An eco-friendly aircraft taxiing approach with collision and conflict avoidance

Soltani, Mojdeh; Ahmadi, Sobhan; Akgündüz, Ali; Bhuiyan, Nadia

doi:10.1016/j.trc.2020.102872

Cited by 23 publications

(10 citation statements)

References 28 publications

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“…Recharging is required only during the night, when no more towing tasks need to be performed. This protocol has been used in Soltani et al [7].…”

Section: Etv Battery Charging Protocolmentioning

confidence: 99%

“…ETV fleet management optimization has been addressed scarcely, and only with simple battery recharging protocols. For instance, in Soltani et al [7] the authors consider an ETV fleet where each vehicle has to be assigned to a subset of flights from a given flight schedule such that the environmental impact of the ETV fleet is maximized. The authors consider a charging protocol where ETVs can only recharge during the night.…”

Section: Introductionmentioning

confidence: 99%

“…We illustrate our approach for a day of operations at Amsterdam Airport Schiphol, where we analyze the impact of the ETV battery size and used charging protocol. We compare our preemptive charging protocol with the ones used in Soltani et al [7] and in Van Baaren and Roling [8]. The flight schedule from the 14th of December of 2019 is used, where 750 flights are considered eligible to be towed.…”

Section: Introductionmentioning

confidence: 99%

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Analyzing the impact of battery capacity and charging protocols on the dispatchment of electric towing vehicles at a large airport

Oosterom

Mitici

2022

AIAA AVIATION 2022 Forum

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The aviation industry aims for net-zero emissions by 2050. In this line, achieving climateneutral ground operations is one of the first objectives. Electric vehicles that tow aircraft during taxiing are a promising technology to achieve climate-neutral ground operations. In this paper, we consider the dispatching of electric towing vehicles at an airport. We study the impact of the maximum battery capacity of these vehicles and the battery recharging protocols, on the total number of electric towing vehicles required at an airport. We propose a mixed-integer linear program to determine the size of the fleet of electric towing vehicles under various battery capacities and various battery recharging protocols. We illustrate our model for one day of operations at Amsterdam Airport Schiphol. The results show that 41, 29, and 24 ETVs are required to tow all aircraft when batteries capacities of 100 kWh, 320 kWh, and 500 kWh are considered, respectively. Compared with the best performing approach existing in literature, our model reduces the required size of the fleet of electric towing vehicles by 27% when considering a nominal battery size of 320 kWh.

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“…Recharging is required only during the night, when no more towing tasks need to be performed. This protocol has been used in Soltani et al [7].…”

Section: Etv Battery Charging Protocolmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Analyzing the impact of battery capacity and charging protocols on the dispatchment of electric towing vehicles at a large airport

Oosterom

Mitici

2022

AIAA AVIATION 2022 Forum

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“…Many publications also address ecological concerns and the minimization of negative impacts on the natural environment, even during the aircraft design stage (Parolin et al, 2021). In this context, decarbonisation of air transport (Klöwer et al, 2020;Chen et al, 2020;Andrych-Zalewska et al, 2023) and the reduction of fuel consumption during flight (Soltani et al, 2020;Ziółkowski et al, 2022) are extensively analysed. Selected publications focus on the assessment of aircraft delays (Yu et al, 2019;Gui et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

A Mathematical Model for Identifying Military Training Flights

Borucka,

Jabłoński,

Patrejko

et al. 2024

Aviation

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The main tasks of the Training Air Base concern the practical training of cadets in piloting techniques as well as maintaining and improving the piloting skills of the instructors. It is essential to maintain the infrastructure of the airfield and the Base as a whole ready for operation. This allows for fulfilling the fundamental mission of such military units, which is to provide effective operations for the defence of the state. Therefore, measures to support and improve the operation of such military facilities are extremely important and also became the genesis of this article. It analyses and evaluates the number of flights carried out over seven years (2016–2022) at the studied training base using mathematical modelling, allowing to assess the variability of the studied series. The phase trends method was used for this purpose, preceded by a seasonality study. It allowed the identification of periods in which the number of flights performed varies significantly. Such knowledge enables better regulation of the airport’s operation, adjustment of activities to the needs, and the determination of further directions for airport development and the justification of potential investments. An additional value of the article is the presentation of a mathematical modelling method specifically designed for seasonal time series, along with their diagnostics. It also provides an opportunity for other institutions to carry out tasks while upholding the highest standards.

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“…The experimental results showed that this method could further reduce the taxiing cost without increasing the computation time. Mojdeh [11] proposed a hybrid taxiing method where part of the taxiing procedure was performed by an electric trailer to reduce carbon emissions and avoid taxiing conflicts. An economic analysis was performed for the use of electric trailers.…”

Section: Introductionmentioning

confidence: 99%

Aircraft Taxi Path Optimization Considering Environmental Impacts Based on a Bilevel Spatial–Temporal Optimization Model

Chen,

Quan,

2024

Energies

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Aircraft taxiing emissions are the main source of carbon dioxide and other pollutant gas emissions during airport ground operations. It is crucial to optimize aircraft taxiing from both spatial and temporal perspectives to improve airport operation efficiency and reduce aviation emissions. In this paper, a bilevel spatial and temporal optimization model of aircraft taxiing is constructed. The upper-level model optimizes the aircraft taxiing path, and the lower-level model optimizes the taxiing start time of the aircraft. By the iterative optimization of the upper- and lower-level interactions, the aviation fuel consumption, flight waiting time, and number of taxiing conflicts are reduced. To improve the calculation accuracy, the depth-first search algorithm is utilized to generate the set of available paths for aircraft during the model solution process, and a model solution method based on the genetic algorithm is constructed. Simulation experiments using Tianjin Binhai International Airport as the research object show that adopting the waiting taxiing strategy can effectively avoid taxiing conflicts and reduce aviation fuel consumption by 753.18 kg and 188.84 kg compared to the available path sets generated using Dijkstra’s algorithm and those created manually based on experience, respectively. Conversely, adopting an immediate taxi-out strategy caused 54 taxiing conflicts and increased aviation fuel consumption by 49.44 kg. These results can provide safe and environmentally friendly taxiing strategies for the sustainable development of the air transportation industry.

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An eco-friendly aircraft taxiing approach with collision and conflict avoidance

Cited by 23 publications

References 28 publications

Analyzing the impact of battery capacity and charging protocols on the dispatchment of electric towing vehicles at a large airport

Analyzing the impact of battery capacity and charging protocols on the dispatchment of electric towing vehicles at a large airport

A Mathematical Model for Identifying Military Training Flights

Aircraft Taxi Path Optimization Considering Environmental Impacts Based on a Bilevel Spatial–Temporal Optimization Model

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