Abstract
Research and/or Engineering Questions/Objectives System-level modeling accelerates the development of distributed mechatronic systems by automating tasks and maintaining the integrity of validated executable specifications and test benches. This paper presents a systematic distributed embedded system development methodology that provides abstraction of hardware and software concerns, facilitates communication via highly accessible models, and promotes reliable early development of both hardware and software. The focus is on the development of complex mechatronic systems with specific emphasis placed on early development and subsequent reuse of hardware-dependent software components and on the concurrent and independent development of embedded electronic hardware, software, and physical plants. Methodology Complex interactions between physical plants and distributed embedded computing components make developing mechatronic systems very difficult—even when everything is fully specified. New technology options add further complications and require diversified skills from system developers. Designers must deal with embedded software, electronic control units (ECUs), electro-mechanical subsystems (mechatronics), and the networks through which they communicate. In order to manage change and accelerate development, collaboration within disparate groups of people is essential; various cross-sections of engineering disciplines must be allowed to work independently from each other without incurring huge integration costs in subsequent development phases. Model Driven Development (MDD) has been a term used in our industry for some time, but it has had a hard time achieving widespread adoption and respect as the most effective way to drive a design process. It accelerates the creation, verification, and validation of embedded software using models as the primary engineering deliverable. Results Domain experts use MDD techniques to complete application-specific tasks early, using highly accurate mechatronic models. As projects progress through architectural design, functional partitioning, and detailed component design, the coherence of a system’s model is maintained via communication abstractions, reuse of standard system-level architectures, and automatic C/C++ code generation. These capabilities decouple the decision points and ease regression testing to accelerate development as early confirmed strategies are successively verified when networks, actuators and sensors, real-time operating systems, embedded processors, and other sub-systems change. Models are captured using standard modeling languages such as xtUML and can be transformed, automatically, into production-ready C/C++ embedded software. Virtual Engineering augments MDD to provide a realistic modeling alternative—using modeling standards such as VHDL-AMS—to the physical electronics, mechanical devices, and other hardware that make up the typical environment that surrounds software under development. Limitations of this Study The technology boundaries inherent in such systems pose two main problems for design teams: compatibility between tools and communication between specialists. Conventional simulation tools cannot adequately deal with diverse modeling requirements; also, technology specialists speak a unique design language that is tailored to his/her specialty. As systems become more complex, contractors who once specialized in narrow technical areas are being forced to act as systems integrators and in turn, are contracting subsystems to a global network of subcontractors. It adds up to significant potential for misunderstandings, errors, and omissions due to communication challenges across language and cultural boundaries. What does the paper offer that is new in the field in comparison to other works of the author MDD provides an approach to the challenge of technology change by separating the application portions of a system from underlying platform technology. This technology promotes early, independent, and concurrent development by empowering designers to focus on application models without regard to platform-specific details. This is the difference between MDD and model-based development. MDD completely preserves early application modeling artefacts; the latter repeats modeling efforts for each platform variant. Conclusions This paper describes the capabilities of a virtual system integration environment that supports conceptual system development used early in the design cycle, as well as complete distributed system development on final embedded computing hardware. It describes how MDD improves productivity in the design cycle, automatically generating parts of a design, thus improving quality by bringing in repeatability and standards compliance. It shows how design team members working on complex projects in disparate locations can effectively collaborate using a common modeling and analysis environment, allowing a common modeling and analysis environment to act as a communications vehicle for the entire team.
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Brooks, L., Wu, J., Teegarden, D. (2013). Early Verification of Complex Distributed Systems Using Model Driven Development and Virtual Engineering. In: Proceedings of the FISITA 2012 World Automotive Congress. Lecture Notes in Electrical Engineering, vol 196. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33738-3_32
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DOI: https://doi.org/10.1007/978-3-642-33738-3_32
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