no code implementations • 3 May 2024 • Fabio Paparella, Pim Labee, Steven Wilkins, Theo Hofman, Soora Rasouli, Mauro Salazar
This paper presents optimization models for electric Mobility-as-a-Service systems, whereby electric vehicles not only provide on-demand mobility, but also perform charging and Vehicle-to-Grid (V2G) operations to enhance the fleet operator profitability.
no code implementations • 14 Apr 2024 • Finn Vehlhaber, Mauro Salazar
This paper presents a Model Predictive Control (MPC) scheme for flight scheduling and energy management of electric aviation networks, where electric aircraft transport passengers between electrified airports equipped with sustainable energy sources and battery storage, with the goal of minimizing grid dependency.
no code implementations • 30 Mar 2024 • Mauro Salazar, Sara Betancur Giraldo, Fabio Paparella, Leonardo Pedroso
Our results show that it is possible to reach an operation that is on average fully fair at the cost of a slight travel time increase compared to a minimum-travel-time solution.
no code implementations • 11 Mar 2024 • Fabio Paparella, Karni Chauhan, Luc Koenders, Theo Hofman, Mauro Salazar
Our results indicate that jointly optimizing the charging infrastructure placement allows to decrease overall energy consumption of the fleet and vehicle hours traveled by approximately 1% compared to an heuristic placement.
no code implementations • 11 Mar 2024 • Jorn van Kampen, Mauro Moriggi, Francesco Braghin, Mauro Salazar
This paper presents model predictive control strategies for battery electric endurance race cars accounting for interactions with the competitors.
1 code implementation • 10 Nov 2023 • Fabio Paparella, Leonardo Pedroso, Theo Hofman, Mauro Salazar
The resulting problem structure remains identical to a standard network flow model, a linear problem, which can be solved in polynomial time for a given ride-pooling request assignment.
no code implementations • 6 Nov 2023 • Camiel Cartignij, Mauro Salazar
This paper presents a framework to jointly optimize the design and control of an electric race car equipped with a multiple-gear transmission, specifically accounting for the discrete gearshift dynamics.
1 code implementation • 6 Nov 2023 • Fabio Paparella, Leonardo Pedroso, Theo Hofman, Mauro Salazar
This paper presents a modeling and optimization framework to study congestion-aware ride-pooling Autonomous Mobility-on-Demand (AMoD) systems, whereby self-driving robotaxis are providing on-demand mobility, and users headed in the same direction share the same vehicle for part of their journey.
no code implementations • 3 Oct 2023 • Juan Pablo Bertucci, Theo Hofman, Mauro Salazar
For a case study in the Netherlands, we assess the impact of different parameters in our optimization problem, specifically, the allowed deviation from existing operations with conventional diesel trucks and the cost factor for daily peak energy usage.
no code implementations • 21 Sep 2023 • Fabio Paparella, Theo Hofman, Mauro Salazar
To this end, this paper presents a framework to jointly optimize the fleet design in terms of battery capacity and number of vehicles, and the operational strategies of the E-AMoD system, with the aim of maximizing the operator's total profit.
no code implementations • 18 Sep 2023 • Finn Vehlhaber, Mauro Salazar
Electric airplanes are expected to take to the skies soon, finding first use cases in small networks within hardly accessible areas, such as island communities.
no code implementations • 24 Jul 2023 • Olaf Borsboom, Martijn Lokker, Mauro Salazar, Theo Hofman
We encapsulate this motor model in a vehicle model together with the transmission, simulate a candidate design on a drive cycle, and find an optimum through a Bayesian optimization solver.
no code implementations • 8 Jun 2023 • Jorn van Kampen, Mauro Salazar, Theo Hofman
This paper presents a modeling framework to optimize the two-dimensional placement of powertrain elements inside the vehicle, explicitly accounting for the rotation, relative placement and alignment.
no code implementations • 30 May 2023 • Fabio Paparella, Theo Hofman, Mauro Salazar
This paper studies mobility systems that incorporate a substantial solar energy component, generated not only on the ground, but also through solar roofs installed on vehicles, directly covering a portion of their energy consumption.
