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The purpose of this paper is to optimize the design of charging station deployed at the terminal station for electric transit, with explicit consideration of heterogenous charging modes.

The authors proposed a bi-level model to optimize the decision-making at both tactical and operational levels simultaneously. Specifically, at the operational level (i.e. lower level), the service schedule and recharging plan of electric buses are optimized under specific design of charging station. The objective of lower-level model is to minimize total daily operational cost. This model is solved by a tailored column generation-based heuristic algorithm. At the tactical level (i.e. upper level), the design of charging station is optimized based upon the results obtained at the lower level. A tabu search algorithm is proposed subsequently to solve the upper-level model.

This study conducted numerical cases to validate the applicability of the proposed model. Some managerial insights stemmed from numerical case studies are revealed and discussed, which can help transit agencies design charging station scientifically.

The joint consideration of heterogeneous charging modes in charging station would further lower the operational cost of electric transit and speed up the market penetration of battery electric buses.

This research aims to focus on the problem of optimizing the layout of charging stations.

The authors estimate the total number of charging stations by the number of existing gas stations using clustering by fast search-and-find of density peaks (CFSFDP) algorithm.

This paper reveals the relationship between the distance and the population. Priority should be given to the short-distance and high-frequency travel charging needs in the city, followed by low frequency and travel, which can improve the use efficiency of the whole charging network.

First, the total number of charging stations is estimated by the number of existing gas stations. This method can fully consider the growth potential of charging vehicles instead of the traditional cars. Besides, the cost-benefit method is proposed to explore the marginal coverage distance of the city’s charging network and can be used to reveal the relationship between the distance and the population.

This paper aims to optimize the charging schedule for battery electric buses (BEBs) to minimize the charging cost considering the time-of-use electricity price.

The BEBs charging schedule optimization problem is formulated as a mixed-integer linear programming model. The objective is to minimize the total charging cost of the BEB fleet. The charge decision of each BEB at the end of each trip is to be determined. Two types of constraints are adopted to ensure that the charging schedule meets the operational requirements of the BEB fleet and that the number of charging piles can meet the demand of the charging schedule.

This paper conducts numerical cases to validate the effect of the proposed model based on the actual timetable and charging data of a bus line. The results show that the total charge cost with the optimized charging schedule is 15.56% lower than the actual total charge cost under given conditions. The results also suggest that increasing the number of charging piles can reduce the charging cost to some extent, which can provide a reference for planning the number of charging piles.

Considering time-of-use electricity price in the BEBs charging schedule will not only reduce the operation cost of electric transit but also make the best use of electricity resources.

The purpose of this paper is to investigate the nascent market settings from a business model innovation perspective with the research questions: How do incumbents and start-ups make sense of an emerging technology through business model design in a nascent market setting, and how does business model choice influence firm performance?

The authors have tracked the development of four case companies in the nascent electric vehicle market from 2009 to 2018 and have conducted interviews and analyzed the archival data.

The authors propose a typology of business model choices and performance where the four types of business models distinguish themselves by how the companies innovate or imitate the value proposition of the current industry as well as how they innovate or imitate the business model archetype. In accordance with these different business model choices, the actors express different logics behind their new to the product market space business model choice. These logics represent different understandings of technology potential, customer needs as well as potential for value capture and contribute to and limit the translation of emerging technologies into dominant designs in diverse ways.

The business model is conceived as a focusing device that can be used to identify market applications for emerging technologies. As new disruptive technologies often require a new to the product market space business model, literature has in recent years put a premium on business model innovation. However, the linkages between emergent technologies and the choice of a novel business model are under investigated especially in relation to how business model choice affects business performance in nascent market settings. This paper aims at filling this gap.

Docking technology plays a crucial role in enabling long-duration operations of autonomous underwater vehicles (AUVs). Visual positioning solutions alone are susceptible to abnormal drift values due to the challenging underwater optical imaging environment. When an AUV approaches the docking station, the absolute positioning method fails if the AUV captures an insufficient number of tracers. This study aims to to provide a more stable absolute position visual positioning method for underwater terminal visual docking.

