Engine and Gearbox Thermal Management Modeling
Amaury Arlotto
Master of Science Thesis TRITA-ITM-EX 2018:672 KTH Industrial Engineering and Management Machine Design SE-100 44 STOCKHOLM
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Examensarbete TRITA-ITM-EX 2018:672
Motor och växellåda termisk hanteringsmodellering
Amaury Arlotto Godkänt Examinator Handledare 2018-09-25 Andreas Cronhjort Andreas Cronhjort Uppdragsgivare Kontaktperson Groupe PSA Diego Pagliari
Sammanfattning
För att förbättra den globala effektiviteten hos en motor inom det franska företaget Groupe PSA, en forskningsaxel fokuserar på växellådans värmemanagement för en snabbare minskning av egen friktion efter en kallstart. Principen är att avleda en liten del av kylvätskenergin mot växellådan – förrän nu värms upp av sina egna inre friktioner – så länge som påverkan på motorns uppvärmning är tillräckligt låg för en global slutförbättring. En kompromiss finns då mellan en växellådans prestationsförbättring och en motornedbrytning för att få den bättre globala konsumtionsvinsten i slutändan.
Detta kommer att uppnås genom 1D-simuleringar tack vare mjukvaran AMESim, parallellt med Simulink och Matlab. Olika kylkretsarkitekturer och parametrar testas i prestations- och säkerhetssynpunkt för att hitta den bästa kompromissen i en förforskningsfas.
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Master of Science Thesis TRITA-ITM-EX 2018:672
Engine and Gearbox Thermal Management Modeling
Amaury Arlotto Approved Examiner Supervisor 2018-09-25 Andreas Cronhjort Andreas Cronhjort Commissioner Contact person Groupe PSA Diego Pagliari
Abstract
In order to improve the global efficiency of an engine within the French company Groupe PSA, a research axis focuses on gearbox thermalmanagement for a quicker reduction of its own friction losse after a cold start. The principle remains in deriving a little part of the coolant energy towards the gearbox – until now heated by its own internal frictions – as long as the impact on the engine warm- up is low enough for a global final gain. A compromise has then to be found between a gearbox performance enhancement and an engine degradation to get the better global consumption gain in the end.
This will be achieved through 1D simulations thanks to the software AMESim, in parallel with Simulink and Matlab. Different cooling circuit architectures and parameters will be tested in a performance and safety point of view to find the best compromise in a pre-research phase.
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Table of Contents
Sammanfattning ______3 Abstract ______4 Acknowledgments ______6 Introduction ______7 Context ______11 I.Research axis ______13 A. State of the art – Original cooling architecture ______13 B. New cooling architecture hypotheses ______14 C. Controlled Valve on a H4 basis ______17 II. Simulation – AMESim ______19 A. Thermal AMESim Model (SAMGa The) ______19 1. General description ______19 2. Mission profile ______21 B. Cooling circuits in AMESim ______23 C. Cosimulation ______25 D. Simulation plan ______27 1. List of variables ______27 2. Post processing ______28 III. Results ______30 A. Differences between the V3 and V4 models ______30 B. Temperature and Friction results ______32 1. First study on V3 ______32 2. V4 model ______33 C. Pressure Losses of Controlled Valves ______40 IV.Computation issues ______42 A. Physical Problems ______42 B. Numerical Problems ______44 Conclusion ______48 List of abbreviations and symbols used ______49 Figures list ______50 Table list ______51 Bibliography ______52 Appendix ______53 A. Cooling Circuit ______53 B. Cosimulation ______55 C. Performance Analyzer ______56
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Acknowledgments
First of all, I would like to thank my supervisors, Mouad DINY and Diego PAGLIARI, for their time in a busy working schedule and their instructions in order to progress in my missions.
During this internship, I have experienced a lot of computation issues while I was learning how to use AMESim, 0D/1D modeling software, and I could count on the support of Madjid TADJADIT to reveal me the mysteries of the cosimulation. That is why I thank him especially for his time, patience and advices.
Concerning the technical part, I would like to thank Thierry LEGIER who worked in parallel on the same thermal model, giving each other help to get the full understanding of the system SAMGa THE, with some very useful clarifications from Antoine AYRAUD, Philippe MARCAIS and Quentin LEFEBVRE.
Also a thank for the work team members who gave presentations on a few automotive technical subjects to get a refreshed vision of the whole engine operation. Same for Marco SIMONETTI with whom I discussed a lot about fluid mechanics.
Finally, I would like to thank the other interns for the good atmosphere. Special mention to Florian HUMBERT – my desk neighbor – for his good mood and having been able to “endure” every single computer problem I have experienced.
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Introduction
The global car fleet is composed by more than one billion vehicles, making this sector one of the main sources of atmospheric pollution [1] and therefore highly regulated to minimize its impact. The European governments impose increasingly severe standards concerning CO2 and other gas emissions such as NOx or CO based so far on the ‘New European Driving Cycle’ (NEDC) that all new cars sold in EU have to respect. That leads car manufacturers to find solutions combining the best quality/price compromise to comply with the law.
Nitrogen oxides (mg/km)
Euro 4 Diesel
Euro 5 Diesel Euro 6 Diesel
Euro 4 Petrol (mg/km) Euro 5 Petrol
Euro 6 Petrol
Particles
Carbonmonoxide (mg/km)
Hydrocarbons (mg/km) Figure 1 : Comparison of limit car emission values fixed by the EU
Between 2012 and 2013 in Europe, the CO2 emissions decreased by an average of 4% for every major brand [2]. But those data do not take into account the latest fraudulent revelations about Volkswagen (2015) and nowadays the trend is inverted… New cars sold in 2017 emitted on average
118.5 g CO2/km, a slight increase of 0.4 g/km compared to 2016. That could be explained in part by the fact that more petrol cars were sold than Diesel ones for the first time since monitoring started in
2010 (Petrol cars ≈ 121.6 g CO2/km, Diesel cars ≈ 117.9 g CO2/km) [3].
The CO2 emissions of a manufacturer is deducted from the rejections average of each brand model times the number of sold vehicles of this type. Most of the companies tend to reach a certain amount of Based Electric Vehicles (BEV) and Hybrid ones to lower their global emissions. The more a low emissions vehicle is sold, the better the manufacturer global CO2 is.
훴[퐶푂2 푉푒ℎ𝑖푐푙푒 퐸푚𝑖푠푠𝑖표푛 ∗ 푁푢푚푏푒푟 표푓 푠푎푙푒푠] 퐶푂 (푀푎푛푢푓푎푐푡푢푟푒푟) = 2 푇표푡푎푙 푛푢푚푏푒푟 표푓 푠푎푙푒푠
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Figure 2 : Average CO2 emissions from new passenger cars in 2016 [4]
The current target for 2021 is 95g CO2/km, based on the largely questionable NEDC which was designed to allow a comparison of emissions for different manufacturers. Nevertheless, the 70’s test procedure does not represent real-world driving conditions and emissions due among others things to a number of flexibilities that allows vehicle manufacturers to optimize the conditions under which their vehicles are tested. Differences up to 37% were measured between the procedure and real drive emissions [5].
Figure 3 : Divergence of “Spritmonitor.de” from manufacturers’ type-approval CO2 emissions by fuel type [5] Master Thesis Report Amaury ARLOTTO 8
That is why in September 2017, the 'Worldwide harmonized Light vehicles Test Procedure' (WLTP or WLTC with C for Cycle) has been introduced for new vehicle types, expected to give closer real drive emissions in laboratory conditions (rolling bench). Will follow all the new vehicles in Sept 2018 and eventually all end-of-series vehicles from Sept 2019. This new cycle is aimed to reduce flexibilities and loopholes such as battery state of charge largely exploited by manufacturers during a
NEDC to lower declared CO2.
Figure 4 : Velocity profile of NEDC versus WLTP
Many changes have been operated, and some of them are summed up in the next table.
NEDC WLTP Time 20 min – 1200 sec 30 min – 1800 sec Stop time 25% 13% Length 11 km 23.25 km Average speed 34 km/h 46.5 km/h Maximum speed 120 km/h 131 km/h Maximum acceleration 1 m/s² 1.5 m/s²
Table 1 : Differences NEDC / WLTP
Those stronger accelerations/speeds and reduced stops will irredeemably lead to higher fuel consumption per kilometer (↗ 15-20%) [6]. It is inconceivable to apply directly the 2021 NEDC target of 95g CO2/km to the new cycle and it has been set the CO2 WLTP emissions standards will be derived from vehicle-specific NEDC – WLTP correlation factors, obtained by the CO2MPAS software [7]. Only will remain identical the other air pollutant emissions limit values.
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Figure 5 : Schematic illustration of the expected effect of the transition from NEDC to WLTP on post-2020 CO2 targets for passenger cars [8]
As a reference in this master thesis, most of the simulations will be based on WLTC in addition to heavier load cycles required for a few specific driving conditions.
This master thesis has been conducted within the French automotive company ‘Groupe PSA’ in La Garenne-Colombes next to Paris, in the advanced research department focusing on thermal engine architecture. It is the second automotive industry in Europe managing five brands :
Peugeot, Citroën, DS Automobiles, Opel and Vauxhall (the last two since August 2017) representing 17% market share, 65.2 billion euros in sales in 2017 and nearly 170 000 employees worldwide.
