Self-organized Modeling for Vehicle Fleet Based Fault Detection 2008-01-1297
Operators of fleets of vehicles desire the best possible availability and usage of their vehicles. This means the preference is that maintenance of a vehicle is scheduled with as long intervals as possible. However, it is then important to be able to detect if a component in a specific vehicle is not functioning properly earlier than expected (due to e.g. manufacturing variations). This paper proposes a telematic based fault detection scheme for enabling fault detection for diagnostics by using a population of vehicles. The basic idea is that it is possible to create low-dimensional representations of a sub-system or component in a vehicle, where the representation (or model parameters) of a vehicle can be monitored for changes compared to the model parameters observed in a fleet of vehicles. If a model in a vehicle is found to deviate compared to a group of models from a fleet of vehicles, then the vehicle is judged to need diagnostics for that component (assuming the deviation in the model cannot be attributed to e.g. a different driver behavior). The representation should be low-dimensional so it is possible to have it transferred over a limited wireless communication channel to a communications center where the comparison is made. The algorithm is shown to be able to detect leakage on simulated data from a cooling system, work is currently in progress for detecting other types of faults.