Could power amplifiers become intelligent?

Role of power amplifiers

To understand the role that power amplifiers play and why they are critical electronic devices, we first need to understand what power amplifiers are. A power amplifier is a device that amplifies an electrical signal to drive loads far greater than what the signal being amplified could otherwise produce.

For example, a microcontroller GPIO output could never be used to drive a large DC motor as a DC motor can require tens of amps to start turning, while GPIO from microcontrollers generally do not allow for more than 20mA. Instead, a power amplifier capable of providing tens of amps could be used to provide power to the DC motor while being controlled by the GPIO output (I.e., 20mA is being amplified to tens of amps).

So where exactly are power amplifiers found? One common example of power amplifiers is in the example given above. Microcontrollers will often be required to control large loads, and this is best done with the use of a power amplifier.

Power amplifiers are also commonly found in power management devices such as battery chargers. A battery management integrated circuit (IC) is responsible for detecting the voltage across a battery while an external power amplifier may be controlled by the power management IC to charge the battery with a specific current.

Industrial systems are another common application for power amplifiers. Any DC motor used in an industrial environment will require a dedicated motor driver as power is almost always three-phase AC, and these drivers will require power amplifiers that can rectify and modulate the power (through pulse width modulation (PWM)) going to these motors.

Radio frequency (RF) systems are also dependent on power amplifiers. Generating complex radio signals for use in cellular, RADAR, and phased arrays require high-end digital signal processors, but these are similar to GPIO in that they cannot source much current. Instead, special RF amplifiers can amplify the output of these processors and convert it to RF energy at an antenna for long range transmission.

What common circuit protection methods exist in power amplifiers?

The large current and voltage variations that are present in high-power circuity can be detrimental to semiconductor devices, including amplifiers and processors. As such, it is common to see power amplifiers integrated with various protection methods to not only protect itself against unexpected circuit behaviour, but also protect external circuits (such as microcontrollers and digital signal processors).

Maximum current ratings in power amplifiers exist to prevent thermal damage caused by high currents (large currents can also damage the semiconductor on an atomic scale, but it is generally the temperature increase that is more damaging). As such, power amplifiers often integrate overcurrent protection circuits to prevent large spikes in current draw.

Overvoltage protection circuits (also known as transient protection) prevent sensitive components in a power amplifier from being damaged. They also prevent the total breakdown of a semiconductor junction. For example, MOSFET-based power amplifiers have a thin gate that can be easily damaged with high voltages; thus, these voltages are generally clamped using a Zener.

Thermal shutdown protection systems prevent power amplifiers from overheating, and this is extremely important in high-current applications. Some semiconductors can suffer from a thermal runaway effect where the increase in temperature causes an increase in conduction which, in turn, causes a further increase in temperature. Semiconductors that get too hot can quickly deteriorate and lead to degraded performance.

Reverse voltage protection is a protective system that prevents large negative voltages from damaging sensitive semiconductor components. Such protection circuits often involve the use of a diode in reverse bias mode so that it conducts in the presence of negative voltages, thereby clamping the value. These are often found in MOSFETs as a body diode and are essential in power amplifiers driving inductive loads (such as motors) that can generate large back electromotive forces (EMFs).

What challenges do these protection methods face?

While the aforementioned protection methods do work, they are not without their own challenges. By far the biggest issue with such protection circuitry is that they are reactionary, and thus respond to something going wrong. For example, thermal shutdown circuitry will engage when the temperature of the amplifier reaches some defined threshold, and overvoltage circuits activate if the voltage across the amplifier is too great.

This is an issue because even though protection systems are designed to prevent damage, they are fallible. As such, a device runs the risk of being damaged should it experience some kind of protection scenario. For example, frequent thermal shutdowns have the risk of degrading the device over time while also introducing potential fire risks.

Additional protection can be achieved with the use of active monitoring from a microcontroller via alert pins. For example, a power amplifier may have an output alert pin that changes state when experiencing overvoltage, and this could be used by the microcontroller to disconnect power to prevent further damage; however, this situation still requires protection circuitry to engage which puts the power amplifier at risk.

How could artificial intelligence be used to create intelligent power amplifiers?

