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Designer19

Member for

11 years 6 months

1,799

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 battery charging example compares direct solar battery charging vs. an MPPT algorithm combined with a buck converter.

The solar panel model in this example allows the user to specify not only the "boilerplate" electrical characteristics (i.e. the open circuit voltage, short circuit current and peak power output capability), which are always given at the full or nominal irradiance level, but also to specify the reduced output and shift in the peak power point at lower irradiance levels. This shift in the load voltage at which peak power transfer occurs gives rise to the performance improvement that can be achieved with MPPT (maximum power point tracking) when the irradiance level varies over time.

The "electronics" section of this design contains a few passive analog circuit elements, but consists mainly of abstract "math block" models. These are used to represent the state-average (non-switching) behavior of the converter. The sampled-data MPPT algorithm dynamically adjusts the buck duty-cycle, to keep the solar panel operating at its peak power output. The user can adjust various "tuning" parameters of that algorithm (e.g. sample rate, the duty-cycle "delta" or perturbation used for tracking, etc.). The simple algorithm is visible in the open-source "MPPT-Solar" model, just right click and select "View/Copy Model".

The simulation results show clear improvement in both panel power output (magenta vs. light blue waveforms) and battery input or charging current (red vs. dark blue waveforms), for MPPT vs. direct charging, respectively. Also, the actual duty-cycle "hunting" or peak power tracking operation is visible in green waveform, as the irradiance level varies sinusoidally (brown waveform).

A companion design is available, which shows a circuit implementation of the buck converter power stage. That design can be used to analyze the efficiency of the MPPT approach. Efficiency can be a key factor in the trade-off assessment vs. simple direct charging. That circuit design can be found here: https://www.systemvision.com/design/solar-energy-harvesting-implementation-mppt-battery-charging

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Electrothermal Energy Harvesting - MPPT Capacitor Charging

Designer19

Member for

11 years 6 months

1,799

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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Step-Down (Buck) DC to DC Converter - Continuous - encapsulateTest

Designer258427

Member for

7 months 3 weeks

4

designs

1

groups

Welcome to the community!!

Description

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Copy of Solar Energy Harvesting - Compare Direct vs. MPPT Battery Charging - on Tue, 09/10/2024 - 00:11

Designer131861

Member for

7 years 10 months

11

designs

1

groups

Add a bio to your profile to share information about yourself with other SystemVision users.

Description

This battery charging example compares direct solar battery charging vs. an MPPT algorithm combined with a buck converter.

The solar panel model in this example allows the user to specify not only the "boilerplate" electrical characteristics (i.e. the open circuit voltage, short circuit current and peak power output capability), which are always given at the full or nominal irradiance level, but also to specify the reduced output and shift in the peak power point at lower irradiance levels. This shift in the load voltage at which peak power transfer occurs gives rise to the performance improvement that can be achieved with MPPT (maximum power point tracking) when the irradiance level varies over time.

The "electronics" section of this design contains a few passive analog circuit elements, but consists mainly of abstract "math block" models. These are used to represent the state-average (non-switching) behavior of the converter. The sampled-data MPPT algorithm dynamically adjusts the buck duty-cycle, to keep the solar panel operating at its peak power output. The user can adjust various "tuning" parameters of that algorithm (e.g. sample rate, the duty-cycle "delta" or perturbation used for tracking, etc.). The simple algorithm is visible in the open-source "MPPT-Solar" model, just right click and select "View/Copy Model".

The simulation results show clear improvement in both panel power output (magenta vs. light blue waveforms) and battery input or charging current (red vs. dark blue waveforms), for MPPT vs. direct charging, respectively. Also, the actual duty-cycle "hunting" or peak power tracking operation is visible in green waveform, as the irradiance level varies sinusoidally (brown waveform).

A companion design is available, which shows a circuit implementation of the buck converter power stage. That design can be used to analyze the efficiency of the MPPT approach. Efficiency can be a key factor in the trade-off assessment vs. simple direct charging. That circuit design can be found here: https://www.systemvision.com/design/solar-energy-harvesting-implementation-mppt-battery-charging

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Copy of Electrothermal Energy Harvesting - MPPT Capacitor Charging - on Fri, 08/16/2024 - 14:13

Designer257853

Member for

8 months 3 weeks

16

designs

1

groups

I am a second-year Ph.D. student at UTP, serving as Professor in the Electrical Engineering program. Currently, I am working in the GCA under the supervision of Eduardo Giraldo. My research interests primarily focus on the optimal design of permanent magnet synchronous machines (PMSM), the design and construction of control systems, 3D printing, and electric mobility. Additionally, I am eager to learn more about robotics, topological optimization, aerospace engineering, and simulation of virtual environments.

