---
_id: '5914'
abstract:
- lang: eng
  text: During the last years, alternative drive technologies, for example electrically
    powered vehicles (EV), have gained more and more attention, mainly caused by an
    increasing awareness of the impact of CO2 emissions on climate change and by the
    limitation of fossil fuels. However, these technologies currently come with new
    challenges due to limited lithium ion battery storage density and high battery
    costs which lead to a considerably reduced range in comparison to conventional
    internal combustion engine powered vehicles. For this reason, it is desirable
    to increase the vehicle range without enlarging the battery. When the route and
    the road slope are known in advance, it is possible to vary the vehicles velocity
    within certain limits in order to reduce the overall drivetrain energy consumption.
    This may either result in an increased range or, alternatively, in larger energy
    reserves for comfort functions such as air conditioning. In this presentation,
    we formulate the challenge of range extension as a multiobjective optimal control
    problem. We then apply different numerical methods to calculate the so-called
    Pareto set of optimal compromises for the drivetrain power profile with respect
    to the two concurrent objectives battery state of charge and mean velocity. In
    order to numerically solve the optimal control problem by means of a direct method,
    a time discretization of the drivetrain power profile is necessary. In combination
    with a vehicle dynamics simulation model, the optimal control problem is transformed
    into a high dimensional nonlinear optimization problem. For the approximation
    of the Pareto set, two different optimization algorithms implemented in the software
    package GAIO are used. The first one yields a global optimal solution by applying
    a set-oriented subdivision technique to parameter space. By construction, this
    technique is limited to coarse discretizations of the drivetrain power profile.
    In contrast, the second technique, which is based on an image space continuation
    method, is more suitable when the number of parameters is large while the number
    of objectives is less than five. We compare the solutions of the two algorithms
    and study the influence of different discretizations on the quality of the solutions.
    A MATLAB/Simulink model is used to describe the dynamics of an EV. It is based
    on a drivetrain efficiency map and considers vehicle properties such as rolling
    friction and air drag, as well as environmental conditions like slope and ambient
    temperature. The vehicle model takes into account the traction battery too, enabling
    an exact prediction of the batterys response to power requests of drivetrain and
    auxiliary loads, including state of charge.
author:
- first_name: Michael
  full_name: Dellnitz, Michael
  last_name: Dellnitz
- first_name: Julian
  full_name: Eckstein, Julian
  last_name: Eckstein
- first_name: Kathrin
  full_name: Flaßkamp, Kathrin
  last_name: Flaßkamp
- first_name: Patrick
  full_name: Friedel, Patrick
  last_name: Friedel
- first_name: Christian
  full_name: Horenkamp, Christian
  last_name: Horenkamp
- first_name: Ulrich
  full_name: Köhler, Ulrich
  last_name: Köhler
- first_name: Sina
  full_name: Ober-Blöbaum, Sina
  id: '16494'
  last_name: Ober-Blöbaum
- first_name: Sebastian
  full_name: Peitz, Sebastian
  id: '47427'
  last_name: Peitz
  orcid: https://orcid.org/0000-0002-3389-793X
