Saab Automobile AB

About: Saab Automobile AB is a based out in . It is known for research contribution in the topics: Radar & Antenna (radio). The organization has 760 authors who have published 890 publications receiving 11811 citations.

Simulator-based human-machine interaction design

Abstract: Human-in-the-loop simulators have been used for some decades in the automotive area. Historically, the most prevalent motive for this, beside training purposes, has been to study human performance in various situations. We suggest another focus, to evaluate human-machine system performance for various car system solutions as a fundamental part of simulator-based design (SBD). Our technical background is human-machine interaction (HMI), which is only one area where SBD could be deployed. However, in combination with human-in-the-loop simulation, HMI should be the most relevant perspective. In order to facilitate this SBD approach, it is necessary to have simulators (software and hardware) that support this way to implement new car system solutions to work seamlessly together with the entire vehicle system. Unfortunately, there are few such simulators available on the market today. We will expand this theme in the article and also address important questions concerning fidelity and validity.

Estimation of process parameter variations in a pre-defined process window using a Latin hypercube method

Abstract: The aim of this paper is to present a methodology that provides an analytical tool for estimation of robustness and response variation within a pre-defined process window. To exemplify the developed methodology, the stochastic simulation technique is used for a sheet-metal forming application. A sampling plan based on the Latin hypercube sampling method for variation of design parameters is utilized, and the thickness reduction is specified as the response. Moreover, the response surface methodology is applied for understanding the quantitative relationship between design parameters and response value. The conclusions of this study are that the applied method gives a possibility to illustrate and interpret the variation of the response versus a design parameter variation. Consequently, it gives significant insights into the usefulness of individual design parameters. It has been shown that the method enables us to estimate the admissible design parameter variations and to predict the actual safe margin for given process parameters. Furthermore, the dominating design parameters can be predicated using sensitivity analysis, and this in its turn clarifies how the reliability criteria are met. Finally, the developed software can be used as an additional module for set-up of stochastic finite element simulations and to collect the numerical results from different solvers within different applications.