Before starting my Ph.D. studies, I completed an MSc in electrical engineering. My thesis centered on designing, constructing, analyzing, and controlling a 3D-printed permanent magnet motor prototype. I also have extensive experience working in different 3D printing companies, where I developed projects for the Colombian industry. As an undergraduate student, I founded the IEEE Control Systems Society (CSS) UTP student branch chapter in 2018, enabling me to support students in their pursuit of different areas of knowledge.

Finally, I would like to announce that I recently founded the IEEE Robotics and Automation Society (RAS) and the IEEE Aerospace and Electronic Systems Society (AESS) UTP student branch chapters.

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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Copy of Solar Energy Harvesting - Compare Direct vs. MPPT Battery Charging - on Wed, 06/26/2024 - 15:12

Designer212493

Member for

6 years 2 months

4

designs

1

groups

Add a bio to your profile to share information about yourself with other SystemVision users.

Description

This battery charging example compares direct solar battery charging vs. an MPPT algorithm combined with a buck converter.

The solar panel model in this example allows the user to specify not only the "boilerplate" electrical characteristics (i.e. the open circuit voltage, short circuit current and peak power output capability), which are always given at the full or nominal irradiance level, but also to specify the reduced output and shift in the peak power point at lower irradiance levels. This shift in the load voltage at which peak power transfer occurs gives rise to the performance improvement that can be achieved with MPPT (maximum power point tracking) when the irradiance level varies over time.

The "electronics" section of this design contains a few passive analog circuit elements, but consists mainly of abstract "math block" models. These are used to represent the state-average (non-switching) behavior of the converter. The sampled-data MPPT algorithm dynamically adjusts the buck duty-cycle, to keep the solar panel operating at its peak power output. The user can adjust various "tuning" parameters of that algorithm (e.g. sample rate, the duty-cycle "delta" or perturbation used for tracking, etc.). The simple algorithm is visible in the open-source "MPPT-Solar" model, just right click and select "View/Copy Model".

The simulation results show clear improvement in both panel power output (magenta vs. light blue waveforms) and battery input or charging current (red vs. dark blue waveforms), for MPPT vs. direct charging, respectively. Also, the actual duty-cycle "hunting" or peak power tracking operation is visible in green waveform, as the irradiance level varies sinusoidally (brown waveform).

A companion design is available, which shows a circuit implementation of the buck converter power stage. That design can be used to analyze the efficiency of the MPPT approach. Efficiency can be a key factor in the trade-off assessment vs. simple direct charging. That circuit design can be found here: https://www.systemvision.com/design/solar-energy-harvesting-implementation-mppt-battery-charging

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Copy of Electrothermal Energy Harvesting - MPPT Capacitor Charging - on Thu, 05/16/2024 - 12:00

Designer256396

Member for

11 months 3 weeks

2

designs

1

groups

Welcome to the community!!

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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Copy of Solar Energy Harvesting - Compare Direct vs. MPPT Battery Charging - on Mon, 01/22/2024 - 22:22

Designer253368

Member for

1 year 3 months

0

designs

1

groups

Welcome to the community!!

Description

This battery charging example compares direct solar battery charging vs. an MPPT algorithm combined with a buck converter.

The solar panel model in this example allows the user to specify not only the "boilerplate" electrical characteristics (i.e. the open circuit voltage, short circuit current and peak power output capability), which are always given at the full or nominal irradiance level, but also to specify the reduced output and shift in the peak power point at lower irradiance levels. This shift in the load voltage at which peak power transfer occurs gives rise to the performance improvement that can be achieved with MPPT (maximum power point tracking) when the irradiance level varies over time.

The "electronics" section of this design contains a few passive analog circuit elements, but consists mainly of abstract "math block" models. These are used to represent the state-average (non-switching) behavior of the converter. The sampled-data MPPT algorithm dynamically adjusts the buck duty-cycle, to keep the solar panel operating at its peak power output. The user can adjust various "tuning" parameters of that algorithm (e.g. sample rate, the duty-cycle "delta" or perturbation used for tracking, etc.). The simple algorithm is visible in the open-source "MPPT-Solar" model, just right click and select "View/Copy Model".

