Impact of BEV Powertrain architectures on energy consumption in various driving cycles Stackpole Powertrain International GmbH

Similar documents
Transmission Technology contribution to CO 2 roadmap a benchmark

Analysis and Simulation of a novel HEV using a Single Electric Machine

Energy Efficiency of Automobiles A Pragmatic View

Driving dynamics and hybrid combined in the torque vectoring

Deep-dive E-Mobility

Powertrain Control Software A Modular (or à la carte) Approach. Powertrain Control Software, A Modular Approach Marco Fracchia, Vocis Ltd

Vehicle Performance. Pierre Duysinx. Research Center in Sustainable Automotive Technologies of University of Liege Academic Year

Fuel Consumption Potential of Different Plugin Hybrid Vehicle Architectures in the European and American Contexts

Scaling Functions for the Simulation of Different SI-Engine Concepts in Conventional and Electrified Power Trains

Analysis of regenerative braking effect to improve fuel economy for E-REV bus based on simulation

State of the Art Development Methodologies for Hybrids and e- Drives

Modeling the Electrically Assisted Variable Speed (EAVS) Supercharger

Early Stage Vehicle Concept Design with GT-SUITE

Integrated Powertrain Simulation for Energy Management of Hybrid Electric Vehicles

Real-world to Lab Robust measurement requirements for future vehicle powertrains

Research Report. FD807 Electric Vehicle Component Sizing vs. Vehicle Structural Weight Report

Fuel Consumption, Exhaust Emission and Vehicle Performance Simulations of a Series-Hybrid Electric Non-Automotive Vehicle

China International Automotive Congress Vehicle concepts, tailor made for e-propulsion. Shenyang, 13. September 2009

12V / 48V Hybrid Vehicle Technology Steven Kowalec

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

IPRO Spring 2003 Hybrid Electric Vehicles: Simulation, Design, and Implementation

VECEPT. All Purpose Cost Efficient Plug-In Hybridized EV. Dr. Michael Nöst, IESTA; Dr. Theodor Sams, AVL. 9. April 2015, Science Brunch Wien

BEYOND TEARDOWN - AVL SERIES BATTERY BENCHMARKING

The Chances and Potentials for Low-Voltage Hybrid Solutions in Ultra-Light Vehicles

Siemens Pioneer in Electric Mobility

E-DRIVE: HIGHLY INTEGRATED AND HIGH EFFICIENT

FUTURE TRANSMISSION TRENDS TRANSMISSION AND DRIVELINE SYSTEMS. Collaboration for a Sustainable Future. 40 th Automotive/Petroleum Industry Forum

Modern Electrification of Power Train needs Integration of Functions

A Detailed DOE Study for Concept Level Battery Electric Vehicle Energy Dimensioning

The Road to Electrification The Magna Powertrain Approach. Dr. Stephan Weng EVP GETRAG Global, Magna Powertrain

Experimental Investigations of Transient Emissions Behaviour Using Engine-in-the-Loop

Development of a Double Variable Cam Phasing Strategy for Turbocharged SIDI Engines

How to calculate the environmental impact of electric vehicles? Energirelaterad Fordonsforskning &5 Oktober 2017 Patricia van Loon

AVL SERIES BATTERY BENCHMARKING. Getting from low level parameter to target orientation

European GT-SUITE Conference 2009 page 1. European GT-SUITE Conference Frankfurt, State-of-the-art and Future Requirements for

MODELING AND SIMULATION OF DUAL CLUTCH TRANSMISSION AND HYBRID ELECTRIC VEHICLES

POWERTRAIN SOLUTIONS FOR ELECTRIFIED TRUCKS AND BUSES

Development of a Plug-In HEV Based on Novel Compound Power-Split Transmission

FE151 Aluminum Association Inc. Impact of Vehicle Weight Reduction on a Class 8 Truck for Fuel Economy Benefits

Multi-disciplinary Design of Alternative Drivetrains an Integrated Approach for Simulation and Validation

Optimal Predictive Control for Connected HEV AMAA Brussels September 22 nd -23 rd 2016

Future Development Targets for manual Transmissions

HyperHybrid. The efficient, affordable plug-innovation.

