Evaluation and Demonstration Boards and Kits

Image Part Number Description / PDF Quantity Rfq
RDHP-1702

RDHP-1702

Power Integrations

EVAL KIT BASIC ISOLATION SID1183

3

RDK-851

RDK-851

Power Integrations

EVAL BOARD FOR BRD1260C

5

RDHP-1608

RDHP-1608

Power Integrations

SID1182K REFERENCE DESIGN BOARD

7

RDK-853

RDK-853

Power Integrations

REFERENCE DESIGN BOARD FOR BRIDG

5

RDHP-1526

RDHP-1526

Power Integrations

SID1182K REFERENCE DESIGN BOARD

25

RDK-252

RDK-252

Power Integrations

KIT REF DESIGN DG CAPZERO

0

2EB0535T2A0

2EB0535T2A0

Power Integrations

EVALUATION BOARD SCALE-2

0

2EB0108T2A0

2EB0108T2A0

Power Integrations

EVALUATION BOARD SCALE-2

0

EB01

EB01

Power Integrations

BASIC BOARD SCALE-1

0

2EB300C17A0

2EB300C17A0

Power Integrations

EVALUATION BOARD SCALE-2

0

2EB0435T2A0

2EB0435T2A0

Power Integrations

EVALUATION BOARD SCALE-2

0

2EB0650P2A0

2EB0650P2A0

Power Integrations

EVALUATION BOARD SCALE-2

0

1EB2060P2A0

1EB2060P2A0

Power Integrations

EVALUATION BOARD SCALE-2

0

RDK-382

RDK-382

Power Integrations

BOARD PROTO PS PFC LLC 150W

0

RDK-852

RDK-852

Power Integrations

REFERENCE DESIGN BOARD FOR BRIDG

5

RDK-249

RDK-249

Power Integrations

KIT REF DESIGN PFS762HG

0

RDK-236

RDK-236

Power Integrations

KIT REF DESIGN PFS714EG

0

RDK-128

RDK-128

Power Integrations

KIT REF DESIGN 36-72W MOTOR DRVR

0

DAK-33

DAK-33

Power Integrations

KIT DESIGN ACCELERATOR LCD ADAPT

0

DAK-31

DAK-31

Power Integrations

KIT DESIGN ACCELERATOR PC CONV

0

Evaluation and Demonstration Boards and Kits

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.

TypeFunctional FeaturesApplication Examples
Microcontroller Development BoardsEmbedded CPUs, GPIOs, integrated peripheralsIoT devices, robotics
FPGA Evaluation BoardsReconfigurable logic, high-speed interfacesCommunication systems, AI accelerators
Sensor Expansion KitsMulti-sensor integration (temperature, motion, etc.)Smart agriculture, environmental monitoring
Wireless Communication ModulesBluetooth/Wi-Fi/LoRa protocols, antenna interfacesConnected 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.

ParameterDescription
Processor Performance (MHz/GHz)Determines computational capability
Memory Capacity (RAM/Flash)Affects program complexity and data storage
Interface TypesDictates 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

ManufacturerRepresentative Products
STMicroelectronicsSTM32 Nucleo Series, SensorTile Kit
IntelIntel Edison, Movidius Neural Compute Stick
XilinxZynq UltraScale+ MPSoC Evaluation Kit
ArduinoArduino 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)

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