«emr for fuel cell vehicles in cold climatic conditions€¦ · emr’19, universite de lille,...
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EMR’19
Universite de Lille
June 2019
Summer School EMR’19
“Energetic Macroscopic Representation”
«EMR for Fuel Cell Vehicles in cold
climatic conditions»
Prof. Loïc BOULON, Dr. Ali AMAMOU
Université du Québec à Trois-Rivières, Canada
Hydrogen Research Institute
eCampus International Laboratory
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EMR’19, Universite de Lille, June 20192
« EMR for Fuel Cell Vehicles in cold climatic conditions»
- Outline -
1. Fundamentals and modeling of Fuel cell systems
2. FCV in winter conditions
Start up in subfreezing temperatures
Limitations of the model based approach
3. Conclusion
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EMR’19
Universite de Lille
June 2019
Summer School EMR’19
“Energetic Macroscopic Representation”
« Fundamentals and modeling of Fuel
cell systems»
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EMR’19, Universite de Lille, June 20194
« EMR for Fuel Cell Vehicles in cold climatic conditions»
- FC and FCV at a Glance-
4
H2 + O2 (air) Fuel Cell (electroC converter)
Electricity +
Heat + Water
For vehicular application
+ No local emission / Fast
Refueling / Large autonomy
- Cost / recharge facilities /
winter conditions
Némo Low Speed Vehicle
(Hydrogen Research Center)
Modeling & Simulation for
✓ Design
✓ Control & Energy
management
✓ System performances
O2 supply
H2 supply
Power
Electronics
Gas
humidification
Temperature
Management
Fuel Cell
Stack
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EMR’19, Universite de Lille, June 20195
« EMR for Fuel Cell Vehicles in cold climatic conditions»
- Fuel cell fundamentals -
• Polarization curve
• The cell polarization curve is formed by subtracting the different losses
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EMR’19, Universite de Lille, June 20196
« EMR for Fuel Cell Vehicles in cold climatic conditions»
- EMR of a FC stack -
• EMR of the FC
stack (ancillaries are
summarized into the
source elements)
• Dynamics are
highlighted
• Control input are on
the source elements
• Strong interactions:
a FC stack cannot be
seen has a cartesian
system
Elec
Electrochemistry
Tfc
Air supply
Atmo
Air
Tfc
Δ𝑆q ifc
qair
qh2
Pair
Therm
Thermal
Tfc
Tfc
vfc
Atmo
H2
H2 supply Tfc
vfc
PH2
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EMR’19, Universite de Lille, June 20197
« EMR for Fuel Cell Vehicles in cold climatic conditions»
- Experimental validation -
Inputs: measured values
are imposed to the model
•Current steps
•Air flow variation
•(Constant H2 flow)
Outputs: simulated values
are compared to
measurements
•H2 input pressure
•Air input pressure
•Voltage
Validation range of such a model is limited
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EMR’19
Universite de Lille
June 2019
Summer School EMR’19
“Energetic Macroscopic Representation”
« FCV in winter conditions »
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EMR’19, Universite de Lille, June 20199
« EMR for Fuel Cell Vehicles in cold climatic conditions»
Starting durationEnergy
consumption
P/2 in 30s
(at -20°C)
DOE requirements
Fuel cell systems in winter conditions
Bellow 0°C: Water is in solid state
• Mechanical damages
• Block the gas channels
• Lower electrochemical performances
• Several methods available in literature (constant current or constant voltages)
but poor performances
• It is very important to manage the stopping phase (flush of the water in the
channels)
5 MJ (at -20°C)
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EMR’19, Universite de Lille, June 201910
« EMR for Fuel Cell Vehicles in cold climatic conditions»
- FC Fundamentals -
• Implication & Use of polarization curve
• Power curve
• Heat production
• Maximum H2 consumption to maximize both electric power and heat
production
• Maximum electric power point = Maximum thermal power point (avoiding
degradation)
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EMR’19, Universite de Lille, June 201911
« EMR for Fuel Cell Vehicles in cold climatic conditions»
- Vectorial representation-
Our Proposal: to start the FC at the Maximum electric power point
H2Bat
TP
EM
ifc ref =f (operating conditions)
From the model and depending the operating conditions, the energy
management calculates the current corresponding to the maximum power
Real fuel cell system
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EMR’19, Universite de Lille, June 201912
« EMR for Fuel Cell Vehicles in cold climatic conditions»
Main issues for model based starting strategy
(a) Polarization and (b) Power curves of the
new PEMFC at -15°C and 5°C(a) Polarization and (b) Power curves of the new
and degraded PEMFC at 30°C
Several important points
- Ageing not taking into account in the current fuel cell models
- Performances of the FC are widely modified during the start phase
(temperature variation over the validity range of the model)
- Poor repetability of the tests• We need to adapt the requested current
during the starting phase
• The model is not able to give us a relevant
information (ifc giving the maximum power)
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EMR’19, Universite de Lille, June 201913
« EMR for Fuel Cell Vehicles in cold climatic conditions»
Identification of model parameters for cold start
1. Identification of the model parameter
during the starting phase
2. Extraction of the polarization and
power curve
3. Optimization to calculate the
requested current (giving the
maximum power)
EMR model
Real time process!!!
