Abstract
Triboelectric nanogenerators (TENGs) have emerged as a promising solution for self-powered Internet of Things (IoT) nodes, owing to their unique capability in harvesting ambient low-frequency and stochastic mechanical energy. However, the mismatch between the high-impedance, pulsed alternating-current output of TENGs and the low-impedance direct-current requirements of electronics remains a critical bottleneck for practical applications. To systematically address this challenge, this work not only reviews recent advances in TENG power management strategies but also innovatively constructs a core two-stage framework ranging from “efficient front-end energy extraction” to “stable back-end power delivery.” Under this framework, we systematically evaluate extraction strategies utilizing rectifiers, metal-oxide-semiconductor field-effect transistors, silicon-controlled rectifiers (SCRs), and gas discharge tubes to maximize charge transfer, followed by voltage regulation techniques based on SCRs, LTC3588 energy-harvesting power-management integrated circuit, voltage detection chips and mechanical switches. On this basis, we achieve the first deep integration of power management with specific application scenarios, detailing integration schemes and implementation efficacy in industrial IoT monitoring, marine blue energy harvesting, and wearable health sensing. Finally, we summarize critical challenges regarding universality, integration, and environmental robustness, proposing a future roadmap toward monolithic chip integration, ultra-low power design, flexible encapsulation, and wearable textile electronic systems. This review provides a theoretical foundation and strategic guidance for next-generation self-powered microsystems.
| Original language | English |
|---|---|
| Article number | 117423 |
| Journal | Renewable and Sustainable Energy Reviews |
| Volume | 243 |
| DOIs | |
| Publication status | Published - Jan 2027 |
| Externally published | Yes |
Keywords
- Impedance matching
- Internet of things
- Power management
- Self-powered systems
- Triboelectric nanogenerator
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