Benefits of SiC MOSFET technology in powertrain inverter of a Formula E racing car

Honda Clarity Fuel Cell HyLAW National Workshop, Budapest, 27. September 2018

Co-Simulation of GT-Suite and CarMaker for Real Traffic and Race Track Simulations

New Features for more efficient Manual Transmissions with additional Customer Benefit

Impact of Technology on Electric Drive Fuel Consumption and Cost

AVL's Future Hybrid X Mode

VT2+: Further improving the fuel economy of the VT2 transmission

Nancy Gioia Director, Global Electrification Ford Motor Company

The Automotive Industry

Automatic Transmission Trends and System Solution Gregoire Cuny

Effects of Battery Voltage on Performance and Economics of the Hyperdrive Powertrain

Low Carbon Vehicle Technology Project Benchmarking and Teardown Activities Undertaken on Nissan Leaf and Chevrolet Volt

Vehicles for Vehicle Classification

New Development of Highly Efficient Front-Wheel Drive Transmissions in the Compact Vehicle Segment

VEHICLE ELECTRIFICATION INCREASES EFFICIENCY AND CONSUMPTION SENSITIVITY

Holistic Method of Thermal Management Development Illustrated by the Example of the Traction Battery for an Electric Vehicle

Energy-efficient Mobility: Challenging Technologies

Impact of Advanced Technologies on Medium-Duty Trucks Fuel Efficiency

SuperGen - Novel Low Cost Electro-Mechanical Mild Hybrid and Boosting System. Jason King, Chief Engineer

Driving to Net Zero with full performance. Bob Simpson - founder and CTO of EVDrive Inc

Progress at LAT. October 23, 2013 LABORATORY OF APPLIED THERMODYNAMICS

SIMULATION OF A SPARK IGNITION ENGINE WITH CYLINDERS DEACTIVATION

Electromechanical Components and its Energy Saving Design Strategy in PHEV Powertrain

SUSTAINABLE TECHNOLOGIES THE CHANGING FACE OF MOBILITY.

Combination of ORC System and Electrified Auxiliaries on a Long Haul Truck Equipped with 48-Volt Board Net

Sreekanth R, Rangarajan S, Anand G -System Simulation

Thermoelectric Network Meeting Engineering Challenges and the Thermoelectric Roadmap Market Applications and Future Activities

THE POTENTIAL OF ELECTRIC EXHAUST GAS TURBOCHARGING FOR HD DIESEL ENGINES

PHEV Control Strategy Optimization Using MATLAB Distributed Computing: From Pattern to Tuning

Parallel Hybrid (Boosted) Range Extender Powertrain

48V Battery System Design for Mild Hybrid Applications. Angela Duren 11 February 2016

Integrated Architectures Management, Behavior models, Controls and Software

World Materials Forum From ownership to mobility service for better material efficiency. Patrick Koller June 2017

Comparing the powertrain energy and power densities of electric and gasoline vehicles

The European Commission s science and knowledge service. Joint Research Centre. VECTO - Overview VECTO Workshop Ispra, November, 2018

Determination of a turbocharged gasoline engine for hybrid powertrains. F. Kercher,

Hybrid Powertrain Development for Straightforward Vehicle Integration

DESIGN AND FUEL ECONOMY OF A SERIES HYDRAULIC HYBRID VEHICLE

Optimierungsstrategien für den Brennstoffzellenantrieb

In Wheel Motors and their Value Propositions in the Automotive Industry

Electric Vehicle Simulation and Animation

Building Fast and Accurate Powertrain Models for System and Control Development

epsilon Structural Design of Body and Battery Housing

Influences of different heating concepts for the energy demand of an airfield luggage tug

