The electric vehicle routing problem with nonlinear charging function

Montoya, Alejandro; Guéret, Christelle; Mendoza, Jorge E.; Villegas, Juan G.

doi:10.1016/j.trb.2017.02.004

Cited by 417 publications

(279 citation statements)

References 33 publications

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“…Even so, this paper studied the relationship between vehicle endurance and refueling gas stations in time and space as well as its calculation model, from which recommendation strategies and a visual vehicle refueling warning system were formed, and consequently it was unclear what impact these differences would have on vehicle refueling strategies. Because there are some considerable differences in energy supply time between electric vehicles and traditional vehicles using liquid fossil fuels [14,16], we can infer that the algorithm presented in this study is probably not suitable for charging strategy recommendations for electric vehicles. (3) The applicability of the algorithm to the refueling of autonomous vehicles.…”

Section: Discussion Of Algorithm Applicabilitymentioning

confidence: 96%

A Distance-Adaptive Refueling Recommendation Algorithm for Self-Driving Travel

Yang

Peng

et al. 2018

IJGI

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Abstract:Taking the maximum vehicle driving distance, the distances from gas stations, the route length, and the number of refueling gas stations as the decision conditions, recommendation rules and an early refueling service warning mechanism for gas stations along a self-driving travel route were constructed by using the algorithm presented in this research, based on the spatial clustering characteristics of gas stations and the urgency of refueling. Meanwhile, by combining ArcEngine and Matlab capabilities, a scenario simulation system of refueling for self-driving travel was developed by using c#.net in order to validate and test the accuracy and applicability of the algorithm. A total of nine testing schemes with four simulation scenarios were designed and executed using this algorithm, and all of the simulation results were consistent with expectations. The refueling recommendation algorithm proposed in this study can automatically adapt to changes in the route length of self-driving travel, the maximum driving distance of the vehicle, and the distance from gas stations, which could provide variable refueling recommendation strategies according to differing gas station layouts along the route. Therefore, the results of this study could provide a scientific reference for the reasonable planning and timely supply of vehicle refueling during self-driving travel.

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Section: Discussion Of Algorithm Applicabilitymentioning

confidence: 96%

A Distance-Adaptive Refueling Recommendation Algorithm for Self-Driving Travel

Yang

Peng

et al. 2018

IJGI

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“…Constraints (5) to (9) indicate the load 123 flow equations that include active power balance (5), reactive power balance (6), active and reactive power flow of lines (7) and 124 (8), and the value of the voltage angle in the reference bus (9) [29]. Equation (10) and (11) …”

Section: The Original Model 104mentioning

confidence: 99%

Proactive operation of electric vehicles in harmonic polluted smart distribution networks

Pirouzi

Aghaei

Niknam

et al. 2018

IET Generation, Transmission & Distribution

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Abstract-This study proposes combined framework for proactive operation, i.e. bidirectional active and reactive power 14 management, of the smart distribution network as well as harmonic compensation of non-linear loads using electric vehicles 15 (EVs) equipped with bidirectional chargers. The problem is in the form of non-linear programming (NLP) where the objective 16 function is to minimise the voltage deviation at the fundamental frequency and the total harmonic distortion. The harmonic load 17 flow equations, EVs constraints, system operation and harmonic indexes limits are formulated as problem constraints. The 18 proposed NLP problem is converted to an equivalent mixed integer linear programming (MILP) model using Taylor series and 19 linearisation techniques for AC power flow formulation. Also, the Benders decomposition (BD) algorithm is used to solve the 20proposed MILP problem that is tested on different distribution test networks to demonstrate its efficiency and performance. The 21 results show that the NLP model can be substituted with the high-speed linear programming model. Moreover, the computation 22 speed is improved by using the BD method. Finally, the network and harmonic indexes improved and charging cost reduced 23 using the proposed idea. 24 25

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“…The authors considered as an optimization objective, the minimization of total distance traveled, energy, salary costs and a third objective with these two same costs and also the costs associated with the life of the battery. Another work that uses nonlinear functions for the EVRP is the one proposed by Montoya et al (2016). Up to this point, all the works discussed only consider the complete charge of the battery at specialized vertices.…”

Section: Literature Reviewmentioning

confidence: 99%

The multi-depot electric vehicle location routing problem with time windows

Paz¹,

Echeverri²,

Escobar³

2018

10.5267/j.ijiec

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In this paper, the Multi-Depot Electric Vehicle Location Routing Problem with Time Windows (MDVLRP) is addressed. This problem is an extension of the MDVLRP, where electric vehicles are used instead of internal combustion engine vehicles. The recent development of this model is explained by the advantages of this technology, such as the diminution of carbon dioxide emissions, and the support that they can provide to the design of the logistic and energy-support structure of electric vehicle fleets. There are many models that extend the classical VRP model to take electric vehicles into consideration, but the multi-depot case for location-routing models has not been worked out yet. Moreover, we consider the availability of two energy supply technologies: the "Plug-in" Conventional Charge technology, and Battery Swapping Stations; options in which the recharging time is a function of the amount of energy to charge and a fixed time, respectively. Three models are proposed: one for each of the technologies mentioned above, and another in which both options are taken in consideration. The models were solved for small scale instances using C++ and Cplex 12.5. The results show that the models can be used to design logistic and energy-support structures, and compare the performance of the different options of energy supply, as well as measure the impact of these decisions on the overall distance traveled or other optimization objectives that could be worked on in the future.

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The electric vehicle routing problem with nonlinear charging function

Cited by 417 publications

References 33 publications

A Distance-Adaptive Refueling Recommendation Algorithm for Self-Driving Travel

A Distance-Adaptive Refueling Recommendation Algorithm for Self-Driving Travel

Proactive operation of electric vehicles in harmonic polluted smart distribution networks

The multi-depot electric vehicle location routing problem with time windows

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