scholarly journals Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 5131
Author(s):  
Leandro do C. Martins ◽  
Rafael D. Tordecilla ◽  
Juliana Castaneda ◽  
Angel A. Juan ◽  
Javier Faulin
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Combustion Engine ◽  
Optimization Methods ◽  
Sustainable Transportation ◽  
Arc Routing ◽  
Learning Approaches ◽  
Optimization Simulation ◽  
Team Orienteering

The increasing use of electric vehicles in road and air transportation, especially in last-mile delivery and city mobility, raises new operational challenges due to the limited capacity of electric batteries. These limitations impose additional driving range constraints when optimizing the distribution and mobility plans. During the last years, several researchers from the Computer Science, Artificial Intelligence, and Operations Research communities have been developing optimization, simulation, and machine learning approaches that aim at generating efficient and sustainable routing plans for hybrid fleets, including both electric and internal combustion engine vehicles. After contextualizing the relevance of electric vehicles in promoting sustainable transportation practices, this paper reviews the existing work in the field of electric vehicle routing problems. In particular, we focus on articles related to the well-known vehicle routing, arc routing, and team orienteering problems. The review is followed by numerical examples that illustrate the gains that can be obtained by employing optimization methods in the aforementioned field. Finally, several research opportunities are highlighted.

scholarly journals frvcpy: An Open-Source Solver for the Fixed Route Vehicle Charging Problem

2021 ◽  
Author(s):  
Nicholas D. Kullman ◽  
Aurelien Froger ◽  
Jorge E. Mendoza ◽  
Justin C. Goodson
Keyword(s):  
Open Source ◽  
Vehicle Routing ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Software Tool ◽  
Sustainable Transportation ◽  
Vehicle Routing Problems ◽  
Routing Problems ◽  
Vehicle Charging ◽  
Community Standard

Electric vehicles offer a pathway to more sustainable transportation, but their adoption entails new challenges not faced by their petroleum-based counterparts. A difficult task in vehicle routing problems addressing these challenges is determining how to make good charging decisions for an electric vehicle traveling a given route. This is known as the fixed route vehicle charging problem. An exact and efficient algorithm for this task exists, but its implementation is sufficiently complex to deter researchers from adopting it. In this work we introduce frvcpy, an open-source Python package implementing this algorithm. Our aim with the package is to make it easier for researchers to solve electric vehicle routing problems, facilitating the development of optimization tools that may ultimately enable the mass adoption of electric vehicles. Summary of Contribution: This work describes a novel software tool for the vehicle routing community. The tool, frvcpy, addresses one of the primary challenges faced by the vehicle routing community when considering problems involving the adoption of electric vehicles (EVs): how to make optimal charging decisions. The state-of-the-art algorithm for solving these problems is sufficiently complex to deter researchers from using it, leading them to adopt less robust methods. frvcpy offers an easy-to-use, lightweight implementation of this algorithm, providing optimal solutions in low (∼5 ms) runtime. It is designed to be easily embedded in larger solution schemes for general EV routing problems, requiring minimal input, offering compatibility with the community standard file types, and offering access both through the command line and a Python API. The tool has thus far proven adaptable, having been used by researchers studying EV routing problems with novel constraints. Our aim with frvcpy is to make it easier for researchers to solve EV routing problems, facilitating the development of optimization tools that may contribute toward the mass adoption of electric vehicles.

scholarly journals Goods Delivery with Electric Vehicles: Electric Vehicle Routing Optimization with Time Windows and Partial or Full Recharge

Energies ◽  
2022 ◽  
Vol 15 (1) ◽  
pp. 285
Author(s):  
Tomislav Erdelić ◽  
Tonči Carić
Keyword(s):  
Vehicle Routing ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Combustion Engine ◽  
Time Windows ◽  
Neighborhood Search ◽  
Routing Problem ◽  
Charging Station ◽  
Routing Optimization ◽  
Mode Of Transport

With the rise of the electric vehicle market share, many logistic companies have started to use electric vehicles for goods delivery. Compared to the vehicles with an internal combustion engine, electric vehicles are considered as a cleaner mode of transport that can reduce greenhouse gas emissions. As electric vehicles have a shorter driving range and have to visit charging stations to replenish their energy, the efficient routing plan is harder to achieve. In this paper, the Electric Vehicle Routing Problem with Time Windows (EVRPTW), which deals with the routing of electric vehicles for the purpose of goods delivery, is observed. Two recharge policies are considered: full recharge and partial recharge. To solve the problem, an Adaptive Large Neighborhood Search (ALNS) metaheuristic based on the ruin-recreate strategy is coupled with a new initial solution heuristic, local search, route removal, and exact procedure for optimal charging station placement. The procedure for the O(1) evaluation in EVRPTW with partial and full recharge strategies is presented. The ALNS was able to find 38 new best solutions on benchmark EVRPTW instances. The results also indicate the benefits and drawbacks of using a partial recharge strategy compared to the full recharge strategy.

