«EMR for Fuel Cell Vehicles in cold climatic conditions€¦ · EMR’19, Universite de Lille, June 2019 2 « EMR for Fuel Cell Vehicles in cold climatic conditions» - Outline -

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

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

EMR’19

Universite de Lille

June 2019



« Fundamentals and modeling of Fuel

cell systems»



- 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



- Fuel cell fundamentals -

• Polarization curve

• The cell polarization curve is formed by subtracting the different losses



- 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



- 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

EMR’19

Universite de Lille

June 2019



« FCV in winter 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)



- 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)



- 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



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)



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!!!



- Vectorial representation-

H2Bat

TP

EMifc ref

Model

parameters

Test bench with a

500W atmospheric

fuel cell



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)

EMR’19

Universite de Lille

June 2019



« Conclusion »



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)

EMR’19

Universite de Lille

June 2019



« BIOGRAPHIES AND REFERENCES »



- 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



- 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.

Documents

«EMR for Fuel Cell Vehicles in cold climatic conditions€¦ · EMR’19, Universite de Lille, June 2019 2 « EMR for Fuel Cell Vehicles in cold climatic conditions» - Outline -