本論文為達成能量管理，尤針對非線性系統如質子交換膜燃料電池、儲氫罐、鋰電池等元件加以調度運用，特以本研究者自行整合之質子交換膜燃料電池混合動力電動機車進行實測，以取得各項次系統元件操作參數，並以 MATLAB/Simulink 模擬軟體為基礎，建構四種燃料電池混合動力車系統動態模型(被動式燃料電池搭配單電池模式、被動式燃料電池搭配雙電池模式、主動式燃料電池搭配單電池模式與主動式燃料電池搭配雙電池模式)。並配合不同之控制，分別以各元件及車輛性能參數，建構各種組合之次系統模型。然後運用車輛動力學 (Vehicle Dynamics) 原理，將電源管理控制系統、馬達、1 kW之PEMFC燃料電池與960 Wh之鋰離子電池之電控系統加以整合，驅動一電動機車。
　　在電控系統方面，透過取得之參數，進而導入3參數輸入(系統需求功率、殘氫量、鋰電池SOC)與1輸出(燃料電池供應系統之總功率比)之27個規則的模糊邏輯控制(Fuzzy Logic Control)。因此能做平滑能量分配。在本論文研究中，係以探討最佳能源運用為目標，對四種設計之能量運用模式，透過行駛ECE-40與FTP-72行車形態與駕駛模式，比較各種條件的輸出性能以及關鍵變量、續駛距離及能耗情形。結果顯示本研究在相同初始能量下，應用模糊邏輯控制雙電池模式輸出，可達最佳之能量管理。運轉時每公里平均氫氣消耗可由單電池搭配燃料電池之0.428g/km降至0.390g/km，行駛距離可增加9.82%。

This study presents a novel energy management, especially to deal with non-linear subsystems such as proton exchange membrane fuel cells (PEMFCs), hydrogen storage tanks, lithium batteries and other components. A real fuel cell/battery hybrid electric motorcycle with preceding components was tested in this study. The retrieved parameters from the subsystems of the scooter were used to build four kinds of PEMFC hybrid vehicle system dynamic models on the Matlab/Simulink environment. They include: passive fuel cells with a single battery, passive fuel cells with dual batteries, aggressive fuel cells with a single battery, and aggressive fuel cells with dual batteries. With different control strategies and vehicle performance parameters for different structures, four modes are constructed by a different combination of subsystems models. The four kinds of established electric scooter models were developed based on the vehicle dynamics theory by combining an in-wheel motor, a 1kW PEMFC and a 960Wh lithium battery. Four types of energy management control systems were thus designed in this study.
For the electronically-controlled systems, 27 fuzzy logic rules were established which included 3 input parameters (system required power, the amount of residual hydrogen gas, and the state of charge of the primary battery, SoC) and an output parameter (the power ratio of the fuel cell supply system). Therefore, the smooth energy distribution was achieved in this study. In this paper, the goal is to discuss the best energy utilization. With the designs of four kinds of energy modes, through two driving cycle (ECE-40 and FTP-72) and driving mode, the output performance under different conditions, key variables, extended range and energy consumption were compared. The results show that under the same initial energy condition, the best energy management can be reached by using fuzzy logic rules to control the dual battery type. The hydrogen consumption can be decreased from 0.428 g/km to 0.390 g/km, and the driving range can be improved by 9.82 % compared to the baseline case.

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