| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Texas Instruments |
EVAL BOARD FOR TUSB544 |
2 |
|
 |
Texas Instruments |
EVAL MODULE FOR BQ24630 |
6 |
|
 |
Texas Instruments |
EVAL BOARD FOR BQ24296 |
1 |
|
 |
Texas Instruments |
EVAL MODULE FOR BQ24075 |
1 |
|
 |
Texas Instruments |
EVALUATION MODULE |
9 |
|
 |
Texas Instruments |
EVAL BOARD FOR LMK04826 |
1 |
|
 |
Texas Instruments |
EVAL MODULE FOR TPD1S514 |
36 |
|
 |
Texas Instruments |
EVAL BOARD WIRELESS RX BQ51003 |
0 |
|
 |
Texas Instruments |
EVAL MODULE FOR DRV8832 |
0 |
|
 |
Texas Instruments |
KIT EVAL MOTHER BRD FOR AMC1210 |
2 |
|
 |
Texas Instruments |
EVAL MODULE FOR AFE7222 |
2 |
|
 |
Texas Instruments |
EVAL MODULE FOR THS7316 |
4 |
|
 |
Texas Instruments |
EVALUATION BOARD TPS22946 |
5 |
|
 |
Texas Instruments |
DEMO/EVAL PLATFORM FOR DRV2605 |
3 |
|
 |
Texas Instruments |
EVAL MODULE FOR BQ24725A-710 |
7 |
|
 |
Texas Instruments |
EVAL MOD BQ27542 |
4 |
|
 |
Texas Instruments |
BOARD EVALUATION FOR LMK01000 |
1 |
|
 |
Texas Instruments |
EVAL MODULE FOR CDCE62002 |
2 |
|
 |
Texas Instruments |
EVM FOR TPS23758 |
4 |
|
 |
Texas Instruments |
EVAL MOD BQ4Z60 2,3,4 SERIES |
3 |
|
Evaluation and Demonstration Boards and Kits are hardware platforms designed to facilitate the development, testing, and demonstration of electronic systems. They serve as critical tools for engineers and developers to prototype applications, validate designs, and accelerate time-to-market. These boards integrate processors, sensors, communication interfaces, and software ecosystems, enabling rapid experimentation across diverse industries such as IoT, automotive, and industrial automation.
| Type | Functional Features | Application Examples |
|---|---|---|
| Microcontroller Development Boards | Embedded CPUs, GPIOs, integrated peripherals | IoT devices, robotics |
| FPGA Evaluation Boards | Reconfigurable logic, high-speed interfaces | Communication systems, AI accelerators |
| Sensor Expansion Kits | Multi-sensor integration (temperature, motion, etc.) | Smart agriculture, environmental monitoring |
| Wireless Communication Modules | Bluetooth/Wi-Fi/LoRa protocols, antenna interfaces | Connected healthcare, smart cities |
Typical architecture includes: - Processing Units: Microcontrollers, FPGAs, or SoCs - Memory: RAM, Flash, EEPROM - Interfaces: USB, UART, SPI, I2C, Ethernet - Power Management: Regulators, battery connectors - Software Stack: SDKs, device drivers, IDEs Physical designs often feature standardized form factors (e.g., Arduino Uno, Raspberry Pi HATs) for modular expansion.
| Parameter | Description |
|---|---|
| Processor Performance (MHz/GHz) | Determines computational capability |
| Memory Capacity (RAM/Flash) | Affects program complexity and data storage |
| Interface Types | Dictates peripheral compatibility |
| Power Consumption (mW/MHz) | Critical for battery-operated devices |
| Operating Temperature (-40 C to +85 C) | Defines environmental durability |
- Internet of Things (IoT): Smart home controllers, edge AI nodes - Automotive: ADAS sensor fusion platforms - Industrial Automation: PLC controllers, predictive maintenance systems - Consumer Electronics: Wearables, AR/VR prototypes
| Manufacturer | Representative Products |
|---|---|
| STMicroelectronics | STM32 Nucleo Series, SensorTile Kit |
| Intel | Intel Edison, Movidius Neural Compute Stick |
| Xilinx | Zynq UltraScale+ MPSoC Evaluation Kit |
| Arduino | Arduino MKR Series, Nano 33 IoT |
Key considerations: 1. Match processor capabilities to application complexity 2. Verify interface compatibility with target peripherals 3. Assess software ecosystem maturity (e.g., ROS support) 4. Evaluate power budget requirements 5. Consider long-term availability and community support
- Growing adoption of RISC-V-based evaluation platforms - Integration of AI/ML accelerators in edge computing boards - Expansion of open-source hardware ecosystems - Increased focus on energy-efficient architectures for IoT - Standardization of form factors (e.g., SparkFun's Qwiic system)