Genetic Algorithm Based Back-Propagation Neural Network Approach for Fault Diagnosis in Lithium-ion Battery System

Gao, Z; Chin, CS; Woo, WL; Jia, JB; Toh, WD

doi:10.1109/PESA.2015.7398911

Genetic Algorithm Based Back-Propagation Neural Network Approach for Fault Diagnosis in Lithium-ion Battery System

Lookup NU author(s): Professor Cheng Chin, Dr Wai Lok Woo

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Abstract

In this paper, Genetic Algorithm (GA) is integrated to build a single hidden layer Back-Propagation Neural Network (BPNN) for fault diagnosis. In the process of training the neural network, GA is used to initialize and optimize the connection weights and thresholds of the neural network. Several faults are detected by the proposed GA optimized fault diagnosis scheme. Simulation results show that the proposed fault diagnosis scheme provides satisfactory results.