MPPT control of a PV-battery system using a gain-scheduled adaptive PI controller and dual active bridge converter

Abstract

Standalone photovoltaic-battery systems face significant challenges in maintaining optimal power extraction under rapidly varying irradiance conditions. Conventional MPPT controllers based on fixed-gain PI approaches suffer from poor dynamic response, oscillations around the maximum power point, and inability to adapt to the nonlinear behavior of dual active bridge (DAB) converters across different operating points. To address these limitations, this work proposes an innovative adaptive control strategy for maximum power point tracking (MPPT) in a stand-alone photovoltaic-battery system connected via a DAB converter. The gain-scheduled PI controller is recalculated at each 1 µs sample by local linearization of the complete nonlinear model of the PV-DAB-battery system, with explicit compensation for measurable disturbances (derived from irradiance G and temperature T). MATLAB/Simulink simulations under realistic irradiance profiles (slow ramps simulating the passage of clouds) demonstrate a clear superiority over a classic PI with fixed gains: ultra-fast response (approximately 1 ms), total absence of oscillations and overshoots, and strict maintenance of a constant second-order dynamic over the entire operating range. To our knowledge, this gain-scheduled analytical approach with explicit perturbation compensation has never before been applied to DAB topology in PV-battery systems. It is distinguished by its ease of implementation, low computational load, and robustness without the need for complex observers. This work lays the groundwork for future experimental validation and extensions to multi-source hybrid systems.