# Multiple Input Energy Harvesting Systems for Autonomous IoT End-Nodes

^{1}

^{2}

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## Abstract

**:**

## 1. Introduction

## 2. IoT End-Node Architecture and Power Management Units

_{ST}), and when the minimum operating value is reached, it sends a control signal to the main converter to start its operation. The main converter in the PMU can have either a switched-capacitor (SC) [3] or switched-inductor [5] implementation. It has been proved that inductor-based converters can harvest power from very low input voltages [15]. However, in order to show acceptable efficiency at the typical power levels of energy harvesting; they require to be implemented with a large external discrete component [6]. This increases the final cost and size of the PMU. On the other hand, SC topologies can be fully integrated [3] and still show similar performance for the same levels of input/output power.

_{Q}) and active (I

_{ACT}) current consumptions are also shown, and their sum is representative of the energy requirements of an IoT end-node. From Table 1, it is observed that the minimum instantaneous power consumption of a typical IoT node in standby mode is within the range of 10’s of microwatts. When actively sensing and transmitting data, the consumption of the node can then reach up to several 100’s of milliwatts. As a way to reduce the average power (P

_{AVRG}) consumed by the IoT system, it is commonly placed under a duty-cycled operation, as depicted in Figure 3.

_{ST}) can be maintained within the minimum and maximum values required by the final regulation stage of the PMU.

_{ST}) needed to constrain the drop in the output voltage (when the system is in active mode) can be calculated using:

_{dchrg}is the total current consumed by the node in active operation, and t

_{dchrg}is the duration of this mode. Both I

_{dchrg}and t

_{dchrh}are defined by individual specs of the system’s components. Observe that a constant discharging current is considered in Equation (1), and that this is just an approximation of actual behavior.

_{ST}to be charged back again to its maximum voltage can be calculated as:

_{o}= 3.3 V to an IoT sensor node system. This is a valid supply voltage for all the components listed in Table 1. If the PMU has an LDO in the regulation block, there is a minimum voltage that is needed at the storage capacitance. This voltage can be estimated as:

_{DO}is the dropout voltage in the linear regulator. Assuming the use of a LP5907 regulator (see Table 1), then V

_{DO}= 200 mV for an output current of 250 mA. That gives V

_{ST,min}= 3.5 V. The maximum voltage allowed in the storage capacitor would be given by the maximum value that the LP5907 tolerates at its input, that is V

_{ST,max}= 5.5 V.

_{dchrg}) and the total current that is being drawn during this time. From Table 1 we observe that the current drawn from the CC3120 Wi-Fi processor is the dominant value over all other components, so we assume I

_{dchrg}≈ 230 mA. If the active time is 10 ms, then:

_{chrg,min}≈ 24 s. This represents a heavily duty-cycled operation with D ≈ 0.04%. Also, observe that the total quiescent current consumption of the IoT node (I

_{Q}≈ 7.5 μA per Table 1) was neglected in the previous calculation, as well as the leakage current in the storage capacitor (estimated below 1 µA [16]). If we consider these extra current consumptions, the total charging time would have to increase its value by almost 10%.

## 3. Overview of Multisource Energy Harvesting Techniques

#### 3.1. Simple methods for Multisource Energy Harvesting

#### 3.1.1. Complementary Use of Energy Sources

_{bias}), which provided the supply voltage to some bias and reference circuits.

#### 3.1.2. Power ORing

_{SC}) ensures the maximum transfer of power from the parallel connection of harvesters [21]. However, this comes at the expense of losing tracking efficiency for each individual transducer, especially for a large number of inputs [14]. Finally, it is important to observe that, in the system of Figure 5; the energy coming from all the harvesters is not really added-up. Rather, only the largest input voltage from V

_{1}, V

_{2}… V

_{N}is selected and delivered to the output. This strategy works well for complementary harvesters (like solar and wind transducers), where usually it is not expected that they will be simultaneously delivering a significant amount of energy. However, the same scheme would offer a poor performance in scenarios where multiple heterogeneous harvesters are at the same time delivering different but comparable levels of energy.

