# Energy-Aware System Design for Autonomous Wireless Sensor Nodes: A Comprehensive Review
## 4 Energy Management
### Energy Management for Single Sources  
Energy management circuits generally include several parts, such as impedance matching circuits, rectifiers, voltage multipliers, DC-DC converters or AC-DC converters, to realize the required output level to the load, which can be a battery, a super-capacitor or the WSN itself (see Figure 7). The elements of energy management can also be active, partly passive [76] or completely passive, where the passive solutions do not require energy supply. For example, DC-DC converters are preferred to classic voltage regulators when the working conditions are stable. However, the selection of an optimum regulator is critical when temperature changes and internal losses occur.  
Figure 6: Operation states of a WSN with respect to energy.  
Energy harvesting sources have a specific current/voltage behavior and a typically fluctuating energy profile. Energy sources, such as solar cells, may deliver different currents depending on the voltage following their characteristics. A maximum efficiency extraction (MEE) is important, and therefore DC-DC converters or AC-DC converters are used to match the impedance of the source to the connected load impedance. They can thereby realize a voltage multiplication to enhance the level of the output voltage. The main challenge in the design of DC/AC-DC converters is the power consumption due to losses of the diode bridges and switching circuits, which becomes more critical at low power levels. Besides, additional sensors may be required to measure characteristics of the source such as energy, voltage peak level or impedance.  
The sources are subject to changes due to environmental conditions and aging. Therefore, maximum power point tracking (MPPT) is needed to follow these changes and maintain an efficient energy extraction. Many control algorithms can be implemented for that, such as perturb and observe, PI controllers, fuzzy logic, neural networks and artificial intelligence algorithm. Tracking maximum power within proper efficiency leads to compensation of changes and environment losses even at a varied duty cycle. MPPT can be realized within AC and DC converters by applying control algorithms to them in a defined manner. Different techniques can be adopted for this, including resistive matching and conjugate impedance matching, depending on the nature of the input of the power processing circuit. Several methods have been demonstrated, such as perturb and observe (P&O) or regulating he output voltage or output current of the diode bridge [77].  
Other techniques allow the use of MPPT in certain ambient power scenarios to extract energy even more efficiently, e.g., parallel synchronized switch harvesting on inductor (P-SSHI) [78] and double synchronized switch harvesting (DSSH) [78]. The aim is to synchronize the voltage and current as well as eliminate the phase shift between them to reach a high energy level. The synchronization can be realized electronically, e.g., by implementing peak detectors. In [79], a random mechanical switching harvester on inductor (RMSHI) has been proposed for piezoelectric transducers, which realizes this synchronization directly from the mechanical part; thus, no electric energy is needed for the synchronization, bringing big advantages in the case of ultra-low-energy sources.