This paper presents a six-degree-of-freedom positioning method for AUV terminal visual docking, which uses lights and triangle codes. The authors use an extended Kalman filter to fuse the visual calculation results with inertial measurement unit data. Moreover, this paper proposes a triangle code recognition and positioning algorithm.

The authors conducted a simulation experiment to compare the underwater positioning performance of triangle codes, AprilTag and Aruco. The results demonstrate that the implemented triangular code reduces the running time by over 70% compared to the other two codes, and also exhibits a longer recognition distance in turbid environments. Subsequent experiments were carried out in Qingjiang Lake, Hubei Province, China, which further confirmed the effectiveness of the proposed positioning algorithm.

This fusion approach effectively mitigates abnormal drift errors stemming from visual positioning and cumulative errors resulting from inertial navigation. The authors also propose a triangle code recognition and positioning algorithm as a supplementary approach to overcome the limitations of tracer light positioning beacons.

The purpose of this paper is to explore how a company which developed an environmentally friendly innovation attempted to address diffusion issues. Specifically, the purpose is to describe the ways in which an electric vehicle (EV) infrastructure company, in partnership with a major car manufacturer, tried to address barriers to diffusion of an environmentally friendly innovation during the development stage to improve the likelihood of success and lessons learned from its failure.

The authors explore a single instrumental case of an Israeli company that developed infrastructure for EVs in partnership with a major automaker. The authors collected data using a series of semi-structured interviews at the companies’ headquarters, through direct observation in the company, and through the examination of archival and secondary data sources.

The authors find that the company tried to incorporate design features in both the product and organization to address key diffusion barriers identified through survey and consumer focus research. The study maps product/service design innovations for infrastructure that combined with multi-stage organizational diffusion strategies for EVs, were used to address both functional (usage, value, and risk) and psychological (tradition and image) barriers for mass-market adoption.

The study provides insights on how to incorporate information about barriers to adoption into product/service design and on the development of organizational-level diffusion strategy to address changes of customer’s behavior required by certain innovative sustainable solutions. In addition, the authors speculate potential causes for more recent developments with the technology that can serve as a lesson for future projects.

Past studies have advanced the knowledge about issues surrounding the adoption and diffusion of EVs. The study expands this stream of research by focussing on product/service and organizational strategy design and by illustrating, through an empirical exploratory case study, how a company attempted to overcome these obstacles. The authors advance various propositions and point out potential exciting avenues for future research on the dissemination of environmentally friendly innovations.

Nowadays, the increase in the capacity of batteries has laid the foundations for a broader diffusion of electric mobility. However, electric mobility is causing a growing electricity demand as well as the need to increase the diffusion of suitable charging stations. Within these last challenges, drawing on the recent literature, this chapter provides a critical and wide-ranging review of papers dealing with the formulation of the problem of the localisation of electric vehicle (EV) charging points. This problem is approached considering the electric charging infrastructure technologies, localisation criteria and related methodologies. This review shows how the ‘electric mobility revolution’ applies the technological innovations provided by the energy supply systems, and the location of these systems within the urban contexts. Since the technological innovations have different options, achieving an international standard of charging systems is still far away. Moreover, as there are several criteria, parameters and methodologies, and some analytical approaches for the localisation of electric vehicle charging points, the formulation of the ‘localisation’ problem should require the application of multi-criteria analysis to be addressed. Finally, the results show that there is no consensus on technologies, criteria, and methodologies to be adopted. Therefore, this wide-ranging analysis of the literature would be useful to support possible benchmarking and systematisation accordingly.

Recently, electric vehicles have been widely used in the cold chain logistics sector to reduce the effects of excessive energy consumption and to support environmental friendliness. Considering the limited battery capacity of electric vehicles, it is vital to optimize battery charging during the distribution process.

