A Fuzzy Energy Management Strategy Based on Grey Bernoulli Prediction for Fuel Cell Vehicle
Source abstract
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: crossref · Quality: baseline
Research context
OpenAlex topics: Fuel Cells and Related Materials · Electric and Hybrid Vehicle Technologies · Advanced Battery Technologies Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310012, China
Jinhua HydroT Technology Company Ltd., Jinhua 321025, China
Zhejiang HydroT Technology Company Ltd., Hangzhou 311400, China
Funding
Zhejiang Provincial Natural Science Foundation · Science and Technology Department of Zhejiang Province · Jinhua Municipal Science and Technology Bureau
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