InformaApp - Publikationen

Digital Nachhaltig F: Angewandte Informatik S: TC Plattling MoMo

Requirements for prescriptive recommender systems extending the lifetime of EV batteries

2020 10th International Conference on Advanced Computer Information Technologies (ACIT), Deggendorf

2020

Vortrag

Nicki Bodenschatz, Markus Eider, Andreas Berl

Mixed-Integer-Linear-Programming model for the charging scheduling of electric vehicle fleets

2020 10th International Conference on Advanced Computer Information Technologies (ACIT), Deggendorf

2020

Digital Mobil F: Angewandte Informatik S: TC Plattling MoMo

Beitrag (Sammelband oder Tagungsband)

Nicki Bodenschatz, Markus Eider, Andreas Berl

Mixed-Integer-Linear-Programming model for the charging scheduling of electric vehicle fleets

Proceedings of the 2020 10th International Conference on Advanced Computer Information Technologies (ACIT) [September 6-8, 2020; Deggendorf]

2020

DOI: 10.1109/ACIT49673.2020.9208875

Mobil Nachhaltig F: Angewandte Informatik S: TC Plattling MoMo

The number of electric vehicles is steadily increasing of the past few years. This transition to electric vehicles bears the challenge, to integrate the charging processes into the grid without overstressing it. To prevent this, research has tackled lately the scheduling of electric vehicle charging. Especially the charging of electric vehicle fleets is in the focus of research. There are already different solution approaches to increase the grid stability, to increase the intake of locally produced renewable energy or simply to reduce the cost. However, all these solution approaches use different mathematical models with different parameters to represent the charging scheduling problem. This results in the problem that each model is applicable for a special use case only, other use cases might need other parameters for the scheduling of the electric vehicle fleet. To ease this problem, this paper provides a detailed mathematical model for the cost minimization of a general electric fleet in the form of a mixed-integer-linearprogram. In order to do this, the paper shows that different research approaches use different parameters in their solutions. Afterwards, the paper presents a general overview of technical limitations for the electric fleets. On foundation of these limitations a mixed-integer-linear-program model for a wide range of electric fleets is established. Also, the paper provides options to extend the model in order to improve the result of an optimal schedule.

Beitrag (Sammelband oder Tagungsband)

DOI: 10.1109/ACIT49673.2020.9209011

Requirements for prescriptive recommender systems extending the lifetime of EV batteries

Proceedings of the 2020 10th International Conference on Advanced Computer Information Technologies (ACIT) [September 6-8, 2020; Deggendorf]

2020

Mobil Nachhaltig F: Elektrotechnik und Medientechnik S: TC Freyung

Lithium-ion batteries in electric vehicles are subject to degradation, which is strongly influenced by the actions of vehicle users. Hereby, inexperienced users can cause the battery to reach its end of life state earlier than average. For this reason, this paper proposes the concept of a prescriptive recommender system that supports users in planning their utilization actions. The paper identifies functionalities of decision support systems relevant to extend the lifetime of electric and electronic systems. This allows to determe generic functional and non-functional requirements for prescriptive recommender systems. Further, the derived requirements are discussed in connection to the practicability of a prescriptive recommender system.

Vortrag

Markus Eider

Nutzerorientierte Empfehlungen für Lithium-Ionen-Batterien in Elektrofahrzeugen

Posterpräsentation

6. Tag der Forschung, Deggendorf

2019

Mobil F: Elektrotechnik und Medientechnik S: TC Freyung

Vortrag

Mobil F: Elektrotechnik und Medientechnik

Verlängerte Batterielebensdauer von Elektrofahrzeugen durch dynamische Nutzungsempfehlungen

4. Jahreskonferenz des Netzwerks INDIGO (Internet und Digitalisierung Ostbayern), Deggendorf

2018

Vortrag

Markus Eider

Dynamic Generation of Recommendations for EV Battery Health

International Conference of Electrical and Electronic Technologies for Automotive (AUTOMOTIVE), Mailand, Italien

2018

Mobil Nachhaltig S: TC Freyung

Beitrag (Sammelband oder Tagungsband)

Mobil Nachhaltig S: TC Freyung

Dynamic EV Battery Health Recommendations

ACM e-Energy '18: Proceedings of the Ninth ACM International Conference on Future Energy Systems (June 12-15, 2018; Karlsruhe, Germany), New York, NY

2018

ISBN: 978-1-4503-5767-8

Beitrag (Sammelband oder Tagungsband)

DOI: 10.23919/EETA.2018.8493182

Dynamic Generation of Recommendations for EV Battery Health

2018 International Conference of Electrical and Electronic Technologies for Automotive (AUTOMOTIVE) [9-11 July, 2018; Milan, Italy]

2018

Electric vehicles equipped with Lithium-ion batteries face performance loss due to battery ageing. This effect can be actively influenced through behaviour introduced by vehicle users. Therefore, this paper proposes a dynamic recommendation architecture to automatically generate dynamic recommendations in order to prolong battery lifetime. We propose dynamic recommendations as well as requirements for them. The recommendations suggest a certain user behaviour for a specific chronological scope in the future as well as a weight based on their impact on maintaining battery health. Furthermore, we present an exemplary architecture, based on the requirements. Using historical electric vehicle driving data, it can automatically derive dynamic recommendations.