#### 3.1.3. Voltage Level Detection

_{max}, they are disconnected from the battery charging circuit till they charge up their corresponding output capacitors. The precise value of V

_{max}would depend on the battery type that is being used. The battery charger is disconnected when the output voltages of the subsystems decrease below a certain minimum threshold, and then connected back again when any of the capacitors reach V

_{max}.

#### 3.2. Architectures for Multiple Source Energy Combining

#### 3.2.1. Energy Combining Through Linear Regulators

#### 3.2.2. Multiple-Input Boost Converter

#### 3.2.3. Shared-Inductor DC-DC Converters

_{buff}) is not directly connected to the harvester, but through an extra pin in the circuit (V

_{CAP}). Thus, 2 external pins per harvester are needed; as shown in Figure 8. This approach reduces the required sampling time down to 2-µs, and the operation is repeated every 8 energy-extraction cycles of the boost converter (i.e., every 25 ms). This scheme allows following the variations of the input voltage, and reducing the wasted energy in the FOCV sampling process when the harvester is disconnected.

_{em}is the emulated resistance of the boost converter, T

_{CLK}is the switching period and L is the inductor’s value. Also, N

_{i}is the number of clock cycles given to the ith-input and N

_{T}is the total number of clock cycles. The previous approach is similar to a hill-climbing algorithm [3], but with a simplified sensing scheme that does not require the measurement of current, as it is replaced by N

_{i}as a parameter that reflects the average current extracted from the harvester.

#### 3.2.4. Fully Integrated Switched-Capacitor Converter for Concurrent Energy Harvesting

_{2}is converted into AC form using a differential low-power oscillator (I

_{0}) composed of thyristor-based delay cells. Then, with the help of drivers I

_{1}and I

_{2,}the pulsed-shaped waveform is coupled to the intermediate nodes (v

_{A}and v

_{B}) through capacitors C

_{1}and C

_{2}. The peak-to-peak voltage of nodes v

_{A}and v

_{B}would equal to V

_{i1}+ V

_{i2}which is further rectified by the transistor pair M

_{3}-M

_{4}. If a large capacitor is connected at the output node of the circuit, V

_{out}will consist of a DC voltage equivalent to the sum of both inputs.

_{1}and C

_{2.}The capacitors are first charged to the voltage V

_{i1}implying the storage of a certain amount of energy. When the voltage at those capacitors is increased to V

_{i1}+ V

_{i2}, the extra charge that has been stored represents an increase in the available energy on the capacitors, resulting in the addition of energies coming from the two individual sources.

#### 3.2.5. Performance Comparison of Multisource Energy Harvesting Architectures

## 4. Conclusions and Open Areas of Research

## Acknowledgments

## Author Contributions

## Conflicts of Interest

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**Figure 2.**Simple architecture of a power management unit for energy harvesting [14].

**Figure 3.**Transient waveforms of the voltage at the storage element (V

_{ST}) in the power management unit (PMU), and the power consumption of an IoT end-node in duty-cycled operation.

**Figure 4.**Simplified architecture for complementary use of energy harvesting sources [11].

**Figure 6.**Simplified scheme of a multiharvested circuit architecture using linear regulators [16].

**Figure 7.**Non-isolated multiple input boost converter proposed in [27].

**Figure 8.**Buck-boost based energy combiner with shared inductor scheme [18].

**Figure 9.**Basic concept of a switched capacitor based (i.e., fully integrated) DC power combiner for energy harvesting.

**Figure 10.**Two-input DC switched-capacitor combiner, which is used as a module for the architecture shown in Figure 9.

Device | Type | I_{Q} | I_{ACTV} |
---|---|---|---|

HDC1080 | Digital Humidity Sensor | 100 nA | 710 nA |

LMT70 | Analog Temperature Sensor | 50 nA | 9.2 µA |

MSP430F1491 | Ultra-low-power mixed-signal µCU | 1.6 µA | 280 µA (at 1 MHz) |

CC3120 | Wi-Fi Wireless Network Processor | 4.5 µA | 59 mA/229 mA (RX/TX) |

XB24-AWI-001 | Zigbee RF Module | 3 µA | 31 mA / 45 mA (RX/TX) |

ADS1113 | I^{2}C-compatible 16-bit ADC | 500 nA | 150 μA |

LPV542 | Dual CMOS Op Amp | 490 nA (per channel) | N.A. |

LP5907 | Low-I_{Q} Linear Regulator | 200 nA | 250 µA |

Device | Type | Size | Power | Conditions |
---|---|---|---|---|

PPA-1001 | Piezo | 54 mm × 22 mm × 0.46 mm | 2.2 mW (RMS) | Acceleration—2 g |

KXOB22-04X3 | Solar | 22 mm × 7 mm × 1.8 mm | 20.1 mW | Irradiation—100 mW/cm^{2} |

