Charge Type Research Articles

A Simulated Annealing Approach to the Scheduling of Battery-Electric Bus Charging

With an increasing adoption of battery-electric bus (BEB) fleets, developing a reliable charging schedule is vital to a successful migration from their fossil fuel counterparts. In this paper, a simulated annealing (SA) implementation is developed for a charge scheduling framework for a fixed-schedule fleet of BEBs that utilizes a proportional battery dynamics model, accounts for multiple charger types, allows partial charging, and further considers the total energy consumed by the schedule as well as peak power use. Two generation mechanisms are implemented for the SA algorithm, denoted as the “quick” and “heuristic” implementations, respectively. The model validity is demonstrated by utilizing a set of routes sampled from the Utah Transit Authority (UTA) and comparing the results against two other models: the BPAP and the Qin-Modified. The results presented show that both SA techniques offer a means of generating operationally feasible schedules quickly while minimizing the cost of operation and considering battery health.

Electrification of marinas in Stockholm: Optimizing charging infrastructure for electric boats

The adoption of electric boats faces challenges due to range anxiety. This study addresses this challenge by optimizing the allocation of slow and fast chargers for public electric boat charging stations. A mixed-integer linear programming model was developed to minimize charging infrastructure and electricity costs while meeting the demand of each participating marina in Stockholm, Sweden. The model identified three distinct categories of stations based on the optimal charger allocation: stations prioritizing fast chargers (e.g., Sickla station with 13 fast and 8 slow chargers for 208 boats), stations prioritizing slow chargers (e.g., Kungsholmen station with 2 slow and 3 fast chargers for 50 boats), and stations with an equal number of both charger types (Äppelviken station with 2 each for 25 boats). This study found out that all stations will achieve financial viability within seven years, indicating a promising return on investment. This study also proposes a novel way for optimizing charger allocation in electric boat charging infrastructure, promoting wider electric boat adoption.

Charging infrastructure assessment for shared autonomous electric vehicles in 374 small and medium-sized urban areas: An agent-based simulation approach

This research examines the use of Shared Autonomous Electric Vehicles (SAEVs) in 374 U.S. small and medium-sized urban areas, focusing on fleet and infrastructure needs through agent-based simulations. It assesses metrics such as fleet size, trips per vehicle, and charging station requirements, considering two charger types: Level 2 and Level 3. The findings show significant spatial differences in SAEV operations and infrastructure across these cities. Statistical analysis links these variations to regional road networks and travel patterns. The study finds Level 3 chargers more efficient, requiring fewer stations and enabling more trips per vehicle compared to Level 2 chargers. Furthermore, Level 3 chargers exhibit a greater number of trips per SAEV and a higher ratio of vehicles to charging stations. These findings highlight the significance of considering charging infrastructure characteristics to optimize SAEV fleet performance and promote sustainable transportation systems in urban areas. This study significantly contributes by identifying the spatial variation and correlates of the SAEVs' operational and charging infrastructural performance. Policymakers, urban planners, and transportation service providers can leverage these insights to design and implement effective charging infrastructure for SAEV fleets, thereby advancing the transition to cleaner and more efficient mobility solutions.

Robo-Chargers: Optimal Operation and Planning of a Robotic Charging System to Alleviate Overstay

Charging infrastructure availability is a major concern for plug-in electric vehicle users. Nowadays, the limited public chargers are commonly occupied by vehicles which have already been fully charged. Such phenomenon, known as overstay, hinders other vehicles' accessibility to charging resources. In this paper, we analyze a charging facility innovation to tackle the challenge of overstay, leveraging the idea of Robo-chargers - automated chargers that can rotate in a charging station and proactively plug or unplug plug-in electric vehicles. We formalize an operation model for stations incorporating Fixed-chargers and Robo-chargers. Optimal scheduling can be solved with the recognition of the combinatorial nature of vehicle-charger assignments, charging dynamics, and customer waiting behaviors. Then, with operation model nested, we develop a planning model to guide economical investment on both types of chargers so that the total cost of ownership is minimized. In the planning phase, it further considers charging demand variances and service capacity requirements. In this paper, we provide systematic techno-economical methods to evaluate if introducing Robo-chargers is beneficial given a specific application scenario. Comprehensive sensitivity analysis based on real-world data highlights the advantages of Robo-chargers, especially in a scenario where overstay is severe. Validations also suggest the tractability of operation model and robustness of planning results for real-time application under reasonable model mismatches, uncertainties and disturbances.

