W-IFL: An Improved Maximum Power Point Control Model to Promote Renewable-Powered Vehicles

Autor: Shuxin Jin, Mai Hao, Ming Cai
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Applied Sciences, Vol 12, Iss 22, p 11785 (2022)
Druh dokumentu: article
ISSN: 2076-3417
DOI: 10.3390/app122211785
Popis: Driven by economic development and environmental protection, vehicles are gradually renovating their power to renewable energy. As an essential part of renewable energy, photovoltaic (PV) energy is highly valued and studied worldwide. Future social development is inseparable from it when facing the current situation of exhausting fossil energy and highly polluting. To solve the problem of the low utilization of converting solar power to electrical energy, this paper proposes a wavelet-improved fuzzy logic (W-IFL) maximum power point (MPP) control model. The W-IFL designs a wavelet network for predicting the MPP and fuzzy rules for tracking the MPP, which achieves full online control on the basis of a neural-fuzzy structure. Comparative analysis indicates that W-IFL outperforms other widely used MPP tracking (MPPT) methods, which reduces oscillation at MPP, prediction error, and tracking time, and improves training efficiency and controlling ability, thus making it more rational to promote the development of the vehicle industry.
Databáze: Directory of Open Access Journals