scholarly journals The Risk of Dissolution of Sustainable Innovation Ecosystems in Times of Crisis: The Electric Vehicle during the COVID-19 Pandemic

2021 ◽  
Vol 13 (3) ◽  
pp. 1319
Author(s):  
Manel Arribas-Ibar ◽  
Petra Nylund ◽  
Alexander Brem
Keyword(s):  
Internal Combustion Engine ◽  
Electric Vehicle ◽  
Combustion Engine ◽  
Internal Combustion ◽  
Sustainable Transportation ◽  
Mobility Patterns ◽  
Innovation Ecosystems ◽  
Sustainable Innovation ◽  
Behavioural Patterns

Innovation ecosystems evolve and adapt to crises, but what are the factors that stimulate ecosystem growth in spite of dire circumstances? We study the arduous path forward of the electric vehicle (EV) ecosystem and analyse in depth those factors that influence ecosystem growth in general and during the pandemic in particular. For the EV ecosystem, growth implies outcompeting the less sustainable internal combustion engine (ICE) vehicles, thus achieving a transition towards sustainable transportation. New mobility patterns provide a strategic opportunity for such a shift to green mobility and for EV ecosystem growth. For innovation ecosystems in general, we suggest that a crisis can serve as an opportunity for new innovations to break through by disrupting prior behavioural patterns. For the EV ecosystem in particular, it remains to be seen if the ecosystem will be able to capitalize on the opportunity provided by the unfortunate disruption generated by the pandemic.

A Methodological Approach for Supporting the Thermal Design of Li-Ion Battery for Customized Electric Vehicles

2014 ◽  
Author(s):  
Daniele Landi ◽  
Paolo Cicconi ◽  
Michele Germani
Keyword(s):  
Thermal Behavior ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Combustion Engine ◽  
Thermal Design ◽  
Battery Pack ◽  
Scale Production ◽  
Li Ion Battery ◽  
Suitable Alternative ◽  
Li Ion

An important issue in the mechanical industry is the reduction of the time to market, in order to meet quickly the customer needs. This goal is very important for SMEs that produce small lots of customized products. In the context of greenhouse gas emissions reduction, vehicles powered by electric motors seem to be the most suitable alternative to the traditional internal combustion engine vehicles. The market of customized electric vehicles is a niche market suitable for SMEs. Nowadays, the energy storage system of an electric vehicle powertrain consists of several Li-ion cells arranged in a container called battery pack. Particularly, the battery unit is considered as the most critical component in electric vehicle, because it impacts on performance and life cycle cost. Currently, the design of a battery pack mostly depends on the related market size. A longer design time is expected in the case of a large scale production. While a small customized production requires more agility and velocity in the design process. The proposed research focuses on a design methodology to support the designer in the evaluation of the battery thermal behavior. This work has been applied in the context of a customized small production. As test case, an urban electric light commercial vehicle has been analyzed. The designed battery layout has been evaluated and simulated using virtual prototyping tools. A cooling configuration has been analyzed and then prototyped in a physical vehicle. The virtual thermal behavior of a Li-ion battery has been validated at the test bench. The real operational conditions have been analyzed reproducing several ECE-15 driving cycles and many acceleration runs at different load values. Thermocouples have measured the temperature values during the physical experiments, in order to validate the analytical thermal profile evaluated with the proposed design approach.

scholarly journals Advancements in Battery Technologies of Electric Vehicle

2021 ◽  
Vol 2129 (1) ◽  
pp. 012011
Author(s):  
V.K Bupesh Raja ◽  
Ignatius Raja ◽  
Rahul Kavvampally
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Automobile Industry ◽  
Combustion Engine ◽  
Maximum Energy ◽  
Electric Cars ◽  
Alternative Materials ◽  
Tremendous Amount ◽  
Battery Technology ◽  
Compact Design

Abstract The Automotive Industry has undergone a huge revolution – Electric Vehicles! Electric cars are growing fast and the demand for them is increasing all around the world, thanks to the more and improved choice, reduced prices, and enhancing battery technology. Introduced more than 100 years ago, electric vehicles have gone through a tremendous amount of advancement. This paper reviews the current major challenges faced by the Electric Vehicle Industry along with possible solutions to overcome them. Although electric vehicles have come a long way, the battery used in the vehicles needs to be further explored to harness maximum energy with a compact design. Electric vehicles should soon be able to compete with combustion engine vehicles in every aspect. Also, this paper reviews alternative materials for electrodes and batteries to make charging faster and reliable than ever. This paper envisages few concepts that could revolutionize Automobile Industry further in the future.

