Battery-Aware Electric Truck Delivery Route Exploration

Baek, Donkyu; Chang, Naehyuck; Macii, Enrico; Poncino, Massimo

doi:10.3390/en13082096

Cited by 7 publications

(3 citation statements)

References 15 publications

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“…The unmanned vehicle delivery routing problem is fundamentally a VRP, which has found a growing range of applications that require its solving in daily life, such as material distributions [9], drone path optimization [10,11], home healthcare system applications [12], public transit services' mode and route optimization [13], electric vehicle path problems considering battery charging status [14][15][16], dynamic VRPs [17,18], emergency material dispatch optimization [19][20][21], service-oriented collaborative VRPs [22], and green delivery path problems [23,24]. In contrast to the traditional vehicle routing problem (VRP), the incorporation of unmanned vehicles facilitates continuous 24 h back-and-forth deliveries without the requirement of human drivers.…”

Section: Literature Reviewmentioning

confidence: 99%

Consideration of Carbon Emissions in Multi-Trip Delivery Optimization of Unmanned Vehicles

Gao,

Liu,

Wang

et al. 2024

Sustainability

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In order to achieve the goal of low-carbon, efficient delivery using unmanned vehicles, a multi-objective optimization model considering carbon emissions in the problem of optimizing multi-route delivery for unmanned vehicles is proposed. An improved genetic algorithm (IGA) is designed for solving this problem. This study takes into account constraints such as the maximum service duration for delivery, the number of vehicles, and the approved loading capacity of the vehicles, with the objective of minimizing the startup cost, transportation cost, fuel cost, and environmental cost in terms of the carbon dioxide emissions of unmanned vehicles. A combination encoding method based on the integer of the number of trips, the number of vehicles, and the number of customers is used. The inclusion of a simulated annealing algorithm and an elite selection strategy in the design of the IGA enhances the quality and efficiency of the algorithm. The international dataset Solomon RC 208 is used to verify the effectiveness of the model and the algorithm in small-, medium-, and large-scale cases by comparing them with the genetic algorithm (GA) and simulated annealing algorithm (SA). The research results show that the proposed model is applicable to the problem of optimizing the multi-route delivery of unmanned vehicles while considering carbon emissions. Compared with the GA and SA, the IGA demonstrates faster convergence speed and higher optimization efficiency. Additionally, as the problem’s scale increases, the average total cost deviation rate changes significantly, and better delivery solutions for unmanned vehicles are obtained with the IGA. Furthermore, the selection of delivery routes for unmanned vehicles primarily depends on their startup costs and transportation distance, and the choice of different vehicle types has an impact on delivery duration, total distance, and the average number of trips. The delivery strategy that considers carbon emissions shows a 22.6% difference in its total cost compared to the strategy that does not consider carbon emissions. The model and algorithms proposed in this study provide optimization solutions for achieving low-carbon and efficient delivery using unmanned vehicles, aiming to reduce their environmental impact and costs. They also contribute to the development and application of unmanned vehicle technology in the delivery field.

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Section: Literature Reviewmentioning

confidence: 99%

Consideration of Carbon Emissions in Multi-Trip Delivery Optimization of Unmanned Vehicles

Gao,

Liu,

Wang

et al. 2024

Sustainability

View full text Add to dashboard Cite

show abstract

“…In contrast with traditional approaches, a prominent focus to overcome the waiting times of recharge and the so called range anxiety is posed in [5], combining the EVRP with mobile battery swapping vans, both synchronized at a designated time and space. In the context of battery efficiency, the research in [45] implements a simulator for an electric truck to achieve the least-energy delivery route, taking into consideration the nonlinear model of the battery and the change of parcel weight over the course of the route.…”

Section: Literature Reviewmentioning

confidence: 99%

A Linearized Approach for the Electric Light Commercial Vehicle Routing Problem Combined with Charging Station Siting and Power Distribution Network Assessment

2021

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Transportation electrification has demonstrated a significant position on power utilities and logistic companies, in terms of assets operation and management. Under this context, this paper presents the problem of seeking feasible and good quality routes for electric light commercial vehicles considering battery capacity and charging station siting on the power distribution system. Different transportation patterns for goods delivery are included, such as the capacitated vehicle routing problem and the shortest path problem for the last mile delivery. To solve the problem framed within a mixed integer linear mathematical model, the GAMS software is used and validated on a test instance conformed by a 19-customer transportation network, spatially combined with the IEEE 34 nodes power distribution system. The sensitivity analysis, performed during the computational experiments, show the behavior of the variables involved in the logistics operation, i.e., routing cost for each transport pattern. The trade-off between the battery capacity, the cost of the charging station installation, and energy losses on the power distribution system is also shown, including the energy consumption cost created by the charging operation.

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“…Baek et al [15] proposed a general method to model the path, vehicle, and battery, predict or optimize the operating range of electric vehicles, and alleviate mileage anxiety. Baek et al [16] implemented an electric vehicle simulator based on the electric vehicle powertrain model and nonlinear battery model. Chen et al [17] realized early electric vehicle simulation by defining the System CAMS framework, which models both physical and mechanical evolution, energy flow, and environmental characteristics.…”

Section: Introductionmentioning

confidence: 99%

Path Planning Method for Electric Vehicles Based on Freeway Network

Liu

Wang

Hua

2021

Journal of Advanced Transportation

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Recently, electric vehicles (EVs) have received more and more attention, but the problem of the insufficient range is still the main reason that hinders electric vehicles to travel long distances. Under the premise of the battery capacity without technological innovation, the path planning method can ensure the safety and efficiency of electric vehicles in long-distance travel. This paper studies the actual freeway network to optimize the vehicle driving path and give the charging strategy based on the shortest travel time of a single vehicle. In this paper, a path and charging strategy planning model is proposed. In this model, the shortest travel time of a single vehicle is taken as the objective function, and the state of charging equipment in the actual road network and the safe electric quantity are considered as constraints. And the genetic algorithm is used to solve the model. Through case analysis, the rationality and optimization efficiency of the model proposed in this paper are verified. Finally, the sensitivity analysis of the three parameters of traffic volume, temperature, and travel speed is carried out with the Shanghai-Nanjing freeway network. The experimental results can get the nodes with the highest service pressure in the network, which can provide a theoretical basis for charging nodes’ expansion in the freeway network in the future.

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Battery-Aware Electric Truck Delivery Route Exploration

Cited by 7 publications

References 15 publications

Consideration of Carbon Emissions in Multi-Trip Delivery Optimization of Unmanned Vehicles

Consideration of Carbon Emissions in Multi-Trip Delivery Optimization of Unmanned Vehicles

A Linearized Approach for the Electric Light Commercial Vehicle Routing Problem Combined with Charging Station Siting and Power Distribution Network Assessment

Path Planning Method for Electric Vehicles Based on Freeway Network

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