An exact algorithm for maximum electric vehicle flow coverage problem with heterogeneous chargers, nonlinear charging time and route deviations

Typical electric vehicles (EVs) should be recharged multiple times to reach a long distance due to the limited travel ranges. The EV flow covering problem determines the locations of charging stations to maximize the “covered” OD flows, respecting a given budget for the new charging stations. This paper proposes an exact algorithm for solving the problem by considering the heterogeneous EV chargers, nonlinear charging time, and route deviations from the shortest distance paths. We develop an exact Benders decomposition-based algorithm, in which the Benders subproblem utilizes a nested cut-generation via a customized labeling algorithm. Two methods for solving the Benders subproblem are developed, which are combined to accelerate the Benders cut generation. In addition, we present a heuristic algorithm based on the proposed exact algorithm for the larger-sized problems. The computational results show that the proposed algorithm could solve real-life problems. Especially, the heuristic algorithm could solve problems up to 339 nodes and 500 km of the EV’s travel range. The extensive computational study shows that addressing the multiple charger types, the charging time, and the deviation routes can be crucial to provide realistic charging infrastructure for EVs.

An analytical framework for assessing equitable access to public electric vehicle chargers

Inequitable distribution of public electric vehicle (EV) charging facilitiesmay result in disparities in charging accessibility, potentially impeding the uptake of EVs. In response, this paper proposes an analytical framework to assess the accessibility-based equity of public EV charging infrastructure systematically, using Hong Kong (HK) as the study area. The results demonstrated severe spatial inequity of charging facilities in central, north, and southwest HK. Meanwhile, the Gini index of all public EV charger types for the total population was 0.751, and the indices for low-income, low-education level, and government-funded housing subgroups were 0.791, 0.809, and 0.893, respectively. These indicated considerable horizontal and vertical inequity from a statistical perspective. Furthermore, age, education level, family structure, and housing type were identified as significant socio-demographic characteristics correlated to the accessibility-based equity of public EV charging infrastructure in HK. These findings are expected to be useful for future policymaking and infrastructure planning.

A new approach based on hybrid ant colony optimization-artificial bee colony algorithm for multi-objective electric vehicle routing problems

In real-life, routing plans try to optimize multiple objectives without relying on just one. So, this paper introduces three multi-objective electric vehicle routing problems (MOEVRP) that consider different charging strategies and electric vehicle (EV) charger types while optimizing five conflicting objectives: a total minimization cost of recharging, the number of vehicles required, a total travel distance, load-dependent energy consumption, and the total number of charging stations required. We develop a new hierarchical approach consisting of two phases: a Hybrid Ant Colony Optimization (HACO) and an Artificial Bee Colony Algorithm (ABCA). In the first phase, an initial solution is obtained using a HACO that integrates local search algorithms and simulated annealing (SA) to reduce the solution time. Then in the second phase, the problem is solved using an ABCA considering the initial solution obtained from the first phase. Using the proposed HACO-ABCA as the search engine, two posteriors’ methods, namely the weighted-sum method (WSM) and the conic method (CM), are applied to scalarize the five objectives. The effectiveness of the proposed hierarchical approach is examined on well-known test-based instances and obtained the best new results in most instances. Additionally, the proposed solution is applied to a real-life case study. The results show that multi-objective traditional methods give more effective results than multi-objective evolutionary algorithms, regardless of the MOEVRP problem type. We can also conclude that the partial recharge and multiple recharge technology options can significantly improve the route decisions of logistic companies.

Queueing-based formulation model in a public transit network considering energy storage technology and demand charges

Battery Electric Buses (BEBs) are quickly emerging as a viable option for dramatically lowering transportation-related emissions. Finding optimal locations of charging stations for BEBs can facilitate the development of electric transit networks that provide continuous services. Using fast charging along with Energy Storage (ES) charger technologies has also garnered attention to mitigate the peak power demand. A consensus regarding two types of chargers may result in more investment in the electric transit network, which resulted in considering installing fast chargers in designing an electric transit network. While this study aims to consider two types of fast- and ES-chargers, along with demand charges and waiting times at terminal stops simultaneously, to minimize the total costs of the electric transit network. The queuing model integrated with the Mixed-Integer Non-Linear Programming (MINLP) model is proposed to locate the optimal placements of charging stations in the electric transit network. To validate the model, a benchmark Mumford0 network is applied. Results indicated that the proposed charging location model could efficiently determine optimal locations of fast- and ES-chargers across the electric transit network. Also, the results confirmed that considering ES chargers could significantly save 16.6 % of the total costs of the Mumford0 transit network and reduce the total demand charge imposed on the network by the fast charger. More interestingly, by purchasing more chargers, transit agencies can decide on an acceptable waiting time that would be comfortable for BEBs arriving at terminal stops.