Electric Vehicle Forecasting for China from 2011 to 2050 Based on Scenario Analysis

2011 ◽  
Vol 128-129 ◽  
pp. 846-849
Author(s):  
Shi Jun Fu ◽  
Yu Long Ren
Keyword(s):  
Climate Change ◽  
Internal Combustion Engine ◽  
Electric Vehicle ◽  
Growth Model ◽  
Electric Vehicles ◽  
Scenario Analysis ◽  
Combustion Engine ◽  
Growth Period ◽  
The Difference ◽  
New Industry

With climate change being growing concerns, the development of EV (Electric Vehicles) has taken on an accelerated pace. This paper is to forecast China’s EV stock from 2011 to 2050 based on the double species growth model. We elaborate two orbits according to two scenarios: with vehicle stock being 200 and 300 per thousand people at 2050. These orbits reveals that, China’s EVs development has a golden stage which will last 10 to 11 years; And before this booming stage, there is a slowly growth period which will last 7 to 8 years. Furthermore, under each scenario, the difference between EVs and ICEVs (Internal Combustion Engine Vehicles) stock at 2030 is 4.69% to 6.77%, which confirms that China’s ambitious EVs program may be realized if government sets strong policy supports on this new industry persistently.

scholarly journals Electric Vehicle Charging Load Forecasting: A Comparative Study of Deep Learning Approaches

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2692 ◽  
Author(s):  
Juncheng Zhu ◽  
Zhile Yang ◽  
Monjur Mourshed ◽  
Yuanjun Guo ◽  
Yimin Zhou ◽  
...  
Keyword(s):  
Deep Learning ◽  
Comparative Study ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Load Forecasting ◽  
Learning Approaches ◽  
Short Term ◽  
Learning Methods ◽  
Electric Vehicle Charging ◽  
Vehicle Charging

Load forecasting is one of the major challenges of power system operation and is crucial to the effective scheduling for economic dispatch at multiple time scales. Numerous load forecasting methods have been proposed for household and commercial demand, as well as for loads at various nodes in a power grid. However, compared with conventional loads, the uncoordinated charging of the large penetration of plug-in electric vehicles is different in terms of periodicity and fluctuation, which renders current load forecasting techniques ineffective. Deep learning methods, empowered by unprecedented learning ability from extensive data, provide novel approaches for solving challenging forecasting tasks. This research proposes a comparative study of deep learning approaches to forecast the super-short-term stochastic charging load of plug-in electric vehicles. Several popular and novel deep-learning based methods have been utilized in establishing the forecasting models using minute-level real-world data of a plug-in electric vehicle charging station to compare the forecasting performance. Numerical results of twelve cases on various time steps show that deep learning methods obtain high accuracy in super-short-term plug-in electric load forecasting. Among the various deep learning approaches, the long-short-term memory method performs the best by reducing over 30% forecasting error compared with the conventional artificial neural network model.

scholarly journals Real-Time Co-optimization of Vehicle Route and Speed Using Generic Algorithm for Improved Fuel Economy

2019 ◽  
Vol 141 (03) ◽  
pp. S08-S15
Author(s):  
Guoming G. Zhu ◽  
Chengsheng Miao
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Fuel Economy ◽  
Autonomous Vehicles ◽  
Hybrid Electric Vehicle ◽  
High Efficiency ◽  
Combustion Engine ◽  
Cruise Control ◽  
Vehicle Performance ◽  
Hybrid Electric

Making future vehicles intelligent with improved fuel economy and satisfactory emissions are the main drivers for current vehicle research and development. The connected and autonomous vehicles still need years or decades to be widely used in practice. However, some advanced technologies have been developed and deployed for the conventional vehicles to improve the vehicle performance and safety, such as adaptive cruise control (ACC), automatic parking, automatic lane keeping, active safety, super cruise, and so on. On the other hand, the vehicle propulsion system technologies, such as clean and high efficiency combustion, hybrid electric vehicle (HEV), and electric vehicle, are continuously advancing to improve fuel economy with satisfactory emissions for traditional internal combustion engine powered and hybrid electric vehicles or to increase cruise range for electric vehicles.

