Battery Swapping Research Articles

Hybrid solar-electric cart efficiency enhancement: A bibliometric analysis

The present study involves the development of an electric cart, with future research aiming to enhance its efficiency by creating a hybrid solar-electric cart. To achieve this goal, a bibliometric analysis of electric vehicle (EV) batteries is required. This study aims to identify research gaps in EV batteries through Bibliometric Analysis, utilizing Scopus Analyze and VOSViewer to analyze 1,276 documents obtained from the Scopus database, including articles (49.7%), conference papers (43.3%) and various other publications such as reviews, book chapters, reports, short surveys, notes, books, erratum, and editorials. The analysis reveals a substantial surge in EV battery research and publications within the Scopus database since 2013, and this trend is projected to continue until the end of 2023. Based on researchers’ affiliations, Chinese institutions have ranked first in contributions, followed by institutions from the United States, India, the United Kingdom, and Canada. Surprisingly, the University of Warwick secured the top among research institutions, with the Beijing Institute of Technology claiming the second position. The VOSViewer analysis generated six keyword clusters relevant to EV battery research. Of particular interest is Cluster 5, which emphasizes the significance of battery management techniques, establishing efficient battery swapping stations, optimizing energy management strategies, and exploring the role of EV batteries in building intelligent grids. These gaps identified in Cluster 5 will become the focal point for future research, especially concerning efficiency enhancement through developing a hybrid battery system capable of a hybrid solar-electric cart.

Business Model Innovation of Off Grid Public Electric Vehicles Battery Swap Station with Solar Powered

Energy transition is Indonesia's national agenda to maintain energy security and realize the use of green energy. The use of electric vehicles (EVs) is one strategy to maintain primary energy security and support the reduction of carbon emissions. To support the growth of the EV ecosystem, Public Electric Vehicle Battery Swap Stations (Stasiun Penukaran Baterai Kendaraan Listrik Umum, SPBKLU) have been developed and installed in several locations. Currently, SPBKLU still uses electricity sources from the PLN (Perusahaan Listrik Negara, Indonesia’s electricity state-owned company) grid, where the majority of the PLN grid itself still relies on gas and coal power plants. Hence, this work proposed a PV-powered battery swap station and presented the Business Model Canvas and financial and SWOT analysis. Two business model schemes are proposed, the BPCOSP (Battery Provider, Cabinet Owner, Solar PV Provider) and BPCOSL (Battery Provider, Cabinet Owner, Solar PV Lease) schemes. From these two business schemes, the results of the financial feasibility analysis for the SPBKLU swap rate were obtained at IDR 18,241 for the BPCOSP scheme and IDR 21,500 for the BPCOSL scheme. From a SWOT analysis perspective, the BPCOSP and BPCOSL business schemes have the opportunity to increase the Solar PV business value chain and support government programs in achieving Net Zero Emissions. However, there are still weaknesses in terms of tariffs which are still not economical compared to the fuel costs of conventional two-wheeled vehicles and the current SPBKLU swap tariff which still uses electricity from the PLN grid.

Offering EV Battery Swapping as a Service: EV Manufacturers or Battery Producers?

Offering EV Battery Swapping as a Service: EV Manufacturers or Battery Producers?

Smart Battery Swapping Control for an Electric Motorcycle Fleet With Peak Time Based on Deep Reinforcement Learning

Smart Battery Swapping Control for an Electric Motorcycle Fleet With Peak Time Based on Deep Reinforcement Learning

Electrifying Urban Transportation: A Comparative Study of Battery Swap Stations and Charging Infrastructure for Taxis in Chicago

Electrifying Urban Transportation: A Comparative Study of Battery Swap Stations and Charging Infrastructure for Taxis in Chicago

Optimized Scheduling of an Integrated Energy System with an Electric Truck Battery Swapping Station

