IoT | PartQuest™ Explore

Electrodynamic Vibration Energy Harvesting for IoT/IIoT - with State-Average Boost Converter

Steven_2
Designer202382

Steven_2

Member for

6 years 2 months

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Description

This example is intended to show relevant modeling and simulation capabilities of SystemVision Cloud, for electrodynamic energy harvesting (EH) systems. It is not necessarily a practical EH design itself, but rather demonstrates the tool's ability to support knowledgeable users who are creating practical designs.The mechanical and magnetic circuit sections of the model are composed of "physical" models, in that user can directly specify size and physical properties of the components. This includes the mass of the armature, the stiffness of the resonant spring, the cross section area and length of the magnetic core, the residual flux density of the permanent magnet, and the number of winding turns.The electronics section (rectifier and boost converter) contains a mix of passive analog circuit elements as well as abstract or "math block" models to represent the state-average (non-switching) behavior of the converter. Finally, constant power load model represents the power demand for periodic transmission of data typical of an (I)IoT sensor node.In the simulation results displayed on the schematic, the upper right waveform viewer shows the amplitude of the external vibration source (e.g. a motor or transformer housing) of 0.07mm peak at 60 Hz, equivalent to a peak acceleration of 1g (light-blue waveform). The armature spring-mass resonance frequency is 60 Hz, so the armature displacement is seen to reach the frame's travel limit of 4mm peak-to-peak (green waveform).In the upper left, the two waveform viewers are zoomed-in near the 1 second simulation time mark, and they show the air-gap lengths and the corresponding core flux density and winding voltage. Note that the air-gaps are configured in parallel for the flux path, so the effective path reluctance is minimized when either gap approaches zero length.In the lower right, the relatively low value of the rectified "DC" voltage is observed (red waveform), as well as the regulated boost output voltage that supplies the transmitter load.

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Electrodynamic Vibration Energy Harvesting for IoT/IIoT - with State-Average Boost Converter

KDAS
Designer197889

KDAS

Member for

6 years 7 months

8

designs

1

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Description

This example is intended to show relevant modeling and simulation capabilities of SystemVision Cloud, for electrodynamic energy harvesting (EH) systems. It is not necessarily a practical EH design itself, but rather demonstrates the tool's ability to support knowledgeable users who are creating practical designs.The mechanical and magnetic circuit sections of the model are composed of "physical" models, in that user can directly specify size and physical properties of the components. This includes the mass of the armature, the stiffness of the resonant spring, the cross section area and length of the magnetic core, the residual flux density of the permanent magnet, and the number of winding turns.The electronics section (rectifier and boost converter) contains a mix of passive analog circuit elements as well as abstract or "math block" models to represent the state-average (non-switching) behavior of the converter. Finally, constant power load model represents the power demand for periodic transmission of data typical of an (I)IoT sensor node.In the simulation results displayed on the schematic, the upper right waveform viewer shows the amplitude of the external vibration source (e.g. a motor or transformer housing) of 0.07mm peak at 60 Hz, equivalent to a peak acceleration of 1g (light-blue waveform). The armature spring-mass resonance frequency is 60 Hz, so the armature displacement is seen to reach the frame's travel limit of 4mm peak-to-peak (green waveform).In the upper left, the two waveform viewers are zoomed-in near the 1 second simulation time mark, and they show the air-gap lengths and the corresponding core flux density and winding voltage. Note that the air-gaps are configured in parallel for the flux path, so the effective path reluctance is minimized when either gap approaches zero length.In the lower right, the relatively low value of the rectified "DC" voltage is observed (red waveform), as well as the regulated boost output voltage that supplies the transmitter load.

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Electrothermal Energy Harvesting - MPPT Capacitor Charging

Ilmir
Designer197998

Ilmir

Member for

6 years 6 months

5

designs

1

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Description

This example is intended to show relevant modeling and simulation capabilities of SystemVision Cloud for Electrothermal Energy Harvesting (EH) systems. It is not necessarily a practical EH design itself, but rather demonstrates the tool's ability to support knowledgeable users who are creating practical designs. The example also illustrates using a sampled-data algorithm for maximum power point tracking (MPPT), to optimize the energy harvest for changing operating temperatures.The design includes a thermoelectric generator (TEG) that is supplied on the "hot" side by a sinusoidally time varying temperature between 75 degC and 100 degC. The "cold" side is held at a fixed 25 degC. The thermal resistance and heat capacitance of the hot-side heat-sink are shown in the schematic. The electronics section includes a mix of analog circuit elements, including an inductor, 1.0 F super-capacitor, LDO regulator and a periodically switched load resistor. It also includes abstract or "math block" models to represent the state-average (non-switching) behavior of a buck-boost converter.The goal of the design is to extract sufficient power from the TEG, to provide a 2.5-Watt/1-second duration power burst once every 10 seconds. This burst is presumably to supply power for a periodic data transmission. The simple MPPT algorithm that helps achieves this is visible in the open-source MPPT-TEG model shown. The MPPT algorithm dynamically adjusts the load current draw from the TEG, to keep it operating at its maximum power output capability. That capability varies with the differential operating temperature. That shift can more easily be seen in the followingTEC/TEG calibration test schematic:https://www.systemvision.com/design/calibrate-tecteg-energy-harvesting