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EMR’19, Universite de Lille, June 201914
« EMR for Fuel Cell Vehicles in cold climatic conditions»
- Vectorial representation-
H2Bat
TP
EMifc ref
Model
parameters
Test bench with a
500W atmospheric
fuel cell
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EMR’19, Universite de Lille, June 201915
« EMR for Fuel Cell Vehicles in cold climatic conditions»
Experimental results
• Identification of the polarization
curve
• Estimation of the power curve
• From -20°C to 0°C in 50s (110s for
potentiostatic start up)
• P/2 in 10s
• Energy consumption divided by 3
(vs potentiostatic)
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EMR’19
Universite de Lille
June 2019
Summer School EMR’19
“Energetic Macroscopic Representation”
« Conclusion »
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EMR’19, Universite de Lille, June 201917
« EMR for Fuel Cell Vehicles in cold climatic conditions»
Conclusion
• Start up of fuel cell vehicles during winter conditions
• Real time identification based energy management
• Work with a “physical” model. Allow to analyse the relevance of the identified
parameters
• Very few preliminary experimental tests: near plug & play solution
• Best results of the litterature (starting duration and energy consumption)
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EMR’19
Universite de Lille
June 2019
Summer School EMR’19
“Energetic Macroscopic Representation”
« BIOGRAPHIES AND REFERENCES »
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EMR’19, Universite de Lille, June 201919
« EMR for Fuel Cell Vehicles in cold climatic conditions»
- Authors -
Dr. Ali Amamou
Université du Québec à Trois-Rivières
PhD in Electrical Engineering at UQTR (2017)
Research topics: Energetic efficiency of autonomous vehicles
Prof. Loïc Boulon
Université du Québec à Trois-Rivières
PhD in Electrical Engineering at Univ. of Franche-Comté (2009)
Research topics: Energy sources for the vehicles of the future
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EMR’19, Universite de Lille, June 201920
« EMR for Fuel Cell Vehicles in cold climatic conditions»
- References -
Mohsen KANDIDAYENI, Alvaro MACIAS, Ali AMAMOU, Loïc BOULON, Sousso KELOUWANI, "Comparative Analysis of Two Online Identification Algorithms in a Fuel Cell System", WileyFuel Cells, Vol. 18, Iss. 3, 2018.
Ali AMAMOU, Mohsen KANDIDAYENI, Loïc BOULON, Sousso KELOUWANI, "Real time Adaptive coldstart strategy of automotive PEMFC", Elsevier Applied Energy, Vol. 216, 2018.
Mohsen KANDIDAYENI, Alvaro MACIAS, Ali AMAMOU, Loïc BOULON, Sousso KELOUWANI, HichamCHAOUI, "Overview of PEMFC parameters estimation methods with a focus on onlineidentification for energy management purposes", Elsevier Journal of Power Sources, Vol. 380,2018.
KHALID ETTIHIR, MAURICIO HIGUITA, LOÏC BOULON, KODJO AGBOSSOU, "Design of an adaptiveEMS for fuel cell vehicles”, Elsevier International Journal of Hydrogen Energy, Vol. 42, Iss. 2,2017.
Khalid ETTIHIR, Loïc BOULON, Kodjo AGBOSSOU, "Energy Management Strategy for a Fuel Cell
Hybrid Vehicle based on Maximum Efficiency and Maximum Power identification", IET
Electrical Systems in Transportations, Vol. 6, Iss. 4, 2016.
ALI AMAMOU, SOUSSO KELOUWANI, LOÏC BOULON, KODJO AGBOSSOU, "A Comprehensive Reviewon Cold Start of Automotive Proton Exchange Membrane Fuel Cells", IEEE Access, Vol. 4,2016.
Khalid ETTIHIR, Loïc BOULON, Kodjo AGBOSSOU, "Optimization-based energy management strategyfor a fuel cell/battery hybrid power system", Elsevier Applied Energy, Vol. 163, pp. 142-153,2016.
Khalid ETTIHIR, Loïc BOULON, Mohamed BECHERIF, Kodjo AGBOSSOU, "Online Identification of AirBreathing PEMFC based on a Semi-Empirical Model", Elsevier International Journal ofHydrogen Energy, Vol. 39, Iss. 36, pp. 21165-21176, 2014.