Abstract

The population of electric vehicles (EVs) has grown rapidly over the past decade due to the development of EV technologies, battery materials, charger facilities, and public charging services. Many governments have implemented plans to ban fossil fuel vehicles considering the significance of EVs in reducing greenhouse gas emissions. However, due to the battery material characteristics and charger power limitations, the EV charging process requires more time than is needed to fill a non-EV with fuel at a gasoline station, causing drivers to experience range anxiety and impeding the promotion of EVs. Hence, the battery swapping station (BSS) model has been proposed as an alternative method. Recently, researchers have studied the BSS approach by proposing various operation systems and optimization methods, and BSS service operators have successfully implemented swapping at commercial and private stations. This paper reviews the state-of-the-art BSS literature and business models, where the BSS offers a recharged battery to an incoming EV with a low state-of-charge. First, four operation modes are presented: a single BSS, multiple BSSs, an integrated BSS and battery charging station (BCS), and multiple BSSs and BCSs. Then, the BSS decision scenarios are surveyed in relation to five operational areas, i.e., charging schedule, service policy, construction and planning, dispatching and routing, and power management, where the scenarios are compared in terms of the BSS mode, decision maker, EV category, number of battery types, vehicle to grid, and focus and objective. Finally, the survey concludes with a discussion of several future research directions for EV BSSs.

Highlights

  • E LECTRIC vehicles (EVs) have developed rapidly over the past decade, and by the end of 2019, the EV population had grown to 7.2 million globally, compared with only 17,000 in 2010 [1]

  • To understand the battery swapping station (BSS) operation models, the present investigation first focuses on the two types of stations (BSS/battery charging station (BCS)) and the number of BSSs and BCSs in the business models; these can be classified into four modes considering different BSS and BCS combinations, i.e., a single BSS, multiple BSSs, an integrated BSS and BCS, and multiple BSSs and BCSs

  • The effectiveness of the proposed model is evaluated with an IEEE 30-bus test system, and the results show that the model is viable and that the proposed algorithm outperforms the baseline methods

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Summary

A Survey of Battery Swapping Stations for Electric Vehicles

Abstract— The population of electric vehicles (EVs) has grown rapidly over the past decade due to the development of EV technologies, battery materials, charger facilities, and public charging services. Due to the battery material characteristics and charger power limitations, the EV charging process requires more time than is needed to fill a non-EV with fuel at a gasoline station, causing drivers to experience range anxiety and impeding the promotion of EVs. the battery swapping station (BSS) model has been proposed as an alternative method. Researchers have studied the BSS approach by proposing various operation systems and optimization methods, and BSS service operators have successfully implemented swapping at commercial and private stations. Four operation modes are presented: a single BSS, multiple BSSs, an integrated BSS and battery charging station (BCS), and multiple BSSs and BCSs. the BSS decision scenarios are surveyed in relation to five operational areas, i.e., charging schedule, service policy, construction and planning, dispatching and routing, and power management, where the scenarios are compared in terms of the BSS mode, decision maker, EV category, number of battery types, vehicle to grid, and focus and objective.

INTRODUCTION
BSS MODES
Single BSS
Multiple BSSs
Integrated BSS and BCS
Multiple BSSs and BCSs
BSS DECISION SCENARIOS
Charging Schedule
Service Policy
Construction and Planning
Dispatching and Routing
Power Management
RESEARCH DIRECTIONS
Extended BSS Models
Multiple Scenarios
Collaborative Decision
Flexible Decision Structure
Findings
CONCLUSION
Full Text
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