Charging forward: deploying EV infrastructure for Uber and Lyft in California

With recent policies such as the Clean Miles Standard in California and Lyft’s announcement to reach 100% electric vehicles (EVs) by 2030, the electrification of vehicles on ride-hailing platforms is inevitable. The impacts of this transition are not well-studied. This work attempts to examine the infrastructure deployment necessary to meet demand from electric vehicles being driven on Uber and Lyft platforms using empirical trip data from the two services. We develop the Widespread Infrastructure for Ride-hail EV Deployment model to examine a set of case studies for charger installation in San Diego, Los Angeles, and the San Francisco Bay Area. We also conduct a set of sensitivity scenarios to measure the tradeoff between explicit costs of infrastructure versus weighting factors for valuing the time for drivers to travel to a charger (from where they are providing rides) and valuing the rate of charging (to minimize the amount of time that drivers have to wait to charge their vehicle). There are several notable findings from our study: (1) DC fast charging infrastructure is the dominant charger type necessary to meet ride-hailing demand, (2) shifting to overnight charging behavior that places less emphasis on daytime public charging can significantly reduce costs, and (3) the necessary ratio of chargers is approximately 10 times higher for EVs in Uber and Lyft compared to chargers for the general EV owning public.

A comprehensive review on EV power converter topologies charger types infrastructure and communication techniques

The energy transition is a crucial effort from many sectors and levels to create a more integrated, carbon-neutral society. More than 20% of all greenhouse gas emissions are attributed to the transportation sector, predominantly concentrated in metropolitan areas. As a result, various technological hurdles are encountered and overcome. It facilitates the adoption of electric vehicles (EVs) run on renewable energy, making them a practical option in the fight against climate change and the completion of the energy revolution. Recent developments suggest that EVs will replace internal combustion engine (ICE) during the next few months. The EV either gets all of its power from batteries and ultra capacitors or some of it from both. In a plug-in electric vehicle, the battery or ultra-capacitor is charged by an AC supply connected to a grid line. In a hybrid electric vehicle, the ICE charges the battery or ultra-capacitor. Regenerative braking is another way to charge the battery from the traction motor. In a plug-in electric vehicle, the energy from of the battery or ultra-capacitor is put back into the AC grid line. Electronic converters are essential to converting power from the grid line to the traction motor and back again. This paper examines the current state of the electric vehicle market throughout the world and its potential future developments. Power electronics converters (PEC) and energy storage devices significantly impact electric vehicles’ efficiency. Furthermore, general opinions about EVs are soon in this sector, as well as research topics that are still open to industry and University researchers.

A space–time-energy flow-based integer programming model to design and operate a regional shared automated electric vehicle (SAEV) system and corresponding charging network

Shared automated vehicles are expected to be part of the supply of transportation systems in the future. Parallel to this evolution, there is the rapid penetration of battery electric vehicles (BEVs). The limitations in battery capacity and charging speed of BEVs can influence the planning and operation of shared automated electric vehicle (SAEV) systems. The design of such systems needs to include these limitations so that their viability is properly estimated. In this paper, we develop a space–time-energy flow-based integer programming (IP) model in support of the strategic design of a regional SAEV system. The proposed approach optimizes the fleet (size and composition) and charging facilities (number and location), while explicitly accounting for vehicle operations in aggregated terms (including movements with users, relocations, and charging times). The model is used to assess the impact of vehicle range and different types of chargers in the optimal design of an interurban SAEV transport system in the center of Portugal. Results show a reduction in profit as the vehicle range increases. In regards to energy, it is observed that the adoption of long-range vehicles reduces the energy spent in relocations, and increases the amount of energy charged at a lower price. Additionally, it is found that a system with long-range vehicles does not take advantage of having fast chargers. Concerning the chargers’ optimal location, systems using short-range vehicles have more chargers close to the main commuter trips attracting cities, while systems with long-range vehicles have the chargers nearby the homes of users.