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Context
In average, a European driver trip does not exceed 8km (lowered at 2km for 40% of the French people!) and happens under cold start [9], [10]. The engine operates then in transient thermal conditions, far from its optimal running temperature; the fuel consumption is increased due to degraded combustion efficiency and an oil still too viscous unable to lubricate enough. Same conclusion for the gas emissions even worsen given the fact post-treatments devices such as the Selective Catalytic Reduction (SCR) or the catalytic converter are inefficient until a certain temperature.
Figure 6 : Comparison of engine consumption on NEDC between cold and warm start (Sogefi Faurecia)
To ensure the fastest engine warm-up, a research axis focuses on engine thermal management, i.e. the control and regulation of the different cooling circuits. Mainly for economic reasons, the cooling circuit kept the same global strategy for a long time. A thermostat – actuaded or not – is used to block the circulation towards the radiator during cold conditions. Once a certain temperature reached, the flow is allowed and the engine cooled. N.B. The heater is often not controlled.
Radiator Radiator
Heating jacket Sealing Radiator plate
Heater Engine Heater Engine
Engine Wax Engine Bypass plate Thermostat closed Thermostat open
Figure 7 : Working principle of a thermostat Master Thesis Report Amaury ARLOTTO 11
A few automotive suppliers have developed solutions including a controlled valve instead of a simple thermostat, giving a more precise and quick control of every cooling circuits. Even if it has a real gain (quick warm-up with no-flow strategy and more precise temperature control) on efficiency and safety, this solution is however more expensive and mostly premium cars are equipped.
Figure 8 : Thermal Management strategy with the controlled valve Mark IV [11]
Another solution currently studied within the PSA Group concerns the thermal management of the gearbox, today warming up with internal frictions and reaching a constant efficiency at 80°C only after a very long time (only 50°C for two WLTC in a row in simulations). The coolant energy during transitional phase could be used to reduce this delay, and improve the efficiency in a shorter time.
This master thesis work is about finding and validating the best cooling circuit architecture compromise between a quick gearbox warm-up with a reasonable impact on the engine performances through simulations on a thermal model.
The report will present the solutions considered by the PSA hydraulic team and their thermal AMESim model associated followed by the simulation plan. In another part will be shown the results obtained. Finally, it will be concluded by an overview of all the main computer issues that happened during the coding period.
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I. Research axis
A. State of the art – Original cooling architecture
For the 4th time in a row, the Turbo PureTech 3-cylinder petrol engine (EB2DTS) was rewarded by the International Engine of the Year Awards. Benefiting from 210 patents, improvements such as a decrease of 4% in fuel consumption and 75% in particulates emissions from the previous generation have been achieved, while reducing turbocharger response time [12].
Figure 9 : EB2DTS designed as 1.0-1.4l Engine of the year 2018
In order to maintain this high level of performances and to respect the new 2021 standards, a focus is done on the gearbox thermal management, neglected in favor of the engine itself till now. As shown in the next figure, the cooling circuit allows a flow in the automatic gearbox only if the main thermostat is opened, i.e. for an engine cooling request. The heat exchanger is located in front of the AGB (automatic gearbox, ATN8 model for PSA) with two hose connections on the radiator return pipe (that could impact the radiator flow about 5-10l/min because of higher pressure losses). Another architecture places the AGB return next to the pump, which is less restrictive. The gearbox does not receive any heat from the coolant during the warm-up
phase, and this is precisely the point of this Radiator research. It aims to check if there is any Heater positive effect on the global friction losses by taking heat from the engine towards the gearbox. Gearbox To be noted also that an auxiliary circuit in purple completed by an electric water pump (used in case of overheating for stopped engine) feeds the Water / Oil exchanger and the Turbo. Figure 10 : EB2DTS ATN8 €6.2 Cooling circuit Master Thesis Report Amaury ARLOTTO 13
B. New cooling architecture hypotheses
To warm-up the gearbox, the heat could either comes from an additionnal electric heater or from the coolant itself through the engine energy. Whatever the solution taken, the use of energy originally given has to be largely compensated in order to get a real global consumption gain.
A few ideas have already been presented within the cooling circuit department of PSA, and the advanced research team from where I belong is aimed to clarify their potential gains of the architectures thanks to 0D-1D simulations. Models are created using the original series production engine architecture (that will be referenced as €6.2 for the rest of the report) and modified to match the new design.
So far, three main concepts have been chosen to be studied in simulations (H1, H2 and H4, ‘H’ for Hypothesis). They require more or less adjustments on the actual circuit (that could be translated by a cost price difference which is a real counter argument in the car manufacturing industry). Those simulations can be divided into two different parts, the first focusing in every hydraulic aspects (flow, pressure losses, etc.) while the second will include heat exchanges and friction losses.
The first hypothesis involves a permanent flow in the AGB. During the warm- up, a slight return flow from the water outlet housing go through the gearbox (represented by the blue arrows) and the turbo. An electric water pump (EWP) is added in the case of a closed thermostat (ThC – Thermostat Closed) and a cooling request in the gearbox.
During ThC (i.e. no radiator flow), the coolant usually takes the bypass circuit and returns directly to the pump as represented in Figure 11 : Hypothesis ‘H1’ Cooling circuit Figure 7 above. It requires however a certain Heating return flow + two check valves pressure to counter the pressure drop of the check valve used to block the flow at low speeds.
Given the actual €6.2 circuit parameters, the return flow does not exceed 3l/min and no significant heating impacts are measured. A solution could be to lower the pressure required upstream the checkvalve spring ( reduction of the stiffness coefficient) but the project has been abandoned and H1 will not be studied more in details in this thesis.
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The two other hypothesis are derived from the same idea of using the coolant energy taken from the Turbo and Water / Oil exchanger circuit (in purple on €6.2 Figure 10). In both cases, a thermostat is meant to define the temperature for which a heating flow towards the AGB is allowed, paired with two check valves to prevent any return flow towards the radiator during warm-up or turbo during cooling.
The flow is derived in part towards the gearbox during warm-up thanks to a thermostat. The turbo water return is directly connected to mechanical pump for the architecture H2, while in H4 the heater benefits from this additional flow, giving a better pleasant interior performance.
Another thermostat is assembled with the first one in a thermostatic housing in H4 to close the heating gearbox circuit for efficiencies and safety issues.
The optimal temperatures for opening and closing are part of the master thesis research.
Figure 12 : Hypothesis ‘H2’ Cooling circuit Thermostat + two check valves
1 2
Figure 13 : Thermostatic housing for H4
During the early warm-up phase, the coolant goes directly from the engine/turbo (A) to the heater (B). Once a certain temperature is reached, the thermostat 1 opens and allows a heating flow towards the gearbox (C). In case of overheat therefore a real need of cooling, the Figure 14 : Hypothesis ‘H4’ Cooling circuit thermostat 2 closes the circuit not for degrading Thermostatic housing + two check valves the process.
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Figure 15 : Opening/Closing Gearbox heating flow in the thermostatic housing
The indicated temperatures are informative and are subject to changes. The thermostat 1 starts opening at T1OP allowing a heating flow towards the gearbox, with maximum section at T1 = T1OP +10°C. The second thermostat is used to close the circuit, with the same principle and a 10°C gap, for safety concerns. The master thesis will work as well on the relevance of this second thermostat, i.e. if this occasional overheat would be really damaging for the gearbox, and by extension for the engine.
In this case, the gearbox receives the maximum heating flow between 80°C and 100°C.
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C. Controlled Valve on a H4 basis
Another working direction would focus on the implementation of a controlled valve instead of a thermostatic housing, aiming to give a better and more precise control according to the situation. It could bring safety by being able to close quickly the heating flow when it is needed, without having to wait the maximum temperature imposed by the 2nd thermostat.
Figure 16 : Hypothesis 'H4' with a two ways controlled valve + one check valve
Figure 17 : Hypothesis 'H4' with a three ways controlled valve
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The choice of a controlled valve (two or three ways) over a thermostatic housing could have both pros and cons. The next table sums up a few of them from a global point of view.
Advantages Drawbacks
• Response time ~ 20 sec Thermostatic • Simple component • Limited number of cycles Housing • PC low • Defined strategy
• Quick and precise • PC high ( x 3) Controlled Valve control • Need of an additional ECU • Controlled flow control • Durable
Table 2 : Differences Thermostatic Housing / Controlled Valve
Given its high production cost (PC), the controlled valve errs from an industrial point of view as it is often the case for more technological solutions. Among all the advantages offered by the valve such as better flow and temperature control, the reliability could make the difference knowing a thermostatic housing suffers from a limited number of cycles (opening/closing) due to the first thermostat operating far from its opening temperature (causing more and more stress on the structure if the temperature gap is bigger and bigger).
The defined temperature for the second thermostat could lead also to a risk of overlapping cooling / heating in the case of maximum cooling request. The simulations have to evaluate the impact in this scenario.
Finally, a three ways valve is supposed to take less space in the engine compartment, which is not negligible.
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II. Simulation – AMESim
The software used to estimate the potential gain of a given architecture is Simcenter AMESim developed by Siemens PLM Software which aims to describe models through nonlinear time- dependent analytical equations that represent the system’s hydraulic, pneumatic, thermal, electric or mechanical behavior in a 1D simulation. Therefore, it does not need a detailed geometry of the system to perform, and is often use in early research phase. By its principle, it is similar to Simulink, or GT- Power.
