This paper reports on the design, fabrication, and experimental validation of a modular and configurable development platform, named PIEZO-DK, tailored for evaluating and optimizing ultralow-frequency piezoelectric energy harvesting systems. Existing MPPT (maximum power point tracking) techniques often have design weaknesses of high complexity, inevitable periodic disconnection, and low efficiency, especially for sub-Hz range, ultralow-power applications. To address this issue, this study pursues a self-powered MPPT method based on a modified fractional open-circuit voltage approach, which is free from microcontroller units. The PIEZO-DK features tunable resistor–capacitor time constants that allow for dynamic adjustment of the power tracking point, making it adaptable to diverse harvester configurations and outputs, including direct compression-type harvesters such as wearables and those embedded in shoes, and resonant systems such as cantilevers. PIEZO-DK’s configurable architecture enables selective, individual isolation of different circuit stages for debugging, probing, and optimization via pin-header jumpers. This feature provides a user-friendly interface for researchers and developers who do not necessarily have extensive knowledge of circuitry design. The experimental validation using a direct compression-type harvester designed for shoes suggests an MPPT efficiency of 96.2% at 0.9 Hz, the highest known to date at a frequency below 1 Hz among those of self-powered MPPT circuits. The results confirm the effectiveness and feasibility in practice for real-world energy harvesting applications. Such a scalable, simple, and energy-efficient tool is ideal for rapid prototyping and system optimization. It helps to accelerate the development pace of Internet of Things systems powered by wearable, biomechanical energy harvesters.
Kaushalya et al. (Fri,) studied this question.