Hybrid physics-data-driven online modelling: Framework, methodology and application to electric vehicles-Reference-Cited by-同舟云学术

Hybrid physics-data-driven online modelling: Framework, methodology and application to electric vehicles

Published:2023-02 Issue: Volume:185 Page:109791
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Chen Hao^ORCID,Lou Shanhe^ORCID,Lv Chen^ORCID

Funder

Agency for Science, Technology and Research

Nanyang Technological University

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference28 articles.

1. From model-based control to data-driven control: Survey, classification and perspective;Hou;Inform. Sci.,2013

2. Coupled longitudinal and lateral control of a vehicle using deep learning;Devineau,2018

3. Intelligent identification of vehicle’s dynamics based on local model network;Abtahi;J. AI Data Min.,2019

4. Modelling longitudinal vehicle dynamics with neural networks;Da Lio;Veh. Syst. Dyn.,2020

5. A novel data-driven control approach for a class of discrete-time nonlinear systems;Hou;IEEE Trans. Control Syst. Technol.,2010

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