Engine downsizing is a promising method to reduce emissions and fuel consumption of
internal combustion engines. The main concept is reducing engine displacement volume …

This article employs surrogate models for large-scale high-speed (HS) electrical machine
optimization to reduce heavy computational burden caused by the finite-element method …

Deep reinforcement learning (DRL) is an area of machine learning that combines a deep
learning approach and reinforcement learning (RL). However, there seem to be few studies …

In order to reduce pollutant and CO2 emissions and fulfill future legislative requirements,
powertrain electrification is one of the key technologies. In this context, especially 48V …

The electric turbocharger (ET) is a promising solution for engine downsizing. It provides
great potential for vehicle fuel efficiency improvement. The ET makes engines run as hybrid …

The impact of assisted boosting technologies on the ability to maintain desired exhaust gas
recirculation is investigated. Regenerative electrically assisted turbocharging is a promising …

Deep reinforcement learning (DRL), which excels at solving a wide variety of Atari and
board games, is an area of machine learning that combines the deep learning approach and …

This study presents an assessment focused on benchmarking the energy distribution and
engine efficiency of a pre-2014, United States Environmental Protection Agency (USEPA) …

Turbocharged diesel engines often suffer significant response delay due to so-called turbo-
lag, especially engines with large displacement. For this reason, many technologies have …

By Yifan Men This dissertation presents the reaction-based modeling of diesel combustion
and model-based control of diesel engine air path. The dissertation first presents a control …