OPTIMIZATION STUDIES OF ENGINE FRICTION EUROPEAN GT CONFERENCE FRANKFURT/MAIN, OCTOBER 8TH, 2018

NAIAS Klaus Rosenfeld CEO Schaeffler AG January 15, 2018

THERMAL MANAGEMENT SYNERGY THROUGH INTEGRATION PETE BRAZAS

elektronik Designing vehicle power nets A single simulation tool from initial requirements to series production

Study on Fuel Economy Performance of HEV Based on Powertrain Test Bed

2012 Audi Q5 2.0T. Technical specifications. Technical specifications Audi Q5 2.0 TFSI. Page 1 of 2 ENGINE:

New Automotive Innovation and Growth Team (NAIGT)

Predictive Control Strategies using Simulink

SupplierBusiness. Transmissions Report Edition

CITY DRIVING ELEMENT COMBINATION INFLUENCE ON CAR TRACTION ENERGY REQUIREMENTS

Validation and Control Strategy to Reduce Fuel Consumption for RE-EV

Management for Multi-Geared Battery Electric. Vehicles

Component Improvements in the Electrification of Passenger Vehicles Drivetrains

Transcription:

Impact of BEV Powertrain architectures on energy consumption in various driving cycles Stackpole Powertrain International GmbH C O N F I D E N T I A L

Authors Sanketh Jammalamadaka Student worker SJammalamadaka@stackpole.com Dipl.-Ing. Philipp Schaeflein Business Development Manager PSchaeflein@stackpole.com Dr.-Ing. Philipp Kauffmann Research and Innovation Manager PKauffmann@stackpole.com Contact: Stackpole Powertrain international GmbH Campus-Boulevard 30, 52074 Aachen Tel.: +49 241 4636 7033 Fax: +49 241 4636 7050 info-aachen@stackpole.com 2

BEV and HEV market projection 1,40E+07 1,20E+07 1,00E+07 8,00E+06 6,00E+06 4,00E+06 2,00E+06 Reduction EVT DCT CVT Automatic AMT 0,00E+00 CY 2017 CY 2018 CY 2019 CY 2020 CY 2021 CY 2022 CY 2023 CY 2024 Source: IHS September 2017 Variety of different powertrain concepts are competing against each other in xev powertrain, not clear which technology will conquer the market System Simulation can help to understand technological advantages of various concepts. 3

Technology analysis of EV powertrains Tesla Model S BMW i3 Existing EV powertrain solutions use 2-stage cylindrical gear sets due to low complexity and low production volume Number of stages 1 2 3 4 Type of stage spur gear planetary gear combination Number of speeds 1 2 3 4 Ratio 7 8 9 10 11 12 Type of lubrication Injection oil bath Total Ratio: 7-10 4

BMW i8 s two-speed concept 1 2 3 4 2 3 1 9 8 5 7 4 6 Wheel Wheel 5 1: PLCD sensor 2: Gearshift fork 3: Input shaft 4: First gear 5: Intermediate shaft 6: Differential 7: Breather 8: Second gear 9: Gear selector 1: First gear 2: Second gear 3: Selector sleeve 4: Final drive 5: Differential 1st gear ratio: 11.38 2nd gear ratio: 5.85 5 The reduction transmission is inferior, which might lead to a replacement in future pure electric vehicles

Our motivation for system simulation 1 Is it possible to model energy consumption of BEV with GT- Suite? 2 3 What are the loss contributors in the standard driving cycle? How does the energy consumption losses differ in urban, suburban and rural driving conditions? 4 5 How does behaviour of BEV differ from ICE Vehicle? Can addition of second gear improve energy consumption in different cycles? 6

Our motivation for system simulation 1 Is it possible to model energy consumption of BEV with GT- Suite? 7

