Optimization of nonlinear quarter car suspension-seat-driver model

A state-of-the-art review on biomechanical models and biodynamic responses

Biomechanical models are mathematical representations of human structure. These models are used to analyse joint and injury mechanics and design of prosthetic devices for human body under various conditions. Biomechanical model development involves the integration of knowledge from various fields, including mechanics, biology, physiology, and mathematics. Biomechanical models have become more significant in the healthcare sector as researchers strive to offer better medical supplies and ride comfort. It has uses in automobile and sports science as well, to create human dummies for accident and segmental vibration transmissibility study, improve training routines, and prevent injuries. These biomechanical models might be anything from straightforward lumped parameter models to intricate multi-body models. The virtues, weaknesses, and contemporary uses of lumped parameter modelling and multi body modelling in biomechanical modelling are discussed in this article. Subsequently, emphasised the recent modelling improvements and explored the future direction of biomechanical modelling. Researchers and professionals who wish to apply biomechanical models to comprehend human movement and enhance performance may find this review to be helpful.

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

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Frequency based Monte Carlo sensitivity of the harvestable power and vehicle dynamics.

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A widely broadened harvestable power is obtainable terms of higher excitation amplitudes.

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The harvestable energy highly correlated to the damping rate and the tire stiffness.

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The harvestable power responded weakly to the stiffness and the body and wheel masses.

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.

Sliding Mode Switch Control of Adjustable Hydro-Pneumatic Suspension based on Parallel Adaptive Clonal Selection Algorithm

The hydro-pneumatic suspension, as a widely used suspension for heavy vehicles, has been taken seriously by researchers for a long time because it is crucial in terms of handling stability, riding comfort, and driving safety of these vehicles. Most previous studies only discussed the control of ride comfort or vehicle handling stability of the suspension system separately. This article proposes a dynamic switch control strategy which can switch between ride comfort and handling stability controllers under different road surfaces and driving conditions. The load transfer ratio (LTR) is selected as the switch performance index, and it is calculated through a six-degrees-of-freedom (6-DOF) model. The ride comfort and handling stability controller of the hydro-pneumatic suspension are designed based on the sliding mode control theory. The objective functions of parameters optimization of the sliding mode controller (SMC) are obtained by means of analytic hierarchy process (AHP), and then the controller’s parameters are optimized by the parallel adaptive clonal selection algorithm (PACSA). The simulation results based on MATLAB/Simulink show that: (1) the PACSA performs better than a genetic algorithm in terms of the parameters optimization of the SMC; (2) the proposed switch control strategy can simultaneously improve the ride comfort and handling stability under several typical steering maneuvers and various road profiles compared with the conventional SMC-controlled suspension.

Musculoskeletal modelling of the human cervical spine for the investigation of injury mechanisms during axial impacts

Head collisions in sport can result in catastrophic injuries to the cervical spine. Musculoskeletal modelling can help analyse the relationship between motion, external forces and internal loads that lead to injury. However, impact specific musculoskeletal models are lacking as current viscoelastic values used to describe cervical spine joint dynamics have been obtained from unrepresentative quasi-static or static experiments. The aim of this study was to develop and validate a cervical spine musculoskeletal model for use in axial impacts. Cervical spine specimens (C2-C6) were tested under measured sub-catastrophic loads and the resulting 3D motion of the vertebrae was measured. Specimen specific musculoskeletal models were then created and used to estimate the axial and shear viscoelastic (stiffness and damping) properties of the joints through an optimisation algorithm that minimised tracking errors between measured and simulated kinematics. A five-fold cross validation and a Monte Carlo sensitivity analysis were conducted to assess the performance of the newly estimated parameters. The impact-specific parameters were integrated in a population specific musculoskeletal model and used to assess cervical spine loads measured from Rugby union impacts compared to available models. Results of the optimisation showed a larger increase of axial joint stiffness compared to axial damping and shear viscoelastic parameters for all models. The sensitivity analysis revealed that lower values of axial stiffness and shear damping reduced the models performance considerably compared to other degrees of freedom. The impact-specific parameters integrated in the population specific model estimated more appropriate joint displacements for axial head impacts compared to available models and are therefore more suited for injury mechanism analysis.