A. Thermal AMESim Model (SAMGa The)
1. General description
PSA has developed a very complete thermal model SAMM (“Simulateur d’Architecture Mécanique Moteur” or “Mechanical Engine Architecture Simulator”) of the engine decomposed into submodels which encompasses the vast majority of engine components (including fluid circuits). It is used as a conception support of the powertrain to define, optimize and justify the thermohydraulic operation by checking the main goals such as :
Guarantee thermomechanical behavior and durability of parts.
Guarantee the thermal resistance of the lubricant.
Optimize engine mechanical efficiency.
Guarantee the cabin thermal comfort.
The computation concept is based on a nodal decomposition approach that divides a physical system (solid or fluid) into a number of finite elementary volumes called « nodes », each considered as isothermal and modelled by means of global parameters. For each node “i” of the thermal network, the first law of thermodynamics applies and the internal energy variation is equal to the amount of heat exchanged with adjacent nodes or with external heat sources/sinks:
Heat sources or sinks (W) Internal energy variation « external » to the nodal network, Ci : thermal capacitance (J/K) but applying on node i
Heat transfers (W) through convection, conduction, radiation or fluid transport between node « i » and adjacent nodes
dT i Ci k sources dt k
Equation 1 : First Law of Thermodynamics applied to a node 'i' Master Thesis Report Amaury ARLOTTO 19
A compromise between model construction/CPU time and model accuracy has to be found in order to optimize the global time of computation. An engine is however a very complex assembly dealing with a certain amount of distinguishable heat transfers complicating the process.
Figure 18 : Description of main heat transfers into an engine
The nodal model derived from the component geometry is explained in the next figure.
Figure 19 : Methodology used in building a SAMM supercomponent
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2. Mission profile
In order to run the SAMM model, the simulation needs to follow a mission profile given by a data file taken from a real driving test. This file includes four very important additional parameters :
Vehicle Velocity, Engine Rotary Speed, Gearbox Shift and BMET*SAMM.
The velocity can be based on a official cycle such as NEDC or WLTC. The rest of it depends on the engine (apart from some gearbox shift specifications). The torque input data for mission profile in the SAMM model is BMET*SAMM (Break Mean Effective Torque* SAMM definition) defined as :
BMET*SAMM =BMET*+ FMET electric load + FMET hydraulic fuel pump losses
Equation 2 : Definition of BMET*SAMM
Vehicle
Wheel VHL torque Electric torque BMET demand accessories
Inertia consumption
Friction losses
+ Hydraulic fuel ΔFriction losses BMET* IMET* IMET Gearbox pump losses + losses + Motored/Fire Electric load Engine Alternator
Engine
The model receives this torque as an input so it can deduce the Indicated Mean Effective Torque (IMET) requested by the engine to counter all the internal friction losses (FMET) already implemented in the simulation. Those FMET can be divided into two categories:
- The “viscous” friction torque which directly contributes to the oil warming (Camshaft, Vacuum pump, Bearings, Crankpin…) - The « mechanical » friction torque (Coolant pump, Accessories, Fuel pump, Oil pump…)
The current working model is a SAMGa The, which is just a SAMM adapted for thermal study.
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Cylinder pressure Exhaust manifold model model
Cooling circuit model Upper cylinder bloc model
Oil circuit model
Crankshaft model
Gearbox model
Figure 20 : SAMGa The model - Mechanical part
Each framed supercomponent is a specific part of the engine that can be change independently as long as it respects the same global connections with the rest of the SAMM. In this master thesis, almost all the focus is done on the cooling circuit.
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B. Cooling circuits in AMESim
In order to complete the study, the previously presented cooling circuit architectures were converted into AMESim models. For a shorter presentation, only the H4 circuit and its variations will be described. The principle remains the same for the others with just local adaptations given their common €6.2 basis.
Thermostat control Sensors
Sensors
Cooling circuit model
Figure 21 : Cooling circuit supercomponent in the SAMGa The model
The dashed lines and the transmitters make the link between the different structures, and depend on the type of physical data (hydraulic, thermal, signal, etc.). The global cooling circuit (H4) can be found in Appendix 1. The main change between the different architectures concerns the gearbox thermal management and as shown in the next figure, one can find the overall concept of the hypothesis H4, with a flow division after turbo between the heater and the gearbox. The thermostatic housing is however not represented leaving only the first thermostat for the model. The second is in theory only requested for safety reasons, and there is no need to take it into account except in the case of specific engine challenging scenario (i.e. strong temperature gradients).
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From bypass From engine
To heater To engine
From Gearbox oil/water 1st Thermostat exchanger
Radiator
To engine (expansion tank) Check valves Gearbox
Figure 22 : AMEsim gearbox cooling circuit H4
The hose, radiator and other components parameters are taken from hydraulic tests. Among other things, the volume/diameter, the maximum coefficient flow Cqmax and the critical flow number (laminar turbulent) are defined. The flow and pressure losses are a result of them.
The previous study used this model H4 as a reference for the tests except for a difference in the mechanical pump (Appendix 1), from a component to a signal representation. The new study will use this updated version (pump with signal) because less crash is noted along with a CPU time optimization.
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The 3 ways valve solution is based on a slight different H4 (Electric pump and thermostatic housing in the turbo bypass) after discussions with the cooling circuit department of the company, and new modeled version of H4 was developed:
Figure 23 : Model H4 with a 3 ways valve solution
On this version of H4 with a 3 ways controlled valve (with a basic step temperature control in this case), the latest improvements are modeled as well as a gearbox modeling refinement. Any changes on the AMESim cooling circuit model have to be checked with the hydraulic department of the company.
C. Cosimulation
AMESim is able to be on its own as long as all the component maps are filled. The previous study had all the system mappings included in the model, and only a mission profile (cycle, engine speed, etc.) was requested. It is however not precise enough given the complexity of running an engine, especially for the control part. That is why a whole cosimulation process was implemented to handle this aspect by mixing three softwares:
AMESim – Matlab – Simulink
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AMESim remains the main modeling software but is not directly controlled anymore from the inside. Simulink gets the whole engine control code, producing data according to the different physical and cycle conditions that AMESim reinjects in the simulation. It gives a more dynamical computation compared to temporal mappings for control. And Matlab aims to coordinate the whole process by defining the initial conditions, starting the simulation and organizing the results.
S-function
Figure 24 : S-function for cosimulation AMESim/Simulink in AMESim
The S-function is a self-generated module between AMESim and Simulink that links both of them. AMESim sends variables such as engine temperatures or fuel consumption and receives in return an adapted control and other defined data. It goes from data from the cycle but also to the thermostat setpoint, air ratio or A/C heat. The same principle can be found in Simulink (Appendix 2).
In fact, it could be possible to use AMESim for the control command as well but Simulink is historically more appropriate, especially given the simpler way offered to convert its code into the one in the electronic control unit (ECU). Moreover, a distinction between a physical model and its control code is a classical division of work.
To clarify, the old model without cosimulation from the first study and the new one including it are referenced as the V3 and V4 model. All the new simulations are meant to be perform on the V4 model once its reliability is checked.
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D. Simulation plan
1. List of variables
Even if it is possible to retrieve the fuel consumption in the AMESim model, it is however not representative of the real conditions due to missing combustion models (too heavy to be included). The main interesting variable in a thermal model is the temperature which can be considered as reliable. Starting from that, three temperatures are required to estimate any consumption gain from the different architectures:
Coolant Temperature – Oil Temperature – AGB Oil Temperature
Indeed, each of these temperatures impacts a particular parameter.
- The coolant temperature (or engine temperature) affects the combustion efficiency, increasing it when it is high. It has to stay under a maximum value to avoid any engine knock. - The oil temperature, while increasing, reduces the engine friction losses. - The AGB oil temperature follows the same principle with gearbox friction losses.
For the first study, a PSA department specialized in consumption was commissioned to evaluate any consumption gain through temperature/friction maps but this master thesis will only be focusing on temperatures and internal friction results, these last referenced in the next table:
Component AMESim Abbreviation Camshafts AAC Vacuum Pump PàV Piston Cylinder SPC Crankpins MBC Crankshaft Vilo Internal Frictions Lubricant Pump Méca PàH Accessories Alternateur Lubricant Pump Hydraulic Hydro PàH Balancing Shafts AEQ Cool Pump Hydraulic Cool Pump Fuel Pump Fuel Pump Engine Loaded FMET Eng loaded FMET Global frictions Engine FMET Eng FMET Torque conv Torque converter losses Gearbox Transmission Internal Losses
Table 3 : Friction losses list Master Thesis Report Amaury ARLOTTO 27
Those frictions are computed in different parts of the AMESim model; respectively in the oil circuit, the main body and the gearbox model. The Energy lost by friction (EMF – Energie Moyenne de Frottement / Friction Mean Energy) is obtained after integration of the friction Power (PMF) itself deducted from the product of the engine speed (n.b. Régime moteur) and friction Torque (CMF – Couple Moyen de Frottement / Friction Mean Torque). The results are taken in output of these computation elements and exported via Matlab.
Figure 25 : Internal Frictions in AMESim - Oil Circuit submodel
A special case concerns the Engine Loaded FMET. Indeed, all the energy computation are based on a motorized engine (running without combustion) and this loaded friction energy is supposed to compensate by simulating an additional combustion load on the mechanical engine links. This calculation is unfortunately not well calibrated and reliable, requesting more evaluation and testing by PSA team to validate it; it has been decided not to take it into account to rank the different settings.
