How to DIY an Edge Computing PLC with Raspberry Pi?

Raspberry Pi is a credit card-sized computer designed for student computer programming education. Based on an open Linux system, it allows free development in programming languages such as C/C++, Python, and Javascript, providing an excellent learning and testing platform for many programming enthusiasts. With the help of open-source software and hardware resources, it has become possible for us to quickly realize IEC61131-3 standard edge computing PLC products.

Before formally introducing how to implement Raspberry Pi edge computing PLC, we first need to look at the background of the concept of edge computing PLC. In the era of Industry 4.0, the boundary between traditional control technology OT (Operation Technology) and information technology IT (Information Technology) is becoming increasingly blurred. Currently, in the field of industrial automation, if we need to integrate traditional PLC controllers with IT systems, a large number of gateway products are used, which may be a helpless move at this stage.

However, the complexity of the system architecture greatly increases the latency of industrial data and reduces the efficiency of big data collection, thereby restricting the accuracy of future industrial big data analysis. At the same time, all raw industrial data will be collected and analyzed by cloud platform servers. As factory applications become more complex, the computational power limits of cloud platforms and the bloated databases will pose great challenges to future industrial intelligence.

To achieve this goal, in addition to powerful data processing capabilities and large-capacity memory hardware support, the software needs to simultaneously support open OT and IT platforms, such as IEC61131-3 programming, PLCopen MC motion control, EtherCAT, CANopen, Modbus, and other traditional OT technologies, as well as open IoT programming platforms like Node-RED, local embedded databases, OPC-UA, MQTT, and other IT technologies.

Here we have also preliminarily sorted out the relevant technical parameters of the Raspberry Pi 3B+ Compute Module core board:

Processor: Broadcom BCM2837B0, Cortex-A53 (ARMv8) 64-bit SoC @ 1.2GHz

RAM Memory: 1GB LPDDR2 SDRAM

Flash Memory: 8GB/16GB/32GB eMMC Flash

Operating Temperature Range: -25℃ – 80℃

Hardware Certification:

Electromagnetic Compatibility Directive (EMC) 2014/30/EU

Restriction of Hazardous Substances (RoHS) Directive 2011/65/EU

Maintenance End Date: January 2026

However, after a comprehensive analysis, we believe that the Raspberry Pi CM core board’s processor still has relatively few peripheral interfaces for industrial control applications. For example, the UART peripherals for implementing industrial controller RS232/RS485/RS422 interfaces only have 2, and there is no CAN bus interface. Ethernet must be expanded through a USB interface chip, which greatly limits the real-time performance of network interaction. This will pose significant challenges for some field buses that require high speed, such as EtherCAT, mainly limited by the bandwidth of the internal USB-to-Ethernet interface chip and the real-time processing of Ethernet packets by the USB chip.

Of course, we need to give the industrial controller products developed based on the Raspberry Pi CM core board an appropriate positioning to fully utilize its hardware features. Traditionally, industrial controllers use processors with lower clock frequencies and very limited memory space. Therefore, the Raspberry Pi CM industrial controller should leverage its high-performance computation and large storage capacity, allowing computations and data storage that traditionally needed to be done on the cloud to be delegated to the Raspberry Pi CM industrial controller as needed. This is the edge computing PLC concept we introduced earlier. At the same time, it can also communicate with other industrial controllers or sensors through industrial field buses and communication protocols, such as Modbus, CANopen, EtherCAT, OPC-UA, etc.

Regarding the hardware part, one last point to note: the processor of the Raspberry Pi CM core board generates significant heat, so proper heat dissipation design is required. Similarly, its power consumption is high and not suitable for some low-power or heat-sensitive application scenarios.