由於科技的飛速發展，交通運輸極大地改善了人類的生活方式。隨著化石燃料的枯竭和環保意識的抬頭，交通工具的電動化勢在必行。電動機車被認為是解決化石燃料短缺和減少碳排放的關鍵技術之一。為了滿足電動機車的電池更換需求與維持系統運行的一致性，提出了具有本地充電模式的電池交換站系統。
在我們的研究中，我們研究了專用於電動機車的具有本地充電模式的電池交換站系統的排隊模型。具有本地充電模式的電池交換站系統由交換子系統與充電子系統組成，當電動車車主在交換子系統將低電量電池更換為充滿電的電池後便會離開此系統，而被更換下來的低電量電池將會透過本地充電模式在交換子系統內充電。電動車車主無需花時間等待電池充滿電。電動機車分為兩個類別，每輛第一類別的電動機車的電池需求量是一個，而每輛第二類別的電動機車的電池需求量是兩個。電動機車車主可能會因為在等待時感到不耐煩而提早離開系統。首先，我們推導所考慮系統的解析模型。接下來，我們使用迭代演算法來計算穩態機率分佈和各種我們感興趣的效能指標。第二，我們探討了受不同系統參數影響的性能變化，例如電動機車的抵達速率和不耐煩率。第三，我們撰寫了模擬程式，來確認解析模型中結果的準確性。最後，我們研究了電池充電站中不同的電池充電時間的機率分佈，並探討了它們對性能變化的影響。

Transportation has greatly improved human’s lifestyle because of the rapid development of technology. With the depletion of fossil fuels and the rise of environmental awareness, the electrification of transportation is imperative. Electric scooters (ESs) are proposed to be one of the key technologies to solve the fossil-fuel scarcity and reduce carbon emissions. In order to fulfill the battery swapping demands of ESs and ensure the consistent operation of ESs, the idea of the battery swapping station (BSS) with locally-charging mode (LCM) system is proposed.
In our work, we study the queueing models of the BSS with LCM system for ESs. The BSS with LCM system consists of the swapping subsystem and the charging subsystem. Once ES owners swap a low battery for a fully charged battery via swapping subsystem, the ES owners leave the system and the low battery is charged in the charging subsystem through the function of LCM. ES owners do not need to spend time on waiting a battery to be fully charged. There are two classes of ESs, class-1 and class-2 ESs. The battery requirement of each class-1 ES is one, and that of each class-2 ES is two. The ESs owner may leave the system without completing the swapping service due to impatience. First, we derive the analytical models for the considered systems. Then, we find the steady-state probability distribution and calculate various interested performance measures by an iterative algorithm. Second, we explore the performance variation influenced with different system parameters, e.g., the arrival rate of ESs and the impatience rate of ESs. Third, we write the simulation program to show the accuracy of analytical models. Finally, different probability distributions of battery charging time are studied, and their impact on performance variation are explored.

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