2. Post processing
The friction energy results are then filtered in function of the fuel consumption, superior or not to zero. Even if the real fuel flow is not reliable, the zero consumption is the only certain value. This filtration is meant to restrain the friction losses sampling for running engine only.
퐸푀퐹푓푖푙푡푒푟푒푑(𝑖) = 퐸푀퐹푓푖푙푡푒푟푒푑(𝑖 − 1) + [퐸푀퐹(𝑖) − 퐸푀퐹(𝑖 − 1)] ∗ (퐶표푛푠표(𝑖) > 0)
Equation 3 : Filtration method of the total friction energy
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Once every friction energy has been filtered, they can be summed depending on which data is required:
EMF Gearbox : Sum of Torque Converter and Internal losses Gearbox losses
EMF Internal : Sum of Internal Frictions
EMF Engine : EMF Internal + Engine FMET
EMF Total Non-Loaded : EMF Engine + EMF Gearbox Final comparator
These data are compared for every architecture with the results from the basis €6.2, giving a percentage of difference:
퐸푀퐹푁푒푤 퐷𝑖푓푓푒푟푒푛푐푒 (%) = ( − 1) ∗ 100 퐸푀퐹€6.2
Equation 4 : Percentage difference between EMF
Another interesting value is the evolution of temperatures on a same plot, to check directly the effects from such-and-such architectures. Obviously, each simulation has to follow the same driving for a true comparison lying on a common factor. For an official gain estimation, the WLTC is mainly chosen but more load demanding cycles are used to check the safety performance.
As presented before, only four data are required to run a simulation:
Vehicle Speed – Engine Speed – Gear Shift – Break Mean Effective Torque (SAMM)
This data file depends also on the vehicle, especially its mass and type of transmission. For schedule reason, the vehicle mainly studied in this master thesis is the lightest in PSA range (EMP1min). In order to identify the results from this type of vehicle, the driving cycle name will be followed by “3.101” which is the type of transmission for those light vehicles (compared to “3.501” for the heaviest vehicles EMP2max).
Even if a previous study has been operated, the SAMM model changed in the meantime with the cosimulation appearance. A first very important task would be then to check if the same previous trend is observed given the architectures. It means that every coolant circuit tested, including the €6.2 one, has to be tested on the different cycles (WLTC and CLTC, C for China) and transmissions. It was decided to focus only the WLTC with 3.101 transmission.
All those tests were done here to verify the reliability of the V4 model, and correct any potential issues. A comparison with a real test could be considered to finalize the reliability estimation. Once everything is done, in addition to the WLTC, two WLTC in a row could be used to test the behavior at high temperatures. Specific other loaded cycles will be tested to check the safety for high increase of load/temperature.
Eventually, a study on pressure losses of the controlled valves will be done to define the characteristics for automotive suppliers.
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III. Results
A. Differences between the V3 and V4 models
In order to investigate further in the research, a first step consists in defining the reliability of the V4 model, supposed to be more accurate thanks to the cosimulation and updated system mappings (such as combustion and gearbox cartographies). The water and oil temperature will be compared to the results obtained in the first study with V3, but also with a reference real test and a V4 model with previous V3 mappings. The cycle is set to be a WLTC on a €6.2 cooling circuit basis.
Unfortunately, not all of input parameters have been similar for strict comparison and could not be changed a posteriori; the initial temperature in V3 model previous tests was 18°C while the only reference real test data received starts at 12°C. It has been decided to run the V4 from both 18 and 12°C. The real engine for reference test is more loaded than the simulation one and the thermostat is controlled in real conditions while it is passive on computer. Despite all these differences in the establishment of a comparison protocol, it will be taken into account for the conclusion.
Figure 26 : Comparison of the water temperature between the V3 and V4 model
The red plot is the reference test water temperature, the dashed one is the V3 result and the orange curve is from V4 (both starting at 18°C). The rising temperature is slower for V4 due to a less loaded engine than real test. After 800 secs, the differences can be explained by the thermostat control, not taken into account in the simulations (passive behaviour only). The control is meant to define a new opening temperature in function of an engine cartography about engine speed and load in order to protect with lower cooling temperature the engine. For WLTC, it happens during the highway part lowering the engine water temperature setpoint around 85°C instead of 97°C.
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Figure 27 : Comparison of oil temperature between the V3 and V4 model (WLTC)
The results are slightly closer in the case of oil temperature between the V4 and reference. Moreover, the V4 with V3 maps tends to show the same quick rising temperature as V3 that can be considered as too far from reality (shorter rising temperature time for less loaded engine than reference).
In conclusion:
- The different starting temperatures do not show a real impact on final results, so it can be considered as negligible. - The temperature rise is quicker for V3 (or V4 with V3 combustion and gearbox maps) than the reference which has a more loaded engine. The V4 results make more sense in this point of view. - The stabilization part (after 800 sec) differences are due to a thermostat control (opening in function of the load in real driving conditions).
The V4 model can be validated, and now the previous results from the first study could be questioned. This is once again the purpose of this master thesis.
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B. Temperature and Friction results
1. First study on V3
A previous study has been conducted on the reliability of the different cooling architectures proposed using several vehicle and transmission types (chassis weight and final gear ratio). Variables such as coolant/oil/gearbox temperature and friction losses were checked. A first set of results suggested H4 gives the most significant gains with a complete opening temperature of the first thermostat at 100°C.
€7 H2, th. €7 H2, th. €7 H4, th. €7 H4, th. €7 H4, th. vehicle trans. cycle €6.2 €7 H1 AGB 0 °C AGB 80 °C AGB 0 °C AGB 80 °C AGB 100 °C EMP1min 2.750 CATC high 0.00% 0.04% -0.45% EMP1min 2.750 CATC normal 0.00% -0.02% -0.74% EMP1min 2.750 WLTC 453 0.00% -0.03% -1.07% EMP1min 3.101 CATC high 0.00% 0.04% -0.90% EMP1min 3.101 CATC normal 0.00% -0.80% EMP1min 3.101 WLTC 453 0.00% -0.03% -1.37% EMP2maxi 3.540 CATC high 0.00% 0.07% -1.85% EMP2maxi 3.540 CATC normal 0.00% -0.73% EMP2maxi 3.540 WLTC 453 0.00% -0.01% -0.96% EMP2maxi 3.540 CLTC 0.00% -1.18% -1.15% -1.21% -1.65% -1.80% EMP2maxi 3.540 WLTC 454 0.00% -0.96% -0.94% -1.42% -1.68% -1.75% EMP1min 3.101 CLTC 0.00% -1.02% -1.00% -1.77% -2.15% -2.38% EMP1min 3.101 WLTC 454 0.00% -1.37% -1.35% -2.72% -3.03% -3.16%
Table 4 : Friction losses (EMF Total Non-Loaded) comparison from €6.2 for V3 model
Not all the configurations were tested (especially special cycles such as CATC) but a special attention was given to the promising H4 architecture. The temperature corresponds to the maximal opening temperature of the gearbox thermostat, and a 10°C gap between closing and maximum temperature has been set (i.e. Thermostat AGB 80°C starts its opening at 70°C). As a reminder, H1 was abandoned given the low performances due to too small flow in the gearbox during warm-up.
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2. V4 model
The first simulations aimed to verify the friction gains from V3, and therefore a common cycle and vehicle were chosen (WLTC – EMP1min) in order to get a real comparison.
The original goal of the internship was to check if a controlled valve instead of a thermostatic housing would be more performing. However, after reflection, there would not be any significant friction gain from a thermostatic housing with optimized temperature opening if the only control parameter is the temperature. The last potential relevant argument concerns the safety, and that is why more engine challenging cycles were followed. Two WLTC in a row to check high temperature behavior, and different loaded cycles (described later).
Nb.: The thermostat control command in the Simulink model was not implemented until mid- August so most of the simulations ran without. Once the update had been done, simulations ran with ThP On (Actuated Thermostat On) and both results will be presented.
WLTC – EMP1min – Thermostat Control Off
As H4 appeared to be the most performing architecture in the previous study, a focus has been done on checking the gains via the V4 model. An additional value of gearbox thermostat temperature was chosen (60°C). None of the previous values could be used in this simulation so the €6.2 reference was also resimulated on V4. The initial temperature has been set to 18°C as it was during the first study. Four thermostat opening temperatures have been tested (0°C 60°C 80°C 100°C) and the temperature results are presented in the next three plots.
Figure 28 : Water Temperature for WLTC (€6.2 and H4) Thp Off
The reference is the dashed plot (€6.2) and the first observation is a slower rise for lower thermostat opening temperature (Water and Oil). The longer the gearbox does not receive any heating flow, the less the engine is impacted. The case H4 100°C fits almost perfectly with the reference due
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to the fact that the water temperature does not reach 100°C (and barely 90°C) preventing a total opening of the heating flow. An engine cooling from the radiator is therefore requested for a stabilization between 90°C and 100°C, and the gearbox barely receive any heat (cf Figure 30).
Figure 29 : Oil Temperature for WLTC (€6.2 and H4) ThP Off
In this case, an opening around 80°C seems to be a good compromise allowing the engine to warm-up without too much slowdown and leading the gearbox temperature quickly at 80 °C where the AGB efficiency starts to be constant.
