Connected and automated road vehicles: state of the art and future challenges

T Ersal, I Kolmanovsky, N Masoud, N Ozay… - Vehicle system …, 2020 - Taylor & Francis
The state of the art of modelling, control, and optimisation is discussed for automated road
vehicles that may utilise wireless vehicle-to-everything (V2X) connectivity. The appropriate …

Trends in onroad transportation energy and emissions

HC Frey - Journal of the Air & Waste Management Association, 2018 - Taylor & Francis
ABSTRACT Globally, 1.3 billion on-road vehicles consume 79 quadrillion BTU of energy,
mostly gasoline and diesel fuels, emit 5.7 gigatonnes of CO2, and emit other pollutants to …

Flexible spacing adaptive cruise control using stochastic model predictive control

D Moser, R Schmied, H Waschl… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
This paper proposes a stochastic model predictive control (MPC) approach to optimize the
fuel consumption in a vehicle following context. The practical solution of that problem …

A logical network approximation to optimal control on a continuous domain and its application to HEV control

Y Wu, J Zhang, T Shen - Science China Information Sciences, 2022 - Springer
The finite-time horizon optimal control problem is investigated for discrete-time dynamical
systems defined on a continuous domain. First, the original optimal control problem in the …

A review on control system architecture of a SI engine management system

B Ashok, SD Ashok, CR Kumar - Annual Reviews in Control, 2016 - Elsevier
Engine management systems (EMS) has become an essential component of a spark ignition
(SI) engine in order to achieve high performance; low fuel consumption and low exhaust …

Mixture density networks-based knock simulator

X Shen, T Ouyang, C Khajorntraidet, Y Li… - IEEE/ASME …, 2021 - ieeexplore.ieee.org
The engine knock simulator is useful for the evaluation of the feedback knock controllers and
also the calibration of the feedforward control input without experiments in spark-ignition …

Gaussian mixture model clustering-based knock threshold learning in automotive engines

X Shen, Y Zhang, K Sata, T Shen - IEEE/ASME Transactions on …, 2020 - ieeexplore.ieee.org
In this article, a Gaussian mixture model (GMM) clustering-based method is proposed to
learn the optimal threshold of the knock intensity metric, which minimizes the probability of …

Adaptive operation strategy of a polymer electrolyte membrane fuel cell air system based on model predictive control

S Hahn, J Braun, H Kemmer, HC Reuss - International Journal of Hydrogen …, 2021 - Elsevier
The present article investigates a model predictive control-based operation strategy of an
automotive fuel cell air system. For this purpose, a nonlinear model of a fuel cell system is …

Spark advance self-optimization with knock probability threshold for lean-burn operation mode of SI engine

X Shen, Y Zhang, T Shen, C Khajorntraidet - Energy, 2017 - Elsevier
In this paper, a spark advance self-optimization strategy is presented for lean-burn operation
mode of spark-ignition (SI) engine which aims on-board combustion phase tuning to achieve …

Model predictive emissions control of a diesel engine airpath: Design and experimental evaluation

D Liao‐McPherson, M Huang, S Kim… - … Journal of Robust …, 2020 - Wiley Online Library
This article presents the development and experimental validation of an emissions oriented
model predictive controller for a diesel engine. The control objective is to minimize …