The inevitable presence of uncertain parameters in critical applications of process
optimization can lead to undesirable or infeasible solutions. For this reason, optimization …

To meet rising demands in performance and emissions compliance, companies are driven
to develop systems of ever-increasing complexity. In-the-loop methods use a hybrid …

Rapidly-evolving connected vehicle technologies offer growing opportunities to improve the
performance of energy management for hybrid electric vehicles (HEVs). In this context, a …

Energy management strategies have been proven to be instrumental in fully realizing the
potential of plug-in hybrid electric vehicles (PHEVs). This paper proposes an improved …

Explicit model predictive control (EMPC) maps offline the control laws as a set of regions as
a function of bounded uncertain parameters using multi-parametric programming. Then, in …

For the last two decades, an extensive transition in automotive X-in-the-loop activities from
isolated electronic control units to real-time related, geographically distributed validation …

The primary objective of a hybrid electric vehicle (HEV) is to optimize the energy
consumption of the automotive powertrain. This optimization has to be applied while …

In order to further increase the efficiency of electrified vehicle drives, various predictive
energy management strategies (driving strategies) have been developed. Therefore, a …

This paper presents an equivalent consumption minimization strategy (ECMS) based on
model predictive control for series hybrid electric mine trucks (SHE-MTs), the objective of …

Abstract Design and optimization of a plug-in hybrid electric vehicle (PHEV) control strategy
is typically based on a backward-looking (BWD) powertrain model, which ensures a high …