Rizky Ajie Aprilianto, Subiyanto, Mario Norman Syah, Dwi Bagas Nugroho
The PV-battery charge controller has integrated maximum power point tracking (MPPT) to optimize the power extraction result. Unfortunately, oscillation existing in steady-state conditions makes power extraction less efficient. This work proposed an improved MPPT performance using a horse herd optimization (HHO) algorithm for PV-battery charge controller application. The proposed system comprises 2 kW PV, MPPT with interleaved buck converter (IBC), and a charge controller dedicated to the lead acid battery type using the constant-current constant-voltage (CC-CV) method. MATLAB/Simulink is used to verify this work by comparing several MPPT algorithms, consisting of perturb and observe (P&O), incremental conductance (INC), and genetic algorithm (GA), with a fair comparison. It includes power extraction capability, dynamic testing performance, ripple cancellation result, and battery charging performance. The findings show that the proposed system with the HHO algorithm achieves the highest average PV power extraction at standard test condition (STC), 1993 W result in 99.53 % efficiency and better stability for dynamic testing conditions. Also, by applying this MPPT method, ripple cancellation is achieved. The proposed system results in a ripple of only 11.56 % from the 35 % inductor ripple design, smaller than adopting other algorithms. It is beneficial because a low current ripple can avoid increasing gasification, power fluctuations, battery temperature, and overheating. Moreover, the proposed system shows the best battery charging performance testing result, outperforming other algorithms. © 2025 IEEE.
Universitas Negeri Semarang, Department of Electrical Engineering, Semarang, Indonesia
