Design Of Dynamically Self-adaptive Load Current Maximization Technique In PV Cell MPPT Systems

As a safe and environmentally friendly renewable energy, the development and utilization of solar energy is of great significance. Thus, the photoelectric conversion (namely photovoltaic power generation) has gradually become one of the most vigorous hot topics in recent years. The maximum power point tracking (MPPT) technique is used to ensure that the PV cells achieve maximum power output in changing external environment conditions so as to raise the energy utilization efficiency of the PV power generation system.The thesis focuses on the research of PV battery charger, the load of which is a common led acid battery. For low-power systems that require high conversion efficiency and low expected cost, a fully analog circuit design has been adopted to build the control unit in order to promote the chip utilization level. In order to simplify the circuitry structure and improve the tracking accuracy, an improved load current maximization technique is proposed by combining the advantages of both the perturbation and observation method and the ordinary load current maximization method. The system senses the load current from the output terminal of the converter, and then dynamically adjusts the current reference Iref to gradually approach the MPP current. As a result, the system is capable of realizing the dynamically self-adaptive process flexibly while maintaining the advantages of less number of sensors. Since it obviates the need to detect and match the different photovoltaic cells and loads in advance, the system has advantages such as low cost, low power consumption, high efficiency and high stability, so it is very suitable for small power photovoltaic power system application.The circuit in this thesis is implemented with VIS 0.5μm 5V mixed-signal 2P3M process and verified in Synopsys(?) HSPICE simulation environment. The simulation results show that the photovoltaic power generation system has a good tracking efficiency in the static condition and a fast response in dynamic conditions with the regulation of the proposed controller, ensuring outstanding performance under changefully natural environment. The overall average tracking accuracy is 95%, and the highest tracking accuracy can reach 98%.