Instead of creating protection systems that are reactionary, imagine if a protection system could predict issues before they occur? Such an amplifier would not only be able to protect itself from conditions well in advance, but it could also signal to connected processors that a problem is about to occur, and thus allow for those devices to also make decisions. Under fault conditions, this power amplifier would have prevented itself from entering dangerous operating zones, thus reducing the amount of degradation faced. But how could such an amplifier be built?

Since their early beginnings, artificial intelligence algorithms have quickly transformed from interesting scientific experiments to fully functional systems capable of performing extremely complex tasks. Not only can AI algorithms reliably predict behaviour in complex systems, they can also learn to recognize abnormal behaviour.

For example, an AI connected to a power measuring device would be able to recognize nominal operation after learning what nominal behavior is supposed to look like. However, even gradual changes in the current or voltage could be detected as unusual behavior, even if the values are within the expected range, and this could then be used to determine whether something has changed (possibly an overheating component, an unexpected device has been connected, software error, etc.).

This predictive capability sees AI integrated into many industrial sensors and machinery as it can inform plant operators if the equipment is starting to behave abnormally. This behavior could include increased vibration, increased current draw, or higher operating temperatures, and all of these could indicate the need for a service. However, the use of predictive maintenance also allows plant operators to plan future services that coincide with other maintenance jobs so that plant downtime is reduced (i.e., fix multiple machines at the same time instead of fixing each machine individually after failures occur).

Considering that entire computing systems can be integrated into tiny SoCs with artificial intelligence capabilities, power amplifiers could be fitted with predictive circuit protection systems. Such an AI would monitor all aspects of the power amplifier including the current consumption, the voltage at each terminal, and junction temperature. From there, nominal operation can be determined either through on-chip machine learning or from an external programmer.

If unusual activity is detected by the AI, the power amplifier could perform a multitude of tasks to determine the best course of action. The first task may be to signal the main controller that there could be a potential problem. If anomalous behavior is still ongoing, then the amplifier could take matters into its own hands and engage circuit protection systems to either power down the amplifier or reduce the current consumption.

Additionally, the on-chip AI could also use sensor data to determine the health of the device. If it is determined that the power amplifier's performance is degrading, it can signal the main controller that the amplifier may require replacement.

But it is not just circuit protection that an AI power amplifier could integrate; it could even be used to maximise device efficiency. Especially true for switching amplifiers, the efficiency of the amplifier greatly depends on the switching voltage, rise and fall times, and voltage drop across the amplifier. An on-chip AI could monitor device efficiency and make corrections to internal driving circuits to maximize the efficiency of the amplifier for all input and output voltages.

Finally, on-chip AI in a power amplifier even has the potential to observe malware. As previously stated, artificial intelligence is very good at detecting anomalous behaviour, and it turns out that the current consumed by a processor often depends on tasks being executed. Thus, a processor that is infected with malware will likely see a change in current consumption, and this could be detected by a power amplifier’s AI, whereupon a signal can be sent to the main controller warning of potential infection.

Do such amplifiers exist yet?

Unfortunately, no such amplifier currently exists, and this could be for numerous reasons. Firstly, integrating an SoC into an amplifier would be expensive, as semiconductors used for power amplifiers may not be suitable for SoCs. As such, an SoC would have to be a secondary chip integrated next to the power amplifier with bond wires connecting the two.

Secondly, AI systems still have plenty of room for improvement, and trying to integrate an AI into a power amplifier may require several more years of development. Thirdly, power amplifiers have undergone decades of development and the protection circuitry offered by such devices is more than sufficient for most applications.

Now, that is not to say that research is not being done in the area. A simple Google search of the terms “artificial intelligence” and “power amplifier” does return interesting results on AI use in power amplifiers. One result that frequently comes up is cellular power amplifiers and how to use AI to improve efficiency (something that will be critical for increasing bandwidth and reducing energy used).

Conclusion

Artificial intelligence is an incredibly powerful tool that allows for predictive maintenance capabilities as well as anomaly detection. Considering that individual sensors are now being integrated with predictive capabilities, it is understood that power amplifiers are ripe for AI integration. A power amplifier with AI would be able to not only make decisions based on its current state, but it could also help offload predictive energy tasks from a central controller.

Additionally, an AI integrated into a power amplifier would be able to adjust its own performance characteristics to maximize efficiency, something that is becoming increasingly important with the rising costs of energy, and subsequent shift to renewable energy resources.