在現代自由車賽事中，騎行效率的提升是受到廣泛關注的議題。選手和團隊投入大量的時間和資源進行訓練和研究，以尋求最佳的設計和策略，從而在賽事中獲得優勢。近年來已更多專業車手使用各種科學儀器數據做為參考依據。而在近期，功率計的發展也發生改變，市面上不再只有透過直接量測騎行者踩踏力量的功率計，同時也出現新型態間接測量的功率計。本研究主旨在透過自由車選手風洞與路騎實驗，探討利用數據分析方法獲得在自由車騎行中阻力係數CD，提供訓練策略和研究方向的指標，以及一種主要透過以風速計測量來推估實際功率方法的可行性。
研究方法包含一次風洞實驗與三次路騎實驗，風洞實驗旨在測試選手和車衣在不同風速下所面臨的風阻，提供確切可控環境因素，佐證理論。而路騎實驗顯示出實際應用環節，相較於風洞實驗，其涵蓋更多不可控之變因。本研究路騎實驗透過功率計、風速計等實驗儀器，計算功率估計公式，藉此分析選手和車衣在不同情況下之阻力，驗證風洞實驗結果。同時，在建立數據資料庫後，藉由基因演算法優化功率估計公式，探討實際應用。
於風洞實驗中，發現不同高寬比選手穿著相同車衣以相同姿勢測試時，皆發生阻力隨高寬比上升而上升的趨勢。並且在風洞與路騎比對中發現，路騎實驗結果顯示所有高寬比選手皆在身穿相同車衣時擁有相對較高的阻力值，差異值為0 ~ 4%，與風洞結果相似，由此可證該車衣擁有較好的減阻效果。接著於路騎期間透過基因演算法進行大數據運算出阻力面積與風速關係，再由估計功率公式反推之估計功率，雖說結果仍有延遲與速度項依賴性等問題，但與參考功率計之觀測資料差異值僅0%~10%，且與商用功率計有極高相同趨勢等優勢，顯示出估計功率數據的價值。預期通過初期功率計、風速計架設，並經過蒐集大數據的過程，便可以知道選手之阻力資訊，往後甚至可以移除功率計，減輕重量的同時亦不失功率資訊，大幅提升功率系統便利性。
透過風洞與路騎實驗研究中將可以觀察到實際環境因素對自由車騎行結果之影響，並從中整理數據之間的關聯性。隨著數據資料庫的完善，勢必能夠更加進一步了解其中奧妙。

The improvement of cycling efficiency in modern cycling events is an issue of great concern. In this study, we investigated the feasibility of utilizing data analysis methods to obtain the drag coefficient in cycling and a method to estimate the actual power mainly by anemometer measurements through wind tunnel and road test experiments of cyclists. The wind tunnel experiments were designed to provide precise and controllable environmental factors to support the theory, while the road cycling experiments were conducted to calculate the power estimation equations by using anemometer and other experimental equipment to analyze the drag of the cyclist and the jersey under different conditions. At the same time, after the establishment of the database, genetic algorithms were used to optimize the power estimation formula and explore the practical applications.
Through the wind tunnel and road cycling experiments, it will be able to observe the influence of actual environmental factors on the results of cycling and organize the correlation between the data.

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