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This paper reports a study on the use of response inverse filtering (RIF) methodology for crash pulse prediction. RIF is based on the finite impulse response (FIR) and inverse filtering (IF) methods. The FIR coefficients obtained by the digital convolution theory and the least squared error approach serve to transfer response from the input (impacting or excitation) side to the output (non-impacting or receiving) side. The FIR method, a process of low pass filtering (e.g. truck body mount), is commonly used in predicting the non-impacting side (e.g. truck body or cab) response with the input excitation in the impacting side (e.g. truck frame). The accuracy in the validation and prediction via FIR transfer function depends on the frequency contents of the input and output accelerometer data from which the transfer function is developed. The prediction accuracy is low if the output data contain higher frequency components than the input.

This paper reports a study of the impact dynamic characteristics of body mounts in a body-on-frame vehicle. Two methods of dynamic analyses are utilized. One method is direct impact; and the other excitation on the body mount. Using a series of component test data, the direct impact method yields the natural frequency, f, and damping factor, ζ, for a spring-mass-damper model of a body mount. The functional relationship between the g-force versus deflection curve and f, ζ, and v (impact speed) is examined. Given a frame impulse, the excitation method predicts the body response by the convolution integral. The transient transmissibility (TT), the ability of a body mount to transmit shock impulse from the frame to the body in the early part of crash duration, is investigated. The degree of front-loadedness on the body pulse is determined by TT and thus it affects the occupant/vehicle crash response.