Electric Vehicle Drivetrain Development in China

2012 ◽  
Author(s):  
Yiqing Yuan ◽  
Guoqiang Wu ◽  
Xiangyan He ◽  
Yanda Song ◽  
Xuewen Zhang
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Combustion Engine ◽  
Automatic Transmission ◽  
Fixed Ratio ◽  
Continuous Variable ◽  
Speed Ratio ◽  
Variable Ratio ◽  
Speed Reduction ◽  
Electric Cars

Despite great progress recently made on applications of in-wheel motors in electric vehicles, almost all production or near-production electric vehicles still utilize mechanical speed reduction systems for transferring torque from the traction motor to wheels for the purposes of torque augmentation and speed reduction. These systems in general fall into three categories, i.e. fixed ratio, stepped variable ratio, or continuously variable ratio. In China, most electric cars retrofitted from internal combustion engine propelled vehicle models use gear reduction systems of a fixed speed ratio, in order to minimize the time to market. Typically a conversion is made to the original 5-speed manual transmission by taking out a few unused gear sets. With the rapid growth in electric vehicle industry, some gearboxes of fixed speed have been engineered and they typically have a layshaft configuration. Most of them still do not come with a “park” gear due to a lack of understanding on customer’s needs. As an exception, a transmission of fixed speed ratio dedicated for electric vehicle applications has been developed at the Electric Vehicle R&D Center, Chinese Academy of Sciences (UCAS). Among electric vehicles announced by domestic vehicle manufacturers in China, some employ 5-speed manual transmissions (MTs) or automatic transmission (ATs) that typically found in traditional vehicles. From the driving convenience, transmission efficiency, or cost standpoints, these transmissions are, in general, not appropriate for applications in electric vehicles. The “misusage” of these transmissions has often something to do with their availability rather than suitability. A great deal of effort has been put into the research and development of automated mechanical transmissions (AMTs) in China to date. Significant progress has been made to the reduction of shift time, improvement of shift quality, and optimization of the mechanical components. Continuously variable transmission (CVT) is considered to be an important trend in drivetrain technology. However, the pulley-belt types of CVT commonly seen in traditional vehicles are not proper for electric vehicle applications. An EVT dedicated for electric vehicles is under development at UCAS, in which the power from an electric motor of dual-rotors is coupled by means of a planetary gear set, allowing continuous variable of the output speed. In summary, the electric vehicle drivetrain technology in China is undergoing rapid advances, which will impact the development of electric vehicle industry at home and abroad.

scholarly journals Future Policy and Technological Advancement Recommendations for Enhanced Adoption of Electric Vehicles in South Africa: A Survey and Review

2021 ◽  
Vol 13 (22) ◽  
pp. 12535
Author(s):  
Mokhele Edmond Moeletsi
Keyword(s):  
South Africa ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Combustion Engine ◽  
Technological Advancement ◽  
Charging Infrastructure ◽  
Electric Vehicle Adoption ◽  
Future Policy ◽  
High Level ◽  
Alternative Propulsion Systems

There are major concerns globally on the increasing population of internal combustion engine (ICE) vehicles and their environmental impact. The initiatives for the advancement of alternative propulsion systems, such as electric motors, have great opportunities, but are marked by a number of challenges that require major changes in policies and serious investment on the technologies in order to make them viable alternative mobility sources around the world. South Africa has struggled a lot in adopting electric vehicles among all the emerging countries. This is mostly attributed to a non-conducive environment for electric vehicle adoption. This study administered a survey consisting of Likert-scale questions in the Gauteng Province to gather information on people’s views on some of the major concerns around electric vehicle technology. The survey results demonstrated that Gauteng residents perceive electric vehicle price as the main constraint towards adoption of the technology and introduction of government policy towards addressing this challenge would be helpful. Some of the suggested interventions, such as the rollout of purchasing subsidies and tax rebates, received a high level of satisfaction among the respondents. Future initiatives that tackle issues of charging infrastructure network also received high satisfaction. Thus, there is a need for all stakeholders in the South African automotive industry to improve the enabling environment for the adoption of electric vehicles.

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