Side Crash Pressure Sensor Prediction for Unitized Vehicles: An ALE Approach

With a goal to help develop pressure sensor calibration and deployment algorithms using computer simulations, an Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this research to predict the responses of side crash pressure sensors for unitized vehicles. For occupant protection, acceleration-based crash sensors have been used in the automotive industry to deploy restraint devices when vehicle crashes occur. With improvements in the crash sensor technology, pressure sensors that detect pressure changes in door cavities have been developed recently for vehicle crash safety applications. Instead of using acceleration (or deceleration) in the acceleration-based crash sensors, the pressure sensors utilize pressure change in a door structure to determine the deployment of restraint devices. The crash pulses recorded by the acceleration-based crash sensors usually exhibit high frequency and noisy responses. Different from those of the acceleration-based crash sensors, the data obtained from the pressure sensors exhibit lower frequency and less noisy responses. Due to its ability to discriminate crash severities and allow the restraint devices to deploy earlier, the pressure sensor technology has gained its popularity for side crash applications. The lower frequency and less noisy characteristics are also more suitable for non-linear finite element codes to predict. Fifteen different benchmark problems were designed and tested in the first stage of this research to investigate the responses of pressure sensors in different impact conditions and the capabilities of the ALE method in the predictions of different pressure sensor responses. The fifteen benchmark problems were divided into three groups to examine the capabilities of the ALE method in detail. Different structures, gases, hole locations, sensor locations, hole sizes, impact speeds, and impactors, were chosen in the fifteen benchmark problems so that the sensitivity of the pressure responses to different factors could be obtained and understood. Computer simulations conducted by employing the ALE method for all fifteen benchmark problems were compared to their corresponding theoretical solutions or test data. The correlations between the tests and the computer simulations were found to be reasonable as reported in a paper published previously. The research was advanced into its final stage, full vehicle tests, after the positive results obtained from the benchmark study. The full vehicle study