E- VEHICLE CHARGING SYSTEM (CHARGING METHODS)

—As we all know that today the era is changing IC engine or Petrol engine vehicles to the electrical vehicles and their demand is increased day by day which is also increase the demand of charging station . The demand of electrical vehicles is increased because they help as t reduce the fuel consumption and help in improve the environment and also create less noise pollution . There are many advantage of E- vehicles. As a demand is increased so we have to focus on the improvement in the electrical vehicles battery life because we know that the battery is heart of an E- vehicle. We have to focus on these issues , development of efficient charging system , charging power level ,quality of supply used for electrical vehicles, different types of chargers , effect of load on the E- vehicles etc. Basically, In this article we talk about the charging of E-vehicles like how a electrical vehicle is charged ,method of charging ,type of chargers are used and which type of battery are used.

Optimized Design of a Wireless Charger Prototype for an e-Scooter

Individual mobility vehicles are revolutionizing transportation in the urban environment. Among them, e-scooters are one of the fastest growing vehicles. However, these vehicles have some drawbacks such as incompatibility among different chargers or reduced autonomy, which especially affects e-scooters rental. Wireless charging is presented as a solution to these drawbacks since it allows the batteries to be charged without user intervention. This paper addresses the design process and implementation details related to a magnetic-resonance charger for an e-scooter. In contrast to the previous works, we present a comprehensive approach that addresses the design of the coil topology, the dimensions of the ferrite tiles, the definition of the gap and the optimised control for a CC-CV charge. The main contribution of the work is the consideration of all these issues jointly while we also take into account the vehicle’s materials and structure for an accurate design and implementation. The dimensions of the vehicle impose a strong restriction on the coil design. Therefore, a detailed analysis about the location of the secondary and primary coils in a real e-scooter is executed with Ansys Maxwell. The study about the geometries of ferrite tiles is also performed considering the particularities of this type of vehicle. This study led to an optimal solution for the coil geometries and ferrite placement that minimizes the costs. The proposed system has been validated with the implementation of a real prototype of 100 W, to which a CC-CV control has been incorporated to achieve a safe charge for different battery states. The control can be easily adapted for a wide range of e-scooters. In this way, the use of this type of chargers on public installations can be maximized.

A Comprehensive Review of Machine-Integrated Electric Vehicle Chargers

Electric Vehicles are becoming increasingly popular due to their environment friendly operation. As the demand for electric vehicles increases, it has become quite important to explore their charging strategies. Since charging and traction do not normally occur simultaneously and the power electronics converters for both operations have some similarities, the practice of integrating both charging and traction systems is becoming popular. These types of chargers are termed ‘Integrated Chargers’. The aim of this paper is to review the available literature on the integrated chargers and present a critical analysis of the pros and cons of different integrated charging architectures. Integrated chargers for electric vehicles with three-phase permanent magnet synchronous machines, multi-phase machines and switched reluctance machines were compared. The challenges with the published integrated chargers and the future aspect of the work were been discussed.

Designing a sustainable logistics network for hazardous medical waste collection a case study in COVID-19 pandemic

The process of collecting and transporting hazardous medical waste poses a potential threat to the environment and public safety. Furthermore, the waste management system faces higher transportation costs due to the increasing human activities related to rapid population growth. The absence of an efficient and safe logistics network for the timely collection and transportation of hazardous wastes may have negative effects on the environment and public health. Therefore, more sustainable transportation of hazardous waste services is a necessity This paper attempts to design a sustainable network for hazardous medical waste collection services during the COVID-19 pandemic. An electric medical waste collection vehicle routing problem is introduced to construct optimal routes and rosters for a fleet of electric vehicles as well as cover their choice of charging technologies, times and locations. This problem allows us to minimize the health risk of hazardous medical waste while providing cost-effective, zero-emission waste management logistics. Therefore, this problem covers environmental and economic objectives to achieve sustainable development. An effective heuristic that covers adaptive large neighbourhood search and a local search is designed to deal with the complex problem. A series of extensive computational experiments is carried out using real-life benchmark instances to assess the performance of the algorithm. A sensitivity analysis is also conducted to investigate the effect of multiple charger types on the cost and risk objectives. The experiment results indicate that mixed-use of different charger types can reduce the total energy cost and transport risk compared to the case of using only a single charger.

