<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Low Power Design Patterns on Embedded Systems Development</title><link>https://applied-ee.github.io/embedded/docs/power-battery/low-power-design/</link><description>Recent content in Low Power Design Patterns on Embedded Systems Development</description><generator>Hugo</generator><language>en-us</language><atom:link href="https://applied-ee.github.io/embedded/docs/power-battery/low-power-design/index.xml" rel="self" type="application/rss+xml"/><item><title>Sleep Modes &amp; Wake Sources</title><link>https://applied-ee.github.io/embedded/docs/power-battery/low-power-design/sleep-modes-and-wake-sources/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://applied-ee.github.io/embedded/docs/power-battery/low-power-design/sleep-modes-and-wake-sources/</guid><description>&lt;h1 id="sleep-modes--wake-sources"&gt;Sleep Modes &amp;amp; Wake Sources&lt;a class="anchor" href="#sleep-modes--wake-sources"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;p&gt;Modern microcontrollers offer a hierarchy of sleep modes, each trading off recovery time and peripheral availability against current draw. An STM32L4 running at 80 MHz draws roughly 100 µA/MHz in Run mode — around 8 mA — but can drop below 1 µA in Standby and under 30 nA in Shutdown. An ESP32-S3 consuming 240 mA during Wi-Fi TX settles to 8 µA in deep sleep and 5 µA in hibernation. An nRF52840 pulling 4.6 mA at 64 MHz in active mode drops to 1.5 µA in System ON idle with RAM retained, and 0.4 µA in System OFF. The key to a power-optimized design is selecting the deepest sleep mode that still preserves enough state to resume quickly when a wake event arrives.&lt;/p&gt;</description></item><item><title>Clock Gating &amp; Peripheral Power</title><link>https://applied-ee.github.io/embedded/docs/power-battery/low-power-design/clock-gating-and-peripheral-power/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://applied-ee.github.io/embedded/docs/power-battery/low-power-design/clock-gating-and-peripheral-power/</guid><description>&lt;h1 id="clock-gating--peripheral-power"&gt;Clock Gating &amp;amp; Peripheral Power&lt;a class="anchor" href="#clock-gating--peripheral-power"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;p&gt;Sleep modes reduce current by halting the CPU, but the CPU is only part of the power budget. On an STM32L476 at 80 MHz, the CPU core draws roughly 4.5 mA while the peripheral clocks — GPIO ports, SPI controllers, timers, DMA — collectively draw another 3–4 mA even when idle. Disabling peripheral clocks when not in use, controlling power domains, and configuring GPIO pins for minimal leakage are essential techniques that can cut active-mode current by 30–50% and shave microamps from sleep current that would otherwise dominate the battery budget.&lt;/p&gt;</description></item><item><title>Current Profiling Techniques</title><link>https://applied-ee.github.io/embedded/docs/power-battery/low-power-design/current-profiling-techniques/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://applied-ee.github.io/embedded/docs/power-battery/low-power-design/current-profiling-techniques/</guid><description>&lt;h1 id="current-profiling-techniques"&gt;Current Profiling Techniques&lt;a class="anchor" href="#current-profiling-techniques"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;p&gt;Measuring the current consumption of a battery-powered embedded device is not as simple as reading a multimeter. A typical firmware duty cycle involves sub-microsecond transitions between sleep (1 µA), active processing (5 mA), and radio transmission (120 mA) — a dynamic range of 100,000:1 that no single instrument captures perfectly. Dedicated current profiling tools like the Nordic Power Profiler Kit II (PPK2) and Qoitech Otii Arc exist specifically for this problem, while a shunt resistor and oscilloscope remain the most flexible approach for capturing fast transients. The goal is always the same: correlate every feature in the current waveform to a specific firmware state, so that each microamp in the power budget is accounted for.&lt;/p&gt;</description></item><item><title>Battery Life Estimation</title><link>https://applied-ee.github.io/embedded/docs/power-battery/low-power-design/battery-life-estimation/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://applied-ee.github.io/embedded/docs/power-battery/low-power-design/battery-life-estimation/</guid><description>&lt;h1 id="battery-life-estimation"&gt;Battery Life Estimation&lt;a class="anchor" href="#battery-life-estimation"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;p&gt;Predicting battery life requires more than dividing capacity by current. A CR2032 coin cell rated at 230 mAh does not deliver 230 mA for one hour — it delivers 230 mAh only under specific conditions (typically 15 kΩ load to 2.0 V cutoff at 23°C). At higher loads, lower temperatures, or higher cutoff voltages, the usable capacity drops significantly. Accurate estimation integrates the measured current profile over the full duty cycle, accounts for self-discharge, derates for temperature and aging, and applies safety margins for production variance. The result is a prediction within 10–20% of real-world runtime — close enough to make informed battery sizing decisions.&lt;/p&gt;</description></item></channel></rss>