Power Management and System Integration for Mechanical Energy Harvesting and Multi-modal Sensing

Abstract

The triboelectric nanogenerator (TENG) has emerged as a transformative technology for sustainable mechanical energy harvesting and sensing application. This innovation is distinguished by its unique material versatility, structural adaptability, and high energy conversion efficiency. However, its deployment in intelligent multi-modal applications such as, mechanical, optical, and thermal systems, faces critical challenges of suboptimal power management efficiency, incompatible high output and sensitivity, and poor system integration.

The suboptimal management efficiency in TENG power regulation and load adaptability stems from a fundamental impedance mismatching: TENGs operate as high-impedance capacitive sources while loading electronics demand low-impedance voltage and current regulation. Current circuit strategies that prioritize charge density enhancement fail to address this core mismatch issue. To address this mismatch constraint, this dissertation proposes a two-stage resistor-capacitor (RC) impedance matching circuit for power management efficiency optimization. On one hand, the introduction of resistor can reduce the impedance of the overall circuit and matches the load demand, thereby reducing energy loss. On the other hand, the capacitor can temporarily store the pulsed energy of TENG, alleviating instantaneous power fluctuation and improving the stability of energy transmission. The two-stage RC topology implements temporally asymmetric energy management through time constant engineering, where the rapid charging phase on the primary stage synergizes with the controlled discharge on the secondary stage. Combined with the optimization of RC parameters, the energy transmission and storage efficiency are greatly improved. Additionally, by integrating a passive amplification topology that employs a hybrid charging-discharging mechanism through capacitor-end series-parallel connection, a threefold increase in current density is achieved while improving the voltage resistance of the circuit. This power management strategy of low-frequency TENG provides a foundation for the integration of subsequent intelligent sensory systems.

The incompatibility of high output and sensitivity hinders the application of TENG in self-powered sensory systems even though it demonstrates considerable potential due to intrinsic mechano-sensitivity. Current research predominantly focuses on isolated sensing metrics rather than system integration with intelligent platforms. A critical limitation stems from the requirement for direct contact between TENG and moving objects, necessitating ultra-flexible devices to minimize signal noise. These structural constraints restrict the effective contact area, resulting in insufficient power output to sustain the peripheral components (e.g., BLE module) in integrated systems. Expanding the effective contact area to enhance power introduces a fundamental trade-off, as larger geometries degrade sensing accuracy through asynchronous interlayer movements. This dissertation introduces an accordion-inspired structure that resolves the power-sensing dichotomy in TENG through geometric amplification of the effective contact area and the enhancement of the kinematic degree of freedom, establishing a generic methodology for highly integrated TENG systems capable of concurrent energy harvesting and mechano-sensing.

The poor system integration due to asynchronous response to environmental multi-stimuli represents a critical challenge for fitting TENG into hybrid smart sensory system applications, where the system is designed to satisfy complex sensing scenarios of mechanical, optical, chemical, and thermal stimuli. Current hybrid stack discrete systems, which are responsible for different stimuli, involve escalating complexity, limited integration, and inefficient control while failing to resolve the core challenge of asynchronous responses. Therefore, this dissertation pioneers photothermal-triggered TENG that harvests energy from solar irradiation without requiring mechanical input, providing a paradigm shift from the conventional vibration-dependent TENG. The device achieves self-actuation under light exposure, resolving the chronic mismatch of optoelectrical systems between optical environment and mechanical energy harvesting. Moreover, photothermal stimulation introduces three critical challenges to TENG: high temperature tolerance, deformation effectiveness, and cycle durability. We resolve these challenges through a programmable bi-layer structural design combining a hygroscopic doping strategy, surpassing state-of-the-art photothermal TENGs.

Therefore, this project aims to provide a universal power management strategy for the practical application of TENG from the load side, demonstrating effectiveness across various TENG-based energy systems. The research focuses on structural design and multi-modal sensing, providing solutions to challenges related to suboptimal power management efficiency, inadequate power density beyond sensing, and asynchronous responses to multi-stimuli environments, enhancing the system integration while promoting adaptability to real-world smart sensory applications.

Date of Award	24 Jun 2025
Original language	English
Awarding Institution	City University of Hong Kong
Supervisor	Walid DAOUD (Supervisor)