Work

A Fuzzy Energy Management Strategy Based on Grey Bernoulli Prediction for Fuel Cell Vehicle

Year: 2026

Type: article

Abstract: Proton exchange membrane fuel cell vehicles (PEMFCVs) have attracted widespread attention in recent years. However, there are many challenges existing in the development, such as the durability and economy of the fuel cell system (FCS). In this investigation, a fuzzy energy management strategy based on Grey Bernoulli Prediction (FEMS-GBP) is proposed to mitigate these two issues. Grey Bernoulli Prediction (GBP) is used to predict the FCS short-term future power demand with a low calculation amount, which is suitable for real-time on-board applications in PEMFCVs. Therefore, FEMS-GBP can proactively adjust FCS output power to reduce large load change times during PEMFCV operation, thereby improving FCS durability. Fuzzy control is employed to accomplish the energy management task between the FCS and the battery for better fuel economy. Numerical simulations and experiments under different vehicle driving cycles are carried out to evaluate the performance of FEMS-GBP. By comparing it with two other conventional energy management strategies, FEMS-GBP is demonstrated to be feasible and effective, as it achieves favorable performance in balancing durability and economy, especially under practical driving conditions.

Source: Applied Sciences

DOI: 10.3390/app16094211

Authors: Jianshan Lu, Yingjia Li, Hongbo Zhou

Institution: Zhejiang University of Technology

Language: English

Topic: Electric and Hybrid Vehicle Technologies

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

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

Open Access status: gold

Estimated APC paid: $2,896