Giantleap Workshop, Belfort, December 12, 2017

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Ivar J. Halvorsen, Federico Zenith, SINTEF Digital

Diagnostics, Prognostics and Control Models for bus Fuel Fell Systems

PHM & Control Issues

Outline

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• FC system Topology

• Basic control and Prognostics & Health Management (PHM) functions

• PHM functions

• Example of identification method for monitoring of a particular PHM parameter

• Summary

Bus FC system topology

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PHM control: Extend Remaining Useful Life (RUL)

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Simple cost analysis:• Nominal investment cash flow; Cost/time = CostInvestment/Tlife0

• Cash flow savings by extending lifetime: ΔTlife

Tlife0+ΔTlife(e.g.: double lifetime saves 50%)

• Energy cost cash flow: Demanded power production × Fuel Cost / efficiency

• Total cost cash flow: Operating + Investment cash flow

• Important questions:• How do operating strategy impact efficiency and lifetime?

• How to implement an optimal strategy in practice?

• The tradeoff: The marginal benefit of a change in operating strategy to increase RUL should balance additional loss related to any reduced efficiency from the same change.

PHM functions in the control hierarchy

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1. Basic Fuel Cell Control

2. PHM performance parameter monitoring and prediction

3. PHM control actions

4. On-line vs off-line functions

PHM functions in the control hierarchy / 1

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Basic Fuel Cell Control System

• Operating points defined based on cell performance optimization

• Controllers to maintain operating conditions and handle transients

• Normal startup and shutdown

• Charging protocol

• Monitor operation and appropriate handling of deviations

• Avoid operating regions known to be damaging to the cell

• Emergency shutdown

Basic Control System by Bosch / 1

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• Fuel Cell Control Unit (FCCU)

• Fuel cell basic control is based on the load power demand (P)

• Optimized scheduling based on performance:• Air pressure setpoint = f(P)

• Air flowrate setpoint =f(P)

• Coolant inlet and delta temperature setpoint = f(P)

• Operating constraints may limit available power

PHM functions in the control hierarchy / 2

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PHM performance parameter monitoring and prediction

• Monitoring functions in open loop based on measurements

• Parameter estimation for selected characteristics

• RUL model updating and RUL prediction

• Information gathering (no action)

• Some function may require active stimulation to extract required information from data

PHM functions in the control hierarchy / 3, 4

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• PHM control actions• Use available degrees of freedom to move to regions with lower wear

• Causal relations between degradation and operation conditions?1. Learning experiments, e.g try different charging protocols

2. Well defined relations can be moved to Basic level

• On-line vs off-line functions• Limitations on data storage

• Long-term analysis only possible on logged data

Basic Control System by Bosch / 2

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How to add on PHM control functions:

• Must use available Degrees of Freedom

• Adjust the scheduled f(): include PHM issues in schedule optimization

• Constraint adjustment based on PHM results

• Charging protocols, adjustment based om ageing state, e.g.:

A: max charging power ON when battery >20% until above 80%, else OFFB: averaged charging power based on average bus consumptionC: something optimized based on logged data

Proposed additional PHM-functions

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Poor Man's PrognosticsMap equivalent model of polarisation curve as in Sapphire. Use only 2 parameters for linear regression. Store current state of parameters somewhere this time. Produce estimate to EoL.

Stack Regeneration/RejuvenationRegeneration effects after stop/start have been observed in long term tests

Poor Man's EIS (this example will be outlined) Estimate of resistance in resonant element of EIS model. Log value for mapping against cell degradation.

Polarisation curveProcedure for straightforward recording of the polarisation curve can be implemented and executed periodically at times where the charging schedule allows. E.g. as a part of the shutdown procedure.

Humidity (Flooding/Drying)As in Sapphire, measure voltage noise to watch for flooding, and pressure drop over cathode.

Advanced Diagnosis and Prognostics for Stack and BoPDefine interfaces with models from UFC. Use directly in control system is possible

The fuel cell voltage degrades in use:

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Graph shows estimated voltage for a nominal current from a test run with a varying load pattern

Method: Estimate polarization curve development from actual operating data and estimate the performance at a normalized current level

Stack regeneration - rejuvenation

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Analyse how the stop/start impact the stack performance

What are the physical mechanisms?

Research area: What is the physical background for the observation and how to reduce both reversible and irreversible degradation. E.g.: Special precautions during:

Shutdown, Handling when switched off and until the next start, Start-up

Method for identification of |Z| when Im(Z(jw))=0(Poor man's EIS)

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Ref.: FESB

Z(jω)

Use relay feedback excitation to establish small oscillation at desired (unknown) frequency when Im(Z(jω))=0

H(s)

0 2 4 6 8 10 12 14 16-1.5

-1

-0.5

0

0.5

1

1.5

Point of interest

Signals in Z: Impedance model (from EIS)

Online R-estimator Shape filter: d(s)=d1×d2

Simulink diagram for relay excitation scheme

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Relay input & output signal

Current input value (delta)

(pre-filter d1(s)'s output

Measured voltage

(with bias & noise)

On-line impedance estimate

(ca 0.03 Ω)

Bias estimate

[time unit: seconds]

FC impedance in Nyquist diagram with estimated result

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Summary

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• PHM functions aid understanding of FC performance development

• Some monitoring functions can be within the Fuel Cell Control Unit

• Functions based on long-term analysis require access to data log

• On-line instrumentation will be limited in real life

• RUL model estimation and RUL prediction are presented by UFC

• Best operation principles should be in the basic control strategy as far as possible

Giantleap Improves Automation of Non-polluting Transportation with Lifetime Extension of Automotive PEM fuel cells

This project has received funding from the Fuel Cells and Hydrogen 2 Joint Undertaking under grant agreement № 700101. This Joint Undertaking receives support from the European Union's Horizon

2020 research and innovation programme and Hydrogen Europe and N.ERGHY.

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