Planning and reconfigurable control of a fleet of unmanned vehicles for taxi operations in airport environment

The optimization of airport operations has gained increasing interest by the aeronautical community, due to the substantial growth in the number of airport movements (landings and take-offs) experienced in the past decades all over the world. Forecasts have confirmed this trend also for the next decades. The result of the expansion of air traffic is an increasing congestion of airports, especially in taxiways and runways, leading to additional amount of fuel burnt by airplanes during taxi operations, causing additional pollution and costs for airlines. In order to reduce the impact of taxi operations, different solutions have been proposed in literature; the solution which this dissertation refers to uses autonomous electric vehicles to tow airplanes between parking lots and runways. Although several analyses have been proposed in literature, showing the feasibility and the effectiveness of this approach in reducing the environmental impact, at the beginning of the doctoral activity no solutions were proposed, on how to manage the fleet of unmanned vehicles inside the airport environment. Therefore, the research activity has focused on the development of algorithms able to provide pushback tractor (also referred as tugs) autopilots with conflict-free schedules. The main objective of the optimization algorithms is to minimize the tug energy consumption, while performing just-in-time runway operations: departing airplanes are delivered only when they can take-off and the taxi-in phase starts as soon as the aircraft clears the runway and connects to the tractor. Two models, one based on continuous time and one on discrete time evolution, were developed to simulate the taxi phases within the optimization scheme. A piecewise-linear model has also been proposed to evaluate the energy consumed by the tugs during the assigned missions. Furthermore, three optimization algorithms were developed: two hybrid versions of the particle swarm optimization and a tree search heuristic. The following functional requirements for the management algorithm were defined: the optimization model must be easily adapted to different airports with different layout (reconfigurability); the generated schedule must always be conflict-free; and the computational time required to process a time horizon of 1h must be less than 15min. In order to improve its performance, the particle swarm optimization was hybridized with a hill-climb meta-heuristic; a second hybridization was performed by means of the random variable search, an algorithm of the family of the variable neighborhood search. The neighborhood size for the random variable search was considered varying with inverse proportionality to the distance between the actual considered solution and the optimal one found so far. Finally, a tree search heuristic was developed to find the runway sequence, among all the possible sequences of take-offs and landings for a given flight schedule, which can be realized with a series of taxi trajectories that require minimum energy consumption. Given the taxi schedule generated by the aforementioned optimization algorithms a tug dispatch algorithm, assigns a vehicle to each mission. The three optimization schemes and the two mathematical models were tested on several test cases among three airports: the Turin-Caselle airport, the Milan-Malpensa airport, and the Amsterdam airport Schiphol. The cost required to perform the generated schedules using the autonomous tugs was compared to the cost required to perform the taxi using the aircraft engines. The proposed approach resulted always more convenient than the classical one

Optimization and Energy Maximizing Control Systems for Wave Energy Converters

In recent years, we have been witnessing great interest and activity in the field of wave energy converters’ (WECs) development, striving for competitiveness and economic viability via increasing power conversion while decreasing costs and ensuring survivability [...

A Route Selection Problem Applied to Auto-Piloted Aircraft Tugs

The antithetical needs of increasing the air traffic, reducing the air pollutant and noise emissions, jointly with the prominent problem of airport congestion spur to radically innovate the entire ground operation system and airport management. In this scenario, an alternative autonomous system for engine-off taxiing (dispatch towing) attracts the interest of the civil aviation world. Even though structural and regulatory limitations undermine the employment of the already existing push-back tractors to this purpose, they remain the main candidates to accomplish the mission. New technologies are already under investigation to optimize towbarless tractor joints, so as to respond to the structure safety requirements. However, regulation limitations will soon be an issue. In this paper, a software solution for a route selection problem in a discretized airport environment is presented, in the believe that a full-authority control system, including tractors’ selection logic, path planning and mission event sequencing algorithms will possibly meet the regulation requirements. Four different algorithms are implemented and compared: two Hopfield-type neural networks and two algorithms based on graph theory. They compute the shortest path, accounting for restricted airport areas, preferential directions and dynamic obstacles. The computed route checkpoints serve as a reference for the tractor autopilot. Two different missions are analyzed, concerning the towing of departing and arriving aircraft respectively. A single mission consists of three different events, called phases: Phase 1 goes from the actual tractor position (eventually the parking zone) to the selected aircraft (parked or just landed); Phase 2 is the actual engine-off taxi towing; Phase 3 is the tractor return to its own parking zone. Both missions are simulated and results are reported and compared

