Work

Data-driven Degradation-Aware Model Predictive Control for Power Electronics

Year: 2024

Type: conference-paper

Abstract: With the development of artificial intelligence, the control strategies for critical power devices has a diversity such that more reliability solution can be guaranteed in diversity complicated working condition. LC-inverter is known as one of the most applied power conversion equipment nowadays due to the significantly increasing demand for more electrical transportation and multiple renewable energy source generation. To address the challenge of developing a degradation-aware control strategy, this paper intend to incorporates a novel degradation to the finite-set model predictive control for the LC inverter.

Source: Proceedings of the Annual Conference of the IEEE Industrial Electronics Society

DOI: 10.1109/iecon55916.2024.10905162

Authors: QiAn He, Junyan Shao, Juan C. Vasquez, Baoze Wei

Institution: Aalborg University

Language: English

Topic: Multilevel Inverters and Converters

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy

Open Access status: green

OpenAlex ID: W4408281763

FWCI: 0.806

Cites: 19

Cited by: 1

Related to: 10