本研究主要針對現今或未來電動車之空調系統進行控制策略之設計及驗證。影響人體感到舒適之主要因子為空氣溫度、濕度與空氣流速。電動車(Electric Vehicle, EV)空調系統與一般燃油汽車最大差異在於，電動車之空調由於缺乏引擎廢熱可供使用，因此較為耗能；由於在空調送風過程中，在電動車座艙內之環境將會有局部舒適度之差異。有鑒於此，本研究使用2組溫溼度與空氣流速感測器，分別量測出風口附近與遠離出風口之舒適度情形，希冀尋找一合適之控制方式，在座艙內各部分局部舒適度、節能與控制效能間取一平衡點，達到空調控制之最大效益。
首先，本實驗針對電動車座艙之熱傳與流體力學等物理性質，以及在空調送風過程局部舒適度不均之現象，建立起了一系統數學模型。再根據此建立之模型，建立了模糊線性二次調節器(Fuzzy Linear Quadratic Regulator, FLQR)，進而在每一時刻皆能對致動器調控出一合適之增益(Gain)值，以達到使成本函數降到最低之效果。
最後，本研究最後透過dSPACE DS1104控制發展套件，搭配商用軟體MATLAB/Simulink進行了實際驗證。實驗結果顯示本研究所提出之控制器FLQR的確可在最小耗能之情形下達成優異之控制效果。

This thesis is aimed to investigate the regulation problem of thermal comfort and control strategy configuration for cabin environment of electric vehicles (EVs). Local thermal comfort is emphasized in the air supplying process. Thermodynamic model to include local thermal comfort is established. To reduce energy consumption is also a significant issue in this thesis. Fuzzy Linear Quadratic Regulation (FLQR) is used to achieve satisfactory performance in addition to low energy consumption. An experimental setup is established to verify the efficacy of FLQR based on real-time feedback signals by necessary sensors and cooperation of three fans which serve as actuators to control air flow rates to adjust thermal comfort degree in the cabin.

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