scholarly journals Optimal Routing and Scheduling of Charge for Electric Vehicles: A Case Study

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
J. Barco ◽  
A. Guerra ◽  
L. Muñoz ◽  
N. Quijano
Keyword(s):  
Energy Consumption ◽  
Electric Vehicles ◽  
Public Transportation ◽  
Differential Evolution Algorithm ◽  
Transportation Systems ◽  
Routing Problems ◽  
Routing Problem ◽  
Routing And Scheduling ◽  
Battery Degradation

There are increasing interests in improving public transportation systems. One of the proposed strategies for this improvement is the use of Battery Electric Vehicles (BEVs). This approach leads to a new challenge as the BEVs’ routing is exposed to the traditional routing problems of conventional vehicles, as well as the particular requirements of the electrical technologies of BEVs. Examples of BEVs’ routing problems include the autonomy, battery degradation, and charge process. This work presents a differential evolution algorithm for solving an electric vehicle routing problem (EVRP). The formulation of the EVRP to be solved is based on a scheme to coordinate the BEVs’ routing and recharge scheduling, considering operation and battery degradation costs. A model based on the longitudinal dynamics equation of motion estimates the energy consumption of each BEV. A case study, consisting of an airport shuttle service scenario, is used to illustrate the proposed methodology. For this transport service, the BEV energy consumption is estimated based on experimentally measured driving patterns.

scholarly journals “Unparking”: How can Smart Mobility Reduce Parking Demand in Our Cities to the Minimum? (Beirut Case Study)

Smart Cities ◽  
2020 ◽  
Vol 3 (2) ◽  
pp. 172-185
Author(s):  
Adib Haydar
Keyword(s):  
Public Transportation ◽  
Transportation Systems ◽  
Decision Makers ◽  
Demand And Supply ◽  
Mobility System ◽  
Smart Mobility ◽  
Public Transportation Systems ◽  
Parking Demand ◽  
The City

Beirut is a car-dependent city, with 80% of Beirut citizens using their private cars to move across the city (the rate of car ownership is higher than regional and global benchmarks: 627 cars/1000 in Beirut, 550/1000 in Dubai and 170/1000 in Singapore). This reality causes two related impacts: an increased parking demand and decreased public transportation usage. Furthermore, in order to discuss these aspects, our study addresses the following question: How can the municipality’s interventions and mobility system reforms, such as smart public transportation systems and shareable mobility, reduce parking demand? As our methodology, it consists of three sections: (1) determine Beirut's parking problems by estimating parking demand and supply; (2) assess the potential effects of Beirut municipality policies in comparison to international experiences; and (3) evaluate the potential impacts of the smart public transportation system and shareable mobility in reducing parking demand. This paper studies parking growth in developing countries, such as Lebanon, and can help planners, decision-makers, and the Beirut municipality to make more informed decisions about parking policies, and to meet growing parking demand by introducing smart interventions that have high local potentials.

scholarly journals Energy economy analysis of the G-Wiz: a two-year case study based on two vehicles

2011 ◽  
Vol 225 (11) ◽  
pp. 1505-1517 ◽  
Author(s):  
A R Chaudhari ◽  
R H Thring
Keyword(s):  
Energy Consumption ◽  
Electric Vehicles ◽  
Discharge Rate ◽  
Vehicle Data ◽  
Maximum Range ◽  
Energy Economy ◽  
Energy Consumption Patterns ◽  
Vehicle Usage ◽  
Main Factor

This paper presents the data recorded from two G-Wiz Reva electric vehicles (EVs) over a period of two years and approximately 8000 km on each vehicle. The analysis of the vehicle data demonstrates that the range of the vehicle obtained for a certain state-of-charge (SOC) drop was not consistent. The results show that the main factor affecting the available range was irregular vehicle usage. The recharge energy consumption patterns of the vehicle were identified and it was demonstrated that infrequent vehicle usage increased energy consumed by the vehicle. A maximum range of 66.8 km was achieved when the vehicle was regularly used, but this fell to 42.8 km when it was infrequently used. The energy economy when the vehicle was regularly used was 8.3 km/kWh. Additionally, the analysis results identify the need to determine discharge rate of the vehicle batteries to determine the precise effects on the available range and energy consumption of the vehicle.

scholarly journals Electric Vehicle Fleet Management Using Ant Colony Optimisation

2020 ◽  
Vol 3 (1) ◽  
pp. 1-16
Author(s):  
Javier Biera Muriel ◽  
Abbas Fotouhi
Keyword(s):  
Limited Range ◽  
Ant Colony ◽  
Fleet Management ◽  
Ant Colony Optimisation ◽  
Routing Problem ◽  
Charging Time ◽  
Battery Degradation ◽  
Optimum Solution ◽  
Advanced Version

This research is focused on implementation of the ant colony optimisation (ACO) technique to solve an advanced version of the vehicle routing problem (VRP), called the fleet management system (FMS). An optimum solution of VRP can bring benefits for the fleet operators as well as contributing to the environment. Nowadays, particular considerations and modifications are needed to be applied in the existing FMS algorithms in response to the rapid growth of electric vehicles (EVs). For example, current FMS algorithms do not consider the limited range of EVs, their charging time or battery degradation. In this study, a new ACO-based FMS algorithm is developed for a fleet of EVs. A simulation platform is built in order to evaluate performance of the proposed FMS algorithm under different simulation case-studies. The simulation results are validated against a well-established method in the literature called nearest-neighbour technique. In each case-study, the overall mileage of the fleet is considered as an index to measure the performance of the FMS algorithm.

