Work

Time-Domain Modeling and Simulation of Hybrid Perturb and Observe–Particle Swarm Optimization Maximum Power Point Tracking for Enhanced CubeSat Photovoltaic Energy Harvesting

Year: 2025

Type: article

Abstract: The escalating demand for efficient energy harvesting in CubeSat missions necessitates advanced maximum power point tracking (MPPT) techniques. This work presents a comprehensive time-domain analysis and simulation of three MPPT algorithms: perturb and observe (PO), particle swarm optimization (PSO), and a novel hybrid PO-PSO method, tailored explicitly for CubeSat photovoltaic (PV) solar modules. Utilizing MATLAB R2025a/Simulink, a detailed model of a PV module based on the Azur Space 3G30C datasheet and a DC-DC boost converter was developed. The conventional PO MPPT, while simple, demonstrated limitations in tracking the global maximum power point (GMPP) under rapidly changing temperature conditions and exhibited significant oscillations around the GMPP. The PSO algorithm, known for its global search capabilities, was investigated to mitigate these shortcomings. This research introduces a hybrid PO-PSO MPPT technique that synergistically combines the low computational complexity of PO with the robust global optimization of PSO. Time-domain simulation results demonstrate that the proposed hybrid PO-PSO MPPT significantly reduces oscillations around the GMPP, enhances tracking accuracy under varying temperature conditions, and stabilizes output parameters more effectively than standalone PO or PSO methods. These findings validate the hybrid approach as a superior and reliable solution for optimizing power generation in constrained CubeSat applications.

Source: Energies

DOI: 10.3390/en18225957

Authors: Khaya Ntutuzelo Dwaza, Senthil Krishnamurthy, Haltor Mataifa

Institutions: Walter Sisulu University, Cape Peninsula University of Technology

Language: English

Topic: Photovoltaic System Optimization Techniques

Subfield: Renewable Energy, Sustainability and the Environment

Field: Energy

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $3,137