Fault Diagnosis Strategy of Four-Switch Buck-Boost Converter Based on BP Neural Network Optimized by Particle Swarm Optimization
- Resource Type
- Conference
- Authors
- Liu, Xueqi; Zhang, Xin; Hu, Kexin
- Source
- 2023 IEEE 18th Conference on Industrial Electronics and Applications (ICIEA) Industrial Electronics and Applications (ICIEA), 2023 IEEE 18th Conference on. :1175-1180 Aug, 2023
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Fault diagnosis
Industrial electronics
Fourier transforms
Simulation
Neural networks
Feature extraction
Electric vehicles
Four-switch Buck-Boost (FSBB)
BP neural network
particle swarm optimization algorithm (PSO)
Fast Fourier Transform (FFT)
- Language
- ISSN
- 2158-2297
The four-switch Buck-Boost converter (FSBB) is widely used in the field of new energy power generation and electric vehicles, and the complexity of its operation mode brings difficulties to fault diagnosis. This paper designs a diagnostic framework that integrates the back propagation (BP) neural network and the particle swarm optimization algorithm (PSO), and realizes the diagnosis of the switches in different modes of the FSBB converter. Effective diagnosis of single-switch open circuit faults and double-switch open circuit faults. Simulation results show that the method has high diagnostic accuracy.