| EPSRC Reference: |
EP/P012620/1 |
| Title: |
SURROGATE ASSISTED APPROACHES FOR FUEL CELL AND BATTERY MODELS |
| Principal Investigator: |
Shah, Dr AA |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Sch of Engineering |
| Organisation: |
University of Warwick |
| Scheme: |
Overseas Travel Grants (OTGS) |
| Starts: |
11 November 2016 |
Ends: |
10 September 2017 |
Value (£): |
66,497
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| EPSRC Research Topic Classifications: |
| Energy Storage |
Fuel Cell Technologies |
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| EPSRC Industrial Sector Classifications: |
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Summary on Grant Application Form |
Physics-based simulation codes for fuel cells and batteries are highly complex, involving coupled nonlinear PDEs, numerous constitutive laws, complex geometries, multiphase transport and multiple layers with disparate spatial scales. Even for relatively simplified geometries and single scales, they can be highly expensive to run. In many important applications, however, accurate but rapid simulations are essential, rendering these full, 'high-fidelity' models impractical. To lower the computational burden, surrogate models can be employed as approximations.
Given the complexity of fuel cell and battery models, the vast number of parameters they involve and the unavoidable uncertainties in parameter values and model assumptions, there is enormous scope for developing surrogates for application that include, but are not limited to, Design optimization (DO), Sensitivity analysis (SA), Uncertainty quantification (UQ), real-time control and inverse parameter estimation. These areas represent the next-generation challenges for those working in fuel cell and battery modelling and the activities within this proposal are aimed at establishing a systematic programme of research activity at the forefront of these areas through fundamental developments combined with large-scale applications, with a focus on high-dimensional (spatio-temporal) data sets.
The focus in this project is on establishing an ambitious long term activity for predictive modelling for DO, SA and UQ by developing and implementing new surrogate assisted approaches, specifically for patio-temporal models (very high dimensional input and output spaces). General frameworks for DO, SA and UQ (using the surrogate models) will be explored and tested on high-fidelity models of H2 fuel cells and vanadium flow batteries. The methods developed will be of direct relevance to other areas such as real-time control and inverse parameter estimation, and will be directly applicable to other fuel cell/battery systems.
We wish to explore a number of ambitious surrogate-assisted approaches building upon our very recent work. The overseas visits will allow us to identify promising methods, which will form the basis of collaborative work over the next few years on all aspects listed above. The lists will establishing/reinforcing international collaborations and will form the foundations for establishing internationally-leading activity in battery and fuel cell modelling with respect to the current and future challenges faced in modelling, developing and commercialising these technologies.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.warwick.ac.uk |