Role-Based Diagnosis for Distributed Vehicle Functions

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Jens Kohl Andreas Bauer

Abstract

With distributed functions taking over more and more safety-relevant functions in modern cars, their possible faulty behaviour has to be detected and dangerous effects to be prevented or mitigated. Additionally, information about the fault’s root cause has to be provided to support repairs in the garage. These are the central tasks of automotive diagnosis, which is arguably a prime application for the methods and tools developed by the diagnosis community at large. However, our experiences have shown that the constraints imposed by this domain, which has a great need for efficient and accurate diagnoses, make it very difficult to use some of the existing methods out of the box. The main contribution of this paper is therefore to introduce a methodology centred around the different stakeholders of automotive diagnosis, in order to facilitate the employment of model-based diagnosis approaches for the diagnosis of vehicle functions as they are part of most modern cars. Besides, we provide an in-depth discussion of some of the challenges imposed by automotive diagnosis and relate these to existing diagnosis methods where feasible, thereby also further motivating our methodology.

How to Cite

Kohl, J. ., & Bauer, . A. (2010). Role-Based Diagnosis for Distributed Vehicle Functions. Annual Conference of the PHM Society, 2(2). https://doi.org/10.36001/phmconf.2010.v2i1.1935
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Keywords

applications: automotive, Model-based diagnosis

References
(Avizienis, A. et al., 2004) Avizienis, A., Laprie, J. C., Randell, B., and Landwehr, C. Basic Concepts and Taxonomy of Dependable and Secure Comput- ing. IEEE Transactions on Dependable and Secure Computing, 1(1):11–33, 2004.

(Bauer, 2007) Andreas Bauer. Model-based runtime analysis of distributed reactive systems. PhD thesis, Technische Universita ̈t Mu ̈nchen, 2007.

(Broy, M., 2006) Broy, M. Challenges in Automotive Software Engineering. In International Conference on Software Engineering (ICSE 2006), pages 33– 42, Shanghai, China, May 2006. ACM.

(Buchanan, B. and Shortliffe, E., 1984) Buchanan, B. and Shortliffe, E., editors. Rule-Based Expert Systems—The MYCIN Experiments of the Stan- ford Heuristic Programming Project, volume 1 of The Addison-Wesley Series in Artificial Intelligence. Addison-Wesley, 1984.

(Ioannou, P. and Chien, C., 1993) Ioannou, P. and Chien, C. Autonomous Intelligent Cruise Control. IEEE Transactions on Vehicular Technology, 42(4):657 – 672, 1993.

(Isermann, R., 2004) Isermann, R. Model-based fault detection and diagnosis: status and applications. In Proceedings of the 16th IFAC Symposium on Automatic Control in Aerospace, St. Petersburg, Russia, June 2004.

(Kleer, de J. and Williams, B. C., 1987) Kleer, de J. and Williams, B. C. Diagnosing multiple faults. AI, 32(1):97–130, 1987.

(MISRA, 2004) Motor Industry Software Reliability Association MISRA. MISRA-C:2004 – Guidelines for the use of the C language in critical systems, 2004.

(Nolte, T. et al., 2005) Nolte, T., Hansson, H., and Bello, L. L. Automotive Communications - Past, Current and Future. In 10th IEEE Conference on Emerging Technologies and Factory Automation (EFTA 2005), volume 1, 2005.

(Nyberg, M. et al., 2001) Nyberg, M., Stutte, T., and Wilhelmi, V. Model based diagnosis of the air path of an automotive Diesel engine. In IFAC Workshop: Advances in Automotive Control, 2001.

(Picardi, C. et al., 2002) Picardi, C., Bray, R., Cascio, F., Console, L., Dague, P., Dressler, O., Millet, D., Rehfus, B., Struss, P., and Valle ́e, C. IDD: Integrating diagnosis in the design of automotive systems. In Proceedings of the Fifteenth European Conference on Artificial Intelligence (ECAI 2002), pages 628 – 632, Lyon, France, July 21 – 26 2002.

(Prestl, W. et al., 2000) Prestl, W., Sauer, T., Steinle, J., and Tschernoster, O. The BMW active cruise control ACC. Society of Automotive Engineers (SAE) Transactions, 109(7):119–125, 2000.

(Pretschner, A. et al., 2007) Pretschner, A., Broy, M., Kru ̈ger, I., and Stauner, T. Software engineering for automotive systems: A roadmap. In Future of Software Engineering (FOSE’07), pages 55 – 71. IEEE Computer Society, Mai 2007.

(Reiter, R., 1987) Reiter, R. A theory of diagnosis from first principles. artificial Intelligence

(Sampath, M. et al., 1995) Sampath, M., Sengupta, R., Lafortune, S., Sinnamohideen, K., and Teneket- zis, D. Diagnosability of discrete-event systems. IEEE Transactions on Automatic Control, 40(9):1555–1575, September 1995.

(Stamatis, D. H., 2003) Stamatis, D. H. Failure Mode and Effect Analysis: FMEA from theory to execution. American Society for Quality (ASQ), 2. edition, 2003.

(Struss, 2006) P. Struss. A model-based methodology for the integration of diagnosis and fault analysis during the entire life cycle. In Proc. of SAFEPRO- CESS 2006. Elsevier, 2006.

(Thiel, S. and Hein, A., 2002) Thiel, S. and Hein, A. Modeling and using product line variability in automotive systems. IEEE Software, 19:66–72, 2002.

(Tripakis, S., 2009) Tripakis, S. A combined on- line/off-line framework for black-box fault diagnosis. In 9th International Workshop on Runtime Verification (RV 2009), pages 152 – 169, Grenoble, France, 2009. Springer
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