This design represents a simple automotive (12V) coffee cup warmer, with digital thermostat. It is not meant to be a practical design, but rather to show some of the capabilities of modeling multi-discipline electro-thermal systems in SystemVision Cloud.

The design includes a "plant" model with both static and dynamic thermal aspects, including a tungsten heater element, conduction and radiation heat transfer, and heat capacitance. A "graphical" model of the temperature sensor includes math function-blocks to set the bandwidth (LPF), gain (sensitivity), offset bias and output voltage limiting. It also includes an output resistance.

The closed loop performance of the system depends on the sensor bandwidth and the sampling rate. Try using 1 Hz instead of 0.1 Hz for the pole frequency "FP" in LPF1, and a 0.2 second period for the sample clock. You'll notice that the faster sensor and sampling greatly improves the temperature regulation.

The thermostat includes a simple amplifier and a single-bit voltage-to-digital converter, with a threshold level that specifies the temperature regulation set-point. A digital clock and D flip-flop sample and preserve the desired state of the heater switch during each clock cycle.

This design represents a simple automotive (12V) coffee cup warmer, with digital thermostat. It is not meant to be a practical design, but rather to show some of the capabilities of modeling multi-discipline electro-thermal systems in SystemVision Cloud.

The design includes a "plant" model with both static and dynamic thermal aspects, including a tungsten heater element, conduction and radiation heat transfer, and heat capacitance. A "graphical" model of the temperature sensor includes math function-blocks to set the bandwidth (LPF), gain (sensitivity), offset bias and output voltage limiting. It also includes an output resistance.

The closed loop performance of the system depends on the sensor bandwidth and the sampling rate. Try using 1 Hz instead of 0.1 Hz for the pole frequency "FP" in LPF1, and a 0.2 second period for the sample clock. You'll notice that the faster sensor and sampling greatly improves the temperature regulation.

The thermostat includes a simple amplifier and a single-bit voltage-to-digital converter, with a threshold level that specifies the temperature regulation set-point. A digital clock and D flip-flop sample and preserve the desired state of the heater switch during each clock cycle.

This design represents a simple automotive (12V) coffee cup warmer, with digital thermostat. It is not meant to be a practical design, but rather to show some of the capabilities of modeling multi-discipline electro-thermal systems in SystemVision Cloud.

The design includes a "plant" model with both static and dynamic thermal aspects, including a tungsten heater element, conduction and radiation heat transfer, and heat capacitance. A "graphical" model of the temperature sensor includes math function-blocks to set the bandwidth (LPF), gain (sensitivity), offset bias and output voltage limiting. It also includes an output resistance.

The closed loop performance of the system depends on the sensor bandwidth and the sampling rate. Try using 1 Hz instead of 0.1 Hz for the pole frequency "FP" in LPF1, and a 0.2 second period for the sample clock. You'll notice that the faster sensor and sampling greatly improves the temperature regulation.

The thermostat includes a simple amplifier and a single-bit voltage-to-digital converter, with a threshold level that specifies the temperature regulation set-point. A digital clock and D flip-flop sample and preserve the desired state of the heater switch during each clock cycle.

This design represents a simple automotive (12V) coffee cup warmer, with digital thermostat. It is not meant to be a practical design, but rather to show some of the capabilities of modeling multi-discipline electro-thermal systems in SystemVision Cloud.

The design includes a "plant" model with both static and dynamic thermal aspects, including a tungsten heater element, conduction and radiation heat transfer, and heat capacitance. A "graphical" model of the temperature sensor includes math function-blocks to set the bandwidth (LPF), gain (sensitivity), offset bias and output voltage limiting. It also includes an output resistance.

The closed loop performance of the system depends on the sensor bandwidth and the sampling rate. Try using 1 Hz instead of 0.1 Hz for the pole frequency "FP" in LPF1, and a 0.2 second period for the sample clock. You'll notice that the faster sensor and sampling greatly improves the temperature regulation.