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Live Electrothermal Energy Harvesting

Mike Donnelly
Designer19

Mike Donnelly

Member for

11 years

1,696

designs

10

groups

Member of the PartQuest Explore Development Team. Focused on modeling and simulation of analog, mixed-signal and multi-discipline systems covering a broad range of applications, including power electronics, controls and mechatronic systems.

Description

This example is intended to show relevant modeling and simulation capabilities of SystemVision Cloud for Electrothermal Energy Harvesting (EH) systems. It is not necessarily a practical EH design itself, but rather demonstrates the tool's ability to support knowledgeable users who are creating practical designs. The example also illustrates using a sampled-data algorithm for maximum power point tracking (MPPT), to optimize the energy harvest for changing operating temperatures.The design includes a thermoelectric generator (TEG) that is supplied on the "hot" side by a sinusoidally time varying temperature between 75 degC and 100 degC. The "cold" side is held at a fixed 25 degC. The thermal resistance and heat capacitance of the hot-side heat-sink are shown in the schematic. The electronics section includes a mix of analog circuit elements, including an inductor, 1.0 F super-capacitor, LDO regulator and a periodically switched load resistor. It also includes abstract or "math block" models to represent the state-average (non-switching) behavior of a buck-boost converter.The goal of the design is to extract sufficient power from the TEG, to provide a 2.5-Watt/1-second duration power burst once every 10 seconds. This burst is presumably to supply power for a periodic data transmission. The simple MPPT algorithm that helps achieves this is visible in the open-source MPPT-TEG model shown. The MPPT algorithm dynamically adjusts the load current draw from the TEG, to keep it operating at its maximum power output capability. That capability varies with the differential operating temperature. That shift can more easily be seen in the followingTEC/TEG calibration test schematic:https://www.systemvision.com/design/calibrate-tecteg-energy-harvesting

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Test EH Tunable

Mike Donnelly
Designer19

Mike Donnelly

Member for

11 years

1,696

designs

10

groups

Member of the PartQuest Explore Development Team. Focused on modeling and simulation of analog, mixed-signal and multi-discipline systems covering a broad range of applications, including power electronics, controls and mechatronic systems.

Description

This example is intended to show relevant modeling and simulation capabilities of SystemVision Cloud, for electrodynamic energy harvesting (EH) systems. It is not necessarily a practical EH design itself, but rather demonstrates the tool's ability to support knowledgeable users who are creating practical designs.The mechanical and magnetic circuit sections of the model are composed of "physical" models, in that user can directly specify size and physical properties of the components. This includes the mass of the armature, the stiffness of the resonant spring, the cross section area and length of the magnetic core, the residual flux density of the permanent magnet, and the number of winding turns.The electronics section (rectifier and boost converter) contains a mix of passive analog circuit elements as well as abstract or "math block" models to represent the state-average (non-switching) behavior of the converter. Finally, constant power load model represents the power demand for periodic transmission of data typical of an (I)IoT sensor node.In the simulation results displayed on the schematic, the upper right waveform viewer shows the amplitude of the external vibration source (e.g. a motor or transformer housing) of 0.07mm peak at 60 Hz, equivalent to a peak acceleration of 1g (light-blue waveform). The armature spring-mass resonance frequency is 60 Hz, so the armature displacement is seen to reach the frame's travel limit of 4mm peak-to-peak (green waveform).In the upper left, the two waveform viewers are zoomed-in near the 1 second simulation time mark, and they show the air-gap lengths and the corresponding core flux density and winding voltage. Note that the air-gaps are configured in parallel for the flux path, so the effective path reluctance is minimized when either gap approaches zero length.In the lower right, the relatively low value of the rectified "DC" voltage is observed (red waveform), as well as the regulated boost output voltage that supplies the transmitter load.