Figure 30 : Automatic Gearbox Temperature for WLTC (€6.2 and H4) Thp Off
Only the friction results could give a real a confirmation so they were exported as well.
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The important variables to look after are the internal frictions / FMET (increased due to slower engine warm-up) and gearbox ones (reduced with faster warm-up) for increasing thermostat opening temperature. The total results in a global reduction of the frictions:
€6.2 H4 0°C H4 60°C H4 80°C H4 100°C EMF Internal 0,00% 3,29% 2,46% 1,25% -0,28% EMF Internal (Filtered) 0,00% 3,15% 2,37% 1,20% -0,32%
Internal + FMET 0,00% 3,64% 2,77% 1,51% -0,04% Internal + FMET (Filtered) 0,00% 3,51% 2,69% 1,47% -0,07%
EMF Gearbox 0,00% -22,85% -21,60% -18,92% -4,86% EMF Gearbox (Filtered) 0,00% -22,97% -21,83% -19,35% -5,10%
Table 5 : Friction differences between €6.2 and H4
For information, the ratio EMF Gearbox / Internal+FMET is around ¼. Both filtered and non- filtered results were dispatched to show the impact of a filtration. The gains are increased after process because the real gain is done when the engine is running. The total gain is presented on the next table.
EMF Total Non-Loaded 0,00% -3,06% -3,39% -3,66% -1,26% EMF Total Non-Loaded (Filtered) 0,00% -3,70% -3,99% -4,20% -1,44%
Table 6 : Total friction gain between €6.2 and H4
As set before, the FMET loaded is not taken into account but for information purposes, the next table includes them because the first study used them.
€6.2 H4 0°C H4 60°C H4 80°C H4 100°C EMF Total Loaded 0,00% -0,72% -1,07% -1,71% -0,60% EMF Total Loaded (Filtered) 0,00% -0,59% -0,95% -1,65% -0,60%
Table 7 : EMF Total Loaded (Internal + Gearbox + FMET Loaded)
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The trend is similar with the previous V3 study (and V4 with V3 cartographies), except for H4 100°C which has a lower gain in V4 compared to a continuous gain augmentation with thermostat temperature for V3.
By comparing the results with two different cartographies on a same model, one can highlight the fact higher temperature rise with old V3 maps leads to better performance on H4 100°C, the poor gearbox gains being compensated by the engine higher temperature gradient.
In a simulation point of view, the loaded results are too different for a validation of this calculation (as previously stated on page 28), and only the non-loaded ones are chosen to classify the performances.
€6.2 H4 0°C H4 80°C H4 100°C EMF Total Loaded (Filtered) V4 mapping V3 0,00% -2,46% -2,76% -2,43% EMF Total Loaded (Filtered) V4 0,00% -0,59% -1,65% -0,60% EMF Total Non-Loaded (Filtered) V4 mapping V3 0,00% -4,11% -4,11% -3,29% EMF Total Non-Loaded (Filtered) V4 0,00% -3,70% -4,20% -1,44%
Table 8 : Friction differences between cartographies on V4
Not only the add of the cosimulation was beneficial, but the update of combustion and gearbox maps are part of creating a model closer to reality. However, no matter the thermostat temperature opening, a gain is always noted proving the relevance of such cooling circuit architectures.
WLTC – EMP1min – Thermostat Control On
The main difference concerns the part after 1600 sec (high speed in a WLTC), and a stronger regulation is applied to the thermostat. The water temperature is closer to 85°C (compared to 90°C for no control). Hence not a lot of changes on the temperatures plots (except for H4 100°C, completely useless).
Figure 31 : Water Temperature for WLTC (€6.2 and H4) Thp On
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€6.2 H4 0°C H4 60°C H4 80°C H4 100°C EMF Internal (Filtered) 0,00% 3,14% 2,36% 1,19% -0,34%
Internal + FMET (Filtered) 0,00% 3,49% 2,67% 1,45% -0,09%
EMF Gearbox (Filtered) 0,00% -22,72% -21,57% -19,09% -3,60%
EMF Total Non-Loaded (Filtered) 0,00% -3,63% -3,92% -4,13% -1,04%
Table 9 : Friction Results Thermostat Control On (WLTC)
The results are slightly lower than without control given a stronger regulation therefore a lower water temperature (and higher engine frictions). But from now, as the results are quite similar, mainly the case without control will be focused given the time spent without in simulations.
Double WLTC – EMP1min – Thermostat control On and Off
This part aims to find out how the system reacts at high temperature. The driving cycle is composed of two WLTC in a row, the second one starting then at high temperature.
Figure 32 : Water temperature for Double WLTC (€6.2 and H4) ThP Off
The gearbox finally reaches 80°C after two WLTC with H4 100°C while it is only at 40°C for €6.2. It shows clearly the need of a gearbox heating because a lot of frictions happen in the gearbox until 80°C. Even if the second thermostat is not represented on the model, supposed to close the heating circuit at 110°C, two WLTC do not reach a fatal temperature value for the gearbox (> 120°C). A thermostatic housing could work well enough and a controlled valve would not be useful even for safety reasons. But more load challenging tests could show an eventual need for closing the heating faster than at 110°C.
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Figure 33 : AGB Temperature for Double WLTC (€6.2 and H4) ThP Off
€6.2 H4 0°C H4 60°C H4 80°C H4 100°C EMF Total Non-Loaded (Filtered) 0,00% -3,61% -3,76% -3,85% -1,97% Double ThP Off WLTC EMF Total Non-Loaded (Filtered) 0,00% -3,37% -3,52% -3,60% -0,83% ThP On EMF Total Non-Loaded (Filtered) 0,00% -3,70% -3,99% -4,20% -1,44% Thp Off WLTC EMF Total Non-Loaded (Filtered) 0,00% -3,63% -3,92% -4,13% -1,04% Thp On
Table 10 : Friction results for double WLTC (and comparison with WLTC)
The results are slightly lower when control is on as before, explained by a lower temperature for stabilization. For a quick comparison, the results from WLTC were added and the gains are higher for a single WLTC in general due to the fact that the whole powertrain is almost already completely hot after 1800 sec, and no further improvements could be achieved by the architectures. They are meant to perform after cold start.
But even if no additional gain is observed, the same trend is present. It justifies completely the relevance of the H4 architecture even for long trips which could find its utility in the Parisians trafic jams where a driver spends 45min on average every day [13].
It is mainly due to the fact the gearbox only heats up by its own frictions in €6.2 which takes a very long time before a constant efficiency appears. All those friction gains come along with fuel consumption.
Once again the H4 80°C is the best compromise, and this means less mechanical stress would be received by the thermostat operating at 95°C after opening (temperature gap of only 15°C).
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Real Driving Emission Cycle with high engine load
Finally, in order to check behavior at high load, a specific cycle has been followed with high load profile, more demanding for the engine and increasing more quickly the temperatures.
Figure 34 : Speed profile of K9 Cycle
As predicted, the water temperature rises in a reduced time 100°C (300 sec compared to 800 secs for WLTC). There is an overshoot for €6.2 and H4 100°C but quickly managed by the thermostat and the constant open gearbox heating circuit does not seem to impact that much on engine safety (Engine T°C max should stay under 120°C to avoid knock).
Figure 35 : Water temperature for K9 cycle (€6.2 and H4)
It can be concluded that even without a closing thermostat in the thermostatic housing (non modelled in AMESim), the engine is not affected enough at high load increase to consider adding it, and even less with a controlled valve solution. It is proven by the fact all the architectures plot fit more or less after 300 secs.
The loaded tests did not show evidences for requirements with such a closing thermostat because the impact of heating the gearbox on engine cooling is too low. The gearbox would not overheat if the engine does not as well, proved by €6.2 behavior for double WLTC. Master Thesis Report Amaury ARLOTTO 39
C. Pressure Losses of Controlled Valves
A study has been conducted however on the parameters that a controlled valve should have, with a focus on a 3 ways solution, more compact. Those results could help also redefining the maximum pressure losses of the thermostatic housing and check valves authorized.
An important subject concerns the pressures losses as well as no flow strategy (potential leakages). It allows to check if the flow in the gearbox is sufficient (for heating and cooling). The first simulations focused on how much the flow would be affected at different temperatures (Thermostat open or not) and engine speed. The pressure losses depend on the coolant speed so for the case of 6000 RPM, three temperatures have been tested: 80°C (Radiator closed and Gearbox Heating flow allowed), 100°C (Radiator opened), 115°C (Radiator opened and Heating flow stopped).
For a three ways valve, two pressure losses are taken into account, the ones from the deviation next to the turbo (heating flow) and from the radiator (cooling flow). For efficient cooling when overload, the gearbox needs to receive more cold flow than hot, otherwise an overheating could appear hence the need of a closing heating flow.
The test consists in checking the flow and pressure losses for 6000 RPM at different valve pressure losses computed at 10l/min (i.e. the pressure losses of each branch when the engine provides 10l/min). The next table show results for the case T = 100°C, both circuits open.
