In this study, the response of the spine acceleration to rib and pelvis acceleration input of the side impact dummy (SID) is modeled using system identification methods. The basis for the modeling is a simplified representation of the SID by a 3-mass, 2-spring system. Based on this spring-mass representation, two response model types are established. The first is a "gray-box" type with rib/pelvis-spine relationship modeled by Auto Regression with eXogenous (or eXtra) input (ARX) type system models. The structure of these models is partially based on the spring-mass simplified representation, hence the "gray-box" notion. The parameters of these models are identified through linear regression from test data. The second type of models is noted "physical model" here, since it is strictly a state-space form of the equation of motion of the simple spring-mass representation. The parameters of the model are identified through non-linear parameter identification with minimization of the prediction error of the state-space model. Data tor parameter estimation of all these models come from three groups of tests: a sled impact, a dummy local impact, and full vehicle test group. It is found that the models are able to predict the trend with tests with impact conditions similar to that of the test on which the estimate is based. However, when the condition deviates significantly, the estimate does not predict the behaviour of the SID satisfactorily.
Samenvatting