Semi-active control of a nonlinear quarter-car model of hyperloop capsule vehicle with Skyhook and Mixed Skyhook-Acceleration Driven Damper controller

Birhan Abebaw Negash,Wonhee You,Kwansup Lee,Jinho Lee,Changyoung Lee

doi:10.1177/1687814021999528

Birhan Abebaw Negash, Wonhee You + Show 3 more

Open Access

https://doi.org/10.1177/1687814021999528

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Abstract

A suspension system is one of the integral parts of a hyperloop capsule train, which is used to isolate the car-body from bogie vibration to provide a safer and comfortable service. A semi-active suspension system is one of the best candidates for its advantageous features. The performance of a semi-active suspension system relies greatly on the control strategy applied. In this article, Skyhook (SH) and mixed Skyhook-Acceleration Driven Damper (SH-ADD) controlling algorithms are adopted for a nonlinear quarter-car model of a capsule with semi-active magnetorheological damper. The nonlinear vertical dynamic response and performance of the proposed control algorithms are evaluated under MATLAB Simulink environment and hardware-in-loop-system (HILS) environment. The SH controlled semi-active suspension system performance is found to be better at the first resonance frequency and worse at the second resonance frequency than the passive MR damper, but the mixed SH-ADD controlled semi-active suspension system performs better than the passive at all frequency domains. Taking the root-mean-square (RMS) value of sprung mass vertical displacement as an evaluation criterion, the response is reduced by 58.49% with mixed SH-ADD controller and by 54.49% with the SH controller compared to the passive MR damper suspension.

Highlights

Nowadays, many companies across the world are doing researches intensively on a hyperloop capsule to unveil it as the fifth mode of transportation, and there is a high computation between them for the new achievement
A new mode of transportation system was intended to be built between San Francisco, California, and Los Angeles, California corridor, that optimizes the benefits of the existing transportation system and improves the limitations
Taking the RMS value in both MATLAB Simulink and hardware-in-loop system (HILS) environment vertical displacement response, the SH Controlled MR damper performance is improved by 54.49% in the HILS environment and 36.75% in the MATLAB Simulink environment relative to the passive MR damper performance, and the mixed SHADD Controlled MR damper performance is improved by 58.22% in the HILS environment and 36.93% in the MATLAB Simulink environment

Summary

Introduction

Many companies across the world are doing researches intensively on a hyperloop capsule to unveil it as the fifth mode of transportation, and there is a high computation between them for the new achievement. In the EDS Stiffness subsystem, the nonlinear levitation electrodynamic force will be calculated based on the relative vertical displacement of the bogie to the guideway, as well as forward velocity and position of the bogie. Xia[25] and Boada et al.[26] proposed a modified neural network technique for the inverse dynamic model of an MR damper to predict the input current for the desired force This technique requires a high amount of experimental data for training and validation of the network. The processor unit analyses the quarter-car model of a capsule on a MATLAB Simulink environment and sends MR damper’s ends relative displacement and input current signals to the plant unit (MR damper) through the signal transmitter.

Findings

Result and discussion

Conclusion