Recurrent Neural Network-Based Nonlinear Optimization for Braking Control of Electric Vehicles

Recurrent Neural Network-Based Nonlinear Optimization for Braking Control of Electric Vehicles

In this paper, electro-hydraulic braking (EHB) force allocation for electric vehicles (EVs) is modeled as a constrained nonlinear optimization problem (NOP). Recurrent neural networks (RNNs) are advantageous in many folds for solving NOPs, yet existing RNNs’ convergence usually requires convexity wi...

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Bibliographic Details
Main Authors: Jiapeng Yan, Huifang Kong, Zhihong Man
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Energies
Subjects:
recurrent neural network (RNN)
nonlinear optimization problems (NOP)
electric vehicle (EV)
electro-hydraulic braking (EHB)
asymptotical convergence
Online Access:https://www.mdpi.com/1996-1073/15/24/9486

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