GT Conference 2017: Simulation Tool for Predictive Control Strategies for an ORC- System in Heavy Duty Vehicles

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GT Conference 217: Simulation Tool for Predictive Control Strategies for an ORC- System in Heavy Duty Vehicles October 9-1, 217 Dipl.-Ing. Jörg Kreyer M.Sc. Prof. Dr.-Ing. Thomas Esch FH Aachen FH Aachen FH AACHEN UNIVERSITY OF APPLIED SCIENCES 9. October 217 1

GT Conference 217 Content Scientific questions and solution methods Model intention and model features Data acquisition for heavy duty truck GT-Model presentation Longitudinal vehicle model incl. ORC-model 1-D engine model Predictive control strategies for ORC-system Summery and outlook FH AACHEN UNIVERSITY OF APPLIED SCIENCES 9. October 217 2

GT Conference 217 Scientific questions and solution methods Scientific questions How can a non-stationary heat offering in the commercial vehicle be used to reduce fuel consumption? Which potentials offer route and environmental information among with predicted speed and load trajectories to increase the efficiency of a ORC-System? Methods Desktop bound holistic simulation model for a heavy duty truck incl. an ORC System Prediction of massflows, temperatures and mixture quality (AFR) of exhaust gas FH AACHEN UNIVERSITY OF APPLIED SCIENCES 9. October 217 3

GT Conference 217 Model intention / Model features Retarder Radiator cooling pump ORC cooling pump M 1D-fuid components and control parameters Engine Injection and combustion EGR and TC Massflow split valve Cooling circuit Pump and thermostat control Batterie CAC C Heat exchanger after EGR T Heat exchanger after EAT ORC pump M Compensation tank Coupled Retarder ORC-System Working fluid: Ethanol Using of EGR and EAT Heat Electrical regeneration Actuators: G Generator/ Expander Bypass valve Recuperator Condenser CAC: Charge Air cooler EGR: Exhaust gas recirculation EAT: Exhaust aftertreatment ORC Fluid pump Split- and Bypassvalves FH AACHEN UNIVERSITY OF APPLIED SCIENCES 9. October 217 4

GT Conference 217 Data acquisition for heavy duty truck Vehicle configuration Actros 1845 LS / OM 471 33 kw @ 18 RPM 22 (24 Top Torque) Nm @ 11 RPM Displacement: 12,81 ltr. / 6 cylinder in-line Maximum Efficiency: ηeff = 46% EURO 6 Gearbox: 12 gears 3 axes tarpaulin trailer Overall vehicle mass: 317 kg FH AACHEN UNIVERSITY OF APPLIED SCIENCES 9. October 217 5

GT Conference 217 Data acquisition for heavy duty truck Volume flow radiator p T Retarder ሶ V p T Radiator T Dashboard information Measuring scope: Temperature, pressure, AFR Analysation of video data ሶ V p T T T distance radar Fleetboard Mass- and volume flow Bosch HFM 7-25. Volumeflow radiator and retarder Venturi nozzle for AGR Airflow before intake filter CAC p T ሶ m L p T V p T p T p λ p T EGR T FPI λ p T EAT OBD II T Venturi nozzle for EGR J1939 Protocol / OBD II: diver load demand indicated engine load engine speed Friction torque Injection amount Injection begin CAC: Charge Air cooler EGR: Exhaust recirculation cooler FPI: Fuel post injection EAT: Exhaust aftertreatment FH AACHEN UNIVERSITY OF APPLIED SCIENCES 9. October 217 6

