A comparative study of driver torque demand prediction methods-Reference-Cited by-同舟云学术

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A comparative study of driver torque demand prediction methods

Published:2022-10-10 Issue:3 Volume:17 Page:534-546
ISSN:1751-956X
Container-title:IET Intelligent Transport Systems
language:en
Short-container-title:IET Intelligent Trans Sys

Author:

Cavanini Luca¹,Ciabattoni Lucio²,Ferracuti Francesco²^ORCID,Marchegiani Enrico²,Monteriù Andrea²

Affiliation:

1. Industrial Systems and Control Lt Glasgow UK

2. Department of Information Engineering (DII) Università Politecnica delle Marche Via Brecce Bianche 1 Ancona 60131 Italy

Publisher

Institution of Engineering and Technology (IET)

Subject

Law,Mechanical Engineering,General Environmental Science,Transportation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/itr2.12278

Reference45 articles.

1. Unified modeling of hybrid electric vehicle drivetrains

2. Serrao L. Onori S. Rizzoni G.:ECMS as a realization of Pontryagin's minimum principle for HEV control. In:2009 American Control Conference pp.3964–3969.IEEE Piscataway NJ(2009)

3. Stochastic MPC With Learning for Driver-Predictive Vehicle Control and its Application to HEV Energy Management

4. LPV-MPC Path Planner for Autonomous Underwater Vehicles

5. Linear Parameter-Varying Model Predictive Control of AUV for Docking Scenarios

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1. A Systematic Review on the Integration of Artificial Intelligence into Energy Management Systems for Electric Vehicles: Recent Advances and Future Perspectives;World Electric Vehicle Journal;2024-08-13

2. Fixed-size LS-SVM LPV System Identification for Large Datasets;International Journal of Control, Automation and Systems;2023-11-03

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