Personal information

Other IDs

Scopus Author ID: 57159206500
ResearcherID: G-6831-2018

Keywords

Computational Intelligence , Machine Learning, Automotive Applications, Genetic Algorithms, Neuronal Networks, Optimization, Multi Objective Problems, Technology Management

Countries

Germany

Activities

Collapse all

Employment (1)

Technical University of Munich: Munich, Bavaria, DE

Phd Candidate (Institute of Automotive Technology)
Employment
Source: Self-asserted source
Michael Fries

Education and qualifications (1)

Technical University of Berlin: Berlin, Berlin, DE

2010-04-01 to 2012-04-30 | M. Sc, (Transportation Studies and Machine Systems)
Education
Source: Self-asserted source
Michael Fries

Works (18)

Maschinelle Optimierung der Antriebsauslegung zur Reduktion von CO2-Emissionen und Kosten im Nutzfahrzeug

2019 | Book
DNB: 1181515653
URN: urn:nbn:de:101:1-2019032222433099750564
ISBN:

978-3-8439-3988-1
Contributors: Michael Fries
Source: Self-asserted source
Michael Fries via Deutsche Nationalbibliothek (DNB)

Technoecological analysis of energy carriers for long-haul transportation

Journal of Industrial Ecology
2019 | Journal article
DOI: 10.1111/jiec.12937
EID:

2-s2.0-85070831112
Contributors: Wolff, S.; Fries, M.; Lienkamp, M.
Source: Self-asserted source
Michael Fries via Scopus - Elsevier

Derivation of a real-life driving cycle from fleet testing data with the Markov-Chain-Monte-Carlo Method

IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
2018 | Conference paper
DOI: 10.1109/ITSC.2018.8569547
EID:

2-s2.0-85060487709
Contributors: Fries, M.; Baum, A.; Wittmann, M.; Lienkamp, M.
Source: Self-asserted source
Michael Fries via Scopus - Elsevier

Multi-criterion optimization of heavy-duty powertrain design for the evaluation of transport efficiency and costs

IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
2018 | Conference paper
DOI: 10.1109/ITSC.2017.8317753
EID:

2-s2.0-85045281939
Contributors: Fries, M.; Lehmeyer, M.; Lienkamp, M.
Source: Self-asserted source
Michael Fries via Scopus - Elsevier
grade
Preferred source (of 3)‎

Operational Strategy of Hybrid Heavy-Duty Trucks by Utilizing a Genetic Algorithm to Optimize the Fuel Economy Multiobjective Criteria

IEEE Transactions on Industry Applications
2018 | Journal article
DOI: 10.1109/TIA.2018.2823693
EID:

2-s2.0-85045211383
Contributors: Fries, M.; Kruttschnitt, M.; Lienkamp, M.
Source: Self-asserted source
Michael Fries via Scopus - Elsevier

An Overview of Costs for Vehicle Components, Fuels, Greenhouse Gas Emissions and Total Cost of Ownership - Update 2017

Unpublished
2017 | Dataset
DOI: 10.13140/rg.2.2.11685.40164
Contributors: Fries, Michael; Kerler, Mathias; Rohr, Stephan; Sinning, Michael; Schickram, Stephan; Lienkamp, Markus; Kochhan, Robert; Fuchs, Stephan; Reuter, Benjamin; Burda, Peter et al.
Source: check_circle
DataCite

An Overview of Costs for Vehicle Components, Fuels, Greenhouse Gas Emissions and Total Cost of Ownership Update 2017

Unpublished
2017 | Dataset
DOI: 10.13140/rg.2.2.19963.21285
Contributors: Fries, Michael; Kerler, Mathias; Rohr, Stephan; Schickram, Stephan; Sinning, Michael; Lienkamp, Markus
Source: check_circle
DataCite
grade
Preferred source (of 3)‎

Bayerische Kooperation für Transporteffizienz - Truck2030 - Status Report 2016 -

https://mediatum.ub.tum.de/1350441
2017 | Report
DOI: 10.13140/rg.2.2.16457.95847
Contributors: Mährle, Christian; Härtl, Martin; Wachtmeister, Georg; Fries, Michael; Sinning, Michael; Lienkamp, Markus; Wotan Wilden; Frenkler, Fritz; Gänßbauer, Bianca; Bick, Werner
Source: check_circle
DataCite
grade
Preferred source (of 2)‎

