Online parameter and state estimation of lithium-ion batteries under temperature effects
Abstract
In this paper, a hybrid estimation technique is proposed for lithium-ion batteries. This strategy makes use of state-space observer theory to reduce the complexity of the design and the stability analysis. However, the battery's parameters knowledge is required for the state-space model, which limits the performance as the battery's parameters vary. Therefore, an online parameter identification strategy is proposed to track the parameters deviation. The stability of the closed-loop estimation scheme is guaranteed by Lyapunov's direct method. Unlike other estimation techniques where temperature effects are ignored, this paper proposes a universal compensation strategy which can be used with many estimation algorithms available in the literature. The performance of the proposed scheme is validated through a set of experiments under different currents and temperatures along with comparison against an adaptive observer.