Self-Sensing Approach for Semi-Active Control of Variable Damping Electromagnetic Suspension System

This paper combines the Kalman filter observer with self-sensing technology and integrates it into the electromagnetic damper (EMD), estimating the displacement and velocity of the EMD based on the three-phase voltage generated by the permanent magnet synchronous motor (PMSM). The self-sensing performance of the EMD is verified through theoretical analysis and experimental results. A vehicle suspension vibration control system composed of one-quarter vehicle electromagnetic suspension (EMS), a acceleration damping driven control (ADDC) algorithm, and a vibration excitation platform is established to test the vibration control performance of the self-sensing EMS. The experimental results show that under random road excitation, compared to passive suspension, the self-sensing-based ADDC reduced the vehicle vertical acceleration of the vehicle suspension, with a 28.92% decrease in the root mean square (RMS) value of the vehicle vertical acceleration. This verifies the effectiveness of the self-sensing capability of the EMS system. Incorporating self-sensing technology into the EMS system improves the vibration reduction performance of the suspension.