Buck converter with integrated inductor




















The Product Advantages. Fewer External components reduce overall footprint. IC and inductor combinded into a single package smaller PCB size. Set the output voltage 2. Set the operating frequency with R ON 3. Select the input capacitor 4. Select the output capacitor 5. Select the feed forward capacitor 6. Select the soft-start capacitor 1 optional design step 7. Select under-voltage lockout divider.

Design the thermal vias. Tested filter configuration with inductor and capacitor order codes. Conducted Emissions The main components for these topologies are input and output capacitors, switches e.

The goal of these devices is to regulate the output voltage. Selecting a suitable IC with the best inductor does not have to be a significant challenge. Taking care of a few design parameters is the key to successfully choosing an inductor that works well with a buck converter, and to avoiding power losses and increasing efficiency.

A block diagram of a buck converter and its basic parts makes it apparent which components contribute to efficiency, and which parameters should be considered see Figure 1.

When breaking down the efficiency and power loss of a buck converter, we can see that the biggest impacts on power loss and efficiency are the MOSFETs and the inductor. The quiescent current and programming resistors are not notable contributors see Figure 2.

Figure 3 shows an efficiency breakdown of a 24V to 5V buck converter with a 2A load. To achieve the highest efficiency and avoid wasting energy, we must ensure that state-of-the-art switching elements are coupled with high-performance inductors. This leads to a nominal inductance L , calculated with Equation 1 :. For this example, the input voltage is 24V, the output voltage is 5V, the ripple current is mA average 2A load , and the switching frequency is kHz.

With these numbers, we can calculate the typical inductance to be 9. The ripple current can be estimated with Equation 2 :. The ripple current oscillates around a 2A load current with a perfect triangular waveform. Due to the physical properties of the ferromagnetic material used in modern inductors, a higher number of turns and inductance L results in a lower the saturation current I SAT. Figure 6 shows a typical I SAT graph. As power supply designers, it is critical to keep in mind that inductance decreases when the current flowing through the inductor increases.

Increasing temperatures decrease the effective inductance. Depending on the technology, structure, and materials used in the inductor, the curve of the saturation current can be stable up to several amperes. Because high-efficiency inductors have a soft saturation and buck converter, ICs have protection features such as peak current limiting.

This means there is no way to choose the wrong inductor. Even with an exceedingly high or low inductance, we will still see reasonable results. However, it is important to have enough margin on the saturation current, as an insufficient margin can lead to a low-efficiency system. A lower saturation current can contribute to sharp spikes on the inductor current see Figure 7. Hence the load should be selected, in such a way that, the maximum output power at the load should not cross the limit of Watts and the maximum load current should not cross 20 amperes.

It supports both the linear and non-linear systems. A graphical user interface GUI is provided by Simulink, in which the models are represented by block diagrams and the operations are click and drag mouse based. The models can be created easily by selecting the appropriate blocks from the existing block library.

The block library consists of sources, sinks and several blocks which result in mathematical outputs. The blocks are connected using the connectors. The block libraries help in modeling, simulating, implementing the design and are then used to test and verify the LTI systems like control and communication systems. SimPowerSystems: SimPowerSystems is a software package of modern design tools, which allow building and simulating the power system models.

Power system is a combination of electrical circuits and electromechanical devices. SimPowerSystems is an analysis tool which involves concepts of power electronic devices and control systems. SimPowerSystems uses the Simulink environment, in which a model is built using click and drag procedures.

The tool helps in drawing and analyzing the circuit topology. Since this uses the Simulink environment, all the parts of the power system interact with Simulink modeling library. Since the systems are often non-linear, one convenient way to understand them is through Simulation. The buck converter topology is a combination of several electronic devices and control system elements. Hence, the buck converter model is simulated with the help of Simulink and SimPowerSystems to analyze the working nature.

All the blocks shown are selected from the SimPowerSystems toolset. The model designed using SimPowerSystems looks exactly same as if we draw it on a paper.

Thus, it is very easy to design the desired model. The model represents the block diagram shown in figure 3.

Figure 6. The element library and electrical sources library is used to select the blocks to design the model. The model uses the measurement blocks to measure current across the wires and voltage across the nodes.

The model is designed by placing the blocks in appropriate sequence inorder to analyze the buck converter model. The purpose of simulation is to verify the condition given in equation 3.

The condition states that, the product of current flowing across the inductor and the ESR across the inductor must be equal to the voltage across the capacitor in current sensing circuit.

The powergui block is very much needed for any kind of Simulink model which contains SimPowerSystems blocks, inorder to simulate the model. This block stores the equivalent Simulink circuit which represents the state-space equations of the SimPowerSystems blocks. The third waveform shows the total input current that enters into the circuit. The elements like capacitor, resistor and inductor are chosen from the elements library.

