MACS - Modular Architecture for Control Software

MACS - Modular Architecture for Control Software

A software development and deployment suite. Use it for HIL/SIL testing to deploying ESS control software on embedded Linux devices.

AvailableV1.0.0Q2 2026
16M
Signals / second
6μs
End-to-end latency
56
Function blocks
Open
Modify and create new nodes

MACS combines visual function-block programming, real-time signal monitoring, and full hardware-in-the-loop testing in a single Linux-native platform. The microservice architecture means each node — from CAN routing to test execution to web dashboards — runs as an independent systemd service. If one node crashes, the rest keep running.

For evaluating engineers: MACS occupies the same problem space as Vector CANoe, dSPACE, and NI VeriStand, but with a fundamentally open architecture. MACS Studio compiles its visual blocks to C for real-time performance (~39μs per update cycle measured), the test framework integrates with standard CI/CD via JUnit XML output, and custom nodes can be developed in either C or Python.

Hybrid simulation/real-ECU mode lets you seamlessly mix simulated and physical signals during a test — a workflow that commercial tools typically force you to choose between.

Available now (V1.0.0, Q2 2026). Runs on standard Linux desktops and ARM embedded targets. Supported protocols include CAN 2.0/FD, J1939, XCP, CCP, Modbus, IO, UDS, and CANopen.

Challenges we solve

What you're working around today, and how MACS addresses it.

Complex ECU modeling requires deep embedded C expertise

MACS Studio — drag-and-drop blocks, automatic C code generation. Integration time 0s.

Long test development cycles delay releases

Python test framework with real-time signal validation.

Gap between simulation and real hardware testing

Hybrid mode — seamlessly switch between simulation and real-time values.

No CI/CD integration for automotive test automation

JUnit XML output — integrates with Jenkins, GitHub Actions, GitLab.

Python too slow for real-time control loops

Visual models compile to C — measured 39μs per update cycle.

Expensive dedicated HIL simulation hardware required

Runs on standard Linux — desktop or embedded Linux ARM.

Multi-channel CAN requires separate tools and manual routing

Unified MCC node with 10-channel support, DBC auto-decoding, and virtual CAN networks.

High licensing costs for commercial tools

Open modular architecture with professional-grade capabilities.

AI integration and modelling

Generate a Python ECU template and import libraries like PyTorch or scikit-learn to train on real-time data.

It's impossible to develop your own functions and features

MACS is open — APIs in C and Python let you create custom nodes.

No remote deployment or monitoring

Deploy via SSH or through the integrated web server.

One part of the program causes a complete stop of the software

Microservice architecture — each node runs as a systemd service and restarts independently.

How do we track software requirements implementation status?

Built-in requirements management connects to test cases for coverage tracking. Requirements attach directly to MACS Studio components.

Existing tools look like Excel sheets with buttons

Modern, purpose-built UI designed for control software workflows.

Inside the platform

MACS Studio

MACS Studio

Drag-and-drop visual programming with 60+ function blocks. Simulation and real-time visualization of generated C code.

MACS Desktop GUI

MACS Desktop GUI

Qt-based system management with layered node architecture, real-time event logging, and project management.

Web Dashboard

Web Dashboard

Browser-based monitoring with REST API and WebSocket. Remote access to signals and deployment of projects.

CAN Network Configurator

CAN Network Configurator

Multi-channel CAN setup with DBC, message routing, and remote discovery. SSH-based interface detection for embedded targets.

Requirements Manager

Requirements Manager

Track requirements implementation status with linked test cases. Coverage analysis and traceability for safety-critical control software.

SOC + Thermal Modeling (BMS demo)

SOC + Thermal Modeling (BMS demo)

Real BMS control sheet running in simulation — OCV-initialized coulomb counting blended with voltage-based correction, plus an I²R thermal model integrated against a cooling term. 35 blocks, live at 10 Hz.

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Interested in MACS - Modular Architecture for Control Software?

Get in touch for a demo or quote.