Research And Implementation For Method Of AUTOSAR System Modeling

The invention of automotive brought much more convenience to human. After nearly 200-year's development, it has been a very important part of our daily life. However people's demand in the performance continues to improve, which results in the increase of the software amount contained in an automotive system. There are lots of difficult things appearances. The engineers may need more time to develop and debug the system, while still could not make sure the system is safe, and strong. Faced with these questions, in order to cope with the tremendous increase in functional scope of automotive electronics and thus implicitly software, a significant reduction of structural complexity by the means of an industry-wide standardized software infrastructure is mandatory.Then, AUTOSAR which is short for Automotive Open System Architecture came to us. The AUTOSAR is a partnership of automotive manufacturers and suppliers working together to develop and establish a de-facto open industry standard for automotive E/E architectures. It deals with the problem above mainly through the mechanism of standardization, Basic Software core, Microcontroller abstraction, RTE and Standardization of interfaces. The efforts of this initiative was the software infrastructure,e.g. to provide technical means within a layered software architecture for abstraction from hardware and abstraction to application layer software, however not limit to this, the focus expands also to another fields. Above all, the AUTOSAR is very useful, powerful and of potential.Firstly, there is an introduction to the AUTOSAR concept, methodology and the software architecture under the AUTOSAR. Modeling elements were given, which coulded be used when designing a system. Then, discussion on the model persistence rules for XML was made, and this is a very important part in the whole AUTOSAR. Finally, by analyzing, the deficiencies of available software were shown. While algorithms to produce the AUTOSAR XML schema were given, also some details were discussed about the projects.