Litcius/Paper detail

Energy-Harvesting Adaptive Vibration Damping in High-Speed Train Suspension Using Electromagnetic Dampers

Qinlin Cai, Yingyu Hua, Songye Zhu

2021International Journal of Structural Stability and Dynamics26 citationsDOI

Abstract

Electromagnetic damper cum energy harvester (EMDEH) is an emerging dual-function device that enables simultaneous energy harvesting and vibration control. This study presents a novel energy-harvesting adaptive vibration control application of EMDEH on the basis of the past EMDEH development in passive control. The proposed EMDEH comprises an electromagnetic damper connected to a specifically designed energy harvesting circuit (EHC), wherein the EHC is a buck–boost converter with a microcontroller unit (MCU) and a bridge rectifier. The effectiveness of the energy-harvesting adaptive vibration damping is validated numerically through a high-speed train (HST) model running at different speeds. MCU-controlled adaptive duty cycle adjustment in the EHC enables the EMDEHs to adaptively offer the optimal damping coefficients that are highly dependent on train speeds. In the meantime, the harvested power can be stored in rechargeable batteries by the EHC. Numerical results project the average output power ranging from 40.5[Formula: see text]W to 589.8[Formula: see text]W from four EMDEHs at train speed of 100–340[Formula: see text]km/h, with a maximum output power efficiency of approximately 35%. In comparison to energy-harvesting passive vibration control and a pure viscous damper, the proposed energy-harvesting adaptive control strategy can improve vibration reductions by approximately 40% and 27%, respectively, at a speed of 340[Formula: see text]km/h. These numerical results clearly demonstrate the benefit and prospect of the proposed energy-harvesting adaptive vibration control in HST suspensions.

Topics & Concepts

DamperEnergy harvestingVibrationControl theory (sociology)Power (physics)Vibration controlEnergy (signal processing)Rectifier (neural networks)Duty cycleMicrocontrollerMaximum power principleSuspension (topology)EngineeringComputer scienceVoltageStructural engineeringElectrical engineeringAcousticsPhysicsMathematicsControl (management)Artificial intelligenceQuantum mechanicsRecurrent neural networkArtificial neural networkHomotopyMachine learningStochastic neural networkPure mathematicsVibration Control and Rheological FluidsInnovative Energy Harvesting TechnologiesMagnetic Bearings and Levitation Dynamics