ThO 100°C – 3 Ways Valve – 6000 RPM 1.4 bar
Heating Flow (l/min) From Heating Circuit (Turbo) dP (mBars) 10l/min 25 50 75 100 125 150 25 24,05 22,30 20,90 19,76 18,81 17,99 50 24,15 22,42 21,04 19,91 18,96 18,14 From 75 24,24 22,52 21,15 20,02 19,08 18,26 Cooling Circuit 100 24,31 22,60 21,24 20,12 19,17 18,36 (Radia) 125 24,37 22,67 21,32 20,20 19,25 18,44 150 24,42 22,74 21,38 20,27 19,32 18,51
Cooling Flow (l/min) From Heating Circuit (Turbo) dP (mBars) 10l/min 25 50 75 100 125 150 25 6,74 7,99 8,95 9,71 10,34 10,87 50 6,38 7,52 8,39 9,08 9,64 10,11 From 75 6,09 7,14 7,94 8,56 9,08 9,51 Cooling Circuit 100 5,84 6,82 7,56 8,14 8,62 9,02 (Radia) 125 5,62 6,54 7,24 7,79 8,23 8,60 150 5,43 6,30 6,96 7,48 7,90 8,24
Table 11 : Flow at 6000RPM from heating and cooling gearbox valve at different pressure losses at 10l/min
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When both circuits are opened, the flow from heating is superior to the cooling one for all cases, due to previous pressure losses more important in the global circuit. It has no effect for intermediates temperatures (except a slight reduction of heating efficiency) and it is not relevant to mandatory add a closing thermostat as the other tests showed.
However, one can define pressure losses requirements for automotive suppliers if a certain target is focused. For example, if the cooling is privileged, the idea would be to find a valve (or thermostatic housing) with the smaller pressure losses from cooling circuit (Radia) along with higher ones from Heating Circuit (Turbo). Those requirements have been colored in green on the previous tables. The heating flow is reduced with the augmentation of pressures losses of the heating valve.
If the cooling circuit valve pressure losses rises, it leads to a reduction of the flow from radiator and vice versa for the heating valve pressure losses. The flow results correlate the ones from dP (Delta pressure/Pressure Losses).
ThO 100°C – 3 Ways Valve – 6000 RPM 1.4 bar
Pressure losses from Turbo (mBars) From Heating Circuit (Turbo) dP (mBars) 10l/min 25 50 75 100 125 150 25 137,7 236,8 312,2 372,1 421,2 462,3 50 138,9 239,4 316,3 377,6 428,0 470,3 From 75 139,9 241,6 319,6 382,0 433,4 476,6 Cooling Circuit 100 140,7 243,3 322,3 385,6 437,7 481,6 (Radia) 125 141,4 244,9 324,7 388,6 441,4 485,9 150 142,0 246,2 326,7 391,3 444,6 489,5
Pressure losses from Radiator (mBars) From Heating Circuit (Turbo) dP (mBars) 10l/min 25 50 75 100 125 150 25 10,8 15,2 19,1 22,5 25,5 28,1 50 19,4 26,9 33,5 39,2 44,2 48,7 From 75 26,5 36,4 45,0 52,4 58,9 64,6 Cooling Circuit 100 32,5 44,3 54,4 63,2 70,8 77,4 (Radia) 125 37,6 51,0 62,4 72,2 80,7 88,1 150 42,1 56,8 69,2 79,9 89,1 97,1
Table 12 : Pressure losses at 6000 RPM for heating and cooling gearbox valve at different pressure losses at 10l/min
For information, a minimum of 10l/min is required in the gearbox to get any significant effects in time. At 6000 RPM, the radiator gets around 225l/min whose only 25l/min (in €6.2) reaches the gearbox. It would mean that the maximum cooling would be affected of around 10% in the case of a thermostatic housing (or controlled valve) with 20l/min of heating flow and 5l/min of cooling in the gearbox (i.e. 200l/min in the gearbox bypass), which is reasonable. Moreover, it is important to keep in mind that the gearbox heating temperature is the coolant’s after engine, which is regulated, preventing from any overheat.
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IV. Computation issues
A long part of this master thesis was about solving all the code/simulation problems before being able to export any data. As the work focused on a new version of the SAMM model just released in May 2018, many tests had to be run in order to check the well-functioning of the simulation, both in terms of physical and numerical points of view.
A. Physical Problems
During the update process, not only the global model had to change but so do the cooling circuit submodels. It means to check every single component parameter to confirm their relevance vis- à-vis the reality, working in parallel with the cooling circuit department of the company.
Moreover and unfortunately, no logbook was available to check the previous changes done on the models and it led to a few deviations from the original work in order to find what was wrong about certain specific values not controlled or resulting in constant output. The advantage with physical problems is they can be easily solved by restoring the right connection. In the other hand, it is quite often very hard to find where the problem comes from because no error message appears as long as the system runs. Giving a result null or another looks the same for a computer point of view.
Among all the physical problems, many were from previous model such as €6.2 which had not been updated for a long time and not suitable for cosimulation in first approach. Some values were stuck at zero, waiting for a cosimulation command. This is the case for the mechanical pump (speed and friction torque). A Cosimulation consign was needed in a constant for an On/Off request, but receiving a constant null value. It was simply deleted to get rid of this problem.
Nb. This Pump model is the ancient one, given that the signal version did not work with €6.2 (cf Appendix 1).
The same happened for the torque calculation. Figure 36 : Error in Pump Consign
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In contrary, the inverted process had to be done to bypass the thermostat command which was incorrect for a very long time, and until any upgrades on it were brought, the thermostat was set to be passive (without control heating of the wax). The water temperature (in red on the next figure) suffers from a too strong decrease after 1550 secs, due to the activation of thermostat heating with a wrong control command decreasing the water temperature under 80°C (to be noted that the thermostat is forced to open when the load is too high, at high speed for example, which is the case at the end of WLTC). Without control, the regulation is around 95°C-100°C and with a good control at high load, it is supposed to be around 87°C. The wax mass has been changed as well to check impact.
T_WATER T_Oil T_AGB
Figure 37 : Temperature rises for WLTC with wrong thermostat control (€6.2)
Another update done on new models such as H4 was forgotten in the €6.2 one. A constant cooling energy (-150 W) in the water expansion tank was previously introduced to regulate the circuit pressure but abandoned in latest updates. But given the very low flow in this pipe, the water temperature could not counter this constant loss of energy, leading the system to decrease the temperature until the absolute zero in this special component. It takes however some time and the crash happens only for long cycles (at 3300 secs with double WLTC for instance), preventing an early discovery of the problem when working on short cycles.
Heat flow rate at port 1 : -150*0+0 W
Error using RunCoSimModif2 (line 164) temperature state in the chamber Error in 'ThMgt_v24_SAMGaThe_20180430/EB2ADTS_ <= 0 K EMP1H4_ATN8_SAMGaThe_20180516/S- CSAC000 instance 1 terminating Function' while executing C MEX S-function program. 'EB2ADTS_EMP1H4_ATN8_SAMGaThe_201805 Total CPU time: 25575.7 seconds 16_', (mdlOutputs), at time 3239.2000000000003. (7 hours 6 min 15.7399 seconds). Caused by: Error using RunCoSimModif2 (line 164) LMS Amesim mexfunction EB2ADTS_EMP1H4_ATN8_SAMGaThe_2018051 6_ did an abnormal exit! Figure 38 : Temperature in the water tank with constant negative energy
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B. Numerical Problems
As often the case in modeling context, the computation time is a factor to take into account. Given the complexity of the system and entanglement of models, problems of convergence are commonplaces leading the CPU time to explode. Depending on the cooling architecture, cosimulation or not, some simulations last over 50h! (especially H4 100°C) while the V3 model only needed 30 min to perform a run (cf Appendix 3). All calculations were run on the computer itself (not on a server) and therefore had to be optimized as much as possible.
Some problem is about the AMESim model, others concern the matlab file used to launch the simulation.
AMESim model issues
▪ Depending on what is exported, some data could not be read due to misunderstood symbols, and a typing error lost in a Pressure sensor was the source of a crash:
Error using xmlread (line 106) Java exception occurred: org.xml.sax.SAXParseException; systemId: file:/C:/User/U538765/Stage/Thermomanagement_BVA/SAMGa_THE/MaJ/Modele_final/01523_17_ 00333_V4_0_CMAG_INCC_SAMMGa_THe_Copie/Models/EB2ADTS_EMP1H4_ATN8_SAMGaThe_201 80516_.vl; lineNumber: 24255; columnNumber: 56; An invalid XML character (Unicode: 0x1) was found in the value of attribute "TITLE" and element is "VAR".
Those errors are solved most of the time thanks to the error message giving a clue about where to find the trouble. Here, a file with the extension “.vl” led to a component unreadable, finally identified in the AMESim model.
▪ Some component cartographies receive data out of their limits that could either slow down the computation or even make it crash. A saturator before the component or defining the limits with extrapolation:
Input data (104.134, 1595.6, 26.4674) are out of bounds in NDFXA0 instance 4 (t=914.25).
▪ The €6.2 model with a signal pump (described with the presentation of H4) does not run and blocks at 2 secs because many components do not converge. Usually, if the problems come from hydraulic component, the best method to handle that is to increase the volume of the hydraulic chamber/pipe. Unfortunately, too many different components were affected, and the solving of one convergence issue created many others somewhere else. It has been decided to use the former version of the mechanical pump for €6.2.