T eff [Nm] Vehicle speed [km/h] Gradient of road [m] Vehicle speed [km/h] Gradient of road [m] GT Conference 217 Data acquisition for heavy duty truck AC AC-F-AC 1 8 6 4 2 1 8 6 4 2,5 1 1,5 2 Driving time [h] 8 64 48 32 16,5 1 1,5 2 2,5 3 3,5 4 4,5 5 5,5 6 6,5 7 7,5 Driving time [h] 8 64 48 32 16 Vehicle speed [km/h] Gradient of road [m] Autobahn cycle: Aachen (AC) Characterized by: High density of construction side High speed restrictions Less road gradient Autobahn cycle: Aachen-Frankfurt-Aachen (AC-F-AC) Characterized by: Traffic congestion Less speed restrictions ATC RR 25 2 15 1 5 4 8 12 16 2 Engine speed [RPM] Full load curve Top Torque Load points ATC Load Points CR High road gradient Aldenhoven Testing Center (ATC) and Rural Road (RR) Stationary load points Cast down curves Breaking tests FH AACHEN UNIVERSITY OF APPLIED SCIENCES 9. October 217 7

ORC Power output [kw] GT Conference 217 Longitudinal vehicle model incl. ORC-model Status of the model development Vehicle dynamics, transmission and clutch controller Forward simulation done by driver model Fuel Consumption and heat release done by engine state model Model overview Operating characteristics of fluid systems: ORC and cooling circuit via Feed-forward controller 6 5 4 3 2 1 Transient Turbine Power Output for Autobahncycle Aachen (AC) 2 4 6 Driving duration [s] ORC circuit model with single heat input and recuperator FH AACHEN UNIVERSITY OF APPLIED SCIENCES 9. October 217 8

Pressure Rato [-] Massflow [kg/s] T eff [Nm] GT Conference 217 Modelling: 1D GT-POWER engine model / OM 471 25 2 EGR Throttle position GT-POWER Engine Modell OM 471 Manifold desigen 15 1 5 4 6 8 1 12 14 16 18 2 Valve timing Combustion EGR and Turbocharger performace control Turbocharger Maps 5,4 CAC C EGR EGR valve T 4,5 4 3,5 3 2,5,35,3,25 EGR throttle 1 2 3 4 5 6 2 1,5 1,2,4,6,8 Massflow [kg/s],2,15 1,5 2,5 3,5 4,5 Pressure Ratio Turbine [-] Source: Daimler AG, 217 www.roadstars.mercedes-benz.com ηmin=,61 ηmax=,78 nmin= 12 1/min nmax= 3 1/min ηmin=,62 ηmax=,692 FH AACHEN UNIVERSITY OF APPLIED SCIENCES 9. October 217 9

T eff [Nm] m_ex [g/s] T eff [Nm] T eff [Nm] EGR Rate [%] T eff [Nm] GT Conference 217 Modelling: 1D GT-POWER engine model / OM 471 25 Measured EGR Rate [%] 25 Simulated EGR Rate [%] 2 15 1 5 4 24 26 26 28 3 32 34 26 26 28 6 8 1 12 14 16 18 2 24 22 2 24 6 5 4 3 2 1 Increasing P eff EGR Rate (MEASUREMENT) EGR Rate (SIMULATION) 1 2 3 4 5 6 7 8 9 1 Load Point [#] 2 15 1 5 4 6 8 1 12 14 16 18 2 25 2 15 1 5 4 Measured exh. massflow [g/s],5 1 1,5 2 6 8 1 12 14 16 18 2 2,5 3 3,5 35 3 25 2 15 1 5 Increasing P eff m_ex (MEASUREMENT) m_ex (SIMULATION) 1 2 3 4 5 6 7 8 9 1 Load Point [#] 25 2 15 1 5 4 Simulated Exh. massflow [g/s] 6 8 1 12 14 16 18 2 FH AACHEN UNIVERSITY OF APPLIED SCIENCES 9. October 217 1

T eff [Nm] T_AT [ C] T eff [Nm] T eff [Nm] T_BT [ C] T eff [Nm] GT Conference 217 Modelling: 1D GT-POWER engine model / OM 471 25 Measured Temp. bevor turbine [ C] Simulated Temp. before turbine [ C] 25 2 15 1 5 4 55 5 45 4 35 3 6 8 1 12 14 16 18 2 7 6 5 4 3 2 1 Increasing P eff 1 2 3 4 5 6 7 8 9 1 Load Point [#] T_BT (MEASUREMENT) T_BT (SIMULATION) 2 15 1 5 4 6 8 1 12 14 16 18 2 Measured Temp. after turbine [ C] Simulated Temp. after turbine [ C] 25 2 15 1 5 4 4 35 3 25 2 6 8 1 12 14 16 18 2 7 6 5 4 3 2 1 Increasing P eff 1 2 3 4 5 6 7 8 9 1 Load Point [#] T_AT (MEASUREMENT) T_AT (SIMULATION) 25 2 15 1 5 4 6 8 1 12 14 16 18 2 FH AACHEN UNIVERSITY OF APPLIED SCIENCES 9. October 217 11

Simulated Maps ሶ Controlling of actuators GT Conference 217 Predictive control strategies for ORC-system Designed Environment v res Natural Environment Map based longitudinal vehicle predictor model α, f R, T u, p u Restrictions: max. ORC fluid temperatures EGR temperature Description of predictive control strategy: Multi-physical model vehicle (GT- SUITE) Restriction for the system behavior Energy prediction for the ORC system Load Prediciton of exhaustenthalpy Teff ma ሶ Teff Engine speed TA T(t) m A t λ(t) Constraint optimization problem x 1 Basic controller and model predictive control (MPC) of ORC system n n x 2 GT model conventional vehicle GT model vehicle incl. ORC System FH AACHEN UNIVERSITY OF APPLIED SCIENCES 9. October 217 12

GT Conference 217 Predictive control strategies for ORC-system Load n GT Power based lookup tables torque Map based longitudinal vehicle predictor model: Designed Environment Legal speed restrictions Speed restrictions by traffic mሶ EGR PT1 mሶ Ex PT1 Natural Environment Road gradient: α T EGR T Ex Roll resistance: f R Ambient conditions: T u, p u Designed Environment v res Driver Load Engine n Veh. Drivetrain Engine Torque i ges f R α T u p u Balance of forces Natural Environment a(t) 1 s v(t) Temperatur caclulation Mapbased with first order delay element PT1: ሶ H in = mሶ Ex c p T in ሶ Q diss du dt = d dt c m w ΔT ሶ H out = mሶ Ex c p T out FH AACHEN UNIVERSITY OF APPLIED SCIENCES 9. October 217 13

Absolute deviation [%] Temperatur after EAT [ C] Absolute deviation [%] Temperature befor turbine[ C] Vehicle speed [km/h] Gradient of road [m] GT Conference 217 Predictive control strategies for ORC-system 1 8 6 4 2 Driving profile: Autobahn Cycle AC Vehicle speed [km/h] Gradient of road [m] 2 16 12 8 4 6 5 4 3 2 1 4 35 3 25 2 15 1-4 5 1 15 2 25 3 35 4 45 5 55 6 Driving Time [s] 4-4 -8 2 Measured Simulated -2 Measured Simulated FH AACHEN UNIVERSITY OF APPLIED SCIENCES 9. October 217 14

GT Conference 217 Summary and outlook Summery A simulation tool for ORC performance analyzation in heavy duty trucks is created A strategy for energy prediction to ORC system was presented A data base of real driving data has been brought up Next Steps Combining of 1-D engine model with driveline, coolant and ORC subsystems Development of feed-backward controller for ORC system FH AACHEN UNIVERSITY OF APPLIED SCIENCES 9. October 217 15

FH Aachen Prof. Dr.-Ing. Thomas Esch European Centre for Sustainable Mobility Hohenstaufenallee 6 5264 Aachen esch@fh-aachen.de T +49. 241. 69 52369 F +49. 241. 69 5268 FH Aachen Dipl.-Ing. (FH) Jörg Kreyer M.Sc. European Centre for Sustainable Mobility Aachener-und-Münchener Allee 1 5264 Aachen kreyer@fh-aachen.de T +49. 241. 69 52827 F +49. 241. 69 52489 FH AACHEN UNIVERSITY OF APPLIED SCIENCES 9. October 217