star global conference - vienna 2014 simulation of the...
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Star Global Conference - Vienna 2014
Dr. David Wenger
Simulation of the hydrogen fueling process
18.03.14
Key Facts
• Engineering company with 15 employees
• Location: Ulm, Germany
• CEO: Dr.-Ing. David Wenger
• Services:
Thermodynamics
CFD Simulation
Refueling Simulation (H2 and CNG)
COMSOL Multiphysics Consulting
MATLAB Programming
Simulation Software Development
• Software: MATLAB, Simulink, COMSOL
Multiphysics, Star-CCM+
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Our customers
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Hydrogen fueling: Overview
• Hydrogen powered fuel cell vehicles
will enter the commercial market in the
next few years.
• Hydrogen is stored on board in high
pressure gas tanks.
• Pressure level: 70 MPa at 15°C
• Fueling of FCV is possible in three
minutes thanks to world wide standard
SAE J2601 (vs. battery electric
vehicles: several hours)
• Typical range of fuel cell vehicle: 400-
600 km (vs. battery electric vehicles
100-200 km)
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Hydrogen fueling storage: Challenges
• State of Charge (SoC) of gas tank is f(p,T).
• Thermodynamic behavior of hydrogen is challenging
– Very high pressure of up to 87.5 MPa
– Compression during fueling leads to fast temperature rise
• Maximum allowed temperature of tank material of 85°C must
not be exceeded
• Therefore gas is precooled at station to -40°C in order to
compensate the heat of compression
• This leads to temperature gradients in components of
T_ambient -40°C +85°C in a few minutes
– High gas velocities of >300 m/s in fueling line, therefore high
pressure drop
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Custumer expectation: All vehicles have to be filled to 98-100% in 3
min regardless of initial and ambient conditions.
Consequences for tank development and modeling
• Real gas behavior: User-defined equations are needed for every
property such as density, heat capacity, viscosity etc.
• Different vehicles have different tank volumes and therefore different
storage capacities.
• Different tank geometries have different surface to volume ratios.
• Tank volume and tank conditions are not known to the station, so a
wide range of conditions has to be analyzed in order to understand
physics.
• Critical: Internal Heat Transfer Coefficient (gas tank wall)
– Different inlet geometries lead to different inlet velocities
– Different inlet velocities lead to different wall velocities and
therefore different heat transfer coefficients
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The model is needed to understand the correlation between initial and
inlet conditions and the heat transfer coefficient gas-wall
Simulation model with Star-CCM+
• The fueling process was simulated with Star-CCM+
• The model only included the vessel, no other components such as
pipes etc. were taken into account.
• Target values are the temperature and the velocity distribution.
• The material properties were added as field functions.
• The incoming hydrogen flow is defined as a mass flow boundary
condition (angle can be defined). Other option: pressure ramp
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Hydrogen
Inlet Plastic or aluminum liner Composite wrap
Picture simplified
due to NDAs
Mesh
• The geometry was meshed with polyhedral elements and prism layers
near the wall.
• Additionally volumetric control entities were added for refining the mesh
around the inlet.
• The mesh was verified by a sensitivity study.
• The whole mesh consists of ~200.000 cells.
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Volumetric
control entity
Prism layer
Polyhedral elements
Picture simplified
due to NDAs
Results of the simulation - Velocity
• With the simulation it is possible to
generate temperature and velocity
plots for every time step.
• The mass flow is given by the
shown ramp function. Because
the pressure and therefore the
density are changing, the
maximum velocity at the inlet
varies between 0 and 670 m/s.
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~ 1m
0
5
10
15
20
25
0 50 100 150
m_in
let
(g/s
)
time (s)
Results of the simulation – Temperature
• The plots show a correlation between
temperature and velocity.
• Highest gas temperature during fueling:
at the back end of the tank
• Highest gas temperature after fueling:
upper part of the tank
• The differences in local gas temperature
are up to 50K
• Depending on the inlet geometry and
angle, the hot spot at the rear end of the
tank can be reduced
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It is obvious that the position of the
temperature sensor is crucial as no “bulk
temperature” exists during fueling
Improvement in inlet geometry
• An optimum inlet angle leads to high velocities at the tank wall instead
of „chaotic turbulence“
• This leads to lower temperature gradients in the tank and to lower end
temperatures
• An example is shown here:
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Conclusion
• The fueling process is extremely challenging, the most difficult question
is the internal heat transfer coefficient.
• This question was answered with our Star-CCM+ model, giving a good
prediction for the heat transfer coefficient as a function of inlet velocity
and initial conditions (1).
• The results were validated with tests at Powertech Labs, Vancouver
• These results were accepted by the whole automotive and gas industry
and used to define the standard.
• SAE J2601 is the world wide standard for fueling hydrogen powered
fuel cell vehicles.
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(1) Chakkrit Na Ranong, Steffen Maus, Jobst Hapke, Georg Fieg, David
Wenger: Approach for the Determination of Heat Transfer Coefficients for
Filling Processes of Pressure Vessels With Compressed Gaseous Media,
Heat Transfer Engineering
Volume 32, Issue 2, 2010, Pages 127-132
Kontakt:
Dr.-Ing. David Wenger
Wenger Engineering GmbH
Einsteinstr. 55
89077 Ulm
0731-159 37 500
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