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Copy of Solar Energy Harvesting - Compare Direct vs. MPPT Battery Charging - on Thu, 02/18/2021 - 09:43

jmorenom
Designer233465

jmorenom

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4 years 5 months

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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 for Battery Charging - on Thu, 01/21/2021 - 10:42

vicente.gongora1
Designer231827

vicente.gongora1

Member for

4 years 7 months

4

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Doctor professor in electrical engineering courses at Senai technology college, in Londrina Pr. Brasil. Areas of interest, static power converters and electric drives.

Description

This circuit is an implementation of a buck converter power stage that could be used in the MPPT solar battery charger reference design found here: https://www.systemvision.com/design/solar-energy-harvesting-compare-direct-vs-mppt-battery-charging

That reference example is appropriate for "system level" trade-off assessment, where the MPPT (maximum power point tracking) approach can be compared with direct solar panel battery charging. It uses a state-average (non-switching) buck converter model for much faster simulation, so that power tracking performance over long time periods can be observed. However, it does not account for some important aspects of a real converter implementation, such as the predicted power loss in the switching components, or the switching noise on the current and voltage measurements that are needed for power detection.

This circuit confirms the performance of the system at full solar panel irradiance, and with the converter duty-cycle set to a fixed value of 0.8. That value was shown to provide maximum power under full irradiance. The results with this design confirm those of the reference design: The steady-state panel power output is just under 60 Watts (light blue waveform); The corresponding voltage (16 V) and current (3.7 A) into the converter (magenta and green waveforms, respectively); The current into the battery is 4.5 A (red waveform), as expected. Note also that the input L-C filter removes most of the switching noise that would be visible on these signals without that filtering effect.

The average power loss in the P-channel MOSFET is 1.3 Watts (brown waveform). This is important for assessing overall system efficiency, a key factor in the trade-off analysis with direct charging. The user can move the waveform probes around and observe the power loss in all of the other components too, as part of the efficiency analysis process.

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Copy of Solar Energy Harvesting - Compare Direct vs. MPPT Battery Charging - on Tue, 12/08/2020 - 15:21

biskovic
Designer237063

biskovic

Member for

4 years

1

designs

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Industrial Electronics and Automation Engineer, with a Master's degree in Embedded 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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Copy of Solar Energy Harvesting - Compare Direct vs. MPPT Battery Charging - on Fri, 12/04/2020 - 12:14

abid.dahouar
Designer236996

abid.dahouar

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4 years

1

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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 Panel Connection - Basic Parallel - on Sun, 11/08/2020 - 14:10

gim
Designer237346

gim

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3 years 11 months

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Solar Energy Harvesting - Implementation of MPPT Battery Charging

cesar.dominguez
Designer231580

cesar.dominguez

Member for

4 years 7 months

6

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Description

This circuit is an implementation of a buck converter power stage that could be used in the MPPT solar battery charger reference design found here: https://www.systemvision.com/design/solar-energy-harvesting-compare-direct-vs-mppt-battery-charging

That reference example is appropriate for "system level" trade-off assessment, where the MPPT (maximum power point tracking) approach can be compared with direct solar panel battery charging. It uses a state-average (non-switching) buck converter model for much faster simulation, so that power tracking performance over long time periods can be observed. However, it does not account for some important aspects of a real converter implementation, such as the predicted power loss in the switching components, or the switching noise on the current and voltage measurements that are needed for power detection.

This circuit confirms the performance of the system at full solar panel irradiance, and with the converter duty-cycle set to a fixed value of 0.8. That value was shown to provide maximum power under full irradiance. The results with this design confirm those of the reference design: The steady-state panel power output is just under 60 Watts (light blue waveform); The corresponding voltage (16 V) and current (3.7 A) into the converter (magenta and green waveforms, respectively); The current into the battery is 4.5 A (red waveform), as expected. Note also that the input L-C filter removes most of the switching noise that would be visible on these signals without that filtering effect.

The average power loss in the P-channel MOSFET is 1.3 Watts (brown waveform). This is important for assessing overall system efficiency, a key factor in the trade-off analysis with direct charging. The user can move the waveform probes around and observe the power loss in all of the other components too, as part of the efficiency analysis process.

About text formats

Solar Energy Harvesting - Compare Direct vs. MPPT Battery Charging

cesar.dominguez
Designer231580

cesar.dominguez

Member for

4 years 7 months

6

designs

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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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TP_OCASS

m.fayolle
Designer236042

m.fayolle

Member for

4 years 1 month

9

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Description

This circuit is an implementation of a buck converter power stage that could be used in the MPPT solar battery charger reference design found here: https://www.systemvision.com/design/solar-energy-harvesting-compare-direct-vs-mppt-battery-charging

That reference example is appropriate for "system level" trade-off assessment, where the MPPT (maximum power point tracking) approach can be compared with direct solar panel battery charging. It uses a state-average (non-switching) buck converter model for much faster simulation, so that power tracking performance over long time periods can be observed. However, it does not account for some important aspects of a real converter implementation, such as the predicted power loss in the switching components, or the switching noise on the current and voltage measurements that are needed for power detection.

