Education, Science, Technology, Innovation and Life
Open Access
Sign In
  1. Home
  2. Journals
  3. Journal of Electrotechnology, Electrical Engineering and Management
  4. Vol 7, Issue 1, 2024

Fault Diagnosis of Sensors for Multi-stack Fuel Cell Thermal Management Subsystem Based on UKF

Download as PDF

DOI: 10.23977/jeeem.2024.070105 | Downloads: 2 | Views: 220

Author(s)

Zhou Su 1, Jiang Yongyuan 1, Gao Jianhua 1

Affiliation(s)

1 College of Automotive Studies, Tongji University, Shanghai, 201804, China

Corresponding Author

Jiang Yongyuan

ABSTRACT

In Multi-stack fuel cell system (MFCS), the thermal management subsystem has various heat dissipation structures and heat dissipation forms, and the stability and accuracy of its operation are important indicators to ensure the safety of the system. In this paper, a water-cooled integrated MFCS thermal management subsystem model is established, and a sensor fault diagnosis method based on Unscented Kalman Filter (UKF) is proposed for the sensor fault in the thermal management subsystem, which adopts the Unscented Transform for the nonlinear system and obtains the estimated value through three processes of prediction, update and iterative calculation. The difference calculation method is adopted to calculate the fused residuals of the UKF estimates and the measured values of the thermal management subsystem sensors to obtain fault information for single or multiple sensors. The results show that the fault diagnosis using the difference method of UKF estimate and the sensor measurements residual signal for the variation of MFCS thermal management subsystem structure and signal acquisition can quickly determine the type and location of single or multiple sensor faults in the thermal management subsystem.

KEYWORDS

Multi-stack fuel cell, Thermal management subsystem, Unscented Kalman Filter, Fault diagnosis, Difference calculation

CITE THIS PAPER

Zhou Su, Jiang Yongyuan, Gao Jianhua, Fault Diagnosis of Sensors for Multi-stack Fuel Cell Thermal Management Subsystem Based on UKF. Journal of Electrotechnology, Electrical Engineering and Management (2024) Vol. 7: 33-41. DOI: http://dx.doi.org/10.23977/jeeem.2024.070105.

REFERENCES

[1] Kwilinski A, Lyulyov O, Pimonenko T. Reducing transport sector CO2 emissions patterns: Environmental technologies and renewable energy [J]. Journal of Open Innovation: Technology, Market, and Complexity, 2024, 10(1): 100217.
[2] Lindstad E, Ask T Ø, Cariou P, et al. Wise use of renewable energy in transport [J]. Transportation Research Part D: Transport and Environment, 2023, 119: 103713.
[3] JIAO Kui, XUAN Jin, DU Qing, et al. Designing the next generation of proton-exchange membrane fuel cells [J]. Nature, 2021, 361-369.
[4] Cullen D A, Neyerlin K C, Ahluwalia R K, et al. New roads and challenges for fuel cells in heavy-duty transportation [J]. Nature Energy, 2021, 462-474.
[5] Zhang G, Zhou S, Gao J, et al. Stacks multi-objective allocation optimization for multi-stack fuel cell systems[J]. Applied Energy, 2023, 331: 120370.
[6] Mehida H, Ayad M Y, Saadi R, et al. Multi-stack fuel cells and interleaved DC/DC converters interactions for embedded applications[C]//2018 International Conference on Electrical Sciences and Technologies in Maghreb (CISTEM). IEEE, 2018: 1-6.
[7] Zhou Su, Fan Lei, Zhang Gang, et al. A review on proton exchange membrane multi-stack fuel cell systems: architecture, performance, and power management [J]. Applied Energy, 2022, 310:118555.
[8] Li Yuehua, Yang Fan, Chen Dongfang, et al. Thermal-physical modeling and parameter identification method for dynamic model with unmeasurable state in 10-kW scale proton exchange membrane fuel cell system[J]. Energy Conversion and Management, 2023, 276:116580.
[9] Dépature C, Boulon L, Sicard P, et al. Simulation model of a multi-stack fuel cell system[C]//2013 15th European Conference on Power Electronics and Applications (EPE). IEEE, 2013: 1-10.
[10] Dijoux E, Steiner N Y, Benne M, et al. A review of fault tolerant control strategies applied to proton exchange membrane fuel cell systems [J]. Journal of Power Sources, 2017, 359(aug.15):119-133.
[11] Mao Lei, Jackson L, Davies B. Effectiveness of a novel sensor selection algorithm in PEM fuel cell on-line diagnosis [J]. IEEE Transactions on Industrial Electronics, 2018:1-1.
[12] Yan Chizhou, Chen Jian, Liu Hao, et al. Model-based Fault Tolerant Control for the Thermal Management of PEMFC Systems [J]. IEEE Transactions on Industrial Electronics, 2019, PP (99):1-1.
[13] Shen D, Yang D, Lyu C, et al. Multi-sensor multi-mode fault diagnosis for lithium-ion battery packs with time series and discriminative features [J]. Energy, 2024, 290: 130151.
[14] Jihani N, Kabbaj M N, Benbrahim M. Kalman filter based sensor fault detection in wireless sensor network for smart irrigation [J]. Results in Engineering, 2023, 20: 101395.

Subscription
E-Mail Alert
Most popular papers
Call for Special Issue
Publication Ethics & OA Statement
Plagiarism Policy
Contact Us
Downloads: 2110
Visits: 99239

Sponsors, Associates, and Links

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.