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

机译:硬件在环测试系统的不确定性预算

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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.
机译:对于汽车行业,在制造系统原型之前要使用两种主要的测试方法:软件在环(SIL)和硬件在环(HIL)。通过这两种测试方法,可以检查软件算法,硬件性能和可靠性。与在实际的汽车系统中一样,HIL测试系统依赖于模拟测量。考虑到这些测量的准确性,分辨率和精确度,已知的主要挑战是定义通过这些测量获得的数据的可靠性。由于所有算法,磁滞特性和状态机都是基于采集的数据样本进行开发和测试的,因此基本需要确定不确定性,或更准确地说,是对测量结果的不确定性进行量化[1]。本文将介绍一种可用于确定HIL系统中进行的测量的不确定性预算的方法。

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