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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.

A new approach is proposed for fault detection. It builds on using the relationships between sensor values on vehicles to detect deviating sensor readings and trends in the system performance. However, in contrast to previous approaches based on such sensor relations, our approach uses a fleet of vehicles to define the normal conditions and relations. The relationships between the sensors are also determined automatically in a self-organized way on each vehicle, i.e. no off-line modeling is required. The proposed method is the first step in a remote diagnostics and maintenance service where error detection is done automatically, followed by a download of special purpose diagnostics software for the particular subsystem where the possible fault was detected.