Reference BEV Vehicle model Vehicle Mass m vehicle 1300 kg Tire Rolling Resistance Factor μ tire 0,01 Air Density ρ 1,17 kg/m 3 Vehicle Drag Coefficient C d 0,29 Vehicle Frontal Area A f 2,38 m 2 Auxiliary Power Consumption - 750 W Note:Auxiliary power consumption is approximated to consumption of power electronics and control unit to operate the powertrain. Lights, horn, cooling and heating systems are not considered. 8

Reference BEV Powertrain model Maximum Power P max 125 kw Electric Motor Maximum Torque T max 250 Nm Maximum Speed N max 11400 RPM Efficiency ƞ EM Efficiency Map Battery Capacity - 60 Ah Number of speeds n 1 Transmission Gear Ratio i - Efficiency ƞ T - 9

Transmission efficiency map Number of Speeds n 1 Transmission Gear Ratio i 9,665 Efficiency ƞ T Efficiency Map Transmission Efficiency BMW i3 transmission efficiency test results. Tests conducted in collaboration with IKA, RWTH Aachen. Efficiency [%] 98.2 98 97.8 97.6 97.4 Efficiency at 40 C Tq=50 Tq=100 Tq=150 Tq=250 97.2 97 96.8 96.6 0 500 1000 1500 2000 2500 3000 Speed [rpm] 10

Benchmarking simulation results Vehicle Mass m vehicle 1300 kg Tire Rolling Resistance μ tire 0,01 Factor Air Density ρ 1,17 kg/m 3 Vehicle Drag Coefficient C d 0,29 BMW i3 NEDC cycle power consumption BMW i3 official specification 12,9 kw-h/100km System simulation 12,2 kw-h/100km Vehicle Frontal Area Electric Motor Transmission A f 2,38 m 2 P max T max N max ƞ EM 125 kw 250 Nm 11400 RPM Efficiency Map n 1 i 9,665 ƞ T Efficiency Map Model is Validated 11

Our motivation for system simulation 1 2 Is it possible to model energy consumption of BEV with GT-Suite? What are the loss contributors in the standard driving cycle? 12

Single speed reference BEV Energy loss contributors Vehicle Mass m vehicle 1300 kg 14 P max 125 kw 12 Electric Motor Transmission T max N max ƞ EM 250 Nm 11400 RPM Efficiency Map n 1 i 9,665 Energy Loss [kw-h/100km] 10 8 6 4 ƞ T Efficiency Map 2 Drag F drag ρ C d A f v 2 / 2 0 Rolling Resistance Auxiliary Loss F tire m vehicle. g. μ tyre. Cos(α) Time dependent -2 NEDC Powertrain Loss 2,2 Drag 4,1 Driving Cycle NEDC Rolling Resistance 3,7 Power Consumption (kw-h/100km) 12,2 Auxiliary Load 2,2 Regenerative Braking -0,8 13

Our motivation for system simulation 1 2 3 Is it possible to model energy consumption of BEV with GT- Suite? What are the loss contributors in the standard driving cycle? How does the energy consumption losses differ in urban, suburban and rural driving conditions? 14

Three representative driving cycles NYCC New York City Cycle Urban Cycle NEDC New European Driving Cycle Sub Urban Cycle HWFET Highway Fuel Economy Test Cycle Rural Cycle < 45 kph < 120 kph < 50 kph > 46 kph 15

Energy loss split-up in representative driving cycles 16 Vehicle Mass m vehicle 1300 kg Electric Motor Transmission Driving Cycle Power Consumption (kwh/100km) P max T max N max ƞ EM 125 kw 250 Nm 11400 RPM Efficiency Map n 1 i 9,665 ƞ T Efficiency Map Drag F drag ρ C d A f v 2 / 2 Rolling Resistance Auxiliary Loss F tire m vehicle. g. μ tyre. Cos(α) Time dependent Power consumption in various driving cycles NYCC NEDC HWFET 14 12,2 12,6 Global Energy Loss in % Powertrain Losses [%] NYCC NEDC HWFET 21 18 17 Drag [%] 5 34 46 Rolling Resistance [%] 27 30 29 Auxiliary Load [%] 47 18 8 Regenerative Braking [%] 100 90 80 70 60 50 40 30 20 10 0-10 -9-7 -5

