| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
|
TRINAMIC Motion Control GmbH |
EVAL KIT FOR TMC2160 |
8 |
|
|
|
TRINAMIC Motion Control GmbH |
BREAKOUTBOARD WITH TMC262 |
19 |
|
|
|
TRINAMIC Motion Control GmbH |
EVAL-KIT FOR TMC6300 |
4 |
|
|
|
TRINAMIC Motion Control GmbH |
EVAL BOARD FOR TMC4331 |
1 |
|
|
|
TRINAMIC Motion Control GmbH |
POWER STAGE FOR TMC4671-EVAL |
7 |
|
|
|
TMC4671+TMC-UPS-2A24V-EVAL-KIT TRINAMIC Motion Control GmbH |
EVAL KIT FOR TMC4671 |
9 |
|
|
|
TMC8670+TMC-UPS-2A24V-EVAL-KIT TRINAMIC Motion Control GmbH |
EVAL KIT FOR TMC8670 |
5 |
|
|
|
TRINAMIC Motion Control GmbH |
BREAKOUTBOARD WITH TMC6300 |
10 |
|
|
|
TRINAMIC Motion Control GmbH |
EVAL MODULE FOR TMC5031 |
3 |
|
|
|
TRINAMIC Motion Control GmbH |
EVAL KIT FOR TMC2208 |
3 |
|
|
|
TRINAMIC Motion Control GmbH |
BREAKOUTBOARD FOR TMC8462 |
7 |
|
|
|
TRINAMIC Motion Control GmbH |
REF DESIGN FOR TMC2300-LA |
10 |
|
|
|
TRINAMIC Motion Control GmbH |
STEP/DIR SIGNAL GENERATOR |
90 |
|
|
|
TRINAMIC Motion Control GmbH |
POWER STAGE FOR TMC8670-EVAL |
6 |
|
|
|
TRINAMIC Motion Control GmbH |
EVAL BOARD FOR TMC2300 |
4 |
|
|
|
TRINAMIC Motion Control GmbH |
EVAL BOARD FOR TMC6300 |
5 |
|
|
|
TRINAMIC Motion Control GmbH |
POWER STAGE FOR TMC4671-EVAL |
4 |
|
|
|
TRINAMIC Motion Control GmbH |
EVAL BOARD FOR TMC1420 AND TMC26 |
0 |
|
|
|
TRINAMIC Motion Control GmbH |
EVAL BOARD FOR TMC1620 AND TMC26 |
0 |
|
|
|
TRINAMIC Motion Control GmbH |
EVAL KIT FOR TMC1420 AND TMC262 |
0 |
|
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)