TY - JOUR
T1 - Control as an Enabler for Electrified Mobility
AU - Alleyne, Andrew G.
AU - Aksland, Christopher T.
N1 - Publisher Copyright:
Copyright © 2022 by Annual Reviews.
PY - 2022
Y1 - 2022
N2 - This article outlines the importance of electrified mobility (e-mobility) in modern transport. One key goal of this review is to illustrate the role that control has played, and must continue to play, as e-mobility grows. The coordination of power in multiple modes (mechanical, electrical, and thermal) requires sophisticated controller algorithms. This review advocates for model-based approaches to control since there may not be readily available physical systems from which to gather data and do data-based control. A second goal of the article is to present methods for modeling these powertrain systems that are modular, scalable, flexible, and computationally efficient. A graph-based approach satisfies many of the desired criteria. The third goal is to review control approaches for these classes of systems and detail a hierarchical approach that makes trades across different domains of power. Optimization-based approaches are well suited to achieving the regulation and tracking goals, along with the minimization of costs and the satisfaction of constraints. Multiple examples, within this article and the references therein, support the presentation throughout. This field of e-mobility is rapidly growing, and control engineers are uniquely positioned to have an impact and lead many of the critical developments.
AB - This article outlines the importance of electrified mobility (e-mobility) in modern transport. One key goal of this review is to illustrate the role that control has played, and must continue to play, as e-mobility grows. The coordination of power in multiple modes (mechanical, electrical, and thermal) requires sophisticated controller algorithms. This review advocates for model-based approaches to control since there may not be readily available physical systems from which to gather data and do data-based control. A second goal of the article is to present methods for modeling these powertrain systems that are modular, scalable, flexible, and computationally efficient. A graph-based approach satisfies many of the desired criteria. The third goal is to review control approaches for these classes of systems and detail a hierarchical approach that makes trades across different domains of power. Optimization-based approaches are well suited to achieving the regulation and tracking goals, along with the minimization of costs and the satisfaction of constraints. Multiple examples, within this article and the references therein, support the presentation throughout. This field of e-mobility is rapidly growing, and control engineers are uniquely positioned to have an impact and lead many of the critical developments.
KW - Electrified mobility
KW - Graph-based modeling
KW - Hierarchical control
KW - Multidomain modeling
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U2 - 10.1146/annurev-control-042920-012513
DO - 10.1146/annurev-control-042920-012513
M3 - Review article
AN - SCOPUS:85129832453
SN - 2573-5144
VL - 5
SP - 659
EP - 688
JO - Annual Review of Control, Robotics, and Autonomous Systems
JF - Annual Review of Control, Robotics, and Autonomous Systems
ER -