Monte Carlo sensitivity analysis of vehicle suspension energy harvesting in frequency domain

Abstract

Regenerative shock absorbers (RSAs) have still not entered production lines despite the promising potentials in energy efficiency and emission reduction. Vibration energy harvesting from vehicle dampers has been replicating the dynamics of passive viscous dampers. An accurate frequency-based analysis of the harvestable energy and dynamics for vehicle suspensions under typical operating conditions is essentially needed for designing functional Vibratory Regenerative Dampers (VRDs). This paper proposes frequency-based parametrical bandwidth sensitivity analyses of both the vehicular suspension dynamics and energy harvesting potentiality in accordance with the Monte Carlo sensitivity simulations. This provides insights into which suspension parameter could highly broaden the harvestable power magnitude, which contributes positively to conceptualizing an efficient design of a wide broad-banded energy harvesting damper leading to improved harvesting efficiencies in different road conditions. The conducted sensitivity analysis included the change in both frequency and amplitude bandwidth of the dissipative damping power, body acceleration, dynamic tire load, and suspension deflection. During the sensitivity simulations, a 2-DOFs (degrees-of-freedom) quarter-car model is considered, being excited by harmonic excitations. The selected suspension parameters were normally randomized according to the Gaussian probability distribution based on their nominal values and a 30% SD (standard deviation) with respect to the uniformly randomized excitation frequency. The results inferred higher sensitivity change in the harvestable power bandwidth versus the excitation parameters, damping rate, and tire properties. Conversely, the harvestable power hardly broadened with respect to the body and wheel masses and the spring stiffness.