The simulation results show clear improvement in both panel power output (magenta vs. light blue waveforms) and battery input or charging current (red vs. dark blue waveforms), for MPPT vs. direct charging, respectively. Also, the actual duty-cycle "hunting" or peak power tracking operation is visible in green waveform, as the irradiance level varies sinusoidally (brown waveform).

A companion design is available, which shows a circuit implementation of the buck converter power stage. That design can be used to analyze the efficiency of the MPPT approach. Efficiency can be a key factor in the trade-off assessment vs. simple direct charging. That circuit design can be found here: https://www.systemvision.com/design/solar-energy-harvesting-implementation-mppt-battery-charging

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Copy of Solar Energy Harvesting - Compare Direct vs. MPPT Battery Charging - on Mon, 01/22/2024 - 22:22

Designer253368

Member for

1 year 3 months

0

designs

1

groups

Welcome to the community!!

Description

This battery charging example compares direct solar battery charging vs. an MPPT algorithm combined with a buck converter.

The solar panel model in this example allows the user to specify not only the "boilerplate" electrical characteristics (i.e. the open circuit voltage, short circuit current and peak power output capability), which are always given at the full or nominal irradiance level, but also to specify the reduced output and shift in the peak power point at lower irradiance levels. This shift in the load voltage at which peak power transfer occurs gives rise to the performance improvement that can be achieved with MPPT (maximum power point tracking) when the irradiance level varies over time.

The "electronics" section of this design contains a few passive analog circuit elements, but consists mainly of abstract "math block" models. These are used to represent the state-average (non-switching) behavior of the converter. The sampled-data MPPT algorithm dynamically adjusts the buck duty-cycle, to keep the solar panel operating at its peak power output. The user can adjust various "tuning" parameters of that algorithm (e.g. sample rate, the duty-cycle "delta" or perturbation used for tracking, etc.). The simple algorithm is visible in the open-source "MPPT-Solar" model, just right click and select "View/Copy Model".

The simulation results show clear improvement in both panel power output (magenta vs. light blue waveforms) and battery input or charging current (red vs. dark blue waveforms), for MPPT vs. direct charging, respectively. Also, the actual duty-cycle "hunting" or peak power tracking operation is visible in green waveform, as the irradiance level varies sinusoidally (brown waveform).

A companion design is available, which shows a circuit implementation of the buck converter power stage. That design can be used to analyze the efficiency of the MPPT approach. Efficiency can be a key factor in the trade-off assessment vs. simple direct charging. That circuit design can be found here: https://www.systemvision.com/design/solar-energy-harvesting-implementation-mppt-battery-charging

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Copy of Solar Energy Harvesting - Compare Direct vs. MPPT Battery Charging - on Fri, 11/24/2023 - 13:46

Designer251696

Member for

1 year 5 months

5

designs

1

groups

Welcome to the community!!

Description

This battery charging example compares direct solar battery charging vs. an MPPT algorithm combined with a buck converter.

The solar panel model in this example allows the user to specify not only the "boilerplate" electrical characteristics (i.e. the open circuit voltage, short circuit current and peak power output capability), which are always given at the full or nominal irradiance level, but also to specify the reduced output and shift in the peak power point at lower irradiance levels. This shift in the load voltage at which peak power transfer occurs gives rise to the performance improvement that can be achieved with MPPT (maximum power point tracking) when the irradiance level varies over time.

The "electronics" section of this design contains a few passive analog circuit elements, but consists mainly of abstract "math block" models. These are used to represent the state-average (non-switching) behavior of the converter. The sampled-data MPPT algorithm dynamically adjusts the buck duty-cycle, to keep the solar panel operating at its peak power output. The user can adjust various "tuning" parameters of that algorithm (e.g. sample rate, the duty-cycle "delta" or perturbation used for tracking, etc.). The simple algorithm is visible in the open-source "MPPT-Solar" model, just right click and select "View/Copy Model".

The simulation results show clear improvement in both panel power output (magenta vs. light blue waveforms) and battery input or charging current (red vs. dark blue waveforms), for MPPT vs. direct charging, respectively. Also, the actual duty-cycle "hunting" or peak power tracking operation is visible in green waveform, as the irradiance level varies sinusoidally (brown waveform).

A companion design is available, which shows a circuit implementation of the buck converter power stage. That design can be used to analyze the efficiency of the MPPT approach. Efficiency can be a key factor in the trade-off assessment vs. simple direct charging. That circuit design can be found here: https://www.systemvision.com/design/solar-energy-harvesting-implementation-mppt-battery-charging

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