| 1. |
- Kehoe, Laura, et al.
(författare)
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Make EU trade with Brazil sustainable
- 2019
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 364:6438, s. 341-
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 2. |
- Basso, Rafael, 1979, et al.
(författare)
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Dynamic Stochastic Electric Vehicle Routing with Safe Reinforcement Learning
- 2022
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Ingår i: Transportation Research Part E: Logistics and Transportation Review. - : Elsevier BV. - 1366-5545. ; 157:157
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Tidskriftsartikel (refereegranskat)abstract
- Dynamic routing of electric commercial vehicles can be a challenging problem since besides the uncertainty of energy consumption there are also random customer requests. This paper introduces the Dynamic Stochastic Electric Vehicle Routing Problem (DS-EVRP). A Safe Reinforcement Learning method is proposed for solving the problem. The objective is to minimize expected energy consumption in a safe way, which means also minimizing the risk of battery depletion while en route by planning charging whenever necessary. The key idea is to learn offline about the stochastic customer requests and energy consumption using Monte Carlo simulations, to be able to plan the route predictively and safely online. The method is evaluated using simulations based on energy consumption data from a realistic traffic model for the city of Luxembourg and a high-fidelity vehicle model. The results indicate that it is possible to save energy at the same time maintaining reliability by planning the routes and charging in an anticipative way. The proposed method has the potential to improve transport operations with electric commercial vehicles capitalizing on their environmental benefits
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| 3. |
- Cavalca, Filippo, et al.
(författare)
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Nature and Distribution of Stable Subsurface Oxygen in Copper Electrodes During Electrochemical CO2 Reduction
- 2017
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Ingår i: The Journal of Physical Chemistry C. - : American Chemical Society (ACS). - 1932-7447 .- 1932-7455. ; 121:45, s. 25003-25009
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Tidskriftsartikel (refereegranskat)abstract
- Oxide-derived copper (OD-Cu) electrodes exhibit higher activity than pristine copper during the carbon dioxide reduction reaction (CO2RR) and higher selectivity toward ethylene. The presence of residual subsurface oxygen in OD-Cu has been proposed to be responsible for such improvements, although its stability under the reductive CO2RR conditions remains unclear. This work sheds light on the nature and stability of subsurface oxygen. Our spectroscopic results show that oxygen is primarily concentrated in an amorphous 1-2 nm thick layer within the Cu subsurface, confirming that subsurface oxygen is stable during CO2RR for up to 1 h at -1.15 V vs RHE. Besides, it is associated with a high density of defects in the OD-Cu structure. We propose that both low coordination of the amorphous OD-Cu surface and the presence of subsurface oxygen that withdraws charge from the copper sp- and d-bands might selectively enhance the binding energy of CO.
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| 4. |
- Basso, Rafael, 1979, et al.
(författare)
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Electric Vehicle Routing Problem with Machine Learning for Energy Prediction
- 2021
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Ingår i: Transportation Research Part B: Methodological. - : Elsevier BV. - 0191-2615. ; 145, s. 24-55
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Tidskriftsartikel (refereegranskat)abstract
- Routing electric commercial vehicles requires taking into account their limited driving range, which is affected by several uncertain factors such as traffic conditions. This paper presents the time-dependent Electric Vehicle Routing Problem with Chance- Constraints (EVRP-CC) and partial recharging. The routing method is divided into two stages, where the first finds the best paths and the second optimizes the routes. A probabilistic Bayesian machine learning approach is proposed for predicting the expected energy consumption and variance for the road links, paths and routes. Hence it is possible to consider the uncertainty in energy demand by planning charging within a confidence interval. The energy estimation is validated with data from electric buses driving a public transport route in Gothenburg-Sweden as well as with realistic simulations for 24 hours traffic in the city of Luxembourg connected to a high fidelity vehicle model. Routing solutions are compared with a deterministic formulation of the problem similar to the ones found in the literature. The results indicate high accuracy for the energy prediction as well as energy savings and more reliability for the routes.
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| 5. |
- Basso, Rafael, 1979, et al.
(författare)
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Energy consumption estimation integrated into the Electric Vehicle Routing Problem
- 2019
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Ingår i: Transportation Research Part D: Transport and Environment. - : Elsevier BV. - 1361-9209. ; 69, s. 141-167
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Tidskriftsartikel (refereegranskat)abstract
- When planning routes for fleets of electric commercial vehicles, it is necessary to precisely predict the energy required to drive and plan for charging whenever needed, in order to manage their driving range limitations. Although there are several energy estimation models available in the literature, so far integration with Vehicle Routing Problems has been limited and without demonstrated accuracy. This paper introduces the Two-stage Electric Vehicle Routing Problem (2sEVRP) that incorporates improved energy consumption estimation by considering detailed topography and speed profiles. First, a method to calculate energy cost coefficients for the road network is outlined. Since the driving cycle is unknown, the model generates an approximation based on a linear function of mass, as the latter is only determined while routing. These coefficients embed information about topography, speed, powertrain efficiency and the effect of acceleration and braking at traffic lights and intersections. Secondly, an integrated two-stage approach is described, which finds the best paths between pairs of destinations and then finds the best routes including battery and time-window constraints. Energy consumption is used as objective function including payload and auxiliary systems. The road cost coefficients are aggregated to generate the path cost coefficients that are used in the routing problem. In this way it is possible to get a proper approximation of the complete driving cycle for the routes and accurate energy consumption estimation. Lastly, numerical experiments are shown based on the road network from Gothenburg-Sweden. Energy estimation is compared with real consumption data from an all-electric bus from a public transport route and with high-fidelity vehicle simulations. Routing experiments focus on trucks for urban distribution of goods. The results indicate that time and energy estimations are significantly more precise than existing methods. Consequently the planned routes are expected to be feasible in terms of energy demand and that charging stops are properly included when necessary.
