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Uncertainty Budget for Hardware-in-the-Loop Test System

When it comes to the automotive industry two main testing approaches are used before a system prototype is manufactured: software-in-the-loop (SIL) and hardware-in-the-loop (HIL). Through these two testing methods, the software algorithms, hardware performance and reliability can be checked. As in a real automotive system, the HIL test system relies on analog measurements. Given that accuracy, resolution, and precision of these measurements are known, the main challenge is to define how reliable is the data acquired by these measurements. Since all the algorithms, hysteresis proprieties and state machines are developed and tested based on acquired data samples, what is basically needed is to determine the uncertainty or, more precise, to quantify the doubt about the measurement results, [1]. This paper will present an approach that can be used to determine the uncertainty budget for the measurements done in HIL systems.