Currently, the focus of integrated energy system scheduling research is the multi-objective’s optimized operational strategies that take into account the economic benefits, carbon emissions, and new energy consumption rates of such systems. The integration of electric trucks with battery charging and swapping capabilities, along with their corresponding battery swapping stations, into an integrated energy system can not only optimize system operation, but also reduce investment costs associated with building energy storage equipment. This study first constructs an operational model for the electric trucks, as well as an electric truck battery swapping station, of the flexible charging and discharging; then, an optimized scheduling model of an integrated energy system is proposed, including an electric truck battery swapping station and using stepped carbon trading. On the basis of meeting the charging and battery swapping needs of electric trucks and coordinating the system’s electrical, thermal and cooling energies, the goal of the optimized scheduling model is to reduce the system’s carbon emissions, improve its economics, and optimize its ability to absorb new energy. Finally, a simulation model of the integrated energy system including an electric truck battery swapping station is built on the MATLAB platform, and commercial software package CPLEX is used to solve the model. In the calculation example, compared to the integrated energy system of disorderly charging and battery swapping of electric trucks and electric truck battery swapping stations, the proposed optimized model of the integrated energy system with the flexible charging and discharging of electric trucks and electric truck battery swapping stations reduces the operating costs by CNY 819, reduces carbon emissions by 414 kg, improves the utilization rate of wind and solar power by 0.3%, and fully utilizes wind and photovoltaic power. Therefore, the rational dispatching of the electric trucks and their battery swapping stations with flexible charging and discharging mentioned in this article can effectively optimize system operations.

Strategic investment in electric vehicle charging service: Fast charging or battery swapping

With the increasing adoption of electric vehicles (EVs), there is a growing need for public charging infrastructure. As a result, significant investments have been made in charging services, particularly, fast-charging (FC) and battery-swapping (BS) services. This paper examines the impact of technical and operational factors, as well as market conditions, on the pricing and profitability of each service to explore whether and how EV charging service providers should invest in these emerging charging services. The analysis with benchmark to private-use slow-charging (SC) services reveals that if the valley electricity price is high and the potential market size is small, lowering service costs does not make BS services a viable option. When the valley electricity price is low, reducing battery loss will not give FC services an advantage. However, in such scenarios, BS services can gain an edge by decreasing service costs. Interestingly, even if both SC and BS services are negatively affected by higher valley electricity prices, the impact on the profitability of BS services is more severe. Our results provide implications for the development of public EV charging service infrastructure. We recommend that implementing energy storage solutions can help alleviate the negative consequences of escalating valley electricity prices and wider peak–valley electricity price differences on BS services and FC services, respectively.

Optimal Placement of Battery Swapping Stations for Power Quality Improvement: A Novel Multi Techno-Economic Objective Function Approach

In recent years, battery swapping stations have become increasingly popular in smart energy networks. Its advantages include reducing the time required for recharging energy, balancing the grid’s load, and extending the battery’s lifespan. Despite efforts focused on the placement and operation of battery swapping stations (BSSs), there is still a lack of a comprehensive and systematic examination that covers all aspects of both the economic and technical aspects of the power network. This encompasses considerations such as power quality and reliability, particularly in terms of where these stations should be located. This paper introduces a novel framework for strategically positioning BSS within smart microgrids that integrate distributed energy resources (DERs). It takes into account various technical factors (such as reliability and power quality) and economic factors (like the cost of generation and operation), which have been overlooked in the previous research. To achieve this goal, a unique hybrid optimization strategy is developed, incorporating a combination of epsilon-constraint and lexicographic (DECL) optimization methods. This approach tackles a multi-objective challenge, treating factors like the number, locations, and sizes of BSS as independent variables, while operational costs and technical power quality metrics are considered dependent variables. To validate this approach, it is tested on standard benchmark distribution power networks such as IEEE 33, 69, and 118 bus systems. The simulation results, showcasing the strengths and capabilities of this innovative strategy, are compared to the findings of previous research studies.

A many-to-many pick-up and delivery problem under stochastic battery depletion of electric vehicles

ABSTRACT The study extends the traditional pick-up and delivery problems (PDPs) to address the specific challenges of urban logistics and electric vehicle (EV) adoption. These challenges include the limited range of EVs, energy consumption along the route, and uncertainty in traffic conditions. To overcome the limited range of EVs, the study includes battery swapping stations to ensure sufficient energy to complete delivery routes. Vehicle energy consumption is considered to reduce range anxiety and optimize energy use. The study also considers the unpredictability of traffic conditions that affect energy consumption and delivery schedules. To address these concerns, the study proposes an approximate Quadratic Chance-Constrained Mixed-Integer Programming (QC-MIP) model with a linear approximation, a constructive heuristic and a meta-heuristic. These quantitative models incorporate comprehensive EV energy estimation approaches, enabling more accurate energy predictions. The proposed approaches provide valuable insights and strategies for improving energy efficiency and delivery performance in urban logistics environments.

