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

机译:硬件循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:涉及汽车行业,在制造系统原型之前使用两种主要的测试方法:软件 - 环路(SIL)和硬件循环(HIL)。通过这两个测试方法,可以检查软件算法,硬件性能和可靠性。与真实的汽车系统一样,HIL测试系统依赖于模拟测量。鉴于这些测量的准确性,分辨率和精度是已知的,主要挑战是定义这些测量所获得的数据的可靠性。由于所有算法,滞后性专题和状态机基于所获取的数据样本,基本需要的是要确定不确定性或更精确,以量化关于测量结果的疑问[1]。本文将提出一种方法,可用于确定HIL系统中的测量的不确定性预算。

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