Co-optimization of total running time, timetables, driving strategies and energy management strategies for fuel cell hybrid trains

Peng, Hujun; Chen, Yuejie; Chen, Zhu; Li, Jianxiang; Deng, Kai; Thul, Andreas; Löwenstein, Lars; Hameyer, Kay

doi:10.1016/j.etran.2021.100130

Cited by 22 publications

(12 citation statements)

References 31 publications

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“…The modeling parameters of FCHT in this paper are listed in Table 3 with references to the design proposed in [29]. The global optimizer used in this study to solve the MILP model is GUROBI9.0 [35].…”

Section: Resultsmentioning

confidence: 99%

“…However, it can be seen from the above research that the existing research on cooptimization mainly adopts dynamic programming [27][28][29] and convex optimization [30]. Different from the existing methods of co-optimization, a new method is proposed in this paper to solve the co-optimization problem, and the hydrogen-saving mechanism of a fuel cell train is studied by using the co-optimization model.…”

Section: Introductionmentioning

confidence: 99%

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Net Hydrogen Consumption Minimization of Fuel Cell Hybrid Trains Using a Time-Based Co-Optimization Model

Meng

Zhang

et al. 2022

Energies

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With increasing concerns on transportation decarbonization, fuel cell hybrid trains (FCHTs) attract many attentions due to their zero carbon emissions during operation. Since fuel cells alone cannot recover the regenerative braking energy (RBE), energy storage devices (ESDs) are commonly deployed for the recovery of RBE and provide extra traction power to improve the energy efficiency. This paper aims to minimize the net hydrogen consumption (NHC) by co-optimizing both train speed trajectory and onboard energy management using a time-based mixed integer linear programming (MILP) model. In the case with the constraints of speed limits and gradients, the NHC of co-optimization reduces by 6.4% compared to the result obtained by the sequential optimization, which optimizes train control strategies first and then the energy management. Additionally, the relationship between NHC and employed ESD capacity is studied and it is found that with the increase of ESD capacity, the NHC can be reduced by up to 30% in a typical route in urban railway transit. The study shows that ESDs play an important role for FCHTs in reducing NHC, and the proposed time-based co-optimization model can maximize the energy-saving benefits for such emerging traction systems with hybrid energy sources, including both fuel cells and ESD.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Net Hydrogen Consumption Minimization of Fuel Cell Hybrid Trains Using a Time-Based Co-Optimization Model

Meng

Zhang

et al. 2022

Energies

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“…Such a solution has made it possible to obtain an overall system efficiency of about 80%, while the efficiency of the cell itself was between just 45% and 65% [23]. The constant pressure to reduce the consumption of energy and fuel (including hydrogen) leads to optimization works in the field of eco-driving of such drives [6,18], and the potential use of ammonia to power SOFC cells [2].…”

Section: Fuel Cells In Rail Vehiclesmentioning

confidence: 99%

Energy flow analysis based on a simulated drive of a hybrid locomotive powered by fuel cells

Pielecha¹,

Dimitrov²,

Mihaylov³

2022

Rail Vehicles/Pojazdy Szynowe

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Implementation of hybrid drives in rail vehicles is a solution aimed at limiingt the negative environmental impact of transport. The use of fuel cell systems is a contemporary trend in the development of locomotives. The paper presents an energy flow analysis in a hybrid locomotive powered using fuel cells. The parallel hybrid drive system consisted of fuel cells, batteries and an electric motor. The simulations and analyzes were performed with the use of AVL Cruise M software. A simulated route, with a length of approximately 300 km, was used as basis for the analasys, taking into account a typical speed profile of a locomotive in passenger traffic. The energy flow and consumption values were estimated, and mean hydrogen consumption values were determined.

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“…Hong et al proposed an EMS technique dependent on a dynamic following coefficient (ECMS-DFC), which could keep up with the entire effectiveness of a power module cross-breed framework above 44% while running it into the scaled down, real-drive pattern of the locomotive [18]. Peng et al proposed a forward dynamic programming-based algorithm and a rule-based online strategy for EMS, which helps facilitate power distribution between the battery and the fuel cell [19]. The optimization-based methodology for using particle swarm optimization for a fuel cell battery hybrid locomotive is proposed in [20].…”

Section: Introductionmentioning

confidence: 99%

Fuel Cell Hybrid Locomotive with Modified Fuzzy Logic Based Energy Management System

Kaleybar

Brenna

et al. 2022

Sustainability

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As one of the most environmentally friendly energy sources today, fuel cells have become the focus of research in countries around the world, especially in the electric transportation field. This paper mainly studies the modeling of fuel cell hybrid locomotives (FCHL) including fuel cells, batteries, motors, and energy management systems. To increase the operating efficiency and improve the performance of FCHL, a modified fuzzy logic-based energy management system (MFL-EMS) is proposed and compared with the traditional power flow energy management system (PF-EMS). Meanwhile, a modified fuel cell hybrid power system model for locomotives is proposed, taking into account the traction motor features that, compared with a simplified controlled source load, can directly reflect the status of the locomotive running speed and the output power of the traction motor load. The proposed system parameters and configurations are determined by combining the characteristics of power and energy density, response characteristics, and charging/discharging characteristics of fuel cells and batteries. The precise simulation results revealed that adopting the proposed MFL-EMS in comparison to the traditional PF-EMS, reduced the hydrogen consumption by 2.943%. Comparing the battery output voltage, it is confirmed that with MFL-EMS it tends to be steeper than the one with PF-EMS, showing the proposed strategy’s robustness. Overall, the obtained results revealed an improved performance in terms of power distribution as well as SOC, which means less hydrogen consumption and therefore a more economical solution.

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Co-optimization of total running time, timetables, driving strategies and energy management strategies for fuel cell hybrid trains

Cited by 22 publications

References 31 publications

Net Hydrogen Consumption Minimization of Fuel Cell Hybrid Trains Using a Time-Based Co-Optimization Model

Net Hydrogen Consumption Minimization of Fuel Cell Hybrid Trains Using a Time-Based Co-Optimization Model

Energy flow analysis based on a simulated drive of a hybrid locomotive powered by fuel cells

Fuel Cell Hybrid Locomotive with Modified Fuzzy Logic Based Energy Management System

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