Fault diagnosis of new energy vehicles based on PSO-IBP neural network

Chengwu Liu, Han Liu and Yinyuan Qiu

International Journal of Low-Carbon Technologies, 2025, vol. 20, 1104-1111

Abstract: This paper proposes a fault diagnosis method for wireless charging system (WCS) of new energy vehicles based on Particle Swarm Optimization (PSO)-IBP. Firstly, the momentum factor and learning rate of back propagation (BP) neural network are optimized. Secondly, the improved BP neural network and PSO algorithm are fused to improve the fault diagnosis accuracy. Finally, taking the fault of charging equipment of new energy vehicles as an example, it is verified that the proposed method can achieve fast and accurate fault diagnosis in the WCS of new energy vehicles.

Keywords: new energy vehicles; charging equipment; fault diagnosis; PSO-IBP network; momentum factor (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:oup:ijlctc:v:20:y:2025:i::p:1104-1111.

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