A novel collaborative electric vehicle routing problem with multiple prioritized time windows and time-dependent hybrid recharging

Due to global warming and environmental deterioration, the development of electric vehicles (EVs) is seen as a key measure to promote energy saving and emission reduction in logistics industries. However, EVs’ limited driving range and long recharging time make them unable to be widely applied in logistics distribution activities. Thus, this study establishes a model for a novel collaborative electric vehicle routing problem with multiple prioritized time windows and time-dependent hybrid recharging to address the above difficulties. The model quantifies and incorporates the priority of different time windows into costs to better satisfy customer demands while minimizing the total costs. A time-dependent hybrid recharging strategy that integrates three modes of in-station fast, in-station normal, and en-route battery swapping with collaborative mobile battery swapping vans (BSVs) is presented to reduce the impact of recharging time on route decision-making. The possible queuing time due to the limited capacity of recharging stations is considered to simulate the practical application scenarios. To effectively solve the complex model of synchronous optimization of EV and BSV routes, an extended adaptive large neighborhood search algorithm with two-dimensional coding scheme is proposed. In the proposed algorithm, several removal and insertion operators are integrated to effectively evolve the solutions, and the variable neighborhood descent algorithm is combined with local search operators to further improve the algorithmic performance. Comparison experiments were conducted to verify the effectiveness of the proposed algorithm by comparing with the other baseline algorithms.

Charging autonomous electric vehicle fleet for mobility-on-demand services: Plug in or swap out?

This paper compares two prevalent charging strategies for electric vehicles, plug-in charging and battery swapping, to investigate which charging strategy is superior for electric autonomous mobility-on-demand (AMoD) systems. To this end, we use a queueing-theoretic model to characterize the vehicle waiting time at charging stations and battery swapping stations, respectively. The model is integrated into an economic analysis of the electric AMoD system operated by a transportation network company (TNC), where the incentives of passengers, the charging/operating shift of TNC vehicles, the operational decisions of the platform, and the planning decisions of the government are captured. Overall, a bi-level optimization framework is proposed for charging infrastructure planning of the electric AMoD system. Based on the proposed framework, we compare the socio-economic performance of plug-in charging and battery swapping, and investigate how this comparison depends on the evolving charging technologies (such as charging speed, battery capacity, and infrastructure cost). At the planning level, we find that when choosing plug-in charging, increased charging speed leads to a transformation of infrastructure from sparsely distributed large stations to densely distributed small stations, while enlarged battery capacity transforms the infrastructure from densely distributed small stations to sparsely distributed large stations. On the other hand, when choosing battery swapping, both increased charging speed and enlarged battery capacity will lead to a smaller number of battery swapping stations. At the operational level, we find that improved charging speed leads to increased TNC profit when choosing plug-in charging, whereas improved charging speed may lead to smaller TNC profit under battery swapping. The above insights are validated through realistic numerical studies.

Risk-aware two-stage stochastic short-term planning of a hybrid multi-microgrid integrated with an all-in-one vehicle station and end-user cooperation

The interconnection between different energy networks considerably improves their technical and economical aspects; however, it increases the complexity of decisions. This paper optimizes the short-term planning of a hybrid multi-microgrid integrated with an all-in-one vehicle station composed of charging facilities, battery swapping slots, parking lots and hydrogen and gasoline refueling parts. In order to achieve the optimal operation in such a complex system and consider the influence of day-ahead and real-time decisions under uncertainties, a risk-aware two-stage stochastic programming is suggested in the presented study. In this regard, fluctuations of wind and solar units and different types of electrical and thermal loads and markets are modeled using various scenarios and their risk is measured by the downside risk method. In addition, the impact of end-user cooperation is analyzed and a sensitivity analysis is implemented. The simulations demonstrate that the proposed model can successfully specify the behavior of all components under a risk-averse strategy with maximum robustness, where the profit is decreased by 8.4 % to achieve an expected risk in profit equal to 0 $. The results also validate that although the all-in-one station can act as a bulk storage, a multi-directional energy injection is required to provide its high demand.

