The invention relates to the technical field of
lithium battery charging under photovoltaic panel power supply, in particular to a Buck-Boost
lithium battery intelligent charging method based on ML-MPPT and dynamic reference
voltage regulation, and the method comprises the steps: dividing a charging stage into a
trickle charging stage, a constant-current charging stage and a constant-
voltage charging stage according to the
voltage of a
lithium battery; the method comprises the following steps: acquiring environment temperature, solar
illuminance and maximum power point voltage data in a
constant current stage, preprocessing the data, training a maximum power point voltage prediction
machine learning model, distilling the model to obtain a compression model, and deploying the compression model on a
microcontroller; real-time environment data is input into the model to predict and obtain the maximum power point voltage as the reference voltage, the output voltage of the photovoltaic panel is sampled, and the input voltage of the Buck-Boost circuit is controlled by using the innovative PWM
control system, that is, the duty ratio of PWM pulses is controlled through the
microcontroller, the
input impedance of the Buck-Boost circuit is adjusted, and the output voltage of the Buck-Boost circuit is adjusted. The output voltage of the photovoltaic panel, namely the input voltage of the
switching power supply, is adjusted to the maximum power point voltage according to environmental conditions; and dynamically switching the
lithium battery in different charging stages according to the battery state and the input power. The method integrates
machine learning into prediction of the maximum power point voltage, and is suitable for an intelligent charging scene of the
lithium battery under photovoltaic power supply.