Abstract The Energy Management Strategy (EMS) in an HEV is the key for improving fuel
economy and simultaneously reducing pollutant emissions. This paper presents a …

Today's computer-based vehicle operation simulators use engine speed, engine torque, and
lookup tables to predict emissions during a driving simulation [1]. This approach is used …

The development and calibration of modern combustion engines is challenging in the area
of continuously tightening emission limits and the necessity for meeting real driving …

In this paper an artificial neural network (ANN) approach to modelling fuel consumption of
heavy duty vehicles is presented. The proposed method uses easy accessible data …

With rapid urbanization and industrialization, the number of light-duty gasoline vehicles
(LDGVs) in China has continued to grow rapidly, leading to a significant increase in traffic …

This paper presents a two-stage emissions predictive model developed by investigating
common feedforward neural network models. The first stage model involves predicting …

West Virginia University has conducted research to characterize the emissions from medium-
duty vehicles operating on Fischer-Tropsch synthetic gas-to-liquid compression ignition fuel …

Accurately and efficiently predicting the fuel consumption of vehicles is the key to improving
their fuel economy. This paper provides a comprehensive review of data-driven fuel …

Portable emission measurement system (PEMS) testing, which is the most accurate
measurement method for vehicle emissions, has been included into the regulations of …

In this paper, a methodology based on data-driven models is developed to predict the NOx
emissions of an internal combustion engine using, as inputs, a set of ECU channels …