Abstract
An eigensystem realization algorithm (ERA) approach for estimating the structural system matrices is proposed in this paper using the measurements of acceleration data available from the real crash test. A mathematical model that represents the real vehicle frontal crash scenario is presented. The model’s structure is a double-spring-mass-damper system, whereby the front mass represents the vehicle-chassis and the rear mass represents the passenger compartment. The physical parameters of the model are estimated using curve-fitting approach, and the estimated state system matrices are estimated by using the ERA approach. The model is validated by comparing the results from the model with those from the real crash test.
Highlights
Car crash test is usually performed in order to ensure safe design standards in crashworthiness
Let m1 be the mass of the chassis, m2 the mass of passenger compartment, and mt = 873 kg the total mass of the vehicle
A method to estimate the parameters of a double-spring-mass-damper model of a vehicle frontal crash is presented
Summary
Car crash test is usually performed in order to ensure safe design standards in crashworthiness (the ability of a vehicle to be plastically deformed and yet maintain a sufficient survival space for its occupants during crash scenario). Mathematical Problems in Engineering others, we can state the following: subspace identification, genetic algorithm, eigensystem realization algorithm, and data-based regressive model approaches. Typical examples where these SIA have been used can be found in [9, 10], [4, 11], and [12, 13], respectively. The main contribution of this paper is the development of a mathematical model for a double-spring-mass-damper system which reconstructs a vehicle frontal crash scenario and estimates structural parameters such as natural frequencies, spring stiffness, and damping coefficients of the system. In [2, 4, 11], the authors validated their models from numerical examples with known parameters
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