2 research outputs found
Theoretical Experiments on Road Profile Data Analysis using Filter Combinations
Get PDFIdentification of road profiles is needed to provide the input of automotive simulation and endurance testing. The analysis with estimation methods is mostly done to identify road profiles. The main goal of analysis methods is to obtain the data of vertical displacements due to road profile measurement. The acceleration data is obtained from measuring road profile by using 4 sensors of accelerometer placed on each car wheel. The measuring data is converted to be vertical displacement data by using a "double integrator", however, it is not easy to get accurate results since the signal obtained carries a lot of noise and it is necessary to design the right filter reduce the noise. In this study, the signal filtering methods reducing the noise were used Fast Fourier Transform (FFT) and Kalman Filter (KF) combination. Experiments were carried out by combining Fast Fourier Transform and Kalman Filters using an input signal with unit (volt) in the time domain. In addition, this research focused on preparing the survey data that has been obtained by eliminating the noise to convert becoming the displacement input data for providing the loads of automotive simulation testing
Development of hydraulic servo controller for mechanical testing with optimization of PID tuning methods
Get PDFThis study explores the use of hydraulic servo control (HSC) systems in static and dynamic structural testing, focusing on optimizing proportional, integral, derivative (PID) controller tuning. The HSC system comprises three main components: hydraulic, control, and measurement systems. To achieve optimal performance, the research begins with preparing setpoint displacement/force data and developing mathematical models for the cylinder actuator and servo valve, incorporating sensors like load cells and linear variable differential transducers (LVDTs). A closed-loop transfer function is used to predict outputs that align closely with setpoint values. Three PID tuning methods—Ziegler-Nichols, Cohen-Coon, and adaptive control—are evaluated. Simulation results show all methods yield satisfactory performance with evaluation errors below 1.5%. Implementation tests further confirm effectiveness, with root mean square deviation (RMSD) values under 1%, indicating high precision. Despite promising results, the study acknowledges limitations due to restricted datasets and test conditions. Future research should address broader dynamic load variations, nonlinearities such as fluid leakage and hysteresis, and integrate intelligent optimization techniques like machine learning to enhance robustness and adaptability. This work contributes to improving the reliability and accuracy of HSC systems in structural testing, paving the way for smarter, more responsive control strategies in engineering applications
