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S.Jones, Frontloaded Development of Efficient & Safe Conventional & Electrified Vehicles in Advanced 1D/3D CoSimulation Toolchain 23th September 2014

Frontloaded Development of Efficient & Safe Conventional & Electrified Vehicles in Advanced 1D/3D Co-Simulation Toolchain

IPG Technology Conference 2014 Dr. Stephen Jones et. al. / DSS 23.09.2014 [email protected] +43 316 787 4484


Outline

Introduction

Connected Vehicle & Predictive Control

Safety Co-Simulation

Special Vehicle Application

Summary & Outlook



Introduction

Challenges in vehicle development

CO2 emission targets Increased complexity

Electrification

Hybridization

Connected vehicles

Safety & Comfort Faster development cycles

Where is the intelligence in it?

THE CONNECTED POWERTRAIN™ for Efficiency Advanced Driver Assistance Systems for Safety & Comfort


Source: www.hybridcars.com

Source: newsroom.scania.com

Source: www.nextenergy.org

Source:IPG.de



Introduction

How to develop interdisciplinary systems of that complexity

Co-simulation toolchain allows vital features to be incorporated:

Detailed road information including realistic real-world 3D driving route simulation

Sensor Cameras, LIDAR, RADAR, Ultrasonic, ….

V2V, C2C, V2I, C2I communication, traffic sign detection, traffic flow information, etc.

Traffic scenarios: traffic lights, overtaking, …

Source: Continental



Introduction

Fast migration from pure office simulation to 4WD InMotion

powertrain testbed

Reusability of all developed use cases on testbed

Tests on realistic real-world 3D driving routes

Vehicle dynamics maneuvers for TCS, ESP, VDC systems

Reproducibility for safety related maneuvers: DLC, µ-split etc.

Development of connected functions & predictive control strategies

under highly realistic conditions


Outline

Introduction




Summary & Outlook





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Example 1: Predictive Energy Management with GPS for Prius III



ADAS RP

GoogleEarth

Virtual driving route

Vehicle Position in GE

Vehicle Position in ADASRP

Following Traffic Attributes


Example 2: eHorizon with ADAS RP

Predictive energy management considering driving route information

Next Traffic Sign Ahead

Electronic Horizon Slope profile in 1 km Current Slope Curve Radius


Flat Road – both vehicles with 85 kph target speed Downhill Road – vehicle with predictive control allows higher velocity Uphill Road – vehicle with predictive control reduces velocity Flat Road – both vehicles with 85 kph target speed

Standard (transparent)

Predictive (solid)

Conventional Driving Conventional Driving Recuperation Sailing Electric Boost Conventional Driving

Conventional Driving

By adapting the target speed based on the current topology,

fuel consumption and battery load can be reduced.


Example 3: Predictive Cruise Control



Example 4: Coasting Assistant

Automatically adapt driving speed due to legal speed limit

Controller receives traffic sign information and acts upon it as feasible

Conceptual HMI visualization through CarMaker Instruments Cluster

to provide information to the driver

S.Jones, Frontloaded Development of Efficient & Safe Conventional & Electrified Vehicles in Advanced 1D/3D CoSimulation Toolchain 23th September 2014 15

Hybrid control strategy

modeled in detail

AVL GPS based predictive

energy management

Co-simulation shows

ca. 4% real world efficiency

improvement by considering

downhill parts


Example 5: Predictive Energy Management with GPS for Prius III


Outline

Introduction




Summary & Outlook



Event

Exposure

Severity

Controllability

Inherent Risk Tolerable Risk Residual Risk

Necessary risk reduction

Actual risk reduction

3 aspects in ASIL


Safety Co-Simulation: in Concept Phase



Example 1: Safety Co-Simulation in Concept Phase

Wet road, Unintended full negative EM torque, Harsh driver braking

2 vehicles in video: Grey (normal, no failure), White (with failure)


Entrance speed: 120km/h


Example 2: Safety Co-Simulation using vehicle software in the loop

Simulated double-lane-change maneuver

Each EM is controlled separately by the Traction Control System (TCS) inside the

ESP®hev.

Recuperation torque and friction torque are coordinated (torque blending) due to

the interaction between the powertrain energy management and the ESP®hev.


First lane change without braking





ESP®hev.




Second lane change with braking





ESP®hev.




Stable driving condition





ESP®hev.







Braking with pure recuperation

Steering causes VDC (Vehicle Dynamics Control) to detect a critical situation

• Reduction of recuperation torque (Torque Blending)

• Increase of right rear brake pressure to maintain continuous braking

Driver steers back to right lane and VDC increases pressure on rear right wheel.

Individual modulation

of rear wheels brake

pressure independent

of pedal actuation




ADAS & Safety function development & testing

Safety maneuvers

Vehicle stability assessment, component failure, …

E.g. double lane change, µ-split

Traffic simulation

Safe and efficient reaction to traffic objects

E.g. optimized regenerative braking

Real-world driving routes

Virtual test drive of any road in the world

E.g. verification of regenerative braking system

Simultaneously maximized:

energy-efficiency & safety


Road Testbed Lab Office

Reuse of office simulation environment on AVL Powertrain Testbed



Simulation toolchain easily supports

development process, model reuse

from Office PC, to HiL, to Testbed

Rapid prototype testing

Fast migration to HiL testing

Realistic real-world conditions

Complex interface between Unit Under Test, automation and measurement systems


Outline

Introduction




Summary & Outlook




Co-simulation platform for simulation of tracked vehicles

Simulation of vehicle-ground interaction on different soil types

Detailed powertrain modeling

Integration of powertrain & vehicle control strategies

Vehicle dynamics: 3D road & driver

CarMaker Controller

Controller Powertrain co-Simulation

3D vehicle dynamics Vehicle & driver model

Longitudinal driveline simulation

Interface Interface

Interface

Control functions: steering, hydraulics, Custom caterpillar track model



Outline

Introduction




Summary & Outlook




Co-simulation platform with model reuse capability for frontloaded

development

Key element to handle complexity of interdisciplinary vehicle design

Powerful & useful foundation available today

Complex traffic scenarios & emulation of sensor information (e.g. radar, video, v2x, …)

Interfaces for various specialized tools & real hardware

HOW DO WE BRING EVERYTHING TOGETHER ?

Modelin

g

Execution



Co-simulation platform with model reuse capability for frontloaded

development

Key element to handle complexity of interdisciplinary vehicle design

Powerful & useful foundation available today

Complex traffic scenarios & emulation of sensor information (e.g. radar, video, v2x, …)

Interfaces for various specialized tools & real hardware

Modelin

g

Execution


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