Our motivation for system simulation 1 2 3 Is it possible to model energy consumption of BEV with GT- Suite? What are the loss contributors in the standard driving cycle? How does the energy consumption losses differ in urban, sub-urban and rural driving conditions? 4 How does behaviour of BEV differ from ICE Vehicle? 17

Energy consumption sensitivity comparison: BEV vs. ICE Vehicle Mass m vehicle 1300 kg Electric Motor P max T max N max 125 kw 250 Nm 11400 RPM NYCC Deviation from NEDC consumption is less for BEV compared to NA SI engine, as a result of unstable driving conditions supported by regenerative braking. Transmission ƞ EM Efficiency Map n 1 i 9,665 ƞ T Efficiency Map HWFET NA SI engines have minimum energy consumption in stable driving conditions. 200 % of energy consumption with NEDC as reference 150 100 50 BEV Simulation NA SI engine NYCC NEDC HWFET 18 Source: Impact of Conventional and Electrified Powertrains on Fuel Economy in Various Driving Cycles by Sarp Mamikoglu, Jelena Andric, and Petter Dahlander, Chalmers University of Technology

Our motivation for system simulation 1 2 3 Is it possible to model energy consumption of BEV with GT- Suite? What are the loss contributors in the standard driving cycle? How does the energy consumption losses differ in urban, suburban and rural driving conditions? 4 5 How does behaviour of BEV differ from ICE Vehicle? Can addition of second gear improve energy consumption in different cycles? 19

Gear shift strategy Gears upshift speed is 60kph and down shift speed is 55kph Driving cycle Number of gear shifts NYCC 0 NEDC 4 HWFET 4 < 45 kph < 120 kph < 50 kph > 46 kph 20

Optimization of gear ratios NYCC Vehicle Mass m vehicle 1300 kg Tire Rolling Resistance Factor μ tire 0,01 9,665 Energy consumed per cycle [kw-h ] Air Density ρ 1,17 kg/m 3 Vehicle Drag Coefficient C d 0,29 Vehicle Frontal Area A f 2,38 m 2 Electric Motor P max T max N max 125 kw 250 Nm 11400 RPM ƞ EM Efficiency Map 21

Optimization of gear ratios NEDC Vehicle Mass m vehicle 1300 kg Tire Rolling Resistance μ tire 0,01 Factor Air Density ρ 1,17 kg/m 3 9,665 9,665 Energy consumed per cycle [kw-h ] Vehicle Drag Coefficient C d 0,29 Vehicle Frontal Area A f 2,38 m 2 Electric Motor P max T max N max 125 kw 250 Nm 11400 RPM ƞ EM Efficiency Map 22

Optimization of gear ratios HWFET cycle Vehicle Mass m vehicle 1300 kg 9,665 Tire Rolling Resistance Factor μ tire 0,01 9,665 Energy consumed per cycle [kw-h ] Air Density ρ 1,17 kg/m 3 Vehicle Drag Coefficient C d 0,29 Vehicle Frontal Area A f 2,38 m 2 Electric Motor P max T max N max 125 kw 250 Nm 11400 RPM ƞ EM Efficiency Map 23

Optimization of gear ratios 0-100kph time Vehicle Mass m vehicle 1300 kg Tire Rolling Resistance Factor μ tire 0,01 9,665 9,665 Time for 0-100kph [sec] Air Density ρ 1,17 kg/m 3 Vehicle Drag Coefficient Vehicle Frontal Area C d 0,29 A f 2,38 m 2 Electric Motor P max T max N max ƞ EM 125 kw 250 Nm 11400 RPM Efficiency Map 24

