鋰離子電池參數估算方法之研究

電池在近代的工程科技發展上，扮演了重要的角色，而因為電池的特性，也使其在數十年來廣泛地被運用在電子電路或機電相關的系統上，而為了要能有效地使用電池，管理與監控電池的使用情形就越顯重要，如電池的老化情形等，種種現象將會反映在電池的許多參數上，故必須萃取電池內部參數，如:電池內部阻抗等，以進一步強化後端系統之設計，而電池參數的萃取方式又可以分為兩種:線上方式與離線方式，本論文即是針對線上之電池估算方式加以研究。本論文主要討論鋰離子電池的參數估算方式，首先在Simulink環境中建立所需使用之多種鋰離子電池模型，並再對其進行驗證，證實電池模型可與實測數據吻合，間接證明其模型正確性。並且使用所建立之電池模型，運用在不同的負載上進行一系列之系統化模擬，使用之模型包含簡化型電池模型，至更為接近真實電池狀態之完整鋰離子電池模型。在電池參數估算方法方面，將對兩種參數估算方法做模擬與比較，分別為適應性觀測器法(Adaptive Observer)以及擴展式卡門濾波器(Extended Kalman Filter,EKF)估算法，對系統之參數與狀態進行估算，希望能藉由此兩種參數估算方法，再配合完整之系統化模擬，觀察系統的整體參數估算情形。模擬情形包含使用不同型態之負載，觀察負載變化情形對估算結果之影響，除此之外，因考慮將此估算方法實用於純電動車(Electric Vehicle, EV)中，故又再設計一隨機變化之負載，進而貼近一般電動車的行車充放電使用情形。而對於適應性觀測器估算方法，我們也將使用不同之數值方法進行離散化並加以比較，進而加強實作上的應用，最後，本論文將電池參數估算方法作結論並討論未來之發展。

關鍵字

鋰離子電池模型；擴展式卡門濾波器；適應性觀測器；參數萃取；純電動車

並列摘要

Battery plays a crucial role in nowadays technology and is extensively used in electrical and electronic systems. In order to utilize battery efficiently and optimally, it is important to be able to provide good control and management functions of the battery while it is in use or charging. Most of those functions are based on the battery operational characteristics as well as accurate measurements or estimations of battery status and/or parameters. For example, parameters such as battery internal resistance could reflect battery status which is very significant information for battery management system. Therefore, it is important that battery parameters can be measured or estimated by different approaches either on-line or off-line. The main focus of this thesis is to investigate and compare two different on-line methods for estimating battery parameters. One is the adaptive observer for dynamical estimation, and the other is the extended Kalman filter for state and parameters estimation. We first carefully examine the derivations and build Matlab simulation programs of the two methods, respectively, and then design and perform a series of systematic simulations for these two methods to study their advantages and disadvantages in battery parameter estimation. Moreover, we also build three Li-ion battery models in Simulink for the aforementioned series of systematic simulations. The battery models can simulate dynamic battery characteristics in Simulink environment under different battery simplification assumptions. These models also can be used for various simulations in different system design applications, e.g., electric vehicle or power system design. By using these Li-ion models, system designers could have a much more accurate simulation result for their systems.

並列關鍵字

Li-ion Battery Model ； Extended Kalman Filter ； Adaptive Observer ； Parameter Extraction ； Electric Vehicle

參考文獻

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鋰離子電池參數估算方法之研究

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