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Next generation drivetrain concept featuring self-learning capabilities enabled by extended information technology functionalities

: Otto, A.; Rzepka, S.


Schulze, T.:
Advanced Microsystems for Automotive Applications 2016 : Smart Systems for the Automobile of the Future; This book contains the papers presented at the 20th anniversary edition of the AMAA conference held in Brussels, Belgium in 2016
Cham: Springer International Publishing, 2016 (Lecture notes in mobility)
ISBN: 978-3-319-44766-7 (Online)
ISBN: 978-3-319-44765-0 (Print)
International Forum on Advanced Microsystems for Automotive Applications (AMAA) <20, 2016, Brussels>
Fraunhofer ENAS ()

With the introduction of electrified drive-trains and autonomous driving features, the requirements for electronic systems in vehicles have rapidly become more and more demanding. In order to face these complex requirement scenarios, a paradigm shift from closed-loop-controlled to truly self-deciding and self-learning automata is strongly needed. In this paper, a novel concept for drive-train platforms enabling self-learning capabilities based on sensor integration, micro and power electronics and secure cloud communication directly integrated into the electric motor will be introduced.