Power vs. Volumetric Density
Power density measures how much power a solution delivers relative to its own volume, while volumetric density describes how efficiently the entire system uses space. In other words, power density focuses on the power module itself, whereas volumetric density reflects the overall system architecture and all supporting components. Power solutions are notorious for being the long pole in the tent—for influencing overall system size, volumetric efficiency, system bill-of-materials costs, and power density. Typically, these are broken down into common figures of merit (FOM) for a system, such as its size, weight, and power (SWaP) characteristics. When combined with a cost metric, this is referred to as SWaP-C factors [1].
Power density is generally a function of total available power versus overall solution volume, which is why component size tends to inversely relate to power density. The power density metric becomes more critical when combined with overall solution mass (typically translated to weight on Earth), which can be a key FOM in nontethered applications, as discussed from multiple perspectives in the content that follows.
It is also important to differentiate power density from volumetric density. Power density can be specifically characterized in the context of the power solution, which is a subset of the overall system volume. In general, power density always increases, whereas volumetric density can decrease as major system loads shrink in size (and possibly in power requirements) and/or increase functionality to perform more work in the same volume from generation to generation. This can create a trend different from that observed directly for power solutions. The industry has attempted to normalize these discrepancies with oversimplified metrics, such as dollar per watt ($/W), which make little sense unless comparing highly similar power supplies.
As with any aspect of evaluating power solutions and their technical and financial impact, it is crucial to look beyond first-order analysis. Power consumption and energy efficiency often resemble a “whack-a-mole” scenario, where optimizing one subsystem may reduce performance in another area, leaving the effective system-level impact the same or worse. Classic examples include when the enhanced power density of a wide-bandgap power switch, such as gallium nitride or silicon carbide, allows for a physically smaller power train (even with increased power-handling capability) by leveraging higher switching frequencies that reduce some power components.
However, this may also necessitate a larger (and potentially costlier) thermal mitigation solution to manage denser power dissipation in smaller geometries or even require liquid cooling. Often, seemingly minor features can disproportionately impact solution size and cost. For example, connectors (especially blind-mate types) and fans can significantly affect all FOMs in a SWaP-C analysis since they can be large, and electromechanical components can be bottlenecks for maximizing system quality and reliability.
Power solutions do not scale at the same rate as items on the load side, such as those influenced by Moore’s Law and microelectromechanical system devices. Consequently, system roadmaps cannot expect an exponential reduction in power solution size (or exponential increase in power density) solely from year-over-year process node improvements. That said, a power solution can help keep pace with enhanced load size and performance by meeting increasing load demands in its own way [2].
Power density is generally a function of total available power versus overall solution volume, which is why component size tends to inversely relate to power density. The power density metric becomes more critical when combined with overall solution mass (typically translated to weight on Earth), which can be a key FOM in nontethered applications, as discussed from multiple perspectives in the content that follows.
It is also important to differentiate power density from volumetric density. Power density can be specifically characterized in the context of the power solution, which is a subset of the overall system volume. In general, power density always increases, whereas volumetric density can decrease as major system loads shrink in size (and possibly in power requirements) and/or increase functionality to perform more work in the same volume from generation to generation. This can create a trend different from that observed directly for power solutions. The industry has attempted to normalize these discrepancies with oversimplified metrics, such as dollar per watt ($/W), which make little sense unless comparing highly similar power supplies.
As with any aspect of evaluating power solutions and their technical and financial impact, it is crucial to look beyond first-order analysis. Power consumption and energy efficiency often resemble a “whack-a-mole” scenario, where optimizing one subsystem may reduce performance in another area, leaving the effective system-level impact the same or worse. Classic examples include when the enhanced power density of a wide-bandgap power switch, such as gallium nitride or silicon carbide, allows for a physically smaller power train (even with increased power-handling capability) by leveraging higher switching frequencies that reduce some power components.
However, this may also necessitate a larger (and potentially costlier) thermal mitigation solution to manage denser power dissipation in smaller geometries or even require liquid cooling. Often, seemingly minor features can disproportionately impact solution size and cost. For example, connectors (especially blind-mate types) and fans can significantly affect all FOMs in a SWaP-C analysis since they can be large, and electromechanical components can be bottlenecks for maximizing system quality and reliability.
Power solutions do not scale at the same rate as items on the load side, such as those influenced by Moore’s Law and microelectromechanical system devices. Consequently, system roadmaps cannot expect an exponential reduction in power solution size (or exponential increase in power density) solely from year-over-year process node improvements. That said, a power solution can help keep pace with enhanced load size and performance by meeting increasing load demands in its own way [2].
