A customized design framework for the model-based development of engine control systems
Martin Hüfner, Christian Sonntag, Sebastian Engell, Sebastian Grobosch
Abstract
Martin Hüfner, Christian Sonntag, Sebastian Engell, Sebastian Grobosch
Abstract
In the model-based design of complex technical systems, many design data artifacts are generated, such as models in different formalisms and design-related documents, which include specifications, test results, and design decisions. The consistent treatment and integration of these design artifacts is a challenge that is as of yet unsolved in industrial practice. This paper illustrates the industrial applicability of a software-based Design Framework (DF) [1] for the model-based design of an engine control system that was developed recently within the European research project MULTIFORM [2]. The goal of the Design Framework is to reduce the design effort, and thus the cost, while improving the quality of the designed system by consistently integrating the artifacts and tools that arise in model-based design processes. To ensure that design inconsistencies and errors are detected as early as possible (i.e. when it is relatively cheap to correct them), the framework provides structured data and model management as well as automated design consistency checking and design parameter propagation.
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In the model-based design of complex technical systems, many design data artifacts are generated, such as models in different formalisms and design-related documents, which include specifications, test results, and design decisions. The consistent treatment and integration of these design artifacts is a challenge that is as of yet unsolved in industrial practice. This paper illustrates the industrial applicability of a software-based Design Framework (DF) [1] for the model-based design of an engine control system that was developed recently within the European research project MULTIFORM [2]. The goal of the Design Framework is to reduce the design effort, and thus the cost, while improving the quality of the designed system by consistently integrating the artifacts and tools that arise in model-based design processes. To ensure that design inconsistencies and errors are detected as early as possible (i.e. when it is relatively cheap to correct them), the framework provides structured data and model management as well as automated design consistency checking and design parameter propagation.
Key concepts: Computer science, Model-based design, Consistency (knowledge bases), Systems engineering, Probabilistic design, Software engineering, Engineering design process, Simulation