed algorithm is investigated via computer simulations conducted using the vehicle dynamics software CARSIM and Matlab/Simulink.