Market Review and Technical Properties of Electric Vehicles in Germany

Electromobility has grown rapidly, and especially in China, Europe, and the United States. Within Europe, Germany is the largest market. Our goal in this paper is to provide a data-driven overview of the key data, including the number of vehicles sold, place of registration, battery capacity, and charging power, in Germany. The results were generated by linking car-registration data with the technical details for each car model. We identified more than 84% of the battery electric vehicles in the fleet, but the uncertainty is larger for plug-in hybrid electric vehicles. The number of sold electric vehicles doubled annually over the last two years. Simultaneously, the battery capacity and charging power per vehicle are rising. Combined, the two effects cause the cumulative battery capacity and charging power of the fleet to grow at an even faster pace. The battery energy built into electric vehicles in Germany registered on 1 August 2022 was 50.5 GWh, of which 9.5 GWh belonged to plug-in hybrids. The combined charging system became the dominant charger type for fast charging in Germany, and only 2% of the vehicle fleet used the competing CHAdeMO standard. To allow fellow researchers to work with the data, we published them free of charge on our data platform mobility charts, and we update the data monthly.

Different Approaches for a Goal: The Electrical Bus-EMT Madrid as a Successful Case Study

A deep review of the state of the electromobility in urban public transport by bus was conducted from all different charging strategies, types of chargers, and e-buses with a general overview and SWOT analysis. A review of five case studies worldwide was also conducted and a real case study with real data was shown in depth: EMT Madrid, where all chargers and charging systems were developed in a single operation center. Total Cost of Ownership (TCO) from the literature and from the case study for e-buses were shown as compared with different bus technologies.

Charging infrastructure planning for ride-sourcing electric vehicles considering drivers’ value of time

ABSTRACT A reliable-charging network is urgently demanded to support electrified ride-sourcing services due to their shorter dwell time, longer daily vehicle miles traveled, and concerns of sacrificing revenue for charging activities. We developed an integer programming (IP) model for the optimal allocation of charging stations and charging plugs to minimize the total investment costs and spatio-temporal varying drivers’ value of time (VOT) for charging activities. The trip chain data of the RideAustin ride-sourcing services have been used as a test case, based on which we estimated the charging needs of ride-sourcing EVs and identified candidate charging locations to fulfill the daily travel needs of ride-sourcing drivers. Through numerical study and sensitivity analyses, we analyze the impacts of different charger types, fleet sizes, government incentives, and VOT considerations on the optimal investment plans and system costs, and show the importance of considering ride-sourcing drivers’ VOT into charging infrastructure planning.

Power Converter Topologies for Grid-Tied Solar Photovoltaic (PV) Powered Electric Vehicles (EVs)—A Comprehensive Review

The transport sector generates a considerable amount of greenhouse gas (GHG) emissions worldwide, especially road transport, which accounts for 95% of the total GHGs. It is commonly known that Electric vehicles (EVs) can significantly reduce GHG emissions. However, with a fossil-fuel-based power generation system, EVs can produce more GHGs and therefore cannot be regarded as purely environmentally friendly. As a result, renewable energy sources (RES) such as photovoltaic (PV) can be integrated into the EV charging infrastructure to improve the sustainability of the transportation system. This paper reviews the state-of-the-art literature on power electronics converter systems, which interface with the utility grid, PV systems, and EVs. Comparisons are made in terms of their topologies, isolation, power and voltage ranges, efficiency, and bi-directional power capability for V2G operation. Specific attention is devoted to bidirectional isolated and non-isolated EV-interfaced converters in non-integrated architectures. A brief description of EV charger types, their power levels, and standards is provided. It is anticipated that the studies and comparisons in this paper would be advantageous as an all-in-one source of information for researchers seeking information related to EV charging infrastructures.

Electric Bus Charging Scheduling for a Single Public Transport Route Considering Nonlinear Charging Profile and Battery Degradation Effect

This study deals with a fundamental electric bus charging scheduling (EBCS) problem for a single public transport route by considering the nonlinear electric bus (EB) charging profile and battery degradation effect under the partial charging policy, which allows EBs to be charged any length of time and make good use of dwell times between consecutive trips. Given a group of trip tasks for an EB fleet and charger type, the problem is to minimize the total cost for a public transport operator of providing peak-hour bus services for a focal single public transport route by simultaneously determining the EB-to-trip assignment and EB charging schedule with charger type choice subject to the necessary EB operational constraints. We first build a mixed-integer nonlinear and nonconvex programming (MINL&NCP) model for the EBCS problem. To effectively solve the MINL&NCP model to global optimality, we subsequently develop two mixed-integer linear programming (MILP) models by means of linearization and approximation techniques. To accelerate the solution efficiency, we further create three families of valid inequalities depending on the unique features of the problem. A real case study based on the No.171 bus route in Singapore is conducted to demonstrate the performance of the developed models. Extensive numerical experiments are carried out to seek valuable managerial insights for public transport operators.