Hybrid Parabolic Assumption-Hill Climbing GMPPT Algorithm for On-Vehicle Solar Panels Under Partial Shading Conditions

Photovoltaic (PV) systems have difficulties under partial shading conditions (PSCs), since multiple local maximum power points (MPPs) are formed, and total solar power production will be reduced if the global MPP (GMPP) is not quickly located. Conventional MPP tracking techniques encounter challenges with PSCs because they may become trapped in local maxima, thus failing to identify the GMPP. To address this problem, this work proposes a new hybrid method based on the Parabolic Assumption (PA) method that combines the fast analytical PA algorithm with the Hill Climbing (HC) algorithm to improve tracking accuracy in the case of PV parameter uncertainty while maintaining a fast tracking speed, which is essential for dynamic PV systems such as those on-board electric vehicles. The algorithm narrows the search area using the PA approach, then refines it with the HC method to balance speed and precision. MATLAB/Simulink simulation results show that the proposed method increases output power by 3.4% for 5% parameter uncertainty and by 6.0% for 7% uncertainty.