電動汽車充電站自動引導APP建置

隨著國內的交通建設及運輸系統的蓬勃發展，以及網際網路與智慧型行動裝置的普及，用路人開始利用多元的交通資訊進行旅行決策。為了改善日益嚴重的環境問題，逐漸發展高能源效率、零污染排放的電動車，且協助電動車使用者在有限的電池容量下，即時瞭解充電站資訊以便有效的補足電池電量，乃為電動車使用者最關心之課題。因此，若能滿足多數電動車使用者的需求，提高充電站搜尋系統之充電站資源分配，以及降低電動車使用者到達充電站後過長的等待時間，將為電動車使用者之一大福音。本研究目的主要建構一電動車充電站自動引導決策支援應用程式(APP)，開發Android作業系統為使用者介面，藉由雲端運算與後端資料庫伺服器的資訊整合，提供使用者查詢即時的充電站資訊及產能狀況，並進行多位使用者同時搜尋充電站時的決策分配，其中運用排程問題中的平行機台概念，結合啟發式演算法求解最適的充電站排程規劃，以達到多位使用者的最大完工時間最小化之指派與支援分配，並同時滿足電動車至充電站後最小化的等待時間及降低多位使用者的衝突之支配規劃，最後輔以Google Maps引導最適的路徑規劃至充電站，藉以提供使用者有效地完成整個充電計畫之參考依據。

關鍵字

電動車；車輛排程問題； Android ；路徑規劃；雲端運算

並列摘要

With the popularity of the Internet and smart mobile devices, and the rapid development of transportation construction and urban transportation systems, people began to take advantage of diverse traffic information to make their travel decisions. In addition, to improve the increasingly serious environmental problems, the auto industry is gradually developing high energy efficiency, zero emission electric vehicles (EV). However, it becomes a big problem to help the EV drivers to get the information of the charging stations within the limited battery. Therefore, power problems are no longer concerns of the EV drivers if the resource allocations of charging station get improved or the waiting time become short. The purpose of this study is to construct a guiding plan for electric vehicle charging decision support application (APP) that use of Android system for development and integration of cloud computing and databases information. This APP not only provides EV users with real-time status information and capacity of charging stations, but also allocates charging stations for multiple EV drivers who are searching the charging information at the same time. Decision problem is scheduling problems in parallel machine concept that combines heuristic algorithm for solving the optimal charging station schedule planning. Furthermore, the goal is achieve the minimization of makespan for multiple EV drivers and satisfy to minimize the waiting times at the charging station and reduce conflict allocation for multiple users. Finally, the Google Maps is adapted to guide the optimal route for the EV drivers to complete the project.

並列關鍵字

Electric vehicle ； Vehicle scheduling problem ； Android, Route planning ； Cloud computing.

參考文獻

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國際替代計量

電動汽車充電站自動引導APP建置

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