Photovoltaic (PV) systems have become indispensable in the renewable energy landscape, harnessing the sun’s abundant and clean potential. However, their efficiency is often compromised by low conversion rates, particularly under partial shading conditions (PSC). This study introduces a novel quadratic spline-based maximum power point tracking (QS-MPPT) technique to optimize PV array performance under both uniform irradiance and PSC. Unlike conventional methods such as Perturb and Observe (P&O) or Incremental Conductance (INC), which struggle to pinpoint the global maximum power point (GMPP) amid the multi-peak power-voltage (P-V) curves typical of PSC, QS-MPPT employs a straightforward quadratic interpolation approach. By leveraging a minimal set of sampled points, this method rapidly and accurately locates the GMPP, ensuring stability without oscillations around the operating point. Simplicity of the proposed method also makes it ideal for implementation on cost-effective microcontrollers, broadening its practical appeal for real-world PV applications. The efficiency of the proposed method is shown by the time domain simulation in the MATLAB/SIMULINK environment and implementation in the way of processor in the loop (PIL). Through MATLAB simulations, QS-MPPT performance is evaluated and compared with MPPT techniques like P&O, Particle Swarm Optimization (PSO) and Flower Pollination Algorithm (FPA) in three- and four-peak PSC scenarios, which the proposed method shows higher accuracy and faster convergence
