Browsing by Author "Moyo, Zandile"

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    Modelling the broadband impedance of a lithium-ion battery cell using the pseudo-random impulse sequence perturbation
    (Stellenbosch : Stellenbosch University, 2023-12) Moyo, Zandile; Mwaniki, Fred; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.
    ENGLISH ABSTRACT: Lithium-ion (Li-ion) batteries are becoming increasingly important for integrating renewable energy sources such as solar and wind into the electrical grid. Battery Energy Storage Systems (BESS) using Li-ion batteries address challenges posed by renewable energy, such as unpredictability and non-dispatchability, thus enhancing grid reliability. Before implementing Li-ion cells in BESS, thorough investigation and optimisation are essential. Accurate prediction of remaining useful life and State-of-Health (SOH) under varying conditions, such as temperature and State-of-Charge (SOC), is vital for effective battery management. Battery impedance, which is frequency-dependent, significantly impacts SOH and SOC, especially in the 1 Hz to 1 kHz range. Therefore, modelling the broadband impedance of the Li-ion battery helps to improve battery management and reliable operation. Accurate battery cell modelling also enables system integrators to perform effective network simulations. The impedance of a Li-ion battery is often computed from its response voltage and current signals to an injected excitation signal. This thesis uses the novel Pseudo-random Impulse Sequence (PRIS), a broadband bipolar excitation signal, for Li-ion battery impedance measurements. The PRIS excitation source is optimised, by tuning its series resistor, inductor and capacitor (RLC) network components and Direct Current (DC) voltage input, to ensure sufficient spectral energy for impedance testing without damaging the battery. The impedance is determined from the battery’s excitation response voltage and current signals using Fourier techniques. An excitation method is proposed for accurate Li-ion cell impedance measurements. This method involves separating the desired frequency range into multiple bands that are perturbed separately using optimised excitation parameters to improve the measurement signal-to-noise ratio, reduce variance, and minimise bias. Parameter Estimation (PE) techniques, via the physics-based Equivalent Circuit Model (ECM) approach, are used to characterise and model Li-ion battery cell impedance. A simulated PE is performed in MATLAB, while a PE using physical experimental data is performed in ZView software. The SOC of the Li-ion cell is varied through discharge tests, and the cell impedance is measured at each SOC using the proposed excitation method. This research demonstrates that the optimised PRIS source and the proposed excitation method improve the accuracy of the measurement of the Li-ion battery impedance, thus enhancing the performance of battery modelling. The excitation responses of the validated Li-ion battery cell model, from PE, closely match the actual system responses across all relevant frequencies. The influence of SOC on impedance is effectively observed, especially at mid to lower frequencies. This thesis confirms that the PRIS and the proposed excitation method are suitable for Li-ion battery impedance measurements and modelling. It is evident that the PRIS excitation signal, along with the proposed method, results in good Li-ion cell impedance measurements with minimal noise and bias. This leads to reliable estimation of the ECM parameters that replicates the physical responses of the battery at varying SOC, thus benefiting future simulations and system integration.