EFM32LG280F256G-F-QFP100 - Silicon Labs

Manufacturer Part Number

EFM32LG280F256G-F-QFP100

Manufacturer

Silicon Labs

Introduction

The EFM32LG280F256G-F-QFP100 is a part of the Energy-Efficient Leopard Gecko Series.

Product Features and Performance

ARM Cortex-M3 core processor

32-Bit single-core architecture with up to 48MHz speed

86 I/O pins for versatile connectivity

Energy-efficient with low power consumption

Product Advantages

High integration reduces system cost

Low-energy sensor interface for efficient sensor reading

Advanced encryption standard hardware engine for enhanced security

Key Technical Parameters

Core size: 32-Bit

Speed: 48MHz

Connectivity includes EBI/EMI, I2C, IrDA, SmartCard, SPI, UART/USART

Peripheral support for Brown-out Detect/Reset, DMA, I2S, POR, PWM, WDT

Program Memory Size: 256KB FLASH

RAM Size: 32KB

Supply Voltage: 1.85V to 3.8V

A/D Converters: 8x12bit SAR

D/A Converters: 2x12bit

Operating Temperature Range: -40°C to 85°C

Quality and Safety Features

Integrated Watchdog Timer for system reliability

Brown-out Detect/Reset for voltage monitoring

Qualified for industrial temperature range to ensure performance under stress

Compatibility

Compatible with other ARM Cortex-M3 peripherals and development tools

100-LQFP (14x14) package easy to mount in standard PCBs

Application Areas

Ideal for energy-sensitive applications

Suitable for industrial, consumer electronics, and smart metering

Flexible for IoT devices

Product Lifecycle

Status Active

Not nearing discontinuation with ongoing manufacturer support

Several Key Reasons to Choose This Product

Low power operation suitable for battery-powered devices

Comprehensive security features to protect sensitive data

High level of integration reduces the need for additional components

Support for a wide range of communication interfaces for connectivity needs

Generous amount of FLASH and RAM for complex applications

Robust support and community for ARM Cortex-M3 development

Leveraging Silicon Labs' energy-friendly ecosystems for development and debugging