Fuel-optimal combined driving strategy and energy management for a parallel hybrid electric railway vehicle

Leska, Maik; Aschemann, Harald

doi:10.1109/mmar.2015.7284037

Cited by 4 publications

(4 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Based on the known duty cycles, the sequence of operating modes can be computed completely off-line. Moreover, also a fuel-optimal combined driving strategy and energy management can be determined using dynamic programming (see Leska and Aschemann, 2015).…”

Section: Introductionmentioning

confidence: 99%

Comparative Calculation of the Fuel–Optimal Operating Strategy for Diesel Hybrid Railway Vehicles

Leska

Aschemann

Melzer

et al. 2017

International Journal of Applied Mathematics and Computer Science

Self Cite

View full text Add to dashboard Cite

In contrast to road-based traffic, the track as well as the corresponding duty cycle for railways are known beforehand, which represents a great advantage during the development of operating strategies for hybrid vehicles. Hence the benefits of hybrid vehicles regarding the fuel consumption can be exploited by means of an off-line optimisation. In this article, the fuel-optimal operating strategy is calculated for one specified track using two hybrid railway vehicles with different kinds of energy storage systems: on the one hand, a lithium-ion battery (high-energy storage) and, on the other, a double layer capacitor (high-power storage). For this purpose, control-oriented simulation models are developed for each architecture addressing the main effects contributing to the longitudinal dynamics of the power train. Based on these simulation models, the fuel-optimal operating strategy is calculated by two different approaches: Bellman’s dynamic programming, a wellknown approach in this field, and an innovative sensitivity-based optimisation.

show abstract

Section: Introductionmentioning

confidence: 99%

Comparative Calculation of the Fuel–Optimal Operating Strategy for Diesel Hybrid Railway Vehicles

Leska

Aschemann

Melzer

et al. 2017

International Journal of Applied Mathematics and Computer Science

Self Cite

View full text Add to dashboard Cite

show abstract

“…Those strategies are normally non-causal and, therefore, process information about the whole drive cycle. The optimal PMAs are divided into numerical methods such as dynamic programming (DP) and analytical approaches, like Pontryagins minimum principle [11,18,19]. DP enables to find a global optimum but is not real-time capable and, therefore, frequently used as benchmark PMA.…”

Section: Classification Of Power Management Algorithmsmentioning

confidence: 99%

“…Often dynamic programming (DP) algorithms are used to optimize the velocity trajectory of hybrid vehicles [19,25]. Due to the fact that DP requires a high computational power, they are not real-time capable.…”

Section: Drive Strategymentioning

confidence: 99%

A Causal and Real-Time Capable Power Management Algorithm for Off-Highway Hybrid Propulsion Systems

Schalk

Aschemann

2016

Energies

Self Cite

View full text Add to dashboard Cite

Hybrid propulsion systems allow for a reduction of fuel consumption and pollutant emissions of future off-highway applications. A challenging aspect of a hybridization is the larger number of system components that further increases both the complexity and the diversification of such systems. Hence, beside a standardization on the hardware side for off-highway systems, a high flexibility and modularity of the control schemes is required to employ them in as many different applications as possible. In this paper, a causal optimization-based power management algorithm is introduced to control the power split between engine and electric machine in a hybrid powertrain. The algorithm optimizes the power split to achieve the maximum power supply efficiency and, thereby, considers the energy cost for maintaining the battery charge. Furthermore, the power management provides an optional function to control the battery state of charge in such a way that a target value is attained. In a simulation case study, the potential and the benefits of the proposed power management for the hybrid powertrain-aiming at a reduction of the fuel consumption of a DMU (diesel multiple unit train) operated on a representative track-will be shown.

show abstract

“…Dynamic programming (DP), as a global optimization method, is widely used in EMS optimization for hybrid railway vehicles [37][38][39]. It was also used in deriving a fuel-optimal combined driving and energy management strategy [40]. Although DP allows for deriving a globally optimal EMS, it is mainly employed for off-line controller optimization, with several drawbacks hindering its real-time applications.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Hybrid and Plug-In Hybrid Alternative Propulsion Systems for Regional Diesel-Electric Multiple Unit Trains

2021

View full text Add to dashboard Cite

This paper presents a simulation-based analysis of hybrid and plug-in hybrid propulsion system concepts for diesel-electric multiple unit regional railway vehicles. These alternative concepts primarily aim to remove emissions in terminal stops with longer stabling periods, with additional benefits reflected in the reduction of overall fuel consumption, produced emissions, and monetary costs. The alternative systems behavior is modeled using a backward-looking quasi-static simulation approach, with the implemented energy management strategy based on a finite state machine control. A comparative assessment of alternative propulsion systems is carried out in a case study of a selected regional railway line operated by Arriva, the largest regional railway undertaking in the Netherlands. The conversion of a standard diesel-electric multiple unit vehicle, currently operating on the network, demonstrated a potential GHG reduction of 9.43–56.92% and an energy cost reduction of 9.69–55.46%, depending on the type of service (express or stopping), energy storage technology selection (lithium-ion battery or double-layer capacitor), electricity production (green or grey electricity), and charging facilities configuration (charging in terminal stations with or without additional charging possibility during short intermediate stops) used. As part of a bigger project aiming to identify optimal transitional solutions towards emissions-free trains, the outcomes of this study will help in the future fleet planning.

show abstract

Fuel-optimal combined driving strategy and energy management for a parallel hybrid electric railway vehicle

Cited by 4 publications

References 15 publications

Comparative Calculation of the Fuel–Optimal Operating Strategy for Diesel Hybrid Railway Vehicles

Comparative Calculation of the Fuel–Optimal Operating Strategy for Diesel Hybrid Railway Vehicles

A Causal and Real-Time Capable Power Management Algorithm for Off-Highway Hybrid Propulsion Systems

Analysis of Hybrid and Plug-In Hybrid Alternative Propulsion Systems for Regional Diesel-Electric Multiple Unit Trains

Contact Info

Product

Resources

About