In this review paper, the integration of Machine Learning (ML) and Model Predictive Control
(MPC) in Automotive Control System (ACS) applications are discussed. ACS can be divided …

Abstract Machine learning (ML) and a nonlinear model predictive controller (NMPC) are
used in this paper to minimize the emissions and fuel consumption of a compression ignition …

Abstract Artificial Neural Network (ANN) and Support Vector Machine (SVM) methods are
designed to accurately predict Laminar Flame Speed (LFS) over the entire engine operating …

At present, regression modeling methods fail to achieve higher simulation accuracy, which
limits the application of simulation technology in more fields such as virtual calibration and …

Engine development needs to reduce costs and time. As the current main development
methods, 1D simulation has the limitations of low accuracy, and 3D simulation is a long, time …

Zero carbon fuels can be used to reduce CO 2 emissions from internal combustion engines.
Hydrogen is an important zero-carbon fuel that can be used as the primary fuel for spark …

A deep reinforcement learning application is investigated to control the emissions of a
compression ignition diesel engine. The main purpose of this study is to reduce the engine …

The high thermal efciency and reliability of the compression-ignition engine makes it the first
choice for many applications. For this to continue, a reduction of the pollutant emissions is …

Laser beam welding offers high productivity and relatively low heat input and is one key
enabler for efficient manufacturing of sandwich constructions. However, the process is …

The use of data-driven algorithms for the integration or substitution of current production
sensors is becoming a consolidated trend in research and development in the automotive …