| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
MPS (Monolithic Power Systems) |
22V, 2A H-BRIDGE MOTOR DRIVER EV |
3 |
|
|
MPS (Monolithic Power Systems) |
2-CELL BOOST CHARGER WITH 2A CHA |
5 |
|
|
MPS (Monolithic Power Systems) |
EMOTION SYSTEM SMART MOTOR MODUL |
9 |
|
|
MPS (Monolithic Power Systems) |
EMOTION SYSTEM SMART MOTOR MODUL |
0 |
|
|
MPS (Monolithic Power Systems) |
EMOTION SYSTEM SMART MOTOR MODUL |
9 |
|
|
MPS (Monolithic Power Systems) |
90VAC/60HZ TO 265VAC/50HZ, 50V/6 |
5 |
|
|
MPS (Monolithic Power Systems) |
2.5A, 35V, BIPOLAR STEPPER MOTOR |
5 |
|
|
MPS (Monolithic Power Systems) |
UNIVERSAL INPUT, NON-ISOLATED OF |
0 |
|
|
MPS (Monolithic Power Systems) |
MPX2001 EVAL BOARD |
4 |
|
|
MPS (Monolithic Power Systems) |
EVALUATION KIT FOR MP2696A |
4 |
|
|
MPS (Monolithic Power Systems) |
SMALL, UNIVERSAL INPUT NON-ISOLA |
5 |
|
|
MPS (Monolithic Power Systems) |
SMALL, UNIVERSAL INPUT NON-ISOLA |
5 |
|
|
MPS (Monolithic Power Systems) |
EMOTION SYSTEM SMART MOTOR MODUL |
10 |
|
|
MPS (Monolithic Power Systems) |
EVALUATION BOARD MP2696A |
4 |
|
|
MPS (Monolithic Power Systems) |
500MA, 5V USB, I2C-CONTROLLED BA |
5 |
|
|
MPS (Monolithic Power Systems) |
EMOTION SYSTEM SMART MOTOR MODUL |
6 |
|
|
MPS (Monolithic Power Systems) |
5V, 0.4A-5A CURRENT LIMIT SWITCH |
5 |
|
|
MPS (Monolithic Power Systems) |
1.5A THERMOELECTRIC COOLER CONTR |
3 |
|
|
MPS (Monolithic Power Systems) |
HIGH EFFICIENCY SYNCHRONOUS RECT |
5 |
|
|
MPS (Monolithic Power Systems) |
EVALUATION BOARD MP2696A W/MCU |
4 |
|
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)