4D Trajectory Optimization Satisfying Waypoint and No-Fly Zone Constraints

This paper presents a model of an innovative Flight Management System (FMS) which is purposely developed to control a commercial airliner along an optimized 4-Dimensional Trajectory (4DT), respecting time and path constraints, while avoiding No-Fly Zones (NFZ). The optimum, expressed in terms of minimum fuel consumption, is optained by solving an Optimization Control Problem (OCP) by means of the Chebyshev Pseudospectral numerical direct collocation scheme. The OCP trajectory solution is a discrete sequence of optimal aircraft states, which guarantee the minimum-fuel trip between two waypoints. With the aim of controlling the aircraft along lateral, vertical and longitudinal axis, and in order to respect NFZ and waypoints constraints along the optimum 4DT, different guidance navigation and control techniques can be implemented. The effectiveness of the algorithms is evaluated through simulations performed in the Multipurpose Aircraft Simulation Laboratory (MASLab), on a Boeing 747-100 model, equipped with a complete Automatic Flight Control System (AFCS) suite

Fast nonlinear Froude–Krylov force calculation for prismatic floating platforms: a wave energy conversion application case

AbstractComputationally fast and accurate mathematical models are essential for effective design, optimization, and control of wave energy converters. However, the energy-maximising control strategy, essential for reaching economic viability, inevitably leads to the violation of linearising assumptions, so the common linear models become unreliable and potentially unrealistic. Partially nonlinear models based on the computation of Froude–Krylov forces with respect to the instantaneous wetted surface are promising and popular alternatives, but they are still too slow when floaters of arbitrary complexity are considered; in fact, mesh-based spatial discretisation, required by such geometries, becomes the computational bottle-neck, leading to simulations 2 orders of magnitude slower than real-time, unaffordable for extensive iterative optimizations. This paper proposes an alternative analytical approach for the subset of prismatic floating platforms, common in the wave energy field, ensuring computations 2 orders of magnitude faster than real-time, hence 4 orders of magnitude faster than state-of-the-art mesh-based approaches. The nonlinear Froude–Krylov model is used to investigate the nonlinear hydrodynamics of the floater of a pitching wave energy converter, extracting energy either from pitch or from an inertially coupled internal degree of freedom, especially highlighting the impact of state constraints, controlled/uncontrolled conditions, and impact on control parameters' optimization, sensitivity and effectiveness

A review of numerical modelling and optimisation of the floating support structure for offshore wind turbines

AbstractCompared to onshore wind power, floating offshore wind power is a promising renewable energy source due to higher wind speeds and larger suitable available areas. However, costs are still too high compared to onshore wind power. In general, the economic viability of offshore wind technology decreases with greater water depth and distance from shore. Floating wind platforms are more competitive compared to fixed offshore structures above a certain water depth, but there is still great variety and no clear design convergence. Therefore, optimisation of the floating support structure in the preliminary phase of the design process is still of great importance, often up to personal experience and sensibility. It is fundamental that a suitable optimisation approach is chosen to obtain meaningful results at early development stages. This review provides a comparative overview of the methods, numerical tools and optimisation approaches that can be used with respect to the conceptual design of the support structure for Floating offshore wind turbines (FOWT) attempting to detail the limitations preventing the convergence to an optimal floating support structure. This work is intended to be as a reference for any researcher and developer that would like to optimise the support platform for FOWT

Estimating the Cost of Wave Energy Converters at an Early Design Stage: A Bottom-Up Approach

