Simultaneous Suspension Control and Energy Harvesting through Novel Design and Control of a New Nonlinear Energy Harvesting Shock Absorber

TL;DR

This paper introduces a novel nonlinear energy harvesting shock absorber design that enhances vehicle suspension performance and energy harvesting efficiency using a new control approach based on stochastic linearization and model predictive control.

Contribution

The paper presents a new EHSA design integrating nonlinear pendulum effects with electromagnetic harvesting and develops a stochastic linearization MPC for improved control accuracy and computational efficiency.

Findings

Enhanced ride comfort and energy harvesting efficiency demonstrated.

Stochastic linearization MPC outperforms standard methods in accuracy.

Simulation results confirm the superiority of the proposed design and control approach.

Abstract

Simultaneous vibration control and energy harvesting of vehicle suspensions have attracted significant research attention over the past decades. However, existing energy harvesting shock absorbers (EHSAs) are mainly designed based on the principle of linear resonance, thereby compromising suspension performance for high-efficiency energy harvesting and being only responsive to narrow bandwidth vibrations. In this paper, we propose a new EHSA design -- inerter pendulum vibration absorber (IPVA) -- that integrates an electromagnetic rotary EHSA with a nonlinear pendulum vibration absorber. We show that this design simultaneously improves ride comfort and energy harvesting efficiency by exploiting the nonlinear effects of pendulum inertia. To further improve the performance, we develop a novel stochastic linearization model predictive control (SL-MPC) approach in which we employ stochastic linearization to approximate the nonlinear dynamics of EHSA that has superior accuracy compared to standard linearization. In particular, we develop a new stochastic linearization method with guaranteed stabilizability, which is a prerequisite for control designs. This leads to an MPC problem that is much more computationally efficient than the nonlinear MPC counterpart with no major performance degradation. Extensive simulations are performed to show the superiority of the proposed new nonlinear EHSA and to demonstrate the efficacy of the proposed SL-MPC.