Optimization of gear ratios for balanced power consumption and performance NYCC i s1 =11,5 i s2 = - NEDC Best efficiency i s1 = 6,9 i s2 = 4,1 HWFET Best efficiency i s1 = 8,3 i s2 = 4,1 0-100kph Best performance i s1 = 20,0 i s2 = 8,4 To have a balanced efficiency and performance, gear ratio i s1 =9,667 and i s2 = 4,47 are chosen with Reference and Eco modes. Reference Mode No gear shifts Constant engaged gear ratio i s1 = 9,665 Eco Mode i s1 =9,665 i s2 =4,47 25

Simulation results - Gear ratios selected to balance efficiency and performance Vehicle Mass m vehicle 1300 kg Tire Rolling Resistance μ tire 0,01 Factor Air Density ρ 1,17 kg/m 3 Vehicle Drag Coefficient C d 0,29 Vehicle Frontal Area A f 2,38 m 2 Electric Motor P max T max N max 125 kw 250 Nm 11400 RPM Energy Consumption [kw-h/100km] 15 14 13 12 ƞ EM Efficiency Map 11 NYCC NEDC HWFET Transmission n 1 is1 9,665 i s2 4,47 Reference mode i=9,665 Eco mode i1=9,665, i2=4,47 14 12,2 12,6 14 11,6 11,5 ƞ T Efficiency Map Optimized gear ratio 13,9 11,6 11,5 26

Dual speed transmission energy loss distribution Vehicle Mass m vehicle Electric Motor Transmission P max T max N max ƞ EM 1300 kg 125 kw 250 Nm 11400 RPM Efficiency Map n 2 i s1 9,665 i s2 4,47 ƞ T Efficiency Map Drag F drag ρ C d A f v 2 / 2 Rolling Resistance Auxiliary Loss F tire m vehicle. g. μ tyre. Cos(α) Time dependent Global Energy Loss in % Powertrain Losses [%] NYCC NEDC HWFET 21 14 9 Drag [%] 5 35 51 Rolling Resistance [%] 27 32 32 Auxiliary Load [%] 47 19 8 Regenerative Braking [%] 100 90 80 70 60 50 40 30 20 10 0-10 -9-7 -5 27

Energy loss distribution comparison Global Energy Loss in % Energy loss for single speed transmission Powertrain Losses [%] NYCC NEDC HWFET 21 18 17 Drag [%] 5 34 46 Rolling Resistance [%] 27 30 29 Auxiliary Load [%] 47 18 8 Regenerative Braking [%] 100 90 80 70 60 50 40 30 20 10 0-10 -9-7 -5 Global Energy Loss in % Energy loss for two speed transmission Powertrain Losses [%] NYCC NEDC HWFET 21 14 9 Drag [%] 5 35 51 Rolling Resistance [%] 27 32 32 Auxiliary Load [%] 47 19 8 Regenerative Braking [%] 100 90 80 70 60 50 40 30 20 10 0-10 -9-7 -5 28

Operational points of electric motor NYCC NEDC 250 250 150 150 Torque [Nm] 50-50 -150 0 5000 10000 Torque [Nm] 50-50 -150 0 5000 10000-250 Speed [RPM] -250 Speed [RPM] HWFET 250 Torque [Nm] 150 50-50 -150-250 0 5000 10000 Speed [RPM] Driving Cycle Average Operational Efficiency Of Transmission Single Speed Dual Speed NYCC 75% 75% NEDC 79% 81% HWFET 85% 93% 29

Questions answered 1 2 3 4 5 Is it possible to model energy consumption of BEV with GT- Suite? What are the loss contributors in the standard driving cycle? How does the energy consumption losses differ in urban, suburban and rural driving conditions? How does behaviour of BEV differ from ICE Vehicle? Can addition of second gear improve energy consumption in different cycles? 30

Statten Sie uns doch bei Ihrer nächsten Reise zum Campus einen Besuch ab! 31 C O N F I D E N T I A L

32 Thank You