Design Article

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Estimating Power IC contributions to your embedded design power budget

David Divins, International Rectifier

11/25/2007 9:00 AM EST

Among the greatest challenges in designing today's power-consuming products is managing the system's thermal budget. Since most electronic equipment include some form of power conversion, it is necessary to understand the design's thermal constraints, which form the context for many design decisions.

In most power-conversion circuits, the hottest elements are the power ICs - diodes, MOSFETs and IGBTs. For a given circuit topology, these components heat up as functions of applied voltage, load current, switching frequency, gate-drive circuit, package type and mounting.

Of these, the first four dissipate power and model as thermal sources, while the last two models as thermal sinks because they remove heat from the system.

A good first-order estimate of power dissipation in switchmode circuits is P = DVI, where I is the average conduction-cycle current through the power IC, V is the average conduction-cycle voltage across the device, and D is the duty cycle.

Figure 1: The power IC's datasheet provides thermal response curves, from which you can calculate the device's temperature rise above the case temperature when operating in switched-mode.

In physical circuits, current is a function of circuit operation. Voltage is a function of current, the device type, junction temperature and IC control method. For example, the forward voltage across a diode is simply a function of current and temperature.

The voltage across a MOSFET in the on state is IDRDS(on) - the product of drain current and channel resistance. RDS(on), in turn, is a function of ID, gate drive and temperature. The voltage across an IGBT in the on state, V=VCE(sat), is a function of current, gate drive and temperature.

To determine the IC's temperature rise, multiply the power dissipation by the thermal impedance. The limitation with this analysis is that it oversimplifies the power calculation and does not account for transient conditions.

The power device's data sheet provides thermal response curves, however, with which you can overcome that limitation (Figure 1 above).

The curves assume a rectangular power pulse of amplitude P for duration t with duty cycle D. Follow the curve appropriate to your circuit's duty cycle to the point along the horizontal axis corresponding to the pulse duration. Read the corresponding thermal response from the vertical axis and multiply that value by the power dissipation to arrive at the temperature rise from case to junction.

Figure 2: The power IC's thermal stack includes the junction, substrate, case, thermal paste or other thermal interface material, heat sink, and ambient.

The thermal response curves only address the case-to-junction temperature rise. They cannot account for the case's mounting method, which contributes to its rise above ambient as a complete thermal-stack model indicates (Figure 2 above).

Rather than approach the problem piece-by-piece, using different tools and data sources to solve each part of the problem, a circuit simulator can calculate the total thermal response. The simulator also allows you to observe the effect of the thermal system on the circuit's parametric performance, which is difficult to deduce from pen-and-paper or spreadsheet analyses.

Circuit simulation uses component models and network analysis, which closely approximates the operating conditions for each device in the circuit. The simulator automatically calculates the power dissipation of power devices, taking into account a full range of circuit and device behaviors that include gate drive, switching transitions and diode reverse-recovery.

Figure 3: A quasidynamic thermal wrapper model accounts for the power device's parametric dependence on temperature.

However, traditional circuit simulators calculate power based on a static thermal model. In other words, they fix device behavior with respect to temperature. This is adequate for low-power IC simulation because devices in such circuits exhibit little self-heating.

Power ICs do self-heat, however, and an accurate simulation must account for the device behavior's temperature dependence. Adding a quasidynamic thermal wrapper model to the static 25 degrees C device model overcomes this limitation (Figure 3 above).

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Symmecon

6/18/2010 10:53 PM EDT

Microchip thermal topology and reaction modeling depend on the data density of the atomic topological function used to image the volume, a process that leads to thermic quanta conclusions. These recent advancements in quantum science have produced the picoyoctometric, 3D, interactive video atomic model imaging function, in terms of chronons and spacons for exact, quantized, relativistic animation. This format returns clear numerical data for a full spectrum of variables. The atom's RQT (relative quantum topological) data point imaging function is built by combination of the relativistic Einstein-Lorenz transform functions for time, mass, and energy with the workon quantized electromagnetic wave equations for frequency and wavelength.

The atom labeled psi (Z) pulsates at the frequency {Nhu=e/h} by cycles of {e=m(c^2)} transformation of nuclear surface mass to forcons with joule values, followed by nuclear force absorption. This radiation process is limited only by spacetime boundaries of {Gravity-Time}, where gravity is the force binding space to psi, forming the GT integral atomic wavefunction. The expression is defined as the series expansion differential of nuclear output rates with quantum symmetry numbers assigned along the progression to give topology to the solutions.

Next, the correlation function for the manifold of internal heat capacity energy particle 3D functions is extracted by rearranging the total internal momentum function to the photon gain rule and integrating it for GT limits. This produces a series of 26 topological waveparticle functions of the five classes; {+Positron, Workon, Thermon, -Electromagneton, Magnemedon}, each the 3D data image of a type of energy intermedon of the 5/2 kT J internal energy cloud, accounting for all of them.

Those 26 energy data values intersect the sizes of the fundamental physical constants: h, h-bar, delta, nuclear magneton, beta magneton, k (series). They quantize atomic dynamics by acting as fulcrum particles. The result is the exact picoyoctometric, 3D, interactive video atomic model data point imaging function, responsive to software application keyboard input of virtual photon gain events by relativistic, quantized shifts of electron, force, and energy field states and positions. This system also gives a new equation for the magnetic flux variable B, which appears as a waveparticle of changeable frequency. Molecular modeling and chip design engineering application software developer features for programming flow are built-in.

Images of the h-bar magnetic energy waveparticle of ~175 picoyoctometers are available online at http://www.symmecon.com with the complete RQT atomic modeling manual titled The Crystalon Door, copyright TXu1-266-788. TCD conforms to the unopposed motion of disclosure in U.S. District (NM) Court of 04/02/2001 titled The Solution to the Equation of Schrodinger.

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