Thermotec Engineering Services GmbH
Air Conditioning and Cooling System
Simulation /
Approaches to Handle Data and Huge
Number of Variations
Robert Tauscher
Overview
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Introduction
Our daily business
System complexity and number of variants
Approaches to handle complexity and variants
Examples
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Component Level: Subassembly Evaporator, Condenser, HX
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System Level: Universal System Template
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Modeling and Calibration Level: System Identification
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Calibration Level: Hydraulic, Thermal
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Verification Level
Conclusion
Who is Thermotec?
■ an engineering company - 15 engineers and physicists ■
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specialized on thermodynamics and .fluid mechanics
automotive, aerospace and defense industries
simulation: thermal/hydraulic systems, thermal
management and cooling .systems
(1D and 3D-CFD)
test benches: wind tunnel for radiator and heat exchanger
performance tests
sensor development / measurement techniques
Technische
cooperations with universities / research projects
Universität
München
our partners:
www.thermotec-es.com
Our Daily Business - General
■ Analysis of AC and Cooling Systems
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Evaluation of concepts, variants, …
Dimensioning of components / complete systems
■ Control Strategies:
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Development and Proof of Concept
Failure Scenarios and Backup Strategies
■ What if … analysis
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Dimensioning / Scaling
■ Pumps, fans (size, operating points, …)
■ Radiators (scaling)
■ Piping (pressure drop  diameter, etc.)
Comparison of concepts / components …
Our Daily Business - Simulation
■ Modeling
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Physical or
System Identification
■ Verification: compare model with experimental data
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Experiment
Data collection and pre-processing
Steady state and transient
■ Model Calibration (experiment, 3D-CFD, …)
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Component level
System level
■ Post-processing / Analysis
■ Presentation / Documentation …
Challenge: Cooling System & Control Strategy for a System with
Battery & Power Electronics + AC-System
loss of thermodynamik potenzial / „thermal resistance“
T.ambient
DT: +2…5K
DT: +5K
Q
Q
Q
air
DT: +5K
Q
DT: +50K
Q
Q
Q
Q
Q
Q
Q
direction of heat flow / heat transfer
component
system
■ cabin
 modeling / system identification
■ cabin
 calibration
■ HX, condenser…  sub-model generation
■ piping/hydraulics  calibration
■ 2ph-/AC-System  integration in vehicle cooling system model
■ vehicle model  system generation / data handling / huge number of variants
Multiple Coupled AC and Cooling System Simulation / Automated
Handling of Data and Variations: Challenges and Approaches
Challenges
large
number of
concepts to
be
evaluated
large
number of
subsystems
within a
model
huge
number of
variants and
derivatives
of a model
frequent
changes of
data during
design
process
very complex
calibration of
model and
subsystems
to experiment
coupled
simulation &
harware in the
loop (HiL),
controls
simulation
time
convergence
evaluation
documentation
robustness
reproducibility
Universal System Model Template
major sub-systems
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universal
system
model
template
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database for
models,
components
and data
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simulation model
thermal / hydraulic
.
modular
simulation
set,
defined
interfaces
.
.
steady-state / transient
.calibration
fast running / real-time
system identification
physical
modelling,
system
identification
scripted
generation
of models,
components
and variants
Approaches
automated
start & check
of
simulations
semiautomatic
model and
subsystem
calibration
automated
standard
and custom
made
evaluation
Vehicle AC and Cooling System –
From a Simple Model to Complex Systems
and a Huge Number of Variants
Gamma‘s example of a simple airFacts & model data of a
conditioning circuit with battery
state of the art vehicle aircooling
conditoning circuit & coupled
(„System_Battery_Cooling“)
cooling system model
what is necessary and
how will the model look like,
that we can meet
the challenges?
The Challenge:
■1
■ 10
■ 40 … 55
?
■ 5.000 … 11.000
■ 25.000 … 110.000
■ 1 … 700
■ 26.000
x 10 … 100
Vehicle Cooling System – Model Complexity and Variants 2016
up to:
1
10
40 … 53 (*50)
5.000 … 11.000 (*10.000)
25.000 … 110.000 (*100.000)
1 … 700 (*400) x 10 … 100
26.000 (*15.000)
(* GT-User Confernce 2015!)