TGP-651 | Thermal | 15 mm × 10 mm × 9.5 mm | 2.5 mW | Hot side temperature—60 °C |

Ref. | Topology | No. of Inputs | Inputs Type | Technology | MPPT | Battery Charging | Peak η | Input Power | Quiescent Current |
---|---|---|---|---|---|---|---|---|---|

[11] | Complemen-tary use | 2 | TEG PZT | HV 0.35 µm CMOS | No | No | 82% | NA | 300 nA |

[12] | Power ORing | 2 | PV Wind | Discrete | Yes | Yes | 80% (PV 85% (wind) | NA | NA |

[20] | Power ORing | 2 | PV PZT | Discrete | Yes | Yes | 85% (PV) 68% (PZT) | 60 mW (PV) 3 mW (PZT) | NA |

[21] | Power ORing | 2 | PV TEG | Discrete | Yes | No | 91% | 392 µW | 50 µA |

[22] | Power ORing | 2 | DC AC | Commercial IC | No | Yes | ≈ 90% | ≈ 4 mW | 950 nA |

[23] | Power ORing | 2 | DC AC | Commercial IC | No | No | ≈ 90% | NA | 1.5 µA |

[24] | Level detection | 2 | RF TEG | 0.35 µm CMOS | No | Yes | 50% | NA | 70 µA |

[25] | Level detection | 3 | DC | 0.13 µm CMOS | No | Yes | 95% | 85 µW | 1.3 µA |

[27] | LDO | 3 | RF, PZT PV | 0.13 µm CMOS | No | No | 85% | 7.3 mW | 65 µA |

[28] | Boost (multiple L) | 2 | DC | Discrete | No | No | NA | NA | NA |

[18] | Shared Inductor | 9 | TEG PZT RF PV | 0.32 µm BCD | Yes | No | 89.6% | 101 µW (TEG) 59 µW (PZT) 55 µW (PV) | 431 nA |

[19] | Shared Inductor | 3 | PZT RF PV | 0.18 µm CMOS | Yes | No | 87% | 20 µW | 18 nA |

[29] | Shared Inductor | 3 | TEG PZT PV | 0.35 µm CMOS | Yes | No | 83% (PV) 58% (TEG) 79% (PZT) | NA | 2.7 µA |

[30] | Shared inductor | 2 | TEG PV | Discrete | Yes | No | NA | 2.5 mW (TEG) 250 µW (PV) | NA |

[31] | SC | 3 | DC | 0.13 µm CMOS | Yes (manual) | No | 58.4% | 600 µW | NA |

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**MDPI and ACS Style**

Estrada-López, J.J.; Abuellil, A.; Zeng, Z.; Sánchez-Sinencio, E.
Multiple Input Energy Harvesting Systems for Autonomous IoT End-Nodes. *J. Low Power Electron. Appl.* **2018**, *8*, 6.
https://doi.org/10.3390/jlpea8010006

**AMA Style**

Estrada-López JJ, Abuellil A, Zeng Z, Sánchez-Sinencio E.
Multiple Input Energy Harvesting Systems for Autonomous IoT End-Nodes. *Journal of Low Power Electronics and Applications*. 2018; 8(1):6.
https://doi.org/10.3390/jlpea8010006

**Chicago/Turabian Style**

Estrada-López, Johan J., Amr Abuellil, Zizhen Zeng, and Edgar Sánchez-Sinencio.
2018. "Multiple Input Energy Harvesting Systems for Autonomous IoT End-Nodes" *Journal of Low Power Electronics and Applications* 8, no. 1: 6.
https://doi.org/10.3390/jlpea8010006