On the Creation of a Chess-AI-Inspired Problem-Specific Optimizer for the Pseudo Two-Dimensional Battery Model Using Neural Networks

Dawson-Elli, Neal and Kolluri, Suryanarayana and Mitra, Kishalay and et al, . (2019) On the Creation of a Chess-AI-Inspired Problem-Specific Optimizer for the Pseudo Two-Dimensional Battery Model Using Neural Networks. Journal of The Electrochemical Society, 166 (6). A886-A896. ISSN 0013-4651

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Abstract

In this work, an artificial intelligence based optimization analysis is done using the porous electrode pseudo two-dimensional (P2D) lithium-ion battery model. Due to the nonlinearity and large parameter space of the physics-based model, parameter calibration is often an expensive and difficult task. Several classes of optimizers are tested under ideal conditions. Using artificial neural networks, a hybrid optimization scheme inspired by the neural network-based chess engine DeepChess is proposed that can significantly improve the converged optimization result, outperforming a genetic algorithm and polishing optimizer pair by 10-fold and outperforming a random initial guess by 30-fold. This initial guess creation technique demonstrates significant improvements on accurate identification of model parameters compared to conventional methods. Accurate parameter identification is of paramount importance when using sophisticated models in control applications.

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IITH Creators:
IITH CreatorsORCiD
Mitra, Kishalayhttp://orcid.org/0000-0001-5660-6878
Item Type: Article
Subjects: Chemical Engineering
Divisions: Department of Chemical Engineering
Depositing User: Team Library
Date Deposited: 22 Aug 2019 09:57
Last Modified: 22 Aug 2019 09:57
URI: http://raiithold.iith.ac.in/id/eprint/5999
Publisher URL: http://doi.org/10.1149/2.1261904jes
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