PREDICTIVE POWERTRAIN – N EW OPPORTUNITIES BY NETWORKING SYSTEMS - Proceeding of the 7th European Congress on Embedded Real Time Software and Systems
Conference Papers Year : 2014

PREDICTIVE POWERTRAIN – N EW OPPORTUNITIES BY NETWORKING SYSTEMS

Matthias Schneider
Adrian Thomys
  • Function : Author

Abstract

These days it is not enough to think about downsizing of engines or the use of hybrid systems to keep upcoming CO 2 regulations as well as customer demands. Furthermore most of the vehicles’ components are highly optimized. The realization of further significant optimizations is only possible through a connection between these components. Intensive research activities play a major role in making Bosch a market and innovation leader in electronic powertrain and safety systems. And in diesel and gasoline engines as well, there are technological possibilities for reducing consumption even further. What all powertrains have in common is the potential to reduce emissions and fuel consumption even further through networking of existing vehicle systems across all vehicle domains. The advent of electromobility is bringing together two areas of automotive technology that were traditionally regarded in isolation from one another – powertrains and chassis. Furthermore Bosch links automotive systems with data from the electronic horizon, which senses the vehicle’s environment and provides a detailed preview of the road ahead. Bosch Engineering GmbH is using cross-system networking within a concept vehicle as well as with external systems to develop new functions. The networking of vehicle systems encompasses the ACC (Adaptive Cruise Control), the electronic stability program ESP® and the whole powertrain (ICE and hybrid). Going beyond vehicle systems, automotive systems are also linked to data from the electronic horizon (interface to navigation system), this feature acts as a sensor to the environment to provide a detailed virtual preview of the route ahead. New functions thereby reduce fuel consumption and increase the level of comfort and safety. This paper provides an overview on the system approach and practical developments of Bosch Engineering in this area.
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Dates and versions

hal-02272443 , version 1 (27-08-2019)

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  • HAL Id : hal-02272443 , version 1

Cite

Matthias Schneider, Adrian Thomys. PREDICTIVE POWERTRAIN – N EW OPPORTUNITIES BY NETWORKING SYSTEMS. Embedded Real Time Software and Systems (ERTS2014), Feb 2014, Toulouse, France. ⟨hal-02272443⟩

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