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2024 | OriginalPaper | Buchkapitel

A Novel Real-Time Data-Based PEMFC Performance Evaluation Model Using Improved PCA-Kmeans-XGBoost for PEMFC Hybrid Vehicles in China

verfasst von : Xinjie Yuan, Linlin Zhuang, Zhongjun Hou

Erschienen in: Proceedings of China SAE Congress 2023: Selected Papers

Verlag: Springer Nature Singapore

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Abstract

Proton exchange membrane fuel cell (PEMFC) with its zero emission and high efficiency is gradually being applied for clean transportation in China. In the quest to achieve higher economic efficiency of PEMFC hybrid vehicles, data-driven modelling methods are being developed in response to the complicated physicochemical phenomena of PEMFC systems. However, there is little research detailing the importance of balance of plants (BOP) features of the hydrogen anode, air cathode and cooling subsystems regarding PEMFC system efficiency at different driving styles. Furthermore, most research applies neural networks based on simulation and bench data rather than dynamic vehicle operation data, which leads to low robustness and unreliable practical results. Accordingly, this paper provides a novel application of the combination of a power-related feature extraction method, an unsupervised dimension reduction method, an unsupervised cluster method and an ensemble learning method, named PCA-Kmeans-XGBoost, to explore the relationship among controllable BOP features, PEMFC system efficiency and driving styles using real-time vehicle datasets. A case study of a PEMFC logistics vehicle is conducted based on the data at the size of 312,641 running in Shanghai in November 2022. The economic analysis explores the clustered driving styles with high power ranges and frequent power requests take 40.9% of the monthly hydrogen consumption per 100 km. The BOP features of the hydrogen and the air subsystems alternately rank top according to the characteristics of the three clustered power profiles. A comparative analysis and a verification study are performed to demonstrate the importance and the robustness of the proposed approach.

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Titel: A Novel Real-Time Data-Based PEMFC Performance Evaluation Model Using Improved PCA-Kmeans-XGBoost for PEMFC Hybrid Vehicles in China
verfasst von: Xinjie Yuan
Linlin Zhuang
Zhongjun Hou
Verlag: Springer Nature Singapore
Buch: Proceedings of China SAE Congress 2023: Selected Papers
Print ISBN: 978-981-9702-51-0

Electronic ISBN: 978-981-9702-52-7

Copyright-Jahr: 2024
DOI: https://doi.org/10.1007/978-981-97-0252-7_95

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