Periodic Reporting for period 3 - RUBY (Robust and reliable general management tool for performance and dUraBility improvement of fuel cell stationarY units)
Período documentado: 2023-08-01 hasta 2024-12-31
Fuel Fells (FCs) are becoming more and more attractive for real world applications, their performance meet the strong constraints imposed by regulations and international policies aiming at reducing the carbon footprint of power systems. Despite the noticeable improvements attained in the last decade, still the competitiveness with respect to conventional solutions is yet to be achieved for FCs efficiency, reliability, availability and durability. The implementation on FC Systems of suitable control, diagnostic and prognostic algorithms can improve those performance, making FC more efficient and competitive. The project covers the areas of Proton Exchange Membrane FC (PEMFC) backup and Solid Oxide FC (SOFC) µ-CHP systems that are among the most mature stationary FC solutions available on the market today.
The project aims at developing, integrating, engineering and testing a comprehensive and generalized Monitoring, Diagnostic, Prognostic and Control (MDPC) tool capable of improving efficiency, reliability and durability of SOFC and PEM systems for stationary applications. The MDPC tool features Electrochemical Impedance Spectroscopy-based stack monitoring for fault diagnosis and lifetime estimation, Balance of Plant diagnostics, supervisory RTO control and mitigation strategies. The tool relies on advanced dedicated HW and will be embedded in the Fuel Cell Systems (FCSs) for on-line validation in relevant operational environment.
Therefore, the RUBY tool will reach at the end of the project the TRL 7. It is foreseen that the tool will be ready for engineering scaling up of production, together with certification for embedding within commercial FCS.
To successfully fulfil the aims of RUBY, the following four main technical objectives were set:
1. Improve FCS performance and durability by implementing an advanced and integrated algorithm that combines monitoring, diagnosis, prognosis, control and mitigation actions for both SOFC and PEM systems.
2. Design and engineer the HW required for MDPC algorithms application, with attention to sensors reduction issues and the specific constraints imposed by stack technologies and systems applications towards industrial scalability.
3. Perform dedicated experimental campaigns for stacks and system characterization and MDPC tool prototype validation embedded on FCSs running in operational environment.
4. Develop an advanced FCS management strategy (supervisory level), with functionalities integrated with remote monitoring, for future smart-grid interaction and predictive maintenance application.
The project aims at developing, integrating, engineering and testing a comprehensive and generalized Monitoring, Diagnostic, Prognostic and Control (MDPC) tool capable of improving efficiency, reliability and durability of SOFC and PEM systems for stationary applications. The MDPC tool features Electrochemical Impedance Spectroscopy-based stack monitoring for fault diagnosis and lifetime estimation, Balance of Plant diagnostics, supervisory RTO control and mitigation strategies. The tool relies on advanced dedicated HW and will be embedded in the Fuel Cell Systems (FCSs) for on-line validation in relevant operational environment.
Therefore, the RUBY tool will reach at the end of the project the TRL 7. It is foreseen that the tool will be ready for engineering scaling up of production, together with certification for embedding within commercial FCS.
To successfully fulfil the aims of RUBY, the following four main technical objectives were set:
1. Improve FCS performance and durability by implementing an advanced and integrated algorithm that combines monitoring, diagnosis, prognosis, control and mitigation actions for both SOFC and PEM systems.
2. Design and engineer the HW required for MDPC algorithms application, with attention to sensors reduction issues and the specific constraints imposed by stack technologies and systems applications towards industrial scalability.
3. Perform dedicated experimental campaigns for stacks and system characterization and MDPC tool prototype validation embedded on FCSs running in operational environment.
4. Develop an advanced FCS management strategy (supervisory level), with functionalities integrated with remote monitoring, for future smart-grid interaction and predictive maintenance application.
The main achievements at end of 3rd Period are:
- Diagnostic and prognostic algorithms for PEMFC and SOFC finalised, verified and coded for implementation in the RUBY Box.
- Successful field testing of RTO resulted in an increase of 10% of the electrical efficiency.
- Design of mitigation strategies to reduce degradation rate and perform stack recovery from reversible degradation.
- Data acquisition via MDPC board successfully performed.
- Design and upgrade of commercial DC/DC converter for on-board EIS implementation.
- Installation of RUBY Box and DC/DC converter on both PEMFC backup and µ-CHP SOFC systems.
- RUBY Box interfaced with DC/DC converter for EIS functions.
- Successful testing of DC/DC converter and acquisition of data for the EIS of PEMFC.
- Integration of MDPC tool in the testing infrastructure at EIFER (PEM system) and EPFL (SOFC system).
- Testing of the communication system among all components (HW & SW) of both systems.
- Test campaign started.
An analysis was conducted to develop MDPC tools for PEM and SOFC technologies. Various algorithms were designed using data from FCSs manufacturers and lab measurements. It was developed an innovative fault isolation method for SOFC technology, machine learning and deep learning techniques. Conventional voltage monitoring and classical approaches for predicting RUL have been implemented together with multiple models for PEM stack prognosis. EIS data were employed for model-based diagnostics. A multiscale model was used to assess the impact of Ni coarsening on SOFC degradation. Enhanced sensor-based diagnostics and soft sensors for adaptive control was exploited and a Real-Time Optimization (RTO) control algorithm for fuel cell stacks and systems was implemented as well.