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Matlab issues
As all calculations were launched on computer, it was better to parallelize them for a time gain. But in contrary of AMESim which can create batch runs where many simulations compute at the same time, it is a bit more tricky to use Matlab 2016b for the same purpose. To sum up the principle, a parallelization on Matlab follows the method described below:
- Definition of the AMESim and Simulink models - Importation of the cycle - Definition of the initial parameters (Initial temperature, pressure, etc.) - Writing of the new global parameters (here, the gearbox thermostat temperatures) - “For Loop” in order to launch the different simulations in a row - “Parfor Loop” in order to parallelize them - Export of the results
For better self-understanding, all the parameters and variables have been renamed because the original Matlab file and AMESim were not linked anymore for some specific tasks (export for example). Special functions were used to link with AMESim that will not be described.
Not a lot of real problems happened in the establishment of the method for serial simulations. Things started to go bad when it was question of parallelizing the for loop. Indeed, the use of a parfor loop implies specifications to avoid computation conflicts between the processors. One of the main problem was about the launch of the simulations themselves (done with the simple function eval(['sim ' SLX_Name])). In Matlab 2017, this function ‘sim’ is replaced by ‘parsim’ in this kind of parfor loop, avoiding conflicts of simulations trying to use a same model at the same time for different runs. The matlab code concerns the serial simulation launch:
% Simulation launch loop ------for i=1:nb_simu
%Recuperation of the new batch parameters in a matrix for k=1:length(plex_param_name) plex_param_value_run(i,k)= param_simu{k}(i); end
%Udpate of real AMESim global parameters in S-Function AMESimSetPar(SFunc_Path, char(plex_param_name), plex_param_value_run(i , :) );
%Starting message ['Starting calcul ' num2str(i) '...']
%Simulation launch eval(['sim ' SLX_Name]) % Starts the simulation with the Simulink model
%Recuperation of AMESim results(i) in a matrix [alias_ame, result_value_ame] = fct_load_ame_value(AME_Name, liste_alias); result_ame{i}= result_value_ame; % Results matrix in a list
%Ending message ['Ending calcul ' num2str(i)]
End
For each loop, the AMESim model receives new global parameters (AGB thermostat temperatures stored in ‘plex_param_value_run’), launches the simulation and creates a results matrix.
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In the case of a parfor loop, as a ‘parsim’ function does not exist in Matlab 2016b, a stratagem has to be set consisting in copying every model and S-functions in a temporary folder in order to launch the simulations on independent models.
%Recuperation of the new batch parameters in a matrix for i=1:nb_simu for k=1:length(plex_param_name) plex_param_value_run(i,k)= param_simu{k}(i); end end
% Duplication of AMESim model for parallelizing sys0 = AME_Name(1:end-4); % AMESim model name without ".ame" list_fic = dir([sys0 '*']); % Every files with AMESim name in it
Core = 2; % Nomber of cores in parallel myPool = parpool(Core); eval(['pctRunOnAll addpath(''',pwd,''')']); eval(['pctRunOnAll cd(''',pwd,''')']);
Ws = ws2struct; % Save current workspace in structure clear mex;
% Simulation launch parallel loop ------parfor i=1:nb_simu
if ~isempty(Ws) assignVariableInWorkspace = @(ws, name, value) assignin(ws, name, value); structurecompute = Ws; variableList = fieldnames(structurecompute); for indexVariable = 1 : size(variableList, 1) assignVariableInWorkspace('base', variableList{indexVariable}, structurecompute.(variableList{indexVariable})); end end % Creates differents workspaces
sys_temp = ['mdl_' num2str(i)];
% Copying of all files from the AMESim detarage
for j=1:length(list_fic) [pathstr, name, ext]=fileparts(list_fic(j).name); Indice = strfind(name,'.'); if ~isempty(Indice) ext = [name(Indice:end) ext]; end if strcmp(ext,'.ame') % no ‘_’ for ame file copyfile(list_fic(j).name,fullfile(pathstr,[sys_temp ext])); else copyfile(list_fic(j).name,fullfile(pathstr,[sys_temp '_' ext])); end end
sys=sys_temp;
dos(['AMECirChecker ' sys '.ame' ' --usecompiler microsoft64 --generateauxfiles -g -- nobackup --quit']); % Compilation AMESim dos(['AMELoad ' sys]); sys_temp2 = ['slx_' num2str(i)]; [pathstr, name, ext]=fileparts(SLX_Name); copyfile(SLX_Name,fullfile(pathstr,[sys_temp2 ext])); open_system(sys_temp2); % Opening of Simulink model, needed for ‘get_param’
SFunc_Path = [sys_temp2 '/' AME_Name(1 : end - 4) '/S-Function'] ; S_Func_Handle = getSimulinkBlockHandle(SFunc_Path);
set(S_Func_Handle,'FunctionName',[sys,'_']); disp(S_Func_Handle);
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% Update Global Parameters
AMESimSetPar(SFunc_Path, char(plex_param_name), plex_param_value_run(i ,:) ); AMESimSetPar(SFunc_Path, 'PreProc_Folder', 'PreProc') ; % pre-processed data root folder access path AMESimSetPar(SFunc_Path, 'Init_T', 18) ; % initialization temperature AMESimSetPar(SFunc_Path, 'Init_p', 1.013) ; % initialization pressure AMESimSetPar(SFunc_Path, 'Int_TType', IntAir_TType) ; % intake air T location: 0 => T0 (default), 3 => T2' AMESimSetPar(SFunc_Path, 'xMETType', Eng_xMETType) ; % xMET type: 1 => indicated, 2 => break (default)
save_system(sys_temp2);
%Starting message ['Starting calcul ' num2str(i) '...']
% Simulation launch sim(sys_temp2,'SrcWorkspace','base');
% Recuperation of AMESim results(i) in a matrix [alias_ame, result_value_ame] = fct_load_ame_value([sys '.ame'], liste_alias); % result_ame{i}= result_value_ame; % Results matrix in a list
% Ending message ['Ending calcul ' num2str(i)]
%dos(['AMESave ' sys]); bdclose(sys_temp2); % Closes of Simulink delete([sys '_*']); % Deletes files .ame delete([sys '.*']); % Deletes files .ame delete([sys_temp2 '.slx*']); % Deletes Simulink model
try rmdir([sys '_*'],'s'); % Deletes AMESim model end end
delete(gcp('nocreate')); % End parallelization
It leads to a bigger coding work in order to duplicate everything, for being sure all the functions are taken into account, pointing to the right datas and receiving the new global parameters. For example, the previous global parameters supposed to define the initial conditions were not copied in the duplications. It has been solved by redefining them inside the parfor loop.
Finally, a complete export code was released in order to gain time for post processing. All the variables described above were recovered, organized and written in an Excel file by a Matlab code.
Given the time needed for the simulations themselves, the aim was not to lose too much time on post processing by hand the results, and get directly what was needed. Given the big amount of simulations parameters to evaluate, this time spent on matlab code optimization was fundamental to save time and focus on physical problems afterwards.
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Conclusion
This master thesis subject aimed to focus on the study of a controlled valve in a gearbox thermal management context. Nevertheless, the goals were redefined as the internship progresses towards a result validation work on new models. Given the time needed to check the reliability of the new tools used, less time was granted for a simple results exportation. The most important output from this work is the creation of reliable method to launch simulations and get results via Matlab coding, that will be reused by the company.
Even if the study focused mainly on a single gearbox cooling architecture, the results confirmed the trend obtained. If more time would have been available, the other configurations with different parameters (lower spring stiffness for Bypass circuit in H1 to allow more return flow in the gearbox for example) could have been tested. In the meantime, the cooling circuit department decided to lock one architecture choice and those results would not have been needed anymore.
The hypothesis H4 gives the best results for a thermostatic housing with first complete opening at 80°C (i.e. 70°C for beginning). Before, the engine is too much impacted by the loss of energy for its own, warming-up slowly and reaching after too long time its optimized running temperature. In the other hand, 100°C is too high and the gearbox barely receives any heating flow before a long time; It is clearly not efficient for a WLTC, and a double WLTC does not succeed at reaching the same gearbox temperature as the others. The engine is too much privileged, the compromise not done.
The 80°C allows the gearbox to reach the same final temperature as 0°C and 60°C hypothesis at the end of the testing cycle WLTC, but with less impact on the engine resulting in higher global gain (Table 5). Compared to the 60°C thermostat, the 80°C one will be less affected by a temperature regulation around 90°C, causing less mechanical stress on the thermostatic structure. The second thermostat could be not necessary for most of the cases, and would be interesting only for safety reasons in really specific high load demand. It does not justify however the implementation of a controlled valve instead, more costly. In addition, the flow from heat is not important enough compared to the one bypassed from the radiator (25l/min in gearbox compared to 200 l/min at 6000 RPM from radiator towards the engine) to impact that much the cooling performances in normal conditions.