Elements are connected using wires. The connection in which an inductor is in series with a resistor is placed in parallel across the connection in which a capacitor is in series with a resistor. Description of each block used in the design: The description and performance of each individual block used in the design is explained inorder to have clear understanding over the circuit.

When the input from the sawtooth generator overtakes the input from PID, the output is 0 and if the input from sawtooth is less than the input from PID, the output is 1. The input current to the system depends on the duty cycle of the signal from PWM block.

The input is the product of the constant voltage source Vg and the duty cycle D. The dependency is shown in figure 6. The output of the pulse width modulator is a series of pulses, whose amplitude varies between 0 and 1, and the width of the each pulse depends on duty cycle.

The simulation was run for duration of 0. The following results were obtained after simulation. Output Voltage 2. Output Current 3. Voltage across modeled capacitor Figure 6.

Current through Inductor 5. Voltage across Inductor 6. Current to the modeled capacitor I. The Output voltage is maintained constant at 3 Volts. Since the load of 1. The output voltage and the output current are in proportion, due to the resistive load. Since the circuit has to maintain or regulate the voltage at 3 Volts, the designed circuit is succeeded in providing the desired result.

Many observations are taken with different load values to verify the circuitry design and were successfully observed. The first waveform shows the Output Current and the second waveform shows the Output Voltage. Voltage across modeled Capacitor Vs Current through Inductor The measurement circuit as described in section 5. The capacitor is denoted C1 in figure 5. In the figure 6. This is shown in figure 6. One more interesting information is observed. The Voltage across inductor is found proportional to the current through the Capacitor.

This observation is shown in the following figure 6. The first waveform shows the current across the Capacitor and the second waveform shows the Voltage across the Inductor. The Simulink model of the buck converter is shown in the figure 6.

The above model is an exact representation of the equations obtained in the section 3. The number of integrators used in the figure 3. The product of the duty cycle from sawtooth generator and the input voltage provides the pwm signal for the buck converter system.

The output voltage and current are duty cycle controlled outputs. The SimPowerSystems model shown in the figure 6. The functionality of pwm is explained in the section 6.

The different waveforms based on the constant duty ratio are shown in figure 6. As mentioned in the section 3. As the error signal is minimized, the output voltage closes to the desired reference voltage and the duty command signal tries to be stable at certain point and the duty ratio also varies.

As the duty command signal oscillates towards a constant value, output of PWM, the duty ratio also tries to maintain a constant value. Hence, when the output voltage equals the desired reference voltage, the error signal becomes zero, and hence there will not be any changes in the duty command signal and in the output of PWM. The figure 6. The duty ratio is stabilized after certain period. The point is, how does this duty ratio controls the output voltage?

The same is shown in the figure 6. The simulation of output voltage and output current is shown in figure 6. Since the circuit elements are chosen to regulate the output voltage to 3 volts, the simulation results helps to understand the designed model as an alternate to the physical model. As stated in the equation 3. Since the aim of the model is to sense the current through inductor with the help of voltage across the capacitor, the output waveform of the model helps to analyze the desired result.

The waveform showed in the figure 6. Both the waveforms look alike in shape, but not same in the values. They are proportional to each other, with proportionality constant. This is another Simulink model of the buck converter system courtesy: Anders Hultgren. The model uses a state space block to read the A, B, C and D parameters from the m-file. There are totally five outputs from the demultiplexer.

The output values are stored in workspace. With reference to the figure 3. The internal resistance of the inductor has been proved to be the proportionality constant between the voltage across the capacitor and the current through the inductor. The current measured across the capacitor is termed as the measurement current and the current through the inductor current is termed as the inductor current.

Current is measured across the capacitor and is compared with the current through the inductor, with reference to the figure 5.

The measured current is found to be similar to the inductor current. The closer view can be seen in the figure 6. The simulation results showed in the figures 6.

This helps in measuring the inductor current with the help of a measurement circuit. All the three simulations are performed under similar conditions.

Here the comparison is performed with controller. Hence, it is easy to compare and provide all the three simulation results in figure. The following figure 6.

As explained in the section 6. Similarly, the same explanation can be given to each of the three models. The output depends on the type of the compensator that we use to regulate the output voltage. The output response can be fast or slow, depending on the type of controller. This is explained later in this section. All the three models produced same result which shows that the analysis of buck converter can be done using any one of these models.

Since the focus is to derive different models that can be used in different simulations of the buck converter, the focus is not to derive the control parameters. The Simulink model II gives a quick response. The model uses Proportional-Derivative control. The proportional controllers are individually fast. The derivative controllers are also fast. Thus the combination is much faster.

The PD control is used for fast response. Hence the model II have fast response than the other two models, where in the other models, the control action is performed by PID control.



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