電動車用鋰電池之殘電量估測

State of Charge Estimation for Li-Ion Batteries Using in Electric Vehicles

盧樹台(Shuh-Tai Lu) ； 陳仁和(Ren-Her Chen) ； 謝文桐(Wun-Tong Sie) ； 任國光(Kuo-Kuang Jen) ； 余安錠(Ann-Ting Yu)

《清雲學報》 31卷3期 (2011/07) Pp. 1-19

https://doi.org/10.7049/JCYU.201107.0001

摘要

由於動態環境下的變數較多，一般的電池殘電量估測是在無負載或是低負載的環境下進行，以便得到較高的電池殘電量估測準確度。然而，電動車在道路行駛中的負載是變動的，必需讓駕駛人知道電池的殘電量，以瞭解電動車的續航力。本文利用曲線擬合技術結合殘電量庫倫測量法，提出了一種多段線性對應方法，將動態環境下測得的電池電流及電壓，對應至先前的動態放電經驗函數，據此估算出電池的殘電量。由實驗結果得知，本文所提出的多段線性對應方法，電池殘電量的估測誤差在8%以內，已達到實用上的價值。

關鍵字

鋰電池 ； 殘電量 ； 動態測量

並列摘要

Owing to the influence of a lot of variations in dynamic environment, the measurement for state of charge (SOC) of battery is usually under no-loaded or lower-loaded conditions to get higher accuracy of SOC estimation. But, the loading conditions of electric vehicles are always different. There must have some mechanism to let the drivers know how much energy is remaining in the battery and how far the vehicles can go? In this paper, we combine curve fitting and Coulomb measurement method and propose a multi-segment matching method to solve the problem. First, we collected a lot of dynamic discharging data of the battery and made them as a database. Then, a lot of polynomial functions can be made from the database by using the curve fitting method. When the current loading and terminal voltage of the battery are measured for an electric vehicle in a dynamic environment, an appropriate polynomial function will be chosen to calculate the SOC of the battery. According to the experimental results, the error of SOC estimation is less than 8%, which means the results are valuable for commercial applications.

並列關鍵字

Lithium-ion battery ； state of charge ； dynamic measurement