Battery electric vehicle energy demand in urban energy system modeling: A stochastic analysis of added flexibility for home charging and battery swapping stations

The successive upsurge in the penetration rate of battery electric vehicles (BEV) in the transport sector stresses electricity grids. Concurrently, batteries in BEVs add flexibility, while the reintroduction of battery swapping stations challenges home charging with regards to added flexibility. To address research gaps regarding the role of BEV charging systems in urban decarbonization pathways, this paper introduces an innovative modeling approach that reflects the implications of home charging and battery swapping stations in urban environments and accounts for the stochasticity of vehicle use.The developed method is demonstrated using a case study that comprises a sample residential area equipped with rooftop PV. The comparison of home charging and battery swapping stations shows that both approaches allow significant increases of self-consumption of locally provided electricity over conventional opportunistic home charging, with battery swapping stations evincing the highest increase in flexibility. This increase in added flexibility might, however, not justify a system-wide introduction of battery swapping stations for BEVs, as required surplus batteries and industry-wide standardization entail added efforts over home charging.Policy recommendations derived by this work support building regulations regarding the installation of charging stations and the utilization of PV rooftop potentials considering the anticipated market penetration of BEVs and the possibility to share electricity within local energy hubs.

Empowering the Capillary of the Urban Daily Commute: Battery Deployment Analysis for the Locker-Based E-bike Battery Swapping

In densely populated Asian countries, e-bikes have become a new supernova in daily urban transportation. To facilitate the operations of e-bike-based mobility, the present paper studies the management of the battery deployment for the e-bike battery-swapping system, where the unique features of e-bike riding are considered. Given the pedal-assisted mode, e-bike users could abandon waiting and return to the station later on without too much range anxiety. However, because of the time-varying nature of the customer arrival and the complicated user behaviors, the battery quantity at each station is altered to guarantee the designated service level. However, little research has been done on the operations management of the e-bike battery-swapping system. To bridge the gap, we propose a nonstationary queueing network model to characterize the customer behaviors during the battery-swapping service. Then we develop a closed-form delayed infinite-server fluid approximation for the battery deployment of the one-time-loop scenario under various quality-of-service targets. In addition, we handle the infinite-time-loop scenario with the simulation-based iterative staffing algorithm. In the simulation study, we observe that the proposed battery deployment algorithms can help stabilize the system performance in terms of abandonment probability and expected delay in the face of time-varying demand and complex customer behaviors. Moreover, we reveal that the number of return loops correlates with the service level targets on the battery deployment decision. Furthermore, a time gap exists between the demand and the optimal battery deployment, making proactive battery management in the system possible. Funding: This work was supported by the National Natural Science Foundation of China [Grants 72271222, 71871203, 71872093, 72271137, L1924063], and the National Social Science Fund of China [Grant 21&ZD128]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2022.0132 .

A study on the demographic differences in visual impact assessments of the external space of electric vehicle battery swapping stations

The construction of electric vehicle (EV) battery swapping stations (BSS), which exerts an increasingly significant impact on urban landscapes. In addition, the external space of BSS is an important means to display corporate image and brand publicity. In this experiment, a sample of nine representative BSS in China, characterized by diverse architectural forms, was selected for the examination of their exterior spaces. The study focused on the physical factors of the BSS, specifically the exterior contour, number and position of entrances, façade material, height-width ratio of front elevation, logo area ratio, and hue as key factors under investigation. Meanwhile, five demographic features, namely, gender, age, education level, EV owner or potential owner, and income level, were set as variables to study the influence of the six physical factors of external space on people's visual impact assessment. The photo stimulation method was used in this experiment. The results show that the above six physical factors affect people's visual impact assessment of the external space of BSS, and people with different demographic features render different visual impact assessments. Therefore, we propose several design recommendations for BSS exterior spaces. In BSS exterior space design, greater consideration should be given to using vertical facade aspect ratios between 1/3 and 1/2, facades combining metal and glass, smaller logo area proportions, and designs combining warm and neutral color tones to meet the visual preferences of a broader audience. Different exterior design schemes should also be adopted when BSSs are targeted at different primary user groups.