■ Universal modular GT-System-Model-Template
■ Fluid Circuits: coolant (ht, lt,…), oil, air, refrigerant …
■ External subassemblies - main modules of vehicle
■ Total number of GT-parts in 1 model
■ Code lines in a „ready-to-simulate“ model file (*.dat-file)
■ Simulations/1 night (variants x use cases)
■ Result files (700 variants with 10 use cases)
Automation in Each Level of Simulation Workflow
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Component Level - Automatic Component-model creation
■ Evaporator, Condenser, Radiator, Heat exchanger
System Level – Automatic Multiple/Cascades Coupled AC-Cooling-System creation
■ Universal System Model Template
Modelling & Calibration Level - System Identification
Calibration Level - Model Calibration (steady state, transient…)
■ hydraulic
■ hydraulic & thermal, ….  Maximum Likelihood Optimization
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Analysis Level / Presentation Level – Custom Made Offline Evaluation Tool
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Verification Level – Development of Sensors and Measurement Techniques
Automation – Component Level:
Component Generation*/Heat Exchanger: Evaporator, Condenser, ..
Evaporator, HX
Condenser, Radiator
Process Relevant Data
Data Sheet (GT-ExcelTemplate or Custom)
Check Input Data
Scaling
(optional)
type (cross-flow, …)
dimensions
geometry, dimensions
properties of matter
hydraulic and thermal
performance
hydraulic (Dp)
thermal efficiency
NTU-limits
…
correction if necessary
dimensions
height
# tubes
width
depth !
fins: spacing /
thickness
tubes: wall thickness
properties of matter
Visual Check & Last
Modifications
Generation of
GT-Subassembly
and Automatic Preprocessing
Documentation of NuRe-Regression Quality
add Model to
Component Database
evap./cond/HX-test
bench
correction of regression
to meet raw data (option)
automatic
manual step
step
*details in GT-User-Conference 2015 presentation
Coupled AC and Cooling System Simulation – Automated
Handling of Data and Variations*
Universal Modular
System Model Template
Database of Variants /
Variants Parts List
for each variant:
all relevant model
parameters and data
sheets
list of all relevant
external Subassemblies
for each model variant
Check Simulations /
Process Results
check simulations
- all runs finished?
- convergence?
Process Results
collect and combine
results / first check
Check
check consistency of
data:
- parameters
- subassemblies
combination
- boundary
conditions
- …
Model Generation
Simulation /
Batch / Distributed Run
generate
*.gtm file for each variant
*.dat file for each variant
check workload of
cluster server and
available licenses
check: all models
generated?
send models to
distributed server
log file of variants
Data Reduction &
Evaluation
Reporting /
Sharing of Results
Excel-Add-In and
template for results:
steady state / transient
- standard report
- interactive evaluation
. tool
8
140
7
120
6
100
5
80
4
60
3
40
2
20
Gang
option: re-start
simulation of selected
models (failed,
crashed…)
Fahrzeuggeschwindigkeit [km/h], Temperaturen [°C]
F56Ha B48 170kW, Guadix, kinematisch vs gemessen
160
1
0
0
200
400
600
800
1000
Fahrzeug_outp ut_Geschw #1_GT_2
WT_KMKHT_output_T_WT_Ein_Inner #1_GT_2
WT_MOEWWT_output_T_WT_Ein_Inner #1_GT_2
WT_GOEWWT_output_T_WT_Ein_Inner #1_GT_2
T_KM_KMKHT_ein Guadix_Messung
T_MO_MOEWWT_ein Guadix_Messung
T_GO_GOEWWT_ein Guadix_Messung
Fahrer_Gang #1_GT_2
0
1200
*details in GT-User-Conference 2015 presentation
Documentation …
archiving
documentation
data proc. for 3rd
party use (3D-CFD…)
clean up
- delete huge
number of files
- free disk space
automatic step
System Battery/Power Electronics + AC-System
■ Cooling strategy for system HVS (high voltage storage) + Power Electronics (PE)
■ Cooling strategy for AC-System + Cabin
System
Condenser
Hydraulics
Evaporator
Cabin
HVS
■ Integration in Vehicle Cooling System Model
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multiple cascaded coupling via fluid circuits (chiller / multi-stage) and via
underhood flow
■ modular universal system model
Simulation Time / Robustness / Convergence …
Modelling & Calibration Level: System Identification
■ Calibration of Cabin and AC model to Pull-Down measurements
Pull-Down Measurement: transient
temperatures at many cabin positions
air flow
temperature
flow rate
…
cabin model template
needs a lot of – often
unknown – input data
Ambient: 3
Vehicle: 4
Component Materials: 13
Component Masses: 7
Component Geometry: 13
View Factors: 7
Cabin Initial State: 11
Solar Properties: 7
Miscellaneous: 6
Layer Weighting: 18
Thermal Comfort Pred.: 3
GT-Post-Output:1
Plots: 5
---------------------------Total: 98 (!) data fields
Cabin Template
calibration to transient
temperatures at many
sensor positions
System Identification
v (t) : disturbances
System Cabin
y (t): output
u (t) : input
T_Head(L+R
)
System
T_Louver
(L+R)
T_Feet (L+R)
 T_Louver_C
u(t)  
 T_Louver_C
 T_Feet_lef

