Solid oxide fuel cell system emulation by multi-renewable working fluids for efficient energy conversion

  • Junhan Cheng

Student thesis: Doctoral ThesisDoctor of Philosophy


The world targets carbon neutral attracting more attention to renewable energy sources and their effective application. Hydrogen as a primary form of fuel is of crucial importance to achieve global aiming, which requires high efficiency, renewable power generation technologies but facing difficulty on its production and storage. Plenty of hydrogen carriers bring a new horizon for future application but its terminal application technology with high efficiency and demonstration doesn’t appear.

Solid oxide fuel cell has the natural advantage on multi-fuel selectivity which bring its wide application with different fuel sources and future power generation technology with promising future. The commercial SOFC system request comprehensive property understanding, diagnosis and system design. The hotbox unit requests the validation for the thermal balance of the SOFC system which integrates with the pre-reformer, SOFC unit, exhaust combustor and heat exchanger. A comprehensive and commercial-aimed model design and simulations are necessary for the SOFC system property understanding of its multi-fuel property.

In this thesis, a complicated and validated semi-empirical SOFC module has been conducted with multi-function to accurately predict the real working condition for the SOFC system design. The hydrogen, ammonia, DME, methanol, and CH4 as primary hydrogen carrier presents its SOFC property difference and operation strategy. The SOFC system emulation result shows the control strategy and feasibility of SOFC application for domestic applications.

Thesis is embargoed until 31 December 2024.
Date of AwardDec 2022
Original languageEnglish
Awarding Institution
  • Queen's University Belfast
SponsorsThe Bryden Centre
SupervisorDavid Rooney (Supervisor) & Chunfei Wu (Supervisor)


  • Solid oxide fuel cell
  • Hydrogen
  • Simulation model
  • Ammonia
  • Methanol
  • Methane
  • DME
  • Optimization
  • Demonstration
  • Semi-empirical model

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