- first_name: Sebastian
  full_name: Tiemeyer, Sebastian
  last_name: Tiemeyer
citation:
  ama: 'Dellnitz M, Eckstein J, Flaßkamp K, et al. Multiobjective Optimal Control
    Methods for the Development of an Intelligent Cruise Control. In: <i>Progress
    in Industrial Mathematics at ECMI 2014 </i>. Cham: Springer International Publishing;
    2017:633-641. doi:<a href="https://doi.org/10.1007/978-3-319-23413-7_87">10.1007/978-3-319-23413-7_87</a>'
  apa: 'Dellnitz, M., Eckstein, J., Flaßkamp, K., Friedel, P., Horenkamp, C., Köhler,
    U., … Tiemeyer, S. (2017). Multiobjective Optimal Control Methods for the Development
    of an Intelligent Cruise Control. In <i>Progress in Industrial Mathematics at
    ECMI 2014 </i> (pp. 633–641). Cham: Springer International Publishing. <a href="https://doi.org/10.1007/978-3-319-23413-7_87">https://doi.org/10.1007/978-3-319-23413-7_87</a>'
  bibtex: '@inproceedings{Dellnitz_Eckstein_Flaßkamp_Friedel_Horenkamp_Köhler_Ober-Blöbaum_Peitz_Tiemeyer_2017,
    place={Cham}, title={Multiobjective Optimal Control Methods for the Development
    of an Intelligent Cruise Control}, DOI={<a href="https://doi.org/10.1007/978-3-319-23413-7_87">10.1007/978-3-319-23413-7_87</a>},
    booktitle={Progress in Industrial Mathematics at ECMI 2014 }, publisher={Springer
    International Publishing}, author={Dellnitz, Michael and Eckstein, Julian and
    Flaßkamp, Kathrin and Friedel, Patrick and Horenkamp, Christian and Köhler, Ulrich
    and Ober-Blöbaum, Sina and Peitz, Sebastian and Tiemeyer, Sebastian}, year={2017},
    pages={633–641} }'
  chicago: 'Dellnitz, Michael, Julian Eckstein, Kathrin Flaßkamp, Patrick Friedel,
    Christian Horenkamp, Ulrich Köhler, Sina Ober-Blöbaum, Sebastian Peitz, and Sebastian
    Tiemeyer. “Multiobjective Optimal Control Methods for the Development of an Intelligent
    Cruise Control.” In <i>Progress in Industrial Mathematics at ECMI 2014 </i>, 633–41.
    Cham: Springer International Publishing, 2017. <a href="https://doi.org/10.1007/978-3-319-23413-7_87">https://doi.org/10.1007/978-3-319-23413-7_87</a>.'
  ieee: M. Dellnitz <i>et al.</i>, “Multiobjective Optimal Control Methods for the
    Development of an Intelligent Cruise Control,” in <i>Progress in Industrial Mathematics
    at ECMI 2014 </i>, 2017, pp. 633–641.
  mla: Dellnitz, Michael, et al. “Multiobjective Optimal Control Methods for the Development
    of an Intelligent Cruise Control.” <i>Progress in Industrial Mathematics at ECMI
    2014 </i>, Springer International Publishing, 2017, pp. 633–41, doi:<a href="https://doi.org/10.1007/978-3-319-23413-7_87">10.1007/978-3-319-23413-7_87</a>.
  short: 'M. Dellnitz, J. Eckstein, K. Flaßkamp, P. Friedel, C. Horenkamp, U. Köhler,
    S. Ober-Blöbaum, S. Peitz, S. Tiemeyer, in: Progress in Industrial Mathematics
    at ECMI 2014 , Springer International Publishing, Cham, 2017, pp. 633–641.'
date_created: 2018-11-27T14:46:52Z
date_updated: 2022-01-06T07:02:47Z
doi: 10.1007/978-3-319-23413-7_87
language:
- iso: eng
page: 633-641
place: Cham
project:
- _id: '52'
  name: Computing Resources Provided by the Paderborn Center for Parallel Computing
publication: 'Progress in Industrial Mathematics at ECMI 2014 '
publication_identifier:
  isbn:
  - '9783319234120'
  - '9783319234137'
  issn:
  - 1612-3956
  - 2198-3283
publication_status: published
publisher: Springer International Publishing
status: public
title: Multiobjective Optimal Control Methods for the Development of an Intelligent
  Cruise Control
type: conference
user_id: '47427'
year: '2017'
...