 T_Feet_rig
y(t)  
T_Head_lef

 T_Head_rig

L

R 
t_target/e xp. 

ht_target/ exp. 
t_target/e xp. 

ht_target/ exp. 
transfer function
■ transient behavior of components and systems very often cannot be described
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sufficiently by simple physical models
e.q. thermal masses / thermal inertia / thermal resistance of cabin model or
engine
with transient test data available dynamical models can be obtained by system
identification (transfer function between input and output, regarding
disturbances)
these models - generated in MATLAB/SIMULINK - can be utilized in GT-Suite
as SimulinkHarness-Objects replacing the standard cabin model object
Modelling & Calibration Level: System Identification
Implementation in GT-Suite Model
identified
State-Space Model
cabin.dll
 T_Louver_C
u(t)  
 T_Louver_C
L

R 
 T_Feet_lef t_target/e xp. 


 T_Feet_rig ht_target/ exp. 
y(t)  
T_Head_lef t_target/e xp. 


 T_Head_rig ht_target/ exp. 


T_Head(L+R)
T_Louver (L+R)
T_Feet (L+R)
System Identification and Model Calibration: Results
 T_Feet_lef t_target/e xp. 


 T_Feet_rig ht_target/ exp. 
y(t)  
T_Head_lef t_target/e xp. 


 T_Head_rig ht_target/ exp. 


T_Head(L+R)
T_Louver (L+R)
test data
exp
test data
T_Feet (L+R)
exp
■ linear State-Space-Model (blackbox)
■ 20 state variables
■ fast model generation (5s)
■ high accuracy
■ if detailed knowledge of physics is
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available greybox models can be used
(parameter identification)
test data should catch dynamical
behaviour in a sufficient way
test data
exp
test data
exp
Automation – Calibration Level: Model Calibration - Hydraulics
Goal: hydraulic calibrated GT-model for each use case / control strategy @each branch in
coolant circuit, esp. local flow rates and pressure distribution
System
CAD
GEM3D
GT-hydraulic model
3D-CFD / experiment
PID-controlled
orifices for each
sector and branch
piping of refrigerant loop
automatic calibration
for each use case
subassembly
hose and piping
system
MEADS Radar Unit
many communicating parallel - but
different - flow paths to be calibrated
(100)
interface
hydraulic calibrated
model
Automation – Calibration Level: Model Calibration – Thermal, …
■ Goal: find measurement errors and model calibration factors for
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heat flow:
heat rejection engine, air cond, gear box, …
flow rates:
refrigerant, coolant, air, oil, atf, …
performance maps:
heat exchangers, pumps, …
■ that the model can reproduce measured
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temperatures
pressures
flow rates, …
■ for all (sensor) positions
■ simultaneously and for all use cases
■ as automatic as possible
■ comply with mass and energy conservation!  consistent solution
Calibration Level: Model Calibration and Test Data Validation
based on Maximum Likelihood Optimization
■ Goal: find measurement errors and model calibration factors
■ GT-Model based on maps for single components
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(Compressor, Condenser,…) and certain boundary
conditions
component maps usually derived from tests or simulation
GT- Model
pGT, TGT, mdotGT
test bench
≠
ptest, Ttest, mdottest
reasons for deviations (simulation vs. experiment):
component data (maps, …) imprecise?
system model inaccurate?
measurement errors (e.g.temperatures)?
or a combination of both?  most likely!
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 Maximum Likelihood Optimization
Verification Level: Thermotec Wind Tunnel / Sensor Technology
■ Wind Tunnel / HX-Test bench
■ HX-Performance
■ Uniformity
■ COOL3D-Benchmark
■ glas fibre sensor: 2-phase-flow, boiling  local gas
content measurement
■ high-dynamic pressure sensors
■ ultra-high-dynamic temperature sensor (twin-sensor),
temperatur gradients > 800K/s
 hight-transient expansion flows,
zB. airbag-unfolding
Verification Level: Thermotec Sensor Technology
■ capacitive gas content sensor  aeration z.B. engine oil
■ wire-mesh sensor / phase and/or component distribution
■ verification simulation filling/degassing
■ verification simulation fording ability
■ Berner Impactor / Particle Image Velocimetry (PIV)
■ verification simulation particel flow
■ contact angle measurement
■ verification fogging and steaming up
Automation – Evaluation / Presentation Level
■ Custom Made & Interactive Evaluation and Presentation Tools for
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Off-Line Usage (no licenses required)
„Non-Experts“
Marketing Purposes
Conclusion
■ What is necessary to handle and simulate complex AC and cooling systems and
what is possible with Gamma Technologies GT-Suite?
■ Models / Simulation
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Short simulation times  fast running models (FRM) / fast convergence
Robust models
■ Modelling
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Automation of model generation (VBA)
■ Component and system-model generation / modification
■ Co-simulation with System Identification / Simulink (SimulinkHarness)
Model data: administration in external file(s) or database (Excel)
Tools to model specified components very detailed
■ Simulation
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Automation of pre- and post-processing (VBA, Excel)
Automation and organisation of simulation-runs  24/7 workload of server and
licenses (VBA, Excel)
Automation of model calibration (VBA and GT)
Thank You for Your Attention!
www.thermotec-es.com