Fleet Analytics – a data-driven and synergetic fleet validation approach

Current developments in automotive industry such as electrification of powertrains and continuously increasing demands from legislation (e.g. emission control systems), are pushing system complexity still further. Validation of such systems lead to a huge amount of test cases and hence extreme testing efforts on different system levels – but also on road. At the same time the pressure to reduce costs and minimize time-to-market are creating challenging boundaries on development teams. Therefore, it is of utmost importance to utilize testing and validation prototypes in the most efficient way. On the one hand it is necessary to apply high levels of instrumentation and collect as much data as possible. On the other hand, a streamlined data pipeline is required to enable the fleet managers and domain stakeholders to get new insights from the measurement data and steer the validation vehicles as well as the development team in the most efficient way. In this paper we will demonstrate a data-driven approach for validation testing. Managing the requirements and deriving the test cases is essential to continuously monitor the testing progress and leverage synergies between the test activities. Digitalization of the vehicle meta data as well as the driver feedback and combining this information with the measurement data enables new ways of analytics. Latest technologies in advanced data science are applied to provide a new level of automation. Digitalization of the validation process and advanced data analytics can provide great benefits such as reduction of prototypes needed and reduced testing time of fleets. But also lead to improved product quality due to verified test case coverage.