About text formats

Electrodynamic Vibration Energy Harvesting for IoT/IIoT - with State-Average Boost Converter

Ilmir
Designer197998

Ilmir

Member for

6 years 6 months

5

designs

1

groups

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Description

This example is intended to show relevant modeling and simulation capabilities of SystemVision Cloud, for electrodynamic energy harvesting (EH) systems. It is not necessarily a practical EH design itself, but rather demonstrates the tool's ability to support knowledgeable users who are creating practical designs.The mechanical and magnetic circuit sections of the model are composed of "physical" models, in that user can directly specify size and physical properties of the components. This includes the mass of the armature, the stiffness of the resonant spring, the cross section area and length of the magnetic core, the residual flux density of the permanent magnet, and the number of winding turns.The electronics section (rectifier and boost converter) contains a mix of passive analog circuit elements as well as abstract or "math block" models to represent the state-average (non-switching) behavior of the converter. Finally, constant power load model represents the power demand for periodic transmission of data typical of an (I)IoT sensor node.In the simulation results displayed on the schematic, the upper right waveform viewer shows the amplitude of the external vibration source (e.g. a motor or transformer housing) of 0.07mm peak at 60 Hz, equivalent to a peak acceleration of 1g (light-blue waveform). The armature spring-mass resonance frequency is 60 Hz, so the armature displacement is seen to reach the frame's travel limit of 4mm peak-to-peak (green waveform).In the upper left, the two waveform viewers are zoomed-in near the 1 second simulation time mark, and they show the air-gap lengths and the corresponding core flux density and winding voltage. Note that the air-gaps are configured in parallel for the flux path, so the effective path reluctance is minimized when either gap approaches zero length.In the lower right, the relatively low value of the rectified "DC" voltage is observed (red waveform), as well as the regulated boost output voltage that supplies the transmitter load.

About text formats

Electrodynamic Vibration Energy Harvesting for IoT/IIoT - with State-Average Boost Converter

ilmirkhai1405
Designer197835

ilmirkhai1405

Member for

6 years 7 months

2

designs

1

groups

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Description

This example is intended to show relevant modeling and simulation capabilities of SystemVision Cloud, for electrodynamic energy harvesting (EH) systems. It is not necessarily a practical EH design itself, but rather demonstrates the tool's ability to support knowledgeable users who are creating practical designs.The mechanical and magnetic circuit sections of the model are composed of "physical" models, in that user can directly specify size and physical properties of the components. This includes the mass of the armature, the stiffness of the resonant spring, the cross section area and length of the magnetic core, the residual flux density of the permanent magnet, and the number of winding turns.The electronics section (rectifier and boost converter) contains a mix of passive analog circuit elements as well as abstract or "math block" models to represent the state-average (non-switching) behavior of the converter. Finally, constant power load model represents the power demand for periodic transmission of data typical of an (I)IoT sensor node.In the simulation results displayed on the schematic, the upper right waveform viewer shows the amplitude of the external vibration source (e.g. a motor or transformer housing) of 0.07mm peak at 60 Hz, equivalent to a peak acceleration of 1g (light-blue waveform). The armature spring-mass resonance frequency is 60 Hz, so the armature displacement is seen to reach the frame's travel limit of 4mm peak-to-peak (green waveform).In the upper left, the two waveform viewers are zoomed-in near the 1 second simulation time mark, and they show the air-gap lengths and the corresponding core flux density and winding voltage. Note that the air-gaps are configured in parallel for the flux path, so the effective path reluctance is minimized when either gap approaches zero length.In the lower right, the relatively low value of the rectified "DC" voltage is observed (red waveform), as well as the regulated boost output voltage that supplies the transmitter load.

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SONOFF

TamsSzab_1
Designer175231

TamsSzab_1

Member for

6 years 10 months

1

designs

1

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Energy Harvesting from TEC12706

JeanVega
Designer152491

JeanVega

Member for

7 years 1 month

2

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Electrothermal Energy Harvesting - MPPT Capacitor Charging

Ricardo_1
Designer152396

Ricardo_1

Member for

7 years 1 month

1

designs

1

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Description

This example is intended to show relevant modeling and simulation capabilities of SystemVision Cloud for Electrothermal Energy Harvesting (EH) systems. It is not necessarily a practical EH design itself, but rather demonstrates the tool's ability to support knowledgeable users who are creating practical designs. The example also illustrates using a sampled-data algorithm for maximum power point tracking (MPPT), to optimize the energy harvest for changing operating temperatures.The design includes a thermoelectric generator (TEG) that is supplied on the "hot" side by a sinusoidally time varying temperature between 75 degC and 100 degC. The "cold" side is held at a fixed 25 degC. The thermal resistance and heat capacitance of the hot-side heat-sink are shown in the schematic. The electronics section includes a mix of analog circuit elements, including an inductor, 1.0 F super-capacitor, LDO regulator and a periodically switched load resistor. It also includes abstract or "math block" models to represent the state-average (non-switching) behavior of a buck-boost converter.The goal of the design is to extract sufficient power from the TEG, to provide a 2.5-Watt/1-second duration power burst once every 10 seconds. This burst is presumably to supply power for a periodic data transmission. The simple MPPT algorithm that helps achieves this is visible in the open-source MPPT-TEG model shown. The MPPT algorithm dynamically adjusts the load current draw from the TEG, to keep it operating at its maximum power output capability. That capability varies with the differential operating temperature. That shift can more easily be seen in the followingTEC/TEG calibration test schematic:https://www.systemvision.com/design/calibrate-tecteg-energy-harvesting

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