Project Diesel Reloaded
Diesel Reloaded A Holistic Approach to Electric Mobility Motivation: Manage complexity of functions Optimal interconnection Project aims: Holistic approach to electric mobility Build demonstrator InnoTruck for evaluation and presentation of results Supported by http//www.innotruck.de 2
Demonstrator InnoTruck - Highlights Design by Luigi Colani Bi-directional, predictive energy management Photovoltaic system and wind generator Gigaliner concept Innovative Human- Machine-Interface Workshop for electric vehicles Centralized IT architecture Drive-By-Wire Hybrid Drive Charging spot for electric vehicles 3
Diesel Reloaded Project Team Siemens / IAS Prof. Spiegelberg TUM Prof. Knoll TUM Prof. Lienkamp Principal Investigators Rudolf Diesel Senior Fellow Institute for Advanced Studies Robotic and Embedded Systems TUM Automotive Technology TUM Doctroal Candidates Hauke Stähle, System Architecture Ljubo Mercep, Human- Machine- Interface Claudia Buitkamp, Energy Management Students 4
Project Roadmap Building of first prototype as a platform for innovative concepts Test of truck and implementing new concepts Evaluation of truck and concepts, Finalization Begin 2011 End 2011 Begin 2012 Mid 2012 Mid 2012 End 2013 5
Research topic #1: System Architecture Vehicle ICT HMI Energy Management New concepts for the system architecture of vehicles, evaluated on the example of advanced driver assistance systems. Optimal information flow between all functions Delivering data with quality-of-service guarantees Structuring functions according to information flow Dipl.-Ing. Hauke Stähle Chair for Robotics and Embedded Systems Department for Informatics Technische Universität München 6
Inform. and Comm. Technology in Today s Vehicles New technologies Increased data exchange New functions Heavily interconnected architecture (Audi A8, Self-study Programme 459, Audi AG) 7
System Architecture A new Paradigm Old Paradigm: Component-Driven Design New Paradigm: Data-Driven Design Acceleration Steering Gear Brake Smart Joystick Smart LCD ECU ECU ECU ECU Centralized Human-Machine- Interface Processing Unit Strategy Level Centralized Drivetrain Processing Unit Execution Level Backbone Smart Motor Smart Wheel 8
System Architecture - Outlook External Comm. Car Sharing Assistance Flexible Parking Assistance Image Sensor Affordable Ultrasonic Sensor Motor Management Radar Sensor Safe Collision Avoidiance Lidar Sensor Key Software Component Hardware Component Update Server Application Server Database 9
Research Topic #2: Drivetrain and Energy Management Electrical energy management for hybrid commercial trucks. Vehicle ICT HMI Energy Management Benefits for the vehicle manufacturer and the operator flexible energy management holistically minimizing operating costs Dipl.-Ing. Claudia Buitkamp Institute of Automotive Technology Department of Mechanical Engineering Technische Universität München 10
InnoTruck with Two Modes While Driving While Standing Innotruck is a serial hybrid truck Innotruck can be seen as a smart home Battery Engine + Generator Electric Motor Movement 11
Energy Management External Power Power Sources Energy Storage Solar Power Combustion Engine + Generator Wind Power Brake Energy Recuperation Global Energy Management LiFePO4- Battery Global Power Grid/ Smart Grid Power Sinks Elektric motor + Drive Shaft, Axle Auxiliaries Electric cars connected to the Innotruck 12
Research topic #3: Human-Machine Interface The goal is to develop and implement a strategy for intelligent user interfaces in road vehicles. Vehicle ICT Energy Management HMI Developing the necessary artificial intelligence Analyzing sidestick and touchscreen-based cockpit Analyzing brain-computer interfaces as the longterm HMI solution Ljubo Mercep, M.Sc. Chair for Robotics and Embedded Systems Department for Informatics Technische Universität München 13
Focus area 1: Artificial intelligence for the HMI Query with QoS requirements HMI Application Query answers ADAS Application Query with QoS requirements Artificial Intelligence Software Unit Vehicle ICT Subscription to data sources and publication of data 14
Focus area 2.1: Sidestick study Method: Learning driver-specific steering profiles for different types of environments In-city Off-road Detecting anomalies in a learned profile is a warning sign for driver assistance Driving task is reduced at the lane following task 15
Focus area 2.2: Touchscreen study 16
Focus area 3: Brain-computer interfaces Side challenge: managing the signal artifacts: Vibration-caused artifacts through Gyroscope data Biological through classical Independent Component Analysis Technology-specific through extended Indepenent Component Analysis 17