Diagnostic Method Combining Map and Fault Models Applied on a Hybrid Electric Vehicle
2014 (English)Manuscript (preprint) (Other academic)
A common situation in the automotive industry is that map based models are available. In general these models accurately describe the fault free system, and are therefore suited for fault detectability in a diagnosis system. However, one drawback using such a model is that fault isolation then requires that measurements of the faulty system is done, which is costly. Another approach is to use a model of the system where the faults are explicitly included. To directly achieve good diagnostic performance such a model needs to be accurate, which also is costly. Therefore, in the new approach taken here, two models are used in combination to achieve both good fault detectability and isolability in a diagnosis system; one is a map based model, and one is describing how the faults affect the system. The approach is exemplified by designing a diagnosis system monitoring the power electronics and the electric machine in a hybrid electric vehicle. In an extensive simulation study it is shown that the approach works well and is a promising path to achieve both good fault detectability and isolability performance, without the need for neither measurements of a faulty system nor detailed physical modeling. In the designed diagnosis system all faults are fully isolated, and the size of the faults are accurately estimated.
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IdentifiersURN: urn:nbn:se:liu:diva-105486OAI: oai:DiVA.org:liu-105486DiVA: diva2:707683