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Neuroevolution And Machine Learning Research Applied To Connected Automated Vehicle And Powertrain Control, Frédéric F. Jacquelin
Neuroevolution And Machine Learning Research Applied To Connected Automated Vehicle And Powertrain Control, Frédéric F. Jacquelin
Dissertations, Master's Theses and Master's Reports
This dissertation focuses on advancing Predictive Energy Management (PrEM) functions applied to modern connected and automated vehicles (CAV) cohorts. PrEM aims to utilize connectivity and ADAS functions to adaptively minimize vehicle energy consumption in a wide array of operations, extending the original control designed around a reduced set of test cycle procedures to adapt to real-world stochastic operating conditions. This research document is built upon three journal publications covering two PrEM schemes; the global cohort and local vehicle optimization paths. Both optimal control solutions are generated using various Neuroevolution centric processes.
Chapter 1 discusses the methods and reasoning behind the …