Design of a robust LMI-based H∞ observer for the state of charge estimation in lithium-ion batteries

Designing a robust Hꝏ observer to estimate the state of charge (SoC) of lithium batteries for various applications, including microgrids, is the principal goal of the present article. Battery dynamic models always have uncertainties that reduce the performance of many model-based estimators. This paper presents a robust nonlinear Hꝏ estimator for battery charge level estimation, in which the impact of measurement disturbances and model uncertainties on the estimation output is minimized. To design the desired estimator, an optimal LMI problem has been used so that the optimal value of the estimator parameters is extracted and its performance is at its best. Using the proposed method, the impact of model uncertainties and disturbances on the estimation output has been reduced. Moreover, the design of the estimator has been converted into an optimal LMI problem to extract the best values for the estimator parameters to increase its performance. The suggested approach performance for the SoC estimation is validated through a series of simulations and software-in-the-loop tests. The results confirm the effective performance of the suggested approach in the SoC estimation. The outcomes indicated that the suggested method could provide better accuracy than the ampere-hour method by 0.25% and reduce the speed of convergence to the real value by 6 s.