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Nicki Bodenschatz

Fakultät Angewandte Informatik

Wissenschaftliche Mitarbeiter:innen

Wissenschaftlicher Mitarbeiter

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Beitrag in Sammelwerk/Tagungsband

  • Nicki Bodenschatz
  • Markus Eider
  • Andreas Berl

Challenges and requirements of electric vehicle fleet charging at company parking sites

pg. 623-628.

  • (2021)

DOI: 10.1109/ACIT52158.2021.9548563

The uprising number of electric vehicles on company parking sites creates a variety of challenges, in terms of scheduling charging processes. In uncoordinated charging, peaks loads can occur that harm the low voltage grid and make the company pay a higher electricity bill. Further, some vehicles may not be charged enough to be used for service appointments at customer homes. In a first step, this paper highlights the individual problems in detail that can appear in a company parking scenario. Next, it is shown that charging scheduling in a company case is not trivial. Finally, requirements to a software-based solution of the challenges are derived from the individual problems.
  • Angewandte Informatik
  • MOBIL
Vortrag

  • Nicki Bodenschatz

Das Forschungsprojekt SmiLE

In: 12. DACHS-Symposium für Lehre und angewandte Forschung in Informatik und Wirtschaftsinformatik

Deggendorf

  • 13.-14.09.2021 (2021)
  • Angewandte Informatik
  • MOBIL
Beitrag in Sammelwerk/Tagungsband

  • Markus Eider
  • Nicki Bodenschatz
  • Andreas Berl

Evaluation of machine learning algorithms for the prediction of simulated company parking space occupancy

pg. 739-743.

  • (2021)

DOI: 10.1109/ACIT52158.2021.9548487

Parking lots of cities and companies are congested when employees get to work in the morning hours. Some people might need to switch to public parking spaces if there is no spot left at their workplace. This is a serious challenge, as nowadays and especially in the future, the ratio of electric vehicles in transportation is growing. Therefore, electric vehicle users require guaranteed charging spots for the continuation of their journey. To enable reservations of parking and charging spots ahead of time, companies want to gain knowledge on upcoming vehicle numbers. So, there is a need for prediction models. However, there is little research done on prediction technologies for company parking spaces. In this paper, four different models from machine learning and statistics are compared in predicting the presence of vehicles from the user groups employees, fleet and visitors. They are trained on simulated occupancy data throughout one year. An evaluation shows that decision trees and artificial neural networks perform well for the case of company parking.
  • Angewandte Informatik
  • MOBIL
Vortrag

  • Nicki Bodenschatz

Challenges and requirements of electric vehicle fleet charging at company parking sites

In: 2021 11th International Conference on Advanced Computer Information Technologies (ACIT)

Deggendorf

  • 15.-17.09.2021 (2021)
  • Angewandte Informatik
  • MOBIL
Vortrag

  • Nicki Bodenschatz
  • Markus Eider
  • Andreas Berl

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

In: 2020 10th International Conference on Advanced Computer Information Technologies (ACIT)

Deggendorf

  • 16.-18.09.2020 (2020)
  • TC Plattling MoMo
  • Angewandte Informatik
  • NACHHALTIG
  • DIGITAL
Vortrag

  • Nicki Bodenschatz

Optimierte Ladeplanung von E-Fahrzeugflotten

In: 2. TRIOKON 2020 – Die ostbayerische Transferkonferenz für Wirtschaft, Wissenschaft und Gesellschaft

Hochschule für angewandte Wissenschaften Landshut Landshut

  • 29.09.2020 (2020)
  • TC Plattling MoMo
  • Angewandte Informatik
  • NACHHALTIG
  • DIGITAL
Beitrag in Sammelwerk/Tagungsband

  • Nicki Bodenschatz
  • Markus Eider
  • Andreas Berl

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

pg. 741-746.