Behavioral-alike model-driven for the power demand of battery swapping stations in supporting two and three-wheeled electrification in the new capital city of Indonesia

An integrated transportation system envisages (near) zero-emission for public and private vehicles toward sustainable and accessible urban mobility as a committed strategy for Indonesia’s new capital city (INCC). Electric mobility (e-mobility) is therefore aligned with the government’s climate mitigation commitment. Proposing an evidence-based solution for the refueling approach, battery swapping technology is considered due to its modularity of ‘plug and play’ (PnP) and cost-effective upfront investment, i.e., modular battery swapping point (MBSP) for two|three-wheeled e-mobility. However, due to the uncertainty and insufficient preliminary data on the number of rolled-out units, intended location, and allocation, the planning process of the supporting infrastructure in the early stages of transition is mostly hampered. Meanwhile, using common assumptions or averaging measures may lead to substantial disparities, risking the initiatives for cost-shared infrastructure spending. Therefore, constructing a framework model of a behavior-alike of MBSP is imperative. The framework has a distinct advantage in generating the time series of power demand profiles over the unknown parameters, i.e., the battery pack (BP) properties, user tendencies of fetching and filling cycles, and tailor-made intentions exploiting the predictive Monte Carlo (PMC) method. This work aims to contribute insight to stakeholders, policymakers, and operators and disseminate relevant planning research.

Policy analysis of electric vehicle infrastructure supporting sustainable energy use

The Presidential Regulation of the Republic of Indonesia 55 of 2019 concerning the Acceleration of the Battery-Based Electric Vehicle (EV) Program for transportation aims to provide direction, foundation, and legal certainty in the implementation of the acceleration of the battery-based electric motor vehicle program in Indonesia, one of which is the strategy of providing electric charging infrastructure. This policy had not fully significant impact on the provision of electric vehicle charging infrastructure, wherein 2021, the provision of EV charging facilities has reached approximately only 74 charging facilities, spread across 188 locations; this condition is still far from the target set by the government, expected about 168 charging facilities units in 2021-2031. The research evaluates existing policies as a reference for preparing policy recommendations to accelerate the provision of EV charging infrastructure. Research has shown that the adoption of electric vehicles is constrained, one of which is the need for more charging station availability of charging stations and their distribution. The government needs to provide incentives for domestic manufacturers of charging stations and battery swapping stations and instruct state-owned enterprises to accelerate the adoption of electric to provide charging station infrastructure.

Structural Charging and Replenishment Policies for Battery Swapping Charging System Operation Under Uncertainty

Structural Charging and Replenishment Policies for Battery Swapping Charging System Operation Under Uncertainty

Analysis of market readiness for the safe use of electric vehicles in Indonesia post-pandemic era

The pandemic has changed the trend of transportation, with many people avoiding mass transit. Facing the impact of the pandemic, people’s activities will gradually return to how they were before the pandemic, and the tendency for people to still use private vehicles as a form of mobility. Socio-economic conditions in Indonesia, the use of motorcycles as a favorite has increased significantly. This results in a more significant greenhouse effect due to exhaust emissions. Electric motorcycle charging station products in the form of Battery Swapping Station (BSS) research results from BPPT (Agency for the Assessment and Application of Technology) answer the problem of availability of the main components of electric vehicle batteries and safety reasons. This article aims to analyze the market readiness of BPPT BSS products and develop strategies to be accepted by the market. The methodology used quantitative descriptive analysis to identify data collection results. Market analysis based on marketing strategy to determine the downstream of BPPT research products. The result of this article is that a potential market can be identified and a marketing strategy to build a downstream ecosystem for research products.

Tri-objective Stochastic Model to Optimize Location and Sizing of Scooter Battery Swapping Station

The optimal locations and sizing of scooter Battery Swap Stations (BSSs) can promote the use of battery-swapping scooters to make cities more environmentally sustainable. Few studies investigated the optimal allocation of BSSs for scooters, especially for tri-objective optimization. Hence, this study presents the proposed Stochastic Tri-objective Grid-based Scooter BSS Allocation Model (STGSBSSAM) based on our previous studies. STGSBSSAM used ModelBuilder to semi-automatically perform data pre-processing and display the layout of the allocation of BSSs. Thus, deep learning algorithm was used to detect the flow of traffic and compensate the insufficiency of data. Also, different from our previous studies, the time slots of battery swapping demands were assumed to be highly correlated with the hourly traffic flow of different land-use types.Based on the results, STGSBSSAM could better allocate BSSs. Also, the rule of equal allocation was better than the rule of inverse distance in terms of the battery allocation rule. Meanwhile, in order to make the optimized allocation of scooters beneficial, the investigation could be made into the three objectives as a whole. The actual allocation of BSSs also indirectly validated the effectiveness of this STGSBSSAM methodology.