Joint Vehicle and Crew Routing and Scheduling

2020 ◽  
Vol 54 (2) ◽  
pp. 488-511
Author(s):  
Edward Lam ◽  
Pascal Van Hentenryck ◽  
Phil Kilby
Keyword(s):  
Vehicle Routing ◽  
Mixed Integer ◽  
Neighborhood Search ◽  
Routing Problems ◽  
Routing Problem ◽  
Military Logistics ◽  
Routing And Scheduling ◽  
Constraint Program ◽  
Mip Model ◽  
Optimization Constraint

Traditional vehicle routing problems implicitly assume that only one crew operates a vehicle for the entirety of its journey. However, this assumption is violated in many applications arising in humanitarian and military logistics. This paper considers a joint vehicle and crew routing and scheduling problem in which crews are able to interchange vehicles, resulting in space and time interdependencies between vehicle routes and crew routes. The problem is formulated as a mixed integer programming (MIP) model and a constraint programming (CP) model that overlay crew routing constraints over a standard vehicle routing problem. The constraint program uses a novel optimization constraint to detect infeasibility and to bound crew objectives. This paper also explores methods using large neighborhood search over the MIP and CP models. Experimental results indicate that modeling the vehicle and crew routing problems jointly and supporting vehicle interchanges for crews may bring significant benefits in cost reduction compared with a method that sequentializes these decisions.

scholarly journals Efficiency Analysis of Public Transportation Subunits Using DEA and Bootstrap Approaches -- Dakar Dem Dikk Case Study

2016 ◽  
Vol 8 (6) ◽  
pp. 114 ◽  
Author(s):  
Oumar Sow ◽  
Amar Oukil ◽  
Babacar M. Ndiaye ◽  
Aboubacar Marcos
Keyword(s):  
Public Transportation ◽  
Planning Process ◽  
Returns To Scale ◽  
Transportation Systems ◽  
Data Envelopment ◽  
Bootstrap Approach ◽  
Scale Characterization ◽  
Constant Returns To Scale

Transportation is a sector which plays an important role in the process of development of countries around the world. A crucial step in transportation planning process is the measure of the efficiency of transportation systems in order to guarantee the desired service. This paper investigates the relative efficiencies of lines of the main public transportation company Dakar Dem Dikk (DDD)\footnote{\textit{Dem Dikk} meaning \guillemotleft Go-Return\guillemotright} in Dakar (Senegal). The objective is to apply Data Envelopment Analysis (DEA) and bootstrapping approaches in order to identify opportunities for improvement. In this study, we examine technical efficiency for the 24 lines of DDD using Constant Returns to Scale (CRS) and Variable Returns to Scale (VRS) DEA output oriented models. We apply bootstrap approach for bias correction and for confidence intervals creation of our estimates. Finally, we examine the returns to scale characterization of lines. The results establish that there exist possibilities for improvement for the lines and also shown that there are potential for restructure for some lines.

scholarly journals Living in Living Cities

2013 ◽  
Vol 19 (3_4) ◽  
pp. 401-420 ◽  
Author(s):  
Carlos Gershenson
Keyword(s):  
Public Transportation ◽  
Transportation Systems ◽  
Living Systems ◽  
Dynamic Problems ◽  
The Core ◽  
Potential Applications ◽  
Urban Problems ◽  
Public Transportation Systems ◽  
Core Features

This article presents an overview of current and potential applications of living technology to some urban problems. Living technology can be described as technology that exhibits the core features of living systems. These features can be useful to solve dynamic problems. In particular, urban problems concerning mobility, logistics, telecommunications, governance, safety, sustainability, and society and culture are presented, and solutions involving living technology are reviewed. A methodology for developing living technology is mentioned, and supraoptimal public transportation systems are used as a case study to illustrate the benefits of urban living technology. Finally, the usefulness of describing cities as living systems is discussed.

scholarly journals Integrated Optimization of Routing and Energy Management for Electric Vehicles in Delivery Scheduling

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1762
Author(s):  
Lixing Wang ◽  
Zhenning Wu ◽  
Changyong Cao
Keyword(s):  
Energy Consumption ◽  
Vehicle Routing ◽  
Energy Management ◽  
Electric Vehicles ◽  
Time Windows ◽  
Case Based Reasoning ◽  
Dynamic Adjustment ◽  
Routing Problem ◽  
Battery Capacity ◽  
Delivery Scheduling

At present, electric vehicles (EVs) are attracting increasing attention and have great potential for replacing fossil-fueled vehicles, especially for logistics applications. However, energy management for EVs is essential for them to be advantageous owing to their limitations with regard to battery capacity and recharging times. Therefore, inefficiencies can be expected for EV-based logistical operations without an energy management plan, which is not necessarily considered in traditional routing exercises. In this study, for the logistics application of EVs to manage energy and schedule the vehicle route, a system is proposed. The system comprises two parts: (1) a case-based reasoning subsystem to forecast the energy consumption and travel time for each route section, and (2) a genetic algorithm to optimize vehicle routing with an energy consumption situation as a new constraint. A dynamic adjustment algorithm is also adopted to achieve a rapid response to accidents in which the vehicles might be involved. Finally, a simulation is performed to test the system by adjusting the data from the vehicle routing problem with time windows. Solomon benchmarks are used for the validations. The analysis results show that the proposed vehicle management system is more economical than the traditional method.

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