# On the Impact of Mobility on Battery-Less RF Energy Harvesting System Performance
## 6 Related Work  
Supercapacitors have become an attractive option for energy storage due to high power density, fast charge time and virtually unlimited charge/discharge cycles. The main limitations of supercapacitors are low energy density and relatively high self-discharge current compared to conventional chemical batteries. As the classical conventional supercapacitor circuit model mostly fails to explain its behaviour, [2] proposed an equivalent model, which consists of multiple nonlinear RC branches and explains self-discharge current as electric charge redistribution between slow and fast RC branches. The model shows that the charging has to be long enough to charge the capacitor in the slowest RC branch, as otherwise, even though the supercapacitor appears to be charged, the electric charge from the fastest branch will flow into other branches, which will appear as leakage current from outside. The work in [18] proposed ladder, three-branch, four-branch models. The work in [19; 20] proposed an energy iteration model, which explains self-discharge as the only reason for the terminal voltage drops, but ignores the effect of charge-redistribution. Task scheduling: The resulting models have been used by researchers for optimizing task scheduling. The work in [20] adapted the duty cycle for sensor nodes to evade the working of the supercapacitor in high leakage current regions. The work in [4] investigated the effect of charge redistribution on power management and established that the knowledge of supercapacitor state helps to select a task scheduling policy that makes full use of stored energy. Although the capacitor models can be quite accurate in estimating the behaviour of supercapacitors, they can be quite complex to parameterize due to the need for extensive measurements and model fitting using numerical optimization techniques. The proposed dual capacitor approach does not require the \begin{table}
\begin{tabular}{l r r r} \hline
**Mode** & **Current, mA** & **Voltage, V** & **Power, mW** \\ \hline sleeping & \(1\times 10^{-3}\) & 3.3 & \(3.3\times 10^{-3}\) \\ active & 3.34 & 3.3 & 11.022 \\ transmitting & 35.587 & 3.3 & 117.44 \\ \hline \end{tabular}
\end{table} 
Table 3: Sensor node power consumption in different modes. The node lifetime increases with capacitor size. knowledge of the equivalent circuit model and simply relies on the fact that the energy stored in the supercapacitor gradually dissipates. RF energy harvesting: Battery-less systems utilize a variety of energy sources, such as solar, vibration, temperature difference and wireless power transfer. RF energy harvesting is a relatively new technique, which harvests power from RF sources and can power devices in the environments where light, vibration and temperature difference are not available. The RF energy harvesting systems can scavenge ambient RF energy, such as Wi-Fi, or TV, or radio broadcast signal [21], or obtain energy radiated by dedicated RF transmitters. In [22], a battery-less RF sensor has been designed to monitor the quality of packed vegetables by observing their temperature and humidity. Such sensors receive a stable flow of energy from a nearby RFID reader for the entire duration of measurement, which is sufficient to complete the sensing and communication task. In contrast, the proposed approach uses sensors that are autonomous and that opportunistically collect energy from charging stations located in strategic positions, and therefore need to be able to extract and utilize tiny amounts of energy, wherever it is available. The work in [23; 24] proposed an RF energy harvesting system that powers low power devices from medium wave radio signals and that can operate forever within relatively large geographical areas, but only in the proximity of a powerful MW radio station. The hybrid approach proposed in this paper however is suitable for any area instrumented by relatively inexpensive and low power custom transmitting stations.