Multi-objective optimization of a long-haul truck hybrid operational strategy and a predictive powertrain control system

2017 12th International Conference on Ecological Vehicles and Renewable Energies, EVER 2017
2017 | Conference paper
DOI: 10.1109/EVER.2017.7935872
EID:

2-s2.0-85021351473
Contributors: Fries, M.; Kruttschnitt, M.; Lienkamp, M.
Source: Self-asserted source
Michael Fries via Scopus - Elsevier

Optimization of hybrid electric drive system components in long-haul vehicles for the evaluation of customer requirements

2017 IEEE 12th International Conference on Power Electronics and Drive Systems (PEDS)
2017 | Conference paper
DOI: 10.1109/peds.2017.8289236
Part of ISBN: 9781509023646
Contributors: M. Fries; S. Wolff; L. Horlbeck; M. Kerler; M. Lienkamp; A. Burke; L. Fulton
Source: Self-asserted source
Michael Fries via Crossref Metadata Search
grade
Preferred source (of 3)‎

Predictive Technology Management for the Identification of Future Development Trends and the Maximum Achievable Potential Based on a Quantitative Analysis

Advances in Science, Technology and Engineering Systems Journal
2017-07 | Journal article
DOI: 10.25046/aj0203132
Contributors: Michael Fries; Markus Lienkamp
Source: Self-asserted source
Michael Fries via Crossref Metadata Search
grade
Preferred source (of 4)‎

Technology assessement based on growth functions for prediction of future development trends and the maximum achieveable potential

IEEE International Conference on Industrial Engineering and Engineering Management
2016 | Conference paper
DOI: 10.1109/IEEM.2016.7798140
EID:

2-s2.0-85009865361
Contributors: Fries, M.; Lienkamp, M.
Source: Self-asserted source
Michael Fries via Scopus - Elsevier

Virtual Truck – A method for customer oriented commercial vehicle simulation

Proc. 4th International Commercial Vehicle Technology Symposium
2016 | Conference paper
DOI: 10.2370/9783844042290
Contributors: Fries, Michael; Michael Sinning, Martin Höpfner, Markus Lienkamp
Source: Self-asserted source
Michael Fries via ResearcherID

Virtual Truck – A method for customer oriented commercial vehicle simulation

Proc. 4th International Commercial Vehicle Technology Symposium
2016 | Conference paper
Part of DOI: 10.2370/9783844042290
Source: Self-asserted source
Michael Fries

COFAT 2015 - Virtual Combination of Commercial Vehicle Modules (Virtual Truck) for characterization of future Concepts

2015 | Journal article
SOURCE-WORK-ID: BASE:4ad6f16decf38e30e0b69c52b82aa002bab309438e249f7827538528c870e02f
Contributors: Michael Fries, Michael Sinning, Markus Lienkamp
Source: Self-asserted source
Michael Fries via BASE - Bielefeld Academic Search Engine

COFAT 2015 - Virtual Combination of Commercial Vehicle Modules (Virtual Truck) for characterization of future Concepts

Conference on Future Automotive Technology
2015 | Conference paper
SOURCE-WORK-ID:

040918044877-8
Contributors: Michael Fries, Michael Sinning, Markus Lienkamp
Source: Self-asserted source
Michael Fries via ResearcherID

COFAT 2015 - Virtual Combination of Commercial Vehicle Modules (Virtual Truck) for characterization of future Concepts

Conference on Future Automotive Technology
2015 | Conference paper
Source: Self-asserted source
Michael Fries

Highly automated truck driving - How can drivers safely perform sport exercises on the go?

Adjunct Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive VehicularApplications, AutomotiveUI 2015
2015 | Conference paper
DOI: 10.1145/2809730.2809733
EID:

2-s2.0-84960117331
Contributors: Richardson, N.T.; Sinning, M.; Fries, M.; Stockert, S.; Lienkamp, M.
Source: Self-asserted source
Michael Fries via Scopus - Elsevier
grade
Preferred source (of 3)‎
How many people are using ORCID?