The role of ocean energy is expected to grow rapidly in the coming years, and techno-economic analysis will play a crucial role. Nowadays, despite strong assumptions, the vast majority of studies model costs using a top-down approach (the TdA) that leads to an unrepresentative economic model. WEC developers usually go through the the TdA approach because more detailed cost data are not available at an earlier design stage. At a very advanced design stage, some studies have also proposed techno-economic optimisation based on the bottom-up approach (BuA). This entails that the detailed cost metrics presented in the literature are very specific to the WEC type (hence not applicable to other cases) or unrepresentative. This lack of easily accessible detailed cost functions in the current state of the art leads to ineffective optimisations at an earlier stage of WEC development. In this paper, a BuA for WECs is proposed that can be used for techno-economic optimisation at the early design stage. To achieve this goal, cost functions of most common components in the WEC field are retrieved from the literature, exposed, and critically compared. The large number of components considered allows the results of this work to be applied to a vast pool of WECs. The novelty of the presented cost functions is their parameterization with respect to the technological specifications, which already enables their adoption in the design optimisation phase. With the goal of quantifying the results and critically discuss the differences between the TdA and the BuA, the developed methodology and cost functions are applied to a case study and specifically adopted for the calculation of the capital cost of PeWEC (pendulum wave energy converter). In addition, a hybrid approach (HyA) is presented and discussed as an intermediate approach between the TdA and the BdA. Results are compared in terms of capital expenditure (CapEx) and pie cost distribution: the impact of adopting different cost metrics is discussed, highlighting the role that reliable cost functions can have on early stage technology development. This paper proposes more than 50 cost functions for WEC components. Referring to the case study, it is shown that while the total cost differs only slightly (11%), the pie distribution changes by up to 22%. Mooring system and power take-off are the cost items where the TdA and the HyA differ more from the BuA cost estimate

Viscous Damping Identification for a Wave Energy Converter Using CFD-URANS Simulations

During the optimization phase of a wave energy converter (WEC), it is essential to be able to rely on a model that is both fast and accurate. In this regard, Computational Fluid Dynamic (CFD) with Reynolds Averaged Navier–Stokes (RANS) approach is not suitable for optimization studies, given its computational cost, while methods based on potential theory are fast but not accurate enough. A good compromise can be found in boundary element methods (BEMs), based on potential theory, with the addition of non-linearities. This paper deals with the identification of viscous parameters to account for such non-linearities, based on CFD-Unsteady RANS (URANS) analysis. The work proposes two different methodologies to identify the viscous damping along the rotational degree of freedom (DOF) of pitch and roll: The first solely involves the outcomes of the CFD simulations, computing the viscous damping coefficients through the logarithmic decrement method, the second approach solves the Cummins’ equation of motion, via a Runge-Kutta scheme, selecting the damping coefficients that minimize the difference with CFD time series. The viscous damping is mostly linear for pitch and quadratic for roll, given the shape of the WEC analysed

Unsteady RANS CFD Simulations of Sailboat’s Hull and Comparison with Full-Scale Test

The hydrodynamic investigation of a hull’s performance is a key aspect when designing a new prototype, especially when it comes to a competitive/racing environment. This paper purports to perform a fully nonlinear unsteady Reynolds Averaged Navier-Stokes (RANS) simulation to predict the motion and hydrodynamic resistance of a sailboat, thus creating a reliable tool for designing a new hull or refining the design of an existing one. A comprehensive range of speeds is explored, and results are validated with hydrodynamic full-scale tests, conducted in the towing tank facility at University of Naples Federico II, Italy. In particular, this work deals with numerical ventilation, which is a typical issue occurring when modeling a hull; a simple and effective solution is here proposed and investigated, based on the phase-interaction substitution procedure. Results of the computational fluid dynamic (CFD) campaign agree with the experimental fluid dynamic (EFD) within a 2% margin

Techno-Economic Optimisation for a Wave Energy Converter via Genetic Algorithm

Although sea and ocean waves have been widely acknowledged to have the potential of providing sustainable and renewable energy, the emergence of a self-sufficient and mature industry is still lacking. An essential condition for reaching economic viability is to minimise the cost of electricity, as opposed to simply maximising the converted energy at the early design stages. One of the tools empowering developers to follow such a virtuous design pathway is the techno-economic optimisation. The purpose of this paper is to perform a holistic optimisation of the PeWEC (pendulum wave energy converter), which is a pitching platform converting energy from the oscillation of a pendulum contained in a sealed hull. Optimised parameters comprise shape; dimensions; mass properties and ballast; power take-off control torque and constraints; number and characteristics of the pendulum; and other subcomponents. Cost functions are included and the objective function is the ratio between the delivered power and the capital expenditure. Due to its ability to effectively deal with a large multi-dimensional design space, a genetic algorithm is implemented, with a specific modification to handle unfeasible design candidate and improve convergence. Results show that the device minimising the cost of energy and the one maximising the capture width ratio are substantially different, so the economically-oriented metric should be preferred