Online measurements of the battery impedance provides valuable information on the battery state-of-charge and state-of-health which can be utilized for improving the safety and the performance of the associated system. The electrochemical-impedance- spectroscopy (EIS) is widely used for battery impedance measurements but it is not the most applicable solution for online measurements due to its slowness and complexity. These drawbacks can be improved using broadband signals, such as, pseudo-random-sequences (PRS), which are fast and easily implementable. However, the non- linear behavior of batteries have significant effect on the impedance measurements and the selection of the PRS signal. Majority of the PRS signals are applicable for measurements of linear systems but also signals for non-linear system identification do exist. Moreover, the reduced accuracy and signal-to-noise ratio of the PRS signals compared to the EIS make the filtering of the results as well as the amplitude design important aspects. This paper demonstrates the use of two PRS signals, the pseudo-random-binary-sequence (PRBS) and a ternary- sequence with better toleration to battery non-linear effects, with comprehensive amplitude and filtering design for battery impedance measurements. The results are referenced and validated to practical EIS measurements in various operating conditions for lithium-iron-phosphate cell.

The impedance of Li-ion batteries contains information about the dynamics and state parameters of the battery. This information can be utilized to improve the performance and safety of the battery application. The battery impedance is typically modeled by an equivalent-circuit-model (ECM) which provides the dynamic information of the battery. In addition, the variations in the model parameters can be used for the battery state-estimation. A fitting algorithm is required to parametrize the ECM due to the non-linearity of both the battery impedance and ECM. However, conventional fitting algorithms, such as the complex-nonlinear-least-squares (CNLS) algorithm, often have a high computational burden and require selection of initial conditions which can be difficult to obtain adaptively. This paper proposes a novel fitting algorithm for the parametrization of battery ECM based on the geometric shape of the battery impedance in the complex-plane. The algorithm is applied to practical and fast broadband pseudo random sequence impedance measurements carried out at various state-of-charges (SOC) and temperatures for lithium-iron-phosphate cell. The performance of the method is compared to conventional CNLS algorithm with different initial conditions. The results show that the proposed method provides fast and accurate fit with low computational effort. Moreover, specific ECM parameters are found to be dependent on the battery SOC at various temperature.

The impedance of a Lithium-ion (Li-ion) battery has been shown to be a valuable tool in evaluating the battery characteristics such as the state-of-charge (SOC) and state-of-health (SOH). Recent studies have shown impedance-measurement methods based on broadband pseudo-random sequences (PRS) and Fourier techniques. The methods can be efficiently applied in real-time applications where the conventional electrochemical-impedance spectroscopy (EIS) is not well suited to measure the impedance. The techniques based on the PRS are, however, strongly affected by the battery nonlinearities. This paper presents the use of a direct-synthesis ternary (DST) signal to minimize the effect caused by the nonlinearities. In such a signal, the second- and third-order harmonics are suppressed from the signal energy spectrum. As a result, the effect of the second- and third-order nonlinearities are suppressed from the impedance measurements. The impedance measurements are carried out for a nickel manganese cobalt Li-ion battery cell. The performance of the method is compared to the conventional EIS, as well as to other PRS signals which are more prone to battery nonlinearities. The Kronig–Kramers (K–K) transformation test is used to validate the uniqueness of the measured impedance spectra. It is shown that the measurement method based on the DST produces highly accurate impedance measurements under nonlinear distortions of the battery. The method shows a good K–K test behavior indicating that the measured impedance complies well to a linearized equivalent circuit model that can be used for the SOC and SOH estimation of the battery. Due to the good performance, low measurement time, and simplicity of the DST, the method is well suited for practical battery applications.

Li-ion batteries have become key energy storage devices in powering various industrial processes and consumer products. Increased demand for Li-ion batteries has raised environmental issues because most of the batteries are landfilled upon reaching end of life. However, studies have suggested that most of the used Li-ion batteries can be reused in second-life applications. Battery state parameters such as the state-of-health (SOH) and state-of-charge (SOC) are typically used for assessing the performance. The SOH is particularly useful in predicting the remaining life cycle of the battery and selecting suitable second-life applications for reuse. However, measuring the SOH can be difficult using existing technology. Recent studies have shown that a battery's internal impedance can be used to determine the SOH of the battery. This paper demonstrates the applicability of the internal impedance in evaluating the SOH and suitability of used Li-ion batteries in second-life applications. Experimental measurements from several commercial Li-ion batteries are shown and analyzed. The work is a revised and extended version of a presentation at ECCE2022 [1].

Battery impedance is an important parameter for estimation of the battery state parameters, such as, state-of-charge (SOC), state-of-health (SOH) and the temperature. However, complexity of the measurement implementation most often prevents wider utilization of the impedance measurement in on-board applications. This paper proposes a cell-level implementation of current-sensorless on-board impedance measurements in multi-cell battery stacks. In the proposed method, the current required for the impedance calculations is estimated based on the voltage measurements and the equivalent circuit resistance compensated by the circuit inductance. Comprehensive introduction on the appropriate battery stack prototype with on-board impedance measurements is presented. The performances of the methods and prototype are validated by experiments on several different different sets of nickel-manganese-cobalt-oxide (NMC) Lithium-ion cells.