Bench Talk

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Up until now, designing electronic systems has been a balancing act between performance, cost, size, and efficiency. If one of these metrics is changed, it usually has a knock-on effect on one or more of the others. For example, if the main aim of the circuit is to be as low cost as possible, then the final design will likely have fewer features, be larger, and draw more power.

Today, that design paradigm is changing. The emergence of a host of new portable, battery-powered products, such as smartwatches and wearable personal health devices, has led to a demand from consumers for devices that are as small as possible, pack in as many features as they can, operate for an extended time on batteries between recharging, and remain cost-effective. That same trend can be seen in many other vertical areas. For example, in industry, sensor clusters also need to be small to fit inside machinery or other tight spaces; they need enough battery life to operate remotely for months, or even years, on a single charge. They also need advanced features like wireless connectivity to communicate and be cost-effective. Furthermore, incorporating AI into smart and healthcare devices is a growing trend. While AI usually requires significant processing power, most AI applications are becoming smaller and more efficient. These applications are installed at the edge of the IoT, where they process data locally and only transmit necessary information to the main server. The message is clear for component manufacturers: customers will no longer tolerate compromise in the design of smart products.

The key to the development of these smart systems is the microcontroller (MCU). In addition to providing processing power, it can be a major consumer of the allocated power budget. By integrating many of the building blocks that make up the system, it can also enable inexpensive and smaller products. For example, integrating a wireless radio into the microcontroller means that no separate wireless module is required, thereby reducing the design's size, cost, complexity, and power consumption. In this blog, we’ll examine Analog Devices’ MCU solutions tailored for design engineers. These uncompromising solutions allow for the smooth integration of numerous functionalities while maximizing battery life and increasing recharge intervals in smart designs that require a miniaturized footprint.

Analog Devices’ Ultra Low Power MCUs for Smart Systems

Analog Devices' Ultra Low Power microcontroller portfolio has been developed to provide a 'no compromise' solution for designers of smart devices. All devices in the range are powered by an Arm^® Cortex^®-M4 core that combines high performance and ultra-low-power use. The processing element also includes a floating-point unit (FPU) for efficient computation of complex mathematical functions and a digital signal processor (DSP) for advanced digital processing. The combination of CPU, FPU, and DSP, along with a high level of integration, the ability to operate over a wide temperature range (-40°C to +105°C), low active and standby power modes, large memories, and advanced security make the devices an ideal choice to be at the heart of wearables, sensor clusters, personal consumer devices, and portable medical solutions.

Each part of the Ultra Low Power family has features to differentiate it in its intended role. For example, the MAX32655 operates at up to 100MHz using its internal oscillator and consumes only 12.9μA/MHz in active mode at 3.0V. It integrates power regulation and management using a single inductor multiple output (SIMO) buck regulator system. SIMO technology allows numerous voltage rails to be generated using a single inductor, reducing cost and board space requirements. For connectivity, the MAX32655 features a Bluetooth^® Low Energy (LE) 5.2 radio with controllable transmit power for higher throughput and longer ranges, reduced latency, and better signal quality. Optional secure boot, a true random number generator (TRNG), and an AES 128/192/256 hardware acceleration engine are included to secure the device and its data.

Aimed at more premium designs, the MAX32690 has much of the same functionality as the MAX32655 but adds more features, better performance, higher levels of security, and more memory. The 3.25MB of flash and 1MB SRAM memory integrated into the device allow it to handle more complex applications and run multiple stacks—tasks that its 150MHz CPU core can easily accomplish. If memory is needed, it can be expanded externally through two quad-SPI interfaces. MAX32690’s Bluetooth LE 5.2 radio also includes an angle of arrival (AoA), an angle of departure (AoD) for direction finding, and a RISC-V core that handles timing-critical controller tasks and reduces interrupt latency. The microcontroller also provides more advanced security features that include an MAA for fast Elliptic Curve Digital Signature Algorithms (ECDSA), an Advanced Encryption Standard (AES) Engine, TRNG, SHA-256 hash, and a secure boot loader. Along with the QSPI interfaces, connectivity is provided through multiple UART, CAN 2.0B, I²C serial interfaces, and a single I²S port.

When it comes to cost-efficient smart integration MCUs that offer robust security and reliability, there is the MAX32675, developed for industrial applications, especially those that use 4-20mA sensors and transmitters. It includes 384KB of flash and 160KB of SRAM, with single and double error detection implemented over the entire flash, SRAM, and cache for dependable code execution.

Also integrated is a high-precision analog front-end (AFE) with two 12-channel delta-sigma analog-to-digital converters (ADCs), a power gain amplifier (PGA) with gains from 1× to 128×, and a 12-bit DAC. The device’s robust security features include an AES Engine, TRNG, and secure boot.

With AI integration into smart and healthcare devices becoming a growing trend, compact design is more imperative than ever. While AI usually requires significant processing power, most AI applications are becoming smaller and more efficient. These applications are installed at the edge of the IoT, where they process data locally and only transmit necessary information to the main server.

To handle use cases like these, the MAX78000 (Figure 1) manages AI workloads using the minimum power. It incorporates a hardware-based convolutional neural network (CNN) accelerator to perform AI inference. The CNN engine can support networks of up to 3.5 million weights using its 442KB SRAM-based memory. The flexible AI architecture allows networks to be trained using conventional toolsets and then converted for execution using Analog Devices' tools. In addition to the AI circuit, the MAX78000 has 512KB flash and up to 128KB SRAM available to the 100Mhz Cortex-M4 processor. It also has multiple high-speed, low-power communications interfaces, including I²S and a parallel camera interface (PCIF).

Figure 1: The MAX 78000 Ultra Low Power AI microcontroller with hardware-based CNN accelerator, enabling AI inferences to be performed at the edge. (Source: Analog Devices)

Conclusion

The popularity of smart devices in consumer, medical, IoT, and other markets is only expected to increase, especially with the introduction of AI processing. Analog Devices' Ultra Low Power MCUs range is already at the heart of many existing products. Their ultra-low power consumption, high performance, small packaging, and wide range of integrated peripherals and features will ensure that engineers can design products without compromising on power efficiency, functionality, or performance.

Author

Since graduating with a BSc in Electronic Systems from the University of the West of Scotland in 1997, Alistair Winning has worked in electronics media across marketing, PR, and journalism roles. During that time, he worked as the editor of Electronics Engineering, Embedded Systems Europe, EENews Embedded, Technology First, Electronic Product Design and Test, and Panel Building and Systems Integration magazines. Currently, Allistair is the European Editor of Power Systems Design and a freelance writer, specializing in electronics and engineering.