This study establishes an electric vehicle routing model for cold chain logistics with charging stations, which will integrate multiple distribution centers to achieve sustainable logistics. The suggested optimization model aimed at minimizing the overall cost of cold chain logistics, which incorporates fixed, damage, refrigeration, penalty, queuing, energy and carbon emission costs. In addition, the proposed model takes into accounts factors such as time-varying speed, time-varying electricity price, energy consumption and queuing at the charging station. In the proposed model, a hybrid crow search algorithm (CSA), which combines opposition-based learning (OBL) and taboo search (TS), is developed for optimization purposes. To evaluate the model, algorithms and model experiments are conducted based on a real case in Chongqing, China.

The result of algorithm experiments illustrate that hybrid CSA is effective in terms of both solution quality and speed compared to genetic algorithm (GA) and particle swarm optimization (PSO). In addition, the model experiments highlight the benefits of joint distribution over individual distribution in reducing costs and carbon emissions.

The optimization model of cold chain logistics routes based on electric vehicles provides a reference for managers to develop distribution plans, which contributes to the development of sustainable logistics.

In prior studies, many scholars have conducted related research on the subject of cold chain logistics vehicle routing problems and electric vehicle routing problems separately, but few have merged the above two subjects. In response, this study innovatively designs an electric vehicle routing model for cold chain logistics with consideration of time-varying speeds, time-varying electricity prices, energy consumption and queues at charging stations to make it consistent with the real world.

Promoting electric vehicles (EVs) is an effective way to achieve carbon neutrality. If EVs are widely adopted, this will undoubtedly be good for the environment. The purpose of this study is to analyze the impact of network externalities and subsidy on the strategies of manufacturer under a carbon neutrality constraint.

In this paper, the authors propose a game-theoretic framework in an EVs supply chain consisting of a government, a manufacturer and a group of consumers. The authors examine two subsidy options and explain the choice of optimal strategies for government and manufacturer.

First, the authors find that the both network externalities of charging stations and government subsidy can promote the EV market. Second, under a relaxed carbon neutrality constraint, even if the government’s purchase subsidy investment is larger than the carbon emission reduction technology subsidy investment, the purchase subsidy policy is still optimal. Third, under a strict carbon neutrality constraint, when the cost coefficient of carbon emission reduction and the effectiveness of carbon emission reduction technology are larger, social welfare will instead decrease with the increase of the effectiveness of emission reduction technology and then, the manufacturer’s investment in carbon emission reduction technology is lower. In the extended model, the authors find the effectiveness of carbon emission reduction technology can also promote the EV market and social welfare (or consumer surplus) is the same whatever the subsidy strategy.

The network externalities of charging stations and the subsidy effect of the government have a superimposition effect on the promotion of EVs. When the network effect of charging stations is relatively strong, government can withdraw from the subsidized market. When the network effect of charging stations is relatively weak, government can intervene appropriately.

Comparing previous studies, this study reveals the impact of government intervention, network effects and carbon neutrality constraints on the EV supply chain. From a sustainability perspective, these insights are compelling for both EV manufacturers and policymakers.

The aim of this paper is to assemble an experimental solar‐based charging station for electric vehicles. This global system integrates a photovoltaic station, electric vehicles and a supervision base. The communication has been set up through a wireless network. This paper presents this project realized by different groups of foreign students working through an International Collaboration in Engineering Education.

The approach is based on connecting technical research with engineering education. For a few years, the need of further research on renewable energies has leaded to the initiation of several student projects at the university. A group of co‐operating foreign students working together within the framework of a technically innovative subject has been created through the international relations activity of the University of Artois, at IUT of Bethune (Institut Universitaire de Technologie), situated in the northern region of France.

A prototype of the recharging station has been built. The measures of the energetic performances showed a good efficiency. The data exchange through the wireless network is operating properly and a computer‐based supervising unit is responsible for the coordination of the station/vehicle control. The established international collaboration has demonstrated the possibility of carrying out common students' projects.

The originality of this paper is coming from the major subjects of sustainability such as renewable energies and transportation. A solar‐based station has been built and supplies electric vehicles. The wireless communication has been applied in order to perform control on long distances. This international collaboration is an innovative way for enhancing the collaboration performance in engineering education.