Scientific advances and impacts
The research has developed and demonstrated
- (i) a comprehensive PEM fuel model, using a bond graph approach, encapsulated within a reliability assessment framework of petri nets
- (ii) a strategy for diagnostic evaluation using data based and model based methods and
- (iii) a knowledge based model offering greater insight into diagnostics.
These scientific advances have made a significant contribution to the academic literature, including, journal publications and multiple national and international conference presentations (as listed in the Resources section).
Industrial impact
This research is supported by Intelligent Energy and with these enhanced modelling capabilities, including quantification of the likelihood of PEM fuel cell stack failure degradation, alongside the diagnostic capability, will enable them and related industry to better evaluate the performance of their systems. The development of the reusable knowledge based model has potential for use across industry.
Public & social impact
Society and the public will benefit from the capability of longer life of fuel cell products through increased diagnostics and mitigation strategies, reducing overall costs and increasing likelihood for utilisation in differing fields.
Economic impact
The steps forward in this project will pave the way for reduced costs in supporting the operation of PEM fuel cells, with longer lifetimes.
Economic impact
The steps forward in this project will pave the way for reduced costs in supporting the operation of PEM fuel cells, with longer lifetimes.
Policy impact
Advanced capabilities in current fuel cell applications could enable policy makers to make more informed decisions regarding use of this techniques in society for other applications.
International impact
Collaborative meeting planned with Brno University of Defence, in Czech Republic, in March 2018, regarding uses and advances of this research.
Other impact
Two PhDs aligned to this research proposal are both in the writing up phase.
Outcomes
Scientific advances and impacts
The research has developed and demonstrated
- (i) a comprehensive PEM fuel model, using a bond graph approach, encapsulated within a reliability assessment framework of petri nets
- (ii) a strategy for diagnostic evaluation using data based and model based methods and
- (iii) a knowledge based model offering greater insight into diagnostics.
These scientific advances have made a significant contribution to the academic literature, including, journal publications and multiple national and international conference presentations (as listed in the Resources section).
Industrial impact
This research is supported by Intelligent Energy and with these enhanced modelling capabilities, including quantification of the likelihood of PEM fuel cell stack failure degradation, alongside the diagnostic capability, will enable them and related industry to better evaluate the performance of their systems. The development of the reusable knowledge based model has potential for use across industry.
Public & social impact
Society and the public will benefit from the capability of longer life of fuel cell products through increased diagnostics and mitigation strategies, reducing overall costs and increasing likelihood for utilisation in differing fields.
Economic impact
The steps forward in this project will pave the way for reduced costs in supporting the operation of PEM fuel cells, with longer lifetimes.
Economic impact
The steps forward in this project will pave the way for reduced costs in supporting the operation of PEM fuel cells, with longer lifetimes.
Policy impact
Advanced capabilities in current fuel cell applications could enable policy makers to make more informed decisions regarding use of this techniques in society for other applications.
International impact
Collaborative meeting planned with Brno University of Defence, in Czech Republic, in March 2018, regarding uses and advances of this research.
Other impact
Two PhDs aligned to this research proposal are both in the writing up phase.