Cyber–physical systems are becoming increasingly complex. In these advanced systems, the different engineering domains involved in the design process become more and more intertwined. Therefore, a traditional (sequential) design process becomes inefficient in finding good design options. Instead, an integrated approach is needed where parameters in multiple different engineering domains can be chosen, evaluated, and optimized to achieve a good overall solution. However, in such an approach, the combined design space becomes vast. As such, methods are needed to mitigate this problem.

In this paper, we show a method for systematically capturing and updating domain knowledge in the context of a co-design process involving different engineering domains, i.e. control and embedded. We rely on ontologies to reason about the relationships between parameters in the different domains. This allows us to derive a stepwise design space exploration workflow where this domain knowledge is used to quickly reduce the design space to a subset of likely good candidates. We illustrate our approach by applying it to the design space exploration process for an advanced electric motor control system and its deployment on embedded hardware.

网络物理系统正变得越来越复杂。在这些先进的系统中，设计过程中涉及的不同工程领域变得越来越交织在一起。因此，传统的（顺序）设计过程在寻找好的设计选项方面变得效率低下。相反，需要一种集成方法，可以选择、评估和优化多个不同工程领域的参数，以实现良好的整体解决方案。然而，在这种方法中，组合的设计空间变得巨大。因此，需要一些方法来缓解这个问题。

在本文中，我们展示了一种在涉及不同工程领域（即控制和嵌入）的协同设计过程中系统地捕获和更新领域知识的方法。我们依靠本体来推理不同域中参数之间的关系。这使我们能够推导出逐步设计空间探索工作流程，其中该领域知识用于快速将设计空间减少到可能的优秀候选者的子集。我们通过将我们的方法应用于先进电机控制系统的设计空间探索过程及其在嵌入式硬件上的部署来说明我们的方法。