This paper proposes a closed-loop maximum power point tracker (MPPT) for subwatt photovoltaic (PV) panels used in wireless sensor networks. Both high power efficiency and low circuit complexity are achieved. A microcontroller (μC) driven by a fast clock was used to implement an MPPT algorithm with a low processing time. This leads to a maximum central-processing-unit duty cycle of 6% and frees the μC to be used in the remaining tasks of the autonomous sensor, such as sensing, processing, and transmitting data. In order to reduce power consumption, dynamic power management techniques were applied, which implied the use of predictive algorithms. In addition, the measurement and acquisition of the output current and voltage of the PV panel, which increase circuit complexity, was avoided. Experimental measurements showed power consumptions of the MPPT controller as low as 52 μW for a 2.7-mW PV power and up to 388 μW for a 94.4-mW PV power. Tracking efficiency was higher than 99.4%. The overall efficiency was higher than 90% for a PV panel power higher than 20 mW. Field measurements showed an energy gain 15.7% higher than that of a direct-coupled solution.

This paper analyzes the energy consumption of direct interface circuits where the data conversion of a resistive sensor is performed by a direct connection to a set of digital ports of a microcontroller (μC). The causes of energy consumption as well as their relation to the measurement specifications in terms of uncertainty are analyzed. This analysis yields a tradeoff between energy consumption and measurement uncertainty, which sets a design procedure focused on achieving the lowest energy consumption for a given uncertainty and a measuring range. Together with this analysis, a novel experimental setup is proposed that allows one to measure the μC's timer quantization uncertainty. An application example is shown where the design procedure is applied. The experimental results fairly fit the theoretical analysis, yielding only 5 μJ to achieve nine effective number of bits (ENOB) in a measuring range from 1 to 1.38 kQ. With the same ENOB, the energy is reduced to 1.9 μJ when the measurement limits are changed to 100 and 138 kQ.

Many autonomous sensor nodes use small photovoltaic (PV) panels oriented toward the direction that provides the highest energy yield in the worst case scenario. Since all those panels operate at similar irradiance and temperature conditions, they can be properly biased at the same bias point by using a single maximum power point tracker (MPPT). But in applications that involve several PV panels with dissimilar orientations, using an MPPT tailored to each panel would increase system cost. A better design option is to implement the MPPT with a single multiple-input converter shared through time-division multiplexing (TDM) control. However, existing TDM controls are usually based on pulsewidth modulation converters wherein the high switching frequency of transistors results in excessive power losses for low-power systems. Consequently, low-power MPPTs are instead usually based on pulse frequency modulation (PFM) converters. This paper proposes a novel TDM control method for MPPTs based on PFM converters.

A simple maximum power pointer tracker (MPPT) controller for low-power photovoltaic (PV) panels is proposed. The MPPT is based on a fractional open circuit voltage controller that dynamically adjusts the sample time and period accordingly to the power of the PV panel. That allows the converter to obtain a good trade-off between the power efficiency and the dynamic response for a wide range of PV powers.