Jae-Cheon Lee

Hardware-in-the loop simulator for ABS/TCS

The prevalence of microprocessor-based controllers in automotive systems has greatly increased the need for simulators to validate and test control systems over their full range of operation. This paper introduces PC-based hardware-in-the loop (HIL) real time simulator for anti-lock braking system (ABS) and traction control system (TCS). The analyses of the commercial electronic control units and components for ABS/TCS were successfully accomplished by utilizing the HIL simulator in this study. Furthermore, it is expected that the simulator could contribute to developing more advanced vehicle dynamics control systems.

Identification of optimal control parameters for a pneumatic active engine mount system

Pneumatic Active Engine Mount (PAEM) with trans-forward control system has been developed to reduce the transmission of the idle-shake vibration induced by engine effectively and economically. A solenoid valve installed between PAEM and vacuum tank is on-off switched by the pulse width modulate (PWM) control signal to decrease the dynamic stiffness of the engine mount. This paper presents the methodology to identify the optimal values of control parameters of a PAEM, i.e. turn-on timing and duty ratio of PWM signal for 6 different idle driving conditions. A scanning algorithm was first applied to the vehicle test to obtain the approximate optimal control parameters minimizing the vibration at front seat rail and at steering wheel. Then the PAEM system identification was fulfilled to find accurate optimal control parameters by using multi-layer neural networks of Levenberg-Marquardt algorithm with vehicle test data.

Research on temperature estimation of smart clutch for vehicle

Clutch is an important component used to transmit or cut off power from engine to transmission. When the clutch is not completely engaged, slipping will happen, yielding generation of friction heat. If slipping frequently happens, the clutch will generate a large amount of friction heat, immediately resulting in increasing of clutch temperatures. Too much high temperature deteriorates the quality and lifespan of the clutch disk. Therefore, a new type clutch, called as smart clutch, is necessary, which can real-time estimate temperature of the clutch in order to prevent overheating and to improve working lifespan. In this paper, a thermal model of the clutch based on lumped parameter is established by analyzing heat conduction and heat convection of all main components of the clutch. Two different test conditions are applied to the clutch in experiment and temperature of the pressure plate is measured. The estimated temperature of the pressure plate in simulation is compared with that of experiment. It is found that the estimated temperature based on the lumped parameter model can fit the experimental results very well, which shows feasibility of the temperature estimation model.

An investigation on the nonlinear adaptive servo control of an electrohydraulic system

Electrohydraulic servo system has been widely utilized in various industries. However, robust adaptive control logic is quite necessary for the electrohydraulic servo to be used in wide operation range because of its complex and nonlinear characteristics with time-varying parameters. This study developed a self-turning regulator (STR) as a nonlinear adaptive control logic robust to noise and disturbance. Properties of electrohydraulic valve was analyzed firstly, and its nonlinearity was compensated by an inverse nonlinear model. The entire dynamic model equation was obtained by system identification techniques, namely, online forgetting factor recursive least square (FFRLS) algorithm. Then robustness of adaptive control scheme in this study against noise was also simulated. The results show that robustness to noise of the adaptive control logic works well and STR control algorithm can effectively compensate system nonlinear characteristics.

Identification of Optimal Control Parameters for a Pneumatic Active Engine Mount System

Pneumatic Active Engine Mount (PAEM) with trans-forward control system has been developed to reduce the transmission of the idle-shake vibration induced by engine effectively and economically. A solenoid valve installed between PAEM and vacuum tank is on-off switched by the pulse width modulate (PWM) control signal to decrease the dynamic stiffness of the engine mount. This paper presents the methodology to identify the optimal values of control parameters of a PAEM, i.e. turn-on timing and duty ratio of PWM signal for 6 different idle driving conditions. A scanning algorithm was first applied to the vehicle test to obtain the approximate optimal control parameters minimizing the vibration at front seat rail and at steering wheel. Then the PAEM system identification was fulfilled to find accurate optimal control parameters by using multi-layer neural networks of Levenberg-Marquardt algorithm with vehicle test data.

Correlation Analysis of TPA Output Variables in a Pneumatic Active Engine Mount System

A PAEM(Pneumatic Active Engine Mount) system has been developed to improve NVH performance of a SUV in idle state. Control objective to attenuate the vibration of a vehicle should be determined prior to the design of control algorithm. This study presents the correlation analysis of output variables of PAEM system by means of TPA(Transfer Path Analysis) using experimental data obtained by vehicle test. The analysis results show that the vibration of vertical direction is more serious than those of longitudinal and lateral direction of the vehicle, and that the correlation between the vibration of front seat rail and that of steer wheel is highest. In conclusion, the vibrations of front seat rail and steer wheel in vertical direction should be considered as the control objectives of the PAEM.

Driving pathfinding of unmanned autonomous ground vehicle using measurement data diffusion

The state of road changes quite often due to the automobiles and pedestrians when the main driving unit controls the unmanned autonomous vehicle along the planned path. The vehicle acknowledges of whether there are obstacles on the driving path using a sensor array and creates the new driving path and adaptively updates route to control the vehicle. This research proposes a novel way to find the possible driving path by diffusing the measurement data collected by the sensor array which contains the unscaled info of the detected obstacles. With the possible driving field, we can recognize whether the current path would be affected by the obstacles, and also possibly create a new driving path to avoid them. Using the driving map created by this way, we made a new driving path applying A∗ algorithm and tested on a unmanned autonomous vehicle (i.e., converted KIA Soul). As a result, after creating the new driving path, we were able to carry out the avoidance driving safely at low speed, also the vehicle drives swiftly and smoothly when we modified the avoidance path within the possible driving field.