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List of abbreviations and symbols used
Abbreviations:
€6.2 : Euro 6.2 Standard AGB : Automatic Gearbox ATN8 : Model Name of the new PSA gearbox BMET : Break Mean Effective Torque
C02 : Carbon dioxide CMF (Couple Moyen de Frottement) : Friction Mean Torque EB2DTS : New Turbo PureTech 3-cylinder petrol engine ECU : Electronic Control Unit EMF (Energie Moyenne de frottement) : Friction Mean Energy EMP1min : Efficient Modular Platform – Light vehicle (208 – DS3 – C3) EMP2max : Efficient Modular Platform – Heavy vehicle (3008 – DS7 Crossback – C5 Aircross) FMET : Friction Mean Effective Torque IMET : Indicated Mean Effective Torque H1/H2/H4 : Hypothesis 1/2/4 HT : High Temperature Km : Kilometers NEDC : New European Driving Cycle PC : Production Cost PMF (Puissance Moyenne de frottement) : Friction Mean Power Th : Thermostat ThC : Thermostat Closed ThO : Thermostat Open ThP : Thermostat Piloté (Actuated thermostat) V3/V4 : Version 3 and Version 4 of the AMESim model WLTC : Worldwide harmonized Light vehicles Test Procedure
Symbols:
Cqmax : Maximum flow coefficient Ø : Diameter
Translation French/English:
Aerotherme : Heater Clapet Anti/Retour : Check Valve ECH E/H eBVA (Echangeur Eau/Huile Boite de vitesse électrique) : Water/oil exchanger electric gearbox Radiateur : Radiator Régime Moteur : Engine Speed
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Figures list
Figure 1 : Comparison of limit car emission values fixed by the EU ______7
Figure 2 : Average CO2 emissions from new passenger cars in 2016 [4] ______8
Figure 3 : Divergence of “Spritmonitor.de” from manufacturers’ type-approval CO2 emissions by fuel type [5] _ 8 Figure 4 : Velocity profile of NEDC versus WLTP ______9 Figure 5 : Schematic illustration of the expected effect of the transition from NEDC to WLTP ______10 Figure 6 : Comparison of engine consumption on NEDC between cold and warm start (Sogefi Faurecia) _____ 11 Figure 7 : Working principle of a thermostat ______11 Figure 8 : Thermal Management strategy with the controlled valve Mark IV [10] ______12 Figure 9 : EB2DTS designed as 1.0-1.4l Engine of the year 2018 ______13 Figure 10 : EB2DTS ATN8 €6.2 Cooling circuit ______13 Figure 11 : Hypothesis ‘H1’ Cooling circuit ______14 Figure 12 : Hypothesis ‘H2’ Cooling circuit ______15 Figure 13 : Thermostatic housing for H4 ______15 Figure 14 : Hypothesis ‘H4’ Cooling circuit ______15 Figure 15 : Opening/Closing Gearbox heating flow in the thermostatic housing ______16 Figure 16 : Hypothesis 'H4' with a two ways controlled valve + one check valve ______17 Figure 17 : Hypothesis 'H4' with a three ways controlled valve ______17 Figure 18 : Description of main heat transfers into an engine ______20 Figure 19 : Methodology used in building a SAMM supercomponent ______20 Figure 20 : SAMGa The model - Mechanical part ______22 Figure 21 : Cooling circuit supercomponent in the SAMGa The model ______23 Figure 22 : AMEsim gearbox cooling circuit H4 ______24 Figure 23 : Model H4 with a 3 ways valve solution ______25 Figure 24 : S-function for cosimulation AMESim/Simulink in AMESim ______26 Figure 25 : Internal Frictions in AMESim - Oil Circuit submodel ______28 Figure 26 : Comparison of the water temperature between the V3 and V4 model ______30 Figure 27 : Comparison of oil temperature between the V3 and V4 model (WLTC) ______31 Figure 28 : Water Temperature for WLTC (€6.2 and H4) Thp Off ______33 Figure 29 : Oil Temperature for WLTC (€6.2 and H4) ThP Off ______34 Figure 30 : Automatic Gearbox Temperature for WLTC (€6.2 and H4) Thp Off ______34 Figure 31 : Water Temperature for WLTC (€6.2 and H4) Thp On ______36 Figure 32 : Water temperature for Double WLTC (€6.2 and H4) ThP Off ______37 Figure 34 : AGB Temperature for Double WLTC (€6.2 and H4) ThP Off ______38 Figure 36 : Speed profile of K9 Cycle______39 Figure 37 : Water temperature for K9 cycle (€6.2 and H4) ______39 Figure 38 : Error in Pump Consign ______42 Figure 39 : Temperature rises for WLTC with wrong thermostat control (€6.2) ______43 Figure 40 : Temperature in the water tank with constant negative energy ______43 Figure 41 : Cooling circuit H4 ______53 Figure 42 : Mechanical Pump (old version) ______54 Figure 43 : Mechanical Pump (New version - signal) ______54 Figure 44 : S-function for cosimulation AMESim/Simulink in Simulink ______55 Figure 45 : Performance Analyzer H4 100°C WLTC ______56
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Table list
Table 1 : Differences NEDC / WLTP ...... 9 Table 2 : Differences Thermostatic Housing / Controlled Valve ...... 18 Table 3 : Friction losses list ...... 27 Table 4 : Friction losses (EMF Total Non-Loaded) comparison from €6.2 for V3 model ...... 32 Table 5 : Friction differences between €6.2 and H4 ...... 35 Table 6 : Total friction gain between €6.2 and H4 ...... 35 Table 7 : EMF Total Loaded (Internal + Gearbox + FMET Loaded) ...... 35 Table 8 : Friction differences between cartographies on V4 ...... 36 Table 9 : Friction Results Thermostat Control On (WLTC) ...... 37 Table 10 : Friction results for double WLTC (and comparison with WLTC)...... 38 Table 11 : Flow at 6000RPM from heating and cooling gearbox valve at different pressure losses at 10l/min ...... 40 Table 12 : Pressure losses at 6000 RPM for heating and cooling gearbox valve at different pressure losses at 10l/min ...... 41
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Bibliography
[1] European Environment Agency , "Contribution of the transport sector to total emissions of the main air pollutants," 05 12 2017. [Online]. Available: https://www.eea.europa.eu/data-and- maps/daviz/contribution-of-the-transport-sector-4#tab-chart_4.
[2] A. DAVID, "Emissions CO2 : le classement des constructeurs [STATISTIQUES]," 19 11 2015. [Online]. Available: http://www.auto-moto.com/actualite/environnement/emissions-co2-classement-des- constructeurs-voitures-modeles-statistiques-europe-47085.html#item=1. [Accessed 30 07 2018].
[3] European Environment Agency, "European Environment Agency," 23 04 2018. [Online]. Available: https://www.eea.europa.eu/highlights/no-improvements-on-average-co2. [Accessed 30 07 2018].
[4] European Environment Agency, "Average CO2 emissions from new passenger cars sold in EU-28 Member States plus Norway, Iceland and Switzerland in 2016," 12 04 2018. [Online]. Available: https://www.eea.europa.eu/data-and-maps/figures/average-co2-emissions-from-new. [Accessed 30 07 2018].
[5] U. TIETGE et al., "FROM LABORATORY TO ROAD, A 2015 update of official and “real-world” fuel consumption and CO2 values for passenger cars in Europe," International Council on Clean Transportation, 2015.
[6] German Association of the Automotive Industry, "Exhaust emissions - Emissions measurement in cars," [Online]. Available: https://www.vda.de/en/topics/environment-and-climate/exhaust- emissions/emissions-measurement.html.
[7] P. MOCK, "2020-2030 CO2 standards for new cars and light-commercial vehicles in the European Union," The International Council on Clean Transportation, 2017.
[8] J. M. P. M. a. U. T. Jan Dornoff, "The European Commission regulatory proposal for post-2020 CO2 targets for cars and vans: A summary and evaluation," The International Council on Clean Transportation, 2018.
[9] Union des Transport Publics et ferroviaires, "Observatoire de la mobilité 2014 : des résultats et de précieux enseignements," 28 10 2014. [Online]. Available: http://utp.fr/actualite/observatoire-de-la- mobilit%C3%A9-2014-des-r%C3%A9sultats-et-de-pr%C3%A9cieux-enseignements. [Accessed 01 08 2018].
[10] M. CORMERAIS, "Thermomanagement Part. 1 Mann+Hummel," 2014.
[11] E. BARRIEU, N. BECKER and A. ROSSI, "Engine Warm-ip Optimization Using Innovative Components," Sogefi Faurecia.
[12] PSA Group, "GROUPE PSA’S TURBO PURETECH PETROL ENGINE GETS AWARDED," 06 06 2018. [Online]. Available: https://www.peugeot.co.uk/news/groupe-psa-engine-awarded/. [Accessed 06 08 2018].
[13] INSEE, "Les Franciliens utilisent autant les transports en commun que la voiture pour se rendre au travail," 2011.
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Appendix
A. Cooling Circuit
Figure 39 : Cooling circuit H4 Master Thesis Report Amaury ARLOTTO 53
Figure 40 : Mechanical Pump (old version)
Figure 41 : Mechanical Pump (New version - signal)
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B. Cosimulation
Figure 42 : S-function for cosimulation AMESim/Simulink in Simulink
This module is used to make the link between Simulink and AMESim, each data are computed in the command code and reinjected in AMESim.
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C. Performance Analyzer
The details of a simulation can be found in an AMESim part called Performance Analyzer, listing all the components and the number of reboots needed to compute a result. The more a component has to reboot, the longer the simulation turns. In this case, the architecture H4 100°C is not optimized, and in order to complete a run, a few components have to restart almost 4 million times (in Gearbox or Cooling Circuit).
Figure 43 : Performance Analyzer H4 100°C WLTC Master Thesis Report Amaury ARLOTTO 56