The focus of WP6 was on designing and manufacturing HW components for MDPC algorithm implementation and onboard EIS spectra acquisition. The design of the HW for EIS stimuli to be injected by a DC/DC converter was completed for both SOFC µ-CHP and PEM backup. The RUBY-Box was built incorporating MDPC, Analog Front End board, Ethernet network connection and cost-effective Raspberry Pi boards. Six new RUBY-Box prototypes were tested in laboratory. The Figure 1 shows the schemes of both µ-CHP and Backup systems integrated with the DC/DC converter embedding the EIS perturbation functions (p) and the RUBY-Box (red boxes) featuring control and measurement functions (f). The partners closely collaborated to design a hardware add-on for EIS stimuli injection, the realization was assigned to Kostal GmbH, who customized its commercial DC/DC converter. This decision has led to a low-cost solution with EIS functions applied to both µ-CHP and Backup systems. This approach ensures marketability for the manufacturer and facilitates the integration of EIS monitoring functions into existing systems.
In WP2, extensive experimental activities were conducted for PEM FCSs. The testing included simulations of various faults, such as fuel and air starvation and cathode contamination, and utilized EIS with sinusoidal perturbations for performance characterization. A modified PEFC stack system was installed on a dedicated test rig, assessing EIS changes with respect to nominal and faulty operations. For SOFC technology within WP3, stack and system were tested in nominal and faulty operations as well as long-term and EIS measurements. A µ-CHP system is installed in a testing environment for final experimental campaign (Figure 2).
In the Figure 3 is reported the plot of the Electrochemical Impedance Spectra elaborated from the current and voltage signals measured during the injection of the stimuli generated by the modified Kostal DC/DC converter installed on the Backup PEMFC system. The Figure 4 sketches the main HW components for the implementation of the MDPC tool along with the the Kostal DC/DC converter installed in both Backup and µ-CHP systems.
- Diagnostic and prognostic algorithms for PEMFC and SOFC finalised, verified and coded for implementation in the RUBY Box.
- Successful field testing of RTO resulted in an increase of 10% of the electrical efficiency.
- Design of mitigation strategies to reduce degradation rate and perform stack recovery from reversible degradation.
- Data acquisition via MDPC board successfully performed.
- Design and upgrade of commercial DC/DC converter for on-board EIS implementation.
- Installation of RUBY Box and DC/DC converter on both PEMFC backup and µ-CHP SOFC systems.
- RUBY Box interfaced with DC/DC converter for EIS functions.
- Successful testing of DC/DC converter and acquisition of data for the EIS of PEMFC.
- Integration of MDPC tool in the testing infrastructure at EIFER (PEM system) and EPFL (SOFC system).
- Testing of the communication system among all components (HW & SW) of both systems.
- Test campaign started.
An analysis was conducted to develop MDPC tools for PEM and SOFC technologies. Various algorithms were designed using data from FCSs manufacturers and lab measurements. It was developed an innovative fault isolation method for SOFC technology, machine learning and deep learning techniques. Conventional voltage monitoring and classical approaches for predicting RUL have been implemented together with multiple models for PEM stack prognosis. EIS data were employed for model-based diagnostics. A multiscale model was used to assess the impact of Ni coarsening on SOFC degradation. Enhanced sensor-based diagnostics and soft sensors for adaptive control was exploited and a Real-Time Optimization (RTO) control algorithm for fuel cell stacks and systems was implemented as well.
The focus of WP6 was on designing and manufacturing HW components for MDPC algorithm implementation and onboard EIS spectra acquisition. The design of the HW for EIS stimuli to be injected by a DC/DC converter was completed for both SOFC µ-CHP and PEM backup. The RUBY-Box was built incorporating MDPC, Analog Front End board, Ethernet network connection and cost-effective Raspberry Pi boards. Six new RUBY-Box prototypes were tested in laboratory. The Figure 1 shows the schemes of both µ-CHP and Backup systems integrated with the DC/DC converter embedding the EIS perturbation functions (p) and the RUBY-Box (red boxes) featuring control and measurement functions (f). The partners closely collaborated to design a hardware add-on for EIS stimuli injection, the realization was assigned to Kostal GmbH, who customized its commercial DC/DC converter. This decision has led to a low-cost solution with EIS functions applied to both µ-CHP and Backup systems. This approach ensures marketability for the manufacturer and facilitates the integration of EIS monitoring functions into existing systems.
In WP2, extensive experimental activities were conducted for PEM FCSs. The testing included simulations of various faults, such as fuel and air starvation and cathode contamination, and utilized EIS with sinusoidal perturbations for performance characterization. A modified PEFC stack system was installed on a dedicated test rig, assessing EIS changes with respect to nominal and faulty operations. For SOFC technology within WP3, stack and system were tested in nominal and faulty operations as well as long-term and EIS measurements. A µ-CHP system is installed in a testing environment for final experimental campaign (Figure 2).
In the Figure 3 is reported the plot of the Electrochemical Impedance Spectra elaborated from the current and voltage signals measured during the injection of the stimuli generated by the modified Kostal DC/DC converter installed on the Backup PEMFC system. The Figure 4 sketches the main HW components for the implementation of the MDPC tool along with the the Kostal DC/DC converter installed in both Backup and µ-CHP systems.
The project outcomes achieved are confirming the potential in generating positive impacts on both technology and market fields, thus contributing to the progress of FCSs products beyond the state-of-the-art. The results confirm the expected advancements though a complete assessment will be performed during the on-going testing campaign. The testing of the RTO on the µ-CHP system led to an improvement of the efficiency by 10% with respect to the standard control strategy. For EIS-based monitoring, the successful upgrading of the existing DC/DC converter will guarantee the implementation of the EIS on commercial systems (SOFC and PEMFC). Furthermore, with respect to the project proposal, additional algorithms have been developed; this result will enlarge the possibility to find more appropriate and effective techniques for diagnostics, prognostics and control to enhance the lifetime while keeping the efficiency closer to that at beginning of life (BOL).