The thermostat includes a simple amplifier and a single-bit voltage-to-digital converter, with a threshold level that specifies the temperature regulation set-point. A digital clock and D flip-flop sample and preserve the desired state of the heater switch during each clock cycle.

This design represents a simple automotive (12V) coffee cup warmer, with digital thermostat. It is not meant to be a practical design, but rather to show some of the capabilities of modeling multi-discipline electro-thermal systems in SystemVision Cloud.

The design includes a "plant" model with both static and dynamic thermal aspects, including a tungsten heater element, conduction and radiation heat transfer, and heat capacitance. A "graphical" model of the temperature sensor includes math function-blocks to set the bandwidth (LPF), gain (sensitivity), offset bias and output voltage limiting. It also includes an output resistance.

The closed loop performance of the system depends on the sensor bandwidth and the sampling rate. Try using 1 Hz instead of 0.1 Hz for the pole frequency "FP" in LPF1, and a 0.2 second period for the sample clock. You'll notice that the faster sensor and sampling greatly improves the temperature regulation.

The thermostat includes a simple amplifier and a single-bit voltage-to-digital converter, with a threshold level that specifies the temperature regulation set-point. A digital clock and D flip-flop sample and preserve the desired state of the heater switch during each clock cycle.

This design represents a simple automotive (12V) coffee cup warmer, with digital thermostat. It is not meant to be a practical design, but rather to show some of the capabilities of modeling multi-discipline electro-thermal systems in SystemVision Cloud.

The design includes a "plant" model with both static and dynamic thermal aspects, including a tungsten heater element, conduction and radiation heat transfer, and heat capacitance. A "graphical" model of the temperature sensor includes math function-blocks to set the bandwidth (LPF), gain (sensitivity), offset bias and output voltage limiting. It also includes an output resistance.

The closed loop performance of the system depends on the sensor bandwidth and the sampling rate. Try using 1 Hz instead of 0.1 Hz for the pole frequency "FP" in LPF1, and a 0.2 second period for the sample clock. You'll notice that the faster sensor and sampling greatly improves the temperature regulation.

The thermostat includes a simple amplifier and a single-bit voltage-to-digital converter, with a threshold level that specifies the temperature regulation set-point. A digital clock and D flip-flop sample and preserve the desired state of the heater switch during each clock cycle.

This is an example showing how you can create a "graphical model" (i.e. a behavioral model "graphically assembled on a schematic" using mathematical continuous function blocks). In this case, the "per unit" solar panel current as a function of voltage data is entered into a PWL Function Block. This was done by a simple copy/paste from a spreadsheet. The data represents a typical i vs. v profile that is normalized from 0.0 to 1.0 for both quantities. This data can then be used to model solar panels of any capacity, simply by scaling the input voltage and the output current appropriately.

In this example, we are modeling a panel with 12V maximum (open circuit) voltage and 2 Amp maximum (short circuit) current. This is achieved by scaling the sensed panel voltage by 1/12. That is, by simply setting the gain of the Voltage to Continuous Quantity converter block to 0.083. Likewise, the panel output current is scaled by a gain of 2.0 in the Current from Continuous Quantity converter block.

In the simulation, the variable resistor load is ramped down from 50 Ohms to 2 Ohms over a 1 second time period, and the corresponding panel output current and voltage can be seen in the top two waveboxes. In addition, it is interesting to see the power dissipated in the load resistor, as that resistance is decreased, as shown in the waveboxes on the right. The peak power capability of this solar panel is just over 17 Watts, and this occurs when the load resistance is approximately 5 Ohms.

Reference: The solar panel data for this example came from a technical paper; C. Hua, J. Lin and C. Shen, "Implementation of a DSP-Controlled Photovoltaic System with Peak Power Tracking", IEEE Transactions on Industrial Electronics, Vol 45, No. 1, February 1998. The voltage and current values were estimated from the graph in Figure 1b, for the case of 25 degree C operation and 100mW/cm^2.