  • (2020)

DOI: 10.1109/ACIT49673.2020.9208875

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.
  • TC Plattling MoMo
  • Angewandte Informatik
  • DIGITAL
  • MOBIL
Beitrag in Sammelwerk/Tagungsband

  • Nicki Bodenschatz
  • Andreas Berl

Viability and Optimality of Electric Vehicle Fleet Schedules

pg. 425-430.

  • (2019)
The number of electric vehicles is steadily growing and commercial fleet owners follow this trend. However, the charging of fleets has a major impact on the already stressed power grid. To prevent negative impact on the grid, it is necessary to schedule charging processes. This charging scheduling should not only utilize the existing charging infrastructure and the available resources, but it should furthermore allow an optimized charging schedule, e.g. in terms of cost reduction. This scheduling problem is complex and it needs significant information about infrastructure and fleet in order to create a viable charging schedule. However, not all of the relevant information is always available. For this reason, this paper analysis the possibilities to create a charging schedule with missing information. To achieve this, the paper provides a detailed description of the charging scheduling problem for a day ahead planning and the necessary input parameters. It clarifies the influence of the input parameters on the viability and optimality of a charging schedule. On this base, the paper establishes data sets with different degrees of scheduling possibilities. Further, the paper analyses the affectation of missing input parameters on the scheduling and it provides possible solutions to approximate the missing parameters under the proposition to guarantee the viability of a charging schedule.
  • Angewandte Informatik
  • MOBIL
Vortrag

  • Nicki Bodenschatz

Electric Vehicle Fleet Charging . Vortrag und Posterpräsentation

In: 6. Tag der Forschung

Technische Hochschule Deggendorf Deggendorf

  • 10.04.2019 (2019)
  • TC Freyung
  • Elektrotechnik und Medientechnik
  • MOBIL
Zeitschriftenartikel

  • Diana Schramm
  • Nicki Bodenschatz
  • Andreas Berl

Usage Profiling in Electric Vehicles

In: Bavarian Journal of Applied Sciences vol. 4 pg. 342-353.

  • (2018)

DOI: 10.25929/bjas.v4i1.52

In the overall effort of reducing CO2 emissions, the significance of alternative drive engines is growing. The transition from combustion engine vehicles to electric vehicles is high on the political agendas, with governments providing extensive funding to promote electric mobility. However, there are still challenges that hamper the dissemination of electric vehicles. One of those challenges is the limited range and the resulting range anxiety. Displayed vehicle range data contribute to this, as they are relatively inaccurate and might vary quite strongly during individual trips. This problem could be addressed by personalizing the range display according to the driving style of the current driver. Driver assistance services, like distance control, are becoming increasingly personalized nowadays, however, they are predominantly designed for internal combustion engine vehicles. In this paper, relevant input parameters for classifying the driving styles of electric vehicle users are identified. Furthermore, a system based on real-life driving data is developed to determine the driving style. Real-life driving data were collected in experiments and used to profile the driving style by means of fuzzy logic. Based on the results, an approach for a realistic classification of driving styles of electric vehicle users is discussed.
  • Elektrotechnik und Medientechnik
  • MOBIL
Beitrag in Sammelwerk/Tagungsband

  • Nicki Bodenschatz
  • Diana Schramm
  • Markus Eider
  • Andreas Berl

Classification of Electric Vehicle Fleets Considering the Complexity of Fleet Charging Schedules . [Status: Presented]

New York, NY

  • (2018)
  • TC Freyung
  • MOBIL
Vortrag

  • Nicki Bodenschatz
  • Markus Eider
  • Diana Schramm
  • Andreas Berl

Optimierte Ladeplanung von Elektrofahrzeugflotten . Posterpräsentation

In: 5. Tag der Forschung

Technische Hochschule Deggendorf Deggendorf

  • 08.03.2018 (2018)
  • TC Freyung
  • MOBIL
Beitrag in Sammelwerk/Tagungsband

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

A Novel Approach on Battery Health Monitoring

  • (2018)

  • TC Freyung
  • DIGITAL