no code implementations • 29 Mar 2023 • Leonardo Pedroso, W. P. M. H., Heemels, Mauro Salazar
Second, we formulate the pricing design problem for each arc to achieve the societally optimal aggregate flows, and reformulate it so that it can be solved with gradient-free optimization methods.
no code implementations • 27 Nov 2022 • David van de Sanden, Maarten Schoukens, Mauro Salazar
Our numerical results show that the proposed data-driven pricing scheme can effectively align the users' flows with the system optimum, significantly reducing the societal costs with respect to the uncontrolled flows (by about 15% and 25% depending on the scenario), and respond to environmental changes in a robust and efficient manner.
no code implementations • 22 Nov 2022 • Fabio Paparella, Karni Chauhan, Theo Hofman, Mauro Salazar
The advent of vehicle autonomy, connectivity and electric powertrains is expected to enable the deployment of Autonomous Mobility-on-Demand systems.
no code implementations • 24 Oct 2022 • Olaf Borsboom, Thijs de Mooy, Mauro Salazar, Theo Hofman
This paper introduces a framework to systematically optimize the control and design of an electric vehicle transmission, connecting powertrain sizing studies to detailed gearbox design methods.
no code implementations • 13 Apr 2022 • Olaf Borsboom, Mauro Salazar, Theo Hofman
We also identify models of the remaining components of the powertrain, namely a battery and a fixed-gear transmission.
no code implementations • 13 Dec 2021 • Sander Tonkens, Paul de Klaver, Mauro Salazar
In this paper, we present an optimization framework to address the dynamic double-dose vaccine allocation problem whereby the available vaccine doses must be administered to different age-groups to minimize specific societal objectives.
no code implementations • 15 Nov 2021 • Mouleeswar Konda, Theo Hofman, Mauro Salazar
This paper presents a modeling and optimization framework to minimize the energy consumption of a fully electric powertrain by optimizing its design and control strategies whilst explicitly accounting for the thermal behavior of the Electric Motor (EM).
no code implementations • 10 Nov 2021 • Jorn van Kampen, Thomas Herrmann, Mauro Salazar
Thereby, the lower level computes the minimum-stint-time Powertrain Operation (PO) for a given battery energy budget and stint length, whilst the upper level leverages that information to jointly optimize the stint length, charge time and number of pit stops, in order to maximize the driven distance in the course of a fixed-time endurance race.
no code implementations • 8 Nov 2021 • Stan Broere, Jorn van Kampen, Mauro Salazar
This paper presents a convex optimization framework to compute the minimum-lap-time control strategies of all-wheel drive (AWD) battery electric race cars, accounting for the grip limitations of the individual tyres.
no code implementations • 13 Oct 2021 • Canqi Yao, Shibo Chen, Mauro Salazar, Zaiyue Yang
Specifically, we first devise a bi-level model whereby the fleet operator optimizes the routes and charging schedules of the fleet jointly with an incentive rate to reimburse the delivery delays experienced by the customers.
no code implementations • 1 Jul 2021 • Justin Luke, Mauro Salazar, Ram Rajagopal, Marco Pavone
Charging infrastructure is the coupling link between power and transportation networks, thus determining charging station siting is necessary for planning of power and transportation systems.
no code implementations • 11 May 2021 • Juriaan van den Hurk, Mauro Salazar
This paper presents models and optimization algorithms to jointly optimize the design and control of the transmission of electric vehicles equipped with one central electric motor (EM).
no code implementations • 20 Apr 2021 • Olaf Korzilius, Olaf Borsboom, Theo Hofman, Mauro Salazar
This paper presents a modeling and optimization framework to design battery electric micromobility vehicles, minimizing their total cost of ownership (TCO).
no code implementations • 23 Nov 2020 • Mauro Salazar, Dario Paccagnan, Andrea Agazzi, W. P. M. H., Heemels
In this paper we address this question within a repeated game framework and propose a fair incentive mechanism based on artificial currencies that routes selfish agents in a system-optimal fashion, while accounting for their temporal preferences.