---
_id: '16579'
author:
- first_name: Michael
  full_name: Dellnitz, Michael
  last_name: Dellnitz
- first_name: Julian
  full_name: Eckstein, Julian
  last_name: Eckstein
- first_name: Kathrin
  full_name: Flaßkamp, Kathrin
  last_name: Flaßkamp
- first_name: Patrick
  full_name: Friedel, Patrick
  last_name: Friedel
- first_name: Christian
  full_name: Horenkamp, Christian
  last_name: Horenkamp
- first_name: Ulrich
  full_name: Köhler, Ulrich
  last_name: Köhler
- first_name: Sina
  full_name: Ober-Blöbaum, Sina
  last_name: Ober-Blöbaum
- first_name: Sebastian
  full_name: Peitz, Sebastian
  last_name: Peitz
- first_name: Sebastian
  full_name: Tiemeyer, Sebastian
  last_name: Tiemeyer
citation:
  ama: 'Dellnitz M, Eckstein J, Flaßkamp K, et al. Multiobjective Optimal Control
    Methods for the Development of an Intelligent Cruise Control. In: <i>Mathematics
    in Industry</i>. Cham; 2016. doi:<a href="https://doi.org/10.1007/978-3-319-23413-7_87">10.1007/978-3-319-23413-7_87</a>'
  apa: Dellnitz, M., Eckstein, J., Flaßkamp, K., Friedel, P., Horenkamp, C., Köhler,
    U., … Tiemeyer, S. (2016). Multiobjective Optimal Control Methods for the Development
    of an Intelligent Cruise Control. In <i>Mathematics in Industry</i>. Cham. <a
    href="https://doi.org/10.1007/978-3-319-23413-7_87">https://doi.org/10.1007/978-3-319-23413-7_87</a>
  bibtex: '@inbook{Dellnitz_Eckstein_Flaßkamp_Friedel_Horenkamp_Köhler_Ober-Blöbaum_Peitz_Tiemeyer_2016,
    place={Cham}, title={Multiobjective Optimal Control Methods for the Development
    of an Intelligent Cruise Control}, DOI={<a href="https://doi.org/10.1007/978-3-319-23413-7_87">10.1007/978-3-319-23413-7_87</a>},
    booktitle={Mathematics in Industry}, author={Dellnitz, Michael and Eckstein, Julian
    and Flaßkamp, Kathrin and Friedel, Patrick and Horenkamp, Christian and Köhler,
    Ulrich and Ober-Blöbaum, Sina and Peitz, Sebastian and Tiemeyer, Sebastian}, year={2016}
    }'
  chicago: Dellnitz, Michael, Julian Eckstein, Kathrin Flaßkamp, Patrick Friedel,
    Christian Horenkamp, Ulrich Köhler, Sina Ober-Blöbaum, Sebastian Peitz, and Sebastian
    Tiemeyer. “Multiobjective Optimal Control Methods for the Development of an Intelligent
    Cruise Control.” In <i>Mathematics in Industry</i>. Cham, 2016. <a href="https://doi.org/10.1007/978-3-319-23413-7_87">https://doi.org/10.1007/978-3-319-23413-7_87</a>.
  ieee: M. Dellnitz <i>et al.</i>, “Multiobjective Optimal Control Methods for the
    Development of an Intelligent Cruise Control,” in <i>Mathematics in Industry</i>,
    Cham, 2016.
  mla: Dellnitz, Michael, et al. “Multiobjective Optimal Control Methods for the Development
    of an Intelligent Cruise Control.” <i>Mathematics in Industry</i>, 2016, doi:<a
    href="https://doi.org/10.1007/978-3-319-23413-7_87">10.1007/978-3-319-23413-7_87</a>.
  short: 'M. Dellnitz, J. Eckstein, K. Flaßkamp, P. Friedel, C. Horenkamp, U. Köhler,
    S. Ober-Blöbaum, S. Peitz, S. Tiemeyer, in: Mathematics in Industry, Cham, 2016.'
date_created: 2020-04-16T05:37:11Z
date_updated: 2022-01-06T06:52:52Z
department:
- _id: '101'
doi: 10.1007/978-3-319-23413-7_87
language:
- iso: eng
place: Cham
publication: Mathematics in Industry
publication_identifier:
  isbn:
  - '9783319234120'
  - '9783319234137'
  issn:
  - 1612-3956
  - 2198-3283
publication_status: published
status: public
title: Multiobjective Optimal Control Methods for the Development of an Intelligent
  Cruise Control
type: book_chapter
user_id: '15701'
year: '2016'
...