This work investigates an autonomous system for charging electric golf cars using photovoltaic panels, a DC-DC boost converter, a buck-boost converter, and a battery. The performance of this system was examined under two centralized and decentralized configurations. The conventional P&O maximum power tracking algorithm is limited by different illumination conditions. In order to minimize the detrimental effects of partial shading on the PV arrays, a neural network-based MPPT algorithm is used to control the DC-DC boost converter. Fuzzy logic was used to control the DC-DC buck-boost controller associated with the battery to regulate the DC bus. Solar energy production generates an imbalance in a photovoltaic system because of its stochastic behavior, requiring a power manager to control power flow. State flow was used to design the power management algorithm. Simulations and real-time experiments have validated the performance and control strategies of the proposed configuration, as well as its power management algorithm.
Results obtained under different conditions such as shading, and load variation are suitable.
| Date | 12 Dec 2022 |
|---|
| Original language | French |
|---|
| Awarding Institution | - École de technologie supérieure
|
|---|
| Supervisor | Ambrish Chandra (Supervisor) & Miloud Rezkallah (Co-supervisor) |
|---|
Raddaoui, M. (Author),
Chandra (Supervisor) & Rezkallah (Co-supervisor),
12 Dec 2022Student thesis: Master's thesis › Master in Engineering: Engineering