Vortrag

Markus Eider

A Novel Approach on Battery Health Monitoring

7th Conference on Future Automotive Technology (CoFAT), Fürstenfeldbruck

2018

Nicki Bodenschatz, Markus Eider, Diana Schramm, Andreas Berl

Vortrag

Optimierte Ladeplanung von Elektrofahrzeugflotten

Posterpräsentation

5. Tag der Forschung, Deggendorf

2018

Nicki Bodenschatz, Diana Schramm, Markus Eider, Andreas Berl

Beitrag (Sammelband oder Tagungsband)

Classification of Electric Vehicle Fleets Considering the Complexity of Fleet Charging Schedules

[Status: Presented]

ACM e-Energy '18: Proceedings of the Ninth ACM International Conference on Future Energy Systems (June 12-15, 2018; Karlsruhe, Germany), New York, NY

2018

ISBN: 978-1-4503-5767-8

Mobil F: Elektrotechnik und Medientechnik

Beitrag (Sammelband oder Tagungsband)

Markus Eider, Diana Schramm, Nicki Bodenschatz, Andreas Berl, P. Danner, H. Meer

A Novel Approach on Battery Health Monitoring

Proceedings of the 7th Conference on Future Automotive Technology (CoFAT) [May 8th-9th, 2018; Fürstenfeldbruck]

2018

Beitrag (Sammelband oder Tagungsband)

B. Kirpes, S. Klingert, R. Basmadjian, H. Meer, Markus Eider, M. Ortega

EV Charging Coordination to Secure Power Grid Stability

1st E-Mobility Power System Integration Symposium (23 October 2017; Berlin)

2017

Stefan Kunze, Rainer Pöschl, Alexander Faschingbauer, Markus Eider

Beitrag (Sammelband oder Tagungsband)

Artificial Neural Networks based Age Estimation of Electronic Devices

Proceedings of the 2017 International Conference on Optimization of Electrical and Electronic Equipment (OPTIM) & 2017 International Aegean Conference on Electrical Machines and Power Electronics (ACEMP) [May 25-27 2017; Brasov, Romania] , vol. IEEE Conference Record #38276

2017

DOI: 10.1145/3077839.3078461

Beitrag (Sammelband oder Tagungsband)

Markus Eider, Diana Schramm, Andreas Berl, R. Basmadjian, H. Meer, S. Klingert, T. Schulze, F. Kutzner, C. Kacperski, M. Štolba

Seamless Electromobility

ACM e-Energy '17: Proceedings of the Eighth ACM International Conference on Future Energy Systems (May 16-19, 2017; Shatin, Hong Kong), New York NY

2017

ISBN: 978-1-4503-5036-5

The existing electromobility (EM) is still in its fledgling stage and multiple challenges have to be overcome to make Electric Vehicles (EVs) as convenient as combustion engine vehicles. Users and Electric Vehicle Fleet Operators (EFOs) want their EVs to be charged and ready for use at all times. This straightforward goal, however, is counteracted from various sides: The range of the EV depends on the status and depletion of the EV battery which is influenced by EV use and charging characteristics. Also, most convenient charging from the user's point of view, might unfortunately lead to problems in the power grid. As in the case of a power peak in the evening when EV users return from work and simultaneously plug in their EVs for charging. Last but not least, the mass of EV batteries are an untapped potential to store electricity from intermittent renewable energy sources. In this paper, we propose a novel approach to tackle this multi-layered problem from different perspectives. Using on-board EV data and grid prediction models, we build up an information model as a foundation for a back end service containing EFO and Charging Station Provider (CSP) logic as well as a central Advanced Drivers Assistant System (ADAS). These components connect to both battery management and user interfaces suggesting various routing and driving behaviour alternatives customized and incentivized for the current user profile optimizing above mentioned goals.

Markus Eider, Stefan Kunze, Wolfgang Dorner

Beitrag (Sammelband oder Tagungsband)

A Customizable Software Tool for Hardware in the Loop Tests

Proceedings of the 21st International Conference on Applied Electronics (AE) 2016 (September 6-7 2016, Pilsen, Czech Republic)

2016