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# Software stack under and over the hood of the fastest accelerating car in the world

How do you code the world's fastest electric hypercar? Dive into the Rimac Nevera's complex software stack, featuring 70 interconnected ECUs, bare-metal C, and high-performance Kafka pipelines.

- **Speakers:** Denis Grahovac
- **Event:** World Congress 2021
- **Published:** June 29, 2021
- **Duration:** 58:48
- **URL:** https://www.wearedevelopers.com/videos/221-software-stack-under-and-over-the-hood-of-the-fastest-accelerating-car-in-the-world

## Summary

The Rimac Nevera, the fastest accelerating electric hypercar in the world, is fundamentally a "computer on wheels" driven by a massively complex, multi-layered software ecosystem. Originating from a garage project that evolved into a premier automotive OEM and Tier-1 technology supplier, Rimac developed the Nevera from scratch to showcase its engineering capabilities. The vehicle's architecture is divided between in-vehicle systems—comprising over 70 interconnected Electronic Control Units (ECUs), real-time torque vectoring, and custom infotainment—and robust off-vehicle telemetry, diagnostic, and deployment platforms. Designing cross-domain software for this environment requires harmonizing bare-metal C and MATLAB for deterministic control alongside embedded Linux, Qt frameworks, and microservices for user interfaces.

A standout innovation is Rimac's approach to Advanced Driver-Assistance Systems (ADAS). Rather than pursuing conventional city autonomy, the Nevera leverages an Nvidia Pegasus supercomputer to act as an AI "driver coach" optimized exclusively for the racetrack. This system utilizes advanced sensor fusion to teach drivers optimal braking and cornering, without restricting the raw performance needed for high-speed engagement. Balancing extreme power with safety requires rigorous adherence to functional safety standards (like ISO 26262) and multi-stage testing workflows involving mocked ECU environments, hardware-in-the-loop "lab cars," and track testing to ensure absolute component reliability.

Off-vehicle connectivity acts as the central data backbone, securely streaming telemetry via MQTT and Kafka to cloud infrastructure. This allows engineering teams to monitor real-time vehicle behavior via modular React-based dashboards and enables owners to control features through native mobile applications. Furthermore, a highly orchestrated Over-The-Air (OTA) deployment system ensures updates are applied sequentially across ECUs, backed by proprietary diagnostic loops for production-line flashing and aftermarket servicing. By designing project-agnostic middleware that supports both its own flagship hypercars and third-party manufacturers, Rimac proves that modular architecture and centralized data pipelines are redefining the modern automotive landscape.

**Keywords:** rimac nevera software stack, automotive electronic control units, bare-metal c and matlab, advanced driver-assistance systems, functional safety iso 26262, automotive telemetry architecture, over-the-air vehicle updates, embedded linux infotainment, qt framework automotive ui, ai racetrack driver coach, mqtt and kafka data streaming, automotive microservices architecture, automