Well-to-Wheel Analysis of Electrified Drivetrains under Realistic Boundary Conditions and User Behaviour

Transcription

1 Well-to-Wheel Analysis of Electrified Drivetrains under Realistic Boundary Conditions and User Behaviour Benedikt Hollweck European GT Conference, Frankfurt am Main, 17 th October 2016

2 Agenda 1. What is a well-to-wheel analysis and why do we need realistic boundary conditions and user behaviour? 2. Methodology for the approach to represent realistic boundary conditions and user behaviour for a well-to-wheel analysis 3. Drivetrains modelled with GT-SUITE Fuel Cell Electric Vehicle (FCEV) Fuel Cell Plug-In Electric Vehicle (FC PHEV) Battery Electric Vehicle (BEV) 4. Possibility to analyse the fuel consumption for different users 5. Well-to-wheel analysis for the typical German driver behaviour 6. Summary Daimler AG GT-Conference / Benedikt Hollweck / / Page 2

3 Well-to-Wheel Analysis A well-to-wheel analysis is the rating of energy consumption and greenhouse gas emissions arising on the path from the energy source to the wheel. Well-to-Wheel Analysis (WtW) Well-to-Tank (WtT) Tank-to-Wheel (TtW) Fuel production Vehicle operation Evaluation criteria: Energy consumption Greenhouse gas emissions Daimler AG GT-Conference / Benedikt Hollweck / / Page 3

4 GHG* Emissions [g CO 2 eq/km] WtW-Analysis: CO 2 - and Energy comparison of EUCAR reference vehicles Fuel Cell: Battery: High range (> 500 km), short refueling time (3 min), applicable for different vehicle concepts Optimal operation in compact cars for the city traffic ( km), recharging over night PH-FCEV (Wind-Electricity, Grid, Centr. Electrolysis, CH2, PlugIn Hybrid-FCEV) BEV (Wind-/PV-/Water-Electricity, Grid, Battery EV Li-Ion) *GHG: Green House Gas FCEV (NG 4000km, Centr. ref., Road, CH2, FCEV) Fuel Cell-EV Hybrid ICE Hybrid Gasoline Hybrid Diesel Battery-EV BEV (EU-Electricity-Mix, Grid, Battery EV Li-Ion) FCEV (Wind-Electricity, Grid, Centr. Electrolysis, CH2, FCEV) ICE = Internal combustion engine BEV = Battery electric vehicle FCV = Fuel cell vehicle PHFCV = Plug-In hybrid fuel cell vehicle Source: JEC, Well-to-Wheel report (version 4), 2014 Electric drivetrains are a real step to reduce energy consumption and GHG-emissions. Using EVs means a significant step forward. Daimler AG GT-Conference / Benedikt Hollweck / / Page 4 Diesel Energy Consumption Well-to-Wheel [MJ/100km] ICE Gasoline CNG

5 Frequency in % Frequency Methodology for the approach to represent realistic boundary conditions and user behaviour for a WtW-analysis Driving performance (MiD) 3 Artemis driving cycles User behaviour (Track-type, traffic flow, typical driver) GT-SUITE vehicle simulation model Driving distance Data of the study: Mobilität in Deutschland (MiD 2008) Small Reference vehicles Medium Large Reference vehicles (small, medium, large) Evaluation by track type and track length Cluster am 23,59% Average value: 7:06 1 hour simulation duration Starting times (MiD) Cluster 2 9 am 1 pm 23,39% 10:54 Cluster pm 19,82% 14:36 Starting time in h Cluster pm 23,16% 17:18 Cluster pm 10,05% 20:36 4*5 climate clusters for Germany Climate boundary conditions and start conditions Specific daytime, track type and track length Results: Realistic energy consumption of a specific user Weighting factors of the study Mobilität in Deutschland Results: Realistic energy consumption for a typical German driver Daimler AG GT-Conference / Benedikt Hollweck / / Page 5

6 Methodology Modular vehicle simulation with GT-SUITE Drivetrain: BEV FC-PHEV / FC-RE FCEV PHEV / RE HEV ICE gasoline ICE diesel ICE CNG Submodel 2 Submodel 1 Auxiliary consumer Operation Fuel cell system strategy Input driving performance Reg. braking Battery Electric motor Single stage transmission Reference vehicle Vehicle architecture: Reference vehicle small Reference vehicle medium Reference vehicle large + Driving cycle NEDC Driving cycle WLTP 3 x Driving cycles user behaviour Submodel 3 Vehicle cabin Submodel 4 Thermal management: Drivetrain BEV Drivetrain ATS FCPHEV Drivetrain ATS FCEV Drivetrain ATS PHEV Drivetrain ATS HEV Drivetrain ATS ICE gasoline Drivetrain ATS ICE diesel Drivetrain ATS ICE CNG Data bus Analysis Radiator control HT cooler FC stack thermal Heat exchanger Intercooler Pipe losses Fresh air supply Fan control Vehicle cabin: Vehicle cabin small Vehicle cabin medium Vehicle cabin large PTC Evaporator control Bypass control Daimler AG GT-Conference / Benedikt Hollweck / / Page 6

7 Simulation model Fuel Cell Plug-In Electric Vehicle (FCPHEV) Operation strategy Auxiliary consumer Input driving performance Fuel cell system Reg. braking Data bus Analysis Electric motor Single stage Transmission Reference vehicle Chiller Vehicle cabin Low temperature circuits Battery Radiator control HT cooler Intercooler FC stack thermal Fresh air supply Heat exchanger Fan control PTC Evaporator control Bypass control Daimler AG GT-Conference / Benedikt Hollweck / / Page 8

8 Simulation model Battery Electric Vehicle (BEV) Auxiliary consumer Reg. braking Input driving performance Reference vehicle Electric motor Single stage Transmission Data bus Analysis Battery Vehicle cabin Radiator control LT circuit Fresh air supply Fan control Heat exchanger PTC Bypass control Evaporator control Daimler AG GT-Conference / Benedikt Hollweck / / Page 9

9 Validation of the simulation models NEDC fuel consumption Fuel consumption Fuel Cell Electric Vehicle: Characteristic Certified fuel consumption Mercedes-Benz B-Class F-CELL Simulated fuel consumption Mercedes-Benz B-Class F-CELL H 2 consumption [kgh 2 /100km] 0,97 0,965 Fuel consumption Battery Electric Vehicle: Characteristic Certified fuel consumption Mercedes-Benz B-Class electric drive Simulated fuel consumption Mercedes-Benz B-Class electric drive Energy consumption [kwh/100km] 16,6 16,61 Daimler AG GT-Conference / Benedikt Hollweck / / Page 10

10 Energy consumption in kwh/100km Validation of the simulation model Fuel consumption at different temperatures 50 Energy consumption at different temperatures simulated and measured 45 Data from the ÖVK-study Simulation Ambient temperature in C Source: Batterieelektrische Fahrzeuge in der Praxis, Österreichischen Vereins für Kraftfahrzeugtechnik (ÖVK), 2016 Daimler AG GT-Conference / Benedikt Hollweck / / Page 11

11 Frequency in % Frequency Methodology for the approach to represent realistic boundary conditions and user behaviour for a WtW-analysis Driving performance (MiD) 3 Artemis driving cycles User behaviour (Track-type, traffic flow, typical driver) GT-SUITE vehicle simulation model Driving distance Data of the study: Mobilität in Deutschland (MiD 2008) Small Reference vehicles Medium Large Reference vehicles (small, medium, large) Evaluation by track type and track length Cluster am 23,59% Average value: 7:06 1 hour simulation duration Starting times (MiD) Cluster 2 9 am 1 pm 23,39% 10:54 Cluster pm 19,82% 14:36 Cluster pm 23,16% 17:18 Cluster pm 10,05% 20:36 4*5 climate clusters for Germany Climate boundary conditions and start conditions Specific daytime, track type and track length Starting time in h Results: Realistic consumption of a specific user Daimler AG GT-Conference / Benedikt Hollweck / / Page 12

12 Energy consumption in kgh 2 / 100km Fuel consumption of specific users driving a Fuel Cell Electric Vehicle Urban driver Drive Drive 1 Drive 2 Drive 3 Starting time 7:06 CET 17:18 CET 20:36 CET Drives per week Driving distance 3 6 km 3 6 km 1 3 km Road type Urban Urban Urban 1,5 1,25 1 Average fuel consumption in kgh 2 /100 km Rural driver Drive Drive 1 Drive 2 Drive 3 Starting time 7:06 CET 17:18 CET 20:36 CET Drives per week Driving distance km km km Road type Rural Rural Rural 0,75 0,5 0,25 0 Average of German users Rural driver Urban driver Average of German users Rural driver Urban driver With this methodology an analysis of different user types is possible. Daimler AG GT-Conference / Benedikt Hollweck / / Page 13

13 Frequency in % Frequency Methodology for the approach to represent realistic boundary conditions and user behaviour for a WtW-analysis Driving performance (MiD) 3 Artemis driving cycles User behaviour (Track-type, traffic flow, typical driver) GT-SUITE vehicle simulation model Driving distance Data of the study: Mobilität in Deutschland (MiD 2008) Small Reference vehicles Medium Large Reference vehicles (small, medium, large) Evaluation by track type and track length Cluster am 23,59% Average value: 7:06 1 hour simulation duration Starting times (MiD) Cluster 2 9 am 1 pm 23,39% 10:54 Cluster pm 19,82% 14:36 Cluster pm 23,16% 17:18 Cluster pm 10,05% 20:36 4*5 climate clusters for Germany Climate boundary conditions and start conditions Specific daytime, track type and track length Weighting factors of the study Mobilität in Deutschland Starting time in h Results: Realistic energy consumption of a specific user Results: Realistic energy consumption for a typical German driver Daimler AG GT-Conference / Benedikt Hollweck / / Page 14

14 Summary The approach of a Well-to-Wheel analysis was introduced and the need to compare different drivetrain topologies under realistic boundary conditions and user behaviour was explained. A methodology to represent realistic boundary conditions and user behaviour for a Well-to-Wheel Analysis was presented. The simulation models of a Fuel Cell Electric Vehicle, a Fuel Cell Plug-In Electric Vehicle and a Battery Electric Vehicle were shown and explained. The possibility to get realistic energy consumptions for different user types, the German driving performance and different vehicle sizes were pointed out. Daimler AG GT-Conference / Benedikt Hollweck / / Page 16

15 Thank you for your attention!