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Röpke, Karsten / Gühmann, Clemens:

Automotive Data Analytics, Methods, Design of Experiments (DoE)

In cooperation with 84 co-authors 2017, ca. 300 S. (RT) Kt.
ca. 66,00 €, 81,00 CHF
ISBN: 978-3-8169-3381-6
Mai 2017
www.iav.de
Klicken Sie hier wenn Sie dieses Buch bestellen wollen. Später können Sie noch die Stückzahl ändern!

The book will expand on the topics discussed in the precursors entitled "DoE in Powertrain Development" with the related areas of "machine learning" and "big data". Now it its ninth outing, the conference will thus be a forum on which to critically engage with the future challenges of the digital revolution.
Real driving emissions (RDE), worldwide harmonized light-duty test procedures (WLTP) and the next round of CO2 guidelines all demand ongoing technical refinement of the drive train. The combination of changed environmental requirements, stricter limit values and new measurement techniques additionally require changes to existing processes and the development of new methods.

To reduce costs, many OEMs are scaling down the size of their engine ranges. A small number of standard engines are then installed in numerous vehicle models with minor hardware modifications. The result is an increased focus on the use of derivatives and the systematic validation of an application.

Contents:
Machine learning and artificial intelligence for engine calibration – Big Data and Machine Learning made easy with MATLAB for Automotive Engineers – Automated calibration using simulation and robust design optimization improving shift and launch quality of automatic transmissions – Development of a simulation platform for validation and optimisation of real-world emissions – Databased model implementation on dedicated ML Hardware (AMU) and its impact on function development and calibration processes – Global DoE Model Based Calibration & Test Automation of the Gasoline Engine – Optimization of ECU Map Sampling Point Values and Positions with model-based Calibration – Optimization of a Compression Ignition Engine using Naphta Fuel with the Help of Advanced DoE Methodologies – System for real-time evaluation of Real-Drive Emission (RDE) data – System optimization for automated calibration of ECU functions – Realtime adaptive test design: An implementation for overall system identification – Dynamic MBC Methodology for Transient Engine Combustion Optimization – Implementierung eines Echtzeitmodells für die Abgastemperatur eines Dieselmotors mit ASC@ECU – Dynamic Modeling Calibration for Gasoline Direct Injection Engine – Excitation Signal Design for Nonlinear Dynamic Systems – Application of a DoE based robust design process chain for system simulation of engine systems – Application of Emulator Models in Hybrid Vehicle Development – Fast response surrogates and sensitivity analysis based on physico-chemical engine simulation applied to modern compression ignition engines – The Connected Car and its new possibilities in ECU calibration – Validating and calibrating vehicle electronics: Quick and easy processes with innovative digital technologies – Processing Automotive Measurement Data – On the selection of appropriate data from normal vehicle operation for system identification of a diesel engine air path – Dynamic Route Based Design of Experiments – Dataplausibility at engine test bench: How important is the human factor in the process – – A Comparison of Non-Convex Data Hulls – Modern Online DoE Methods for Calibration: Constraint Modeling, Continuous Boundary Estimation, and Active Learning – Model-based iterative DoE in highly constrained spaces

Target group:
Development and application engineers from automotive manufacturers and supply industry as well as universities

The Editors:
Dr.-Ing. Karsten Röpke is Head of Department Development Methods at IAV.
Prof. Dr.-Ing. Clemens Gühmann is Head of the Chair of Electronic Measurement and Diagnostic Technology at TU Berlin


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