A self-sensing approach for estimating suspension displacement and velocity in semi-active electromagnetic dampers

Abstract

Electromagnetic damper (EMD) suspension systems have gained significant recognition for their fast response and precise control capabilities. Nonetheless, the necessity of sensor-based control escalates system costs too high and limits its application. This paper introduces an innovative self-sensing approach for semi-active EMD that aims to autonomously acquire vehicle suspension state information without external sensors. The goal is to improve the performance of vibration damping while remaining cost-efficiency. Initially, the EMD is designed and modelled, followed by an analysis of the variable damping principle of the permanent magnet synchronous motor (PMSM). The variable damping EMD model is formulated using the machine-electric coupling equation. Subsequently, a detailed explanation of the principle behind the proposed self-sensing approach is presented. Simulation results confirm its precise capability to estimate the suspension displacement and velocity even in the absence of external sensor input. Moreover, bench experiments for the EMD are conducted to validate the effectiveness of the variable damping and self-sensing approach. Experimental results indicate that the damping characteristic of the EMD can be controlled by manipulating external resistance value. In addition, accurate estimation of suspension displacement and velocity can be achieved under varying excitation conditions, even with changes in damper damping.