This circuit confirms the performance of the system at full solar panel irradiance, and with the converter duty-cycle set to a fixed value of 0.8. That value was shown to provide maximum power under full irradiance. The results with this design confirm those of the reference design: The steady-state panel power output is just under 60 Watts (light blue waveform); The corresponding voltage (16 V) and current (3.7 A) into the converter (magenta and green waveforms, respectively); The current into the battery is 4.5 A (red waveform), as expected. Note also that the input L-C filter removes most of the switching noise that would be visible on these signals without that filtering effect.

The average power loss in the P-channel MOSFET is 1.3 Watts (brown waveform). This is important for assessing overall system efficiency, a key factor in the trade-off analysis with direct charging. The user can move the waveform probes around and observe the power loss in all of the other components too, as part of the efficiency analysis process.

About text formats

Copy of Solar Energy Harvesting - Implementation of MPPT Battery Charging - on Mon, 11/02/2020 - 11:55

m.fayolle
Designer236042

m.fayolle

Member for

4 years 1 month

9

designs

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

Description

This circuit is an implementation of a buck converter power stage that could be used in the MPPT solar battery charger reference design found here: https://www.systemvision.com/design/solar-energy-harvesting-compare-direct-vs-mppt-battery-charging

That reference example is appropriate for "system level" trade-off assessment, where the MPPT (maximum power point tracking) approach can be compared with direct solar panel battery charging. It uses a state-average (non-switching) buck converter model for much faster simulation, so that power tracking performance over long time periods can be observed. However, it does not account for some important aspects of a real converter implementation, such as the predicted power loss in the switching components, or the switching noise on the current and voltage measurements that are needed for power detection.

This circuit confirms the performance of the system at full solar panel irradiance, and with the converter duty-cycle set to a fixed value of 0.8. That value was shown to provide maximum power under full irradiance. The results with this design confirm those of the reference design: The steady-state panel power output is just under 60 Watts (light blue waveform); The corresponding voltage (16 V) and current (3.7 A) into the converter (magenta and green waveforms, respectively); The current into the battery is 4.5 A (red waveform), as expected. Note also that the input L-C filter removes most of the switching noise that would be visible on these signals without that filtering effect.

The average power loss in the P-channel MOSFET is 1.3 Watts (brown waveform). This is important for assessing overall system efficiency, a key factor in the trade-off analysis with direct charging. The user can move the waveform probes around and observe the power loss in all of the other components too, as part of the efficiency analysis process.

About text formats

Copy of Solar Energy Harvesting - Implementation of MPPT Battery Charging - on Fri, 10/23/2020 - 11:02

m.fayolle
Designer236042

m.fayolle

Member for

4 years 1 month

9

designs

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

Description

This circuit is an implementation of a buck converter power stage that could be used in the MPPT solar battery charger reference design found here: https://www.systemvision.com/design/solar-energy-harvesting-compare-direct-vs-mppt-battery-charging

That reference example is appropriate for "system level" trade-off assessment, where the MPPT (maximum power point tracking) approach can be compared with direct solar panel battery charging. It uses a state-average (non-switching) buck converter model for much faster simulation, so that power tracking performance over long time periods can be observed. However, it does not account for some important aspects of a real converter implementation, such as the predicted power loss in the switching components, or the switching noise on the current and voltage measurements that are needed for power detection.

This circuit confirms the performance of the system at full solar panel irradiance, and with the converter duty-cycle set to a fixed value of 0.8. That value was shown to provide maximum power under full irradiance. The results with this design confirm those of the reference design: The steady-state panel power output is just under 60 Watts (light blue waveform); The corresponding voltage (16 V) and current (3.7 A) into the converter (magenta and green waveforms, respectively); The current into the battery is 4.5 A (red waveform), as expected. Note also that the input L-C filter removes most of the switching noise that would be visible on these signals without that filtering effect.

The average power loss in the P-channel MOSFET is 1.3 Watts (brown waveform). This is important for assessing overall system efficiency, a key factor in the trade-off analysis with direct charging. The user can move the waveform probes around and observe the power loss in all of the other components too, as part of the efficiency analysis process.

About text formats

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jmorenomDesigner233465

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gimDesigner237346

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cesar.dominguezDesigner231580

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jmorenom
Designer233465

vicente.gongora1
Designer231827

biskovic
Designer237063

abid.dahouar
Designer236996

gim
Designer237346

cesar.dominguez
Designer231580

cesar.dominguez
Designer231580

m.fayolle
Designer236042

m.fayolle
Designer236042

m.fayolle
Designer236042