SIVEH: numerical computing simulation of wireless energy-harvesting sensor nodes

Area of Science:

• Electrical Engineering
• Computer Science
• Energy Systems

Background:

• Traditional energy modeling for sensor nodes often lacks accuracy due to component variations.
• Accurate energy harvesting predictions are crucial for the long-term operation of autonomous sensor networks.

Purpose of the Study:

• To present SIVEH (Simulator I-V for EH), a numerical energy harvesting model for sensor nodes.
• To demonstrate the enhanced accuracy of I-V hardware tracking over conventional methods.
• To enable fast, long-term simulations of energy harvesting systems.

Main Methods:

• Developed a numerical energy harvesting model, SIVEH, utilizing I-V hardware tracking.
• Integrated dynamic adjustment of sleep time rates for energy-neutral operation.
• Performed functional verification and comparison with classic energy modeling approaches.

Main Results:

• SIVEH shows higher accuracy than traditional models, especially with varying power dissipation.
• The model allows rapid simulation of extended periods (days to years) using real solar data.
• Enhanced modeling with dynamic sleep time adjustment aids in achieving energy-neutral operation.

Conclusions:

• SIVEH provides a more accurate and efficient tool for energy harvesting modeling in sensor nodes.
• The I-V tracking approach is superior for components with voltage- or current-dependent power dissipation.
• The model facilitates the design of sustainable, energy-neutral sensor systems.