Publication detail

Performance Study of a Developed Rule-Based Control Strategy with Use of an ECMS Optimization Control Algorithm on a Plug-In Hybrid Electric Vehicle

UŠIAK, M. BÖHM, M. ŠEBELA, K.

English title

Performance Study of a Developed Rule-Based Control Strategy with Use of an ECMS Optimization Control Algorithm on a Plug-In Hybrid Electric Vehicle

Type

journal article in Scopus

Language

en

Original abstract

Greenhouse gases jeopardize world’s climate. A significant amount of these pollutants is produced by road vehicles, so their producers are forced to reduce their emissions significantly. This means that every car manufacturer is expanding their electrified vehicle range. Fully electric vehicles are the best way for long-term elimination of greenhouse gases production in road transport. However, in the short term it is not possible to switch all vehicles to EVs. Temporary solutions are hybrid electric vehicles, which offer a compromise between conventional and electric vehicles. In addition to the right choice of hybrid powertrain and correct scaling of its components, it is also important to develop a suitable control strategy for its energy management. The main goal of this work is to compare the performance of the rule-based control strategy with the built-in local optimization algorithm ECMS in GT-SUITETM software. ECMS means Equivalent Consumption Minimization Strategy and is based on an optimization of selected control parameters in each time step of the driving cycle simulation. A fuel efficiency improvement is assessed on a selected plug-in hybrid vehicle. Results of WLTC driving cycle simulations in charge sustaining mode (state of charge of the battery at the beginning and at the end of the simulation is the same) shows fuel consumption of 5 l/100km for rule based control strategy and 4.2 l/100km for ECMS algorithm. This means that ECMS can achieve more than 16% improvement for this particular vehicle.

English abstract

Greenhouse gases jeopardize world’s climate. A significant amount of these pollutants is produced by road vehicles, so their producers are forced to reduce their emissions significantly. This means that every car manufacturer is expanding their electrified vehicle range. Fully electric vehicles are the best way for long-term elimination of greenhouse gases production in road transport. However, in the short term it is not possible to switch all vehicles to EVs. Temporary solutions are hybrid electric vehicles, which offer a compromise between conventional and electric vehicles. In addition to the right choice of hybrid powertrain and correct scaling of its components, it is also important to develop a suitable control strategy for its energy management. The main goal of this work is to compare the performance of the rule-based control strategy with the built-in local optimization algorithm ECMS in GT-SUITETM software. ECMS means Equivalent Consumption Minimization Strategy and is based on an optimization of selected control parameters in each time step of the driving cycle simulation. A fuel efficiency improvement is assessed on a selected plug-in hybrid vehicle. Results of WLTC driving cycle simulations in charge sustaining mode (state of charge of the battery at the beginning and at the end of the simulation is the same) shows fuel consumption of 5 l/100km for rule based control strategy and 4.2 l/100km for ECMS algorithm. This means that ECMS can achieve more than 16% improvement for this particular vehicle.

Keywords in English

Hybrid electric vehicle, Energy management, ECMS, Optimization control strategy

Released

18.11.2022

Publisher

SjF STU Bratislava

Location

Bratislava

ISSN

2450-5471

Volume

72

Number

3

Pages from–to

61–70

Pages count

10

BIBTEX


@article{BUT180093,
  author="Michal {Ušiak} and Michael {Böhm} and Kamil {Šebela},
  title="Performance Study of a Developed Rule-Based Control Strategy with Use of an ECMS Optimization Control Algorithm on a Plug-In Hybrid Electric Vehicle",
  year="2022",
  volume="72",
  number="3",
  month="November",
  pages="61--70",
  publisher="SjF STU Bratislava",
  address="Bratislava",
  issn="2450-5471"
}