ReDi2Service
Remote Diagnostic Tools and Services
ReDi2Service | |
Project start: | |
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1 April 2009 | |
Project end: | |
31 December 2013 | |
More info (PDF): | |
Contact: | |
Thorsteinn Rögnvaldsson | |
Application Area: | |
Intelligent Vehicles | |
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Abstract
Cost and energy efficient transports requires methods for maximizing vehicle up-time at low (or minimal) cost. To do this requires low cost methods that can gauge vehicle health status so that unplanned stops are prevented and maintenance is optimally planned. Modern vehicles have communication networks where signals are sent back and forth between different control units and sensors. This is a continuous stream of data on each vehicle and a fleet of vehicles are a mobile database of streaming data. We develop methods for data mining this database of data streams, combined with in-house databases at Volvo, in order to discover relationships and events that can be used to gauge and predict vehicle health. An important aspect is to use currently available sensors and signals on-board, i.e. no additional sensors, and increase their usefulness by combining them with additional information. We also study how such methods can be exploited in services.
The project consists of two parts, one technical part that involves diagnostics and prediction of maintenance. This involves continuing the work from the previous project (Remote Diagnostics & Maintenance), but with a focus on methods for diagnosing faults (using multiple vehicles). The second part involves the business models and services that can be developed from the technical solutions. This involves e.g. studying the requirements on the information infrastructure and identifying relevant customers.
The project is funded by VINNOVA within the FFI (Fordonsstrategisk Forskning och Innovation) programme "Transporteffektivitet".
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