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| 6. |
- Basso, Rafael, 1979, et al.
(författare)
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Electric vehicle routing problem – a nested two level approach
- 2017
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Ingår i: Proceedings of Swedish transportation research conference Stockholm 17-18 October 2017.
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Konferensbidrag (refereegranskat)abstract
- Some of the main constraints of electric vehicles are related to their battery, in terms of energy capacity, time to recharge, weight and cost. One of the most important consequences is a limitation in driving range, which especially impacts commercial vehicles. Therefore in order to plan routes for this kind of vehicle, it is necessary to precisely estimate the energy required to drive and plan for charging whenever needed. This paper introduces the Two-stage Electric Vehicle Routing Problem (2sEVRP) that considers detailed information about the paths when estimating energy consumption and planning the routes. First, a method to calculate cost parameters for the road network is outlined including topography, speed, powertrain efficiency and the effect of acceleration and braking at traffic lights and intersections. Second, an integrated two-stage approach is described, which finds the best paths between pairs of nodes and then finds the best routes including battery and time-window constraints. Energy consumption is used as cost function including payload and auxiliary systems. The road cost parameters are aggregated to generate the path cost parameters that are used in the routing problem. In this way all the details of the paths are taken into account when computing energy demand for the routes. Last, numerical experiments were conducted with the road network from Gothenburg-Sweden and high-fidelity vehicle model simulations, focusing on trucks for urban distribution of goods. The results indicate that time and energy estimation are signeficantly more precise than existing methods. Consequently it is possible to generate important savings and be sure that the planned routes are feasible.
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| 7. |
- De Paz Urueña, Rafael, et al.
(författare)
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Momate. Moderniser la formation sur les Energies Renouvelables (ER) au Maghreb : Transfer de l'expérience
- 2017
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Le projet vise à développer une formation de type DUT (Diplôme Universitaire de Technologie) en ingénierie des Energies Renouvelables et à soutenir l'émergence de technopoles spécialisées dans les Energies Renouvelables. L'objectif est de développer des compétences permettant d'acquérir des connaissances de base sur la production d'électricité à partir d'énergies renouvelables (éolienne, solaire, photovoltaïque, etc.). El proyecto pretende desarrollar un programa de formación como el DUT (Diplôme Universitaire de Technologie) en ingeniería de Energías Renovables y apoyar la aparición de tecnopolos especializados en Energías Renovables. Para ello se pretende desarrollar competencias que permitan adquirir conocimientos básicos sobre la producción de energía eléctrica a partir de energías renovables (eólica, solar, fotovoltaica, etc.)
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| 8. |
- Sanchez-Diaz, Ivan, 1984, et al.
(författare)
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A Time-Efficiency Study of Medium-Duty Trucks Delivering in Urban Environments
- 2020
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Ingår i: Sustainability. - 2071-1050. ; 12:1, s. 425-
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Tidskriftsartikel (refereegranskat)abstract
- This paper uses data from a major logistics service provider in Gothenburg (Sweden) to (i) identify the different activities in a typical urban distribution tour, (ii) quantify the time required by drivers to perform each of these activities, and (iii) identify potential initiatives to improve time efficiency. To do so, the authors collected GPS data, conducted a time-study of the activities performed by the drivers for a week, conducted a focus group with the drivers, and a set of interviews with managers. The results show that driving represents only 30% of the time, another 15% is spent on breaks, and the remaining 55% is used to perform activities related to customer service, freight handling, and planning. The latter are subdivided into multiple activities, each taking a small amount of time. A focus group with the drivers and some interviews revealed several initiatives to improve time efficiency. Most initiatives can bring small gains, but when aggregating all potential time savings there is a big potential to improve overall time efficiency. Initiatives with highest potential and low cost are: providing better pre-advice on upcoming customers, improving route planning, having hand-free cell phone use, and enhancing handling equipment.
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| 9. |
- Sarmiento Nova, Silvia J., et al.
(författare)
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Response Surface Method strategies coupled with NLFEA for structural reliability analysis of prestressed bridges
- 2021
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Ingår i: IABSE Congress Ghent 2021. - Zurich, Switzerland : International Association for Bridge and Structural Engineering (IABSE). ; , s. 1813-1822
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Konferensbidrag (refereegranskat)abstract
- The Response Surface Method (RSM) has become an essential tool to solve structural reliability problems due to its accuracy, efficacy, and facility for coupling with Nonlinear Finite Element Analysis (NLFEA). In this paper, some strategies to improve the RSM efficacy without compromising its accuracy are tested. Initially, each strategy is implemented to assess the safety level of a highly nonlinear explicit limit state function. The strategy with the best results is then identified and used to carry out a reliability analysis of a prestressed concrete bridge, considering the nonlinear material behavior through NLFEA simulation. The calculated value of ? is compared with the target value established in Eurocode for ULS. The results showed how RSM can be a practical methodology and how the improvements presented can reduce the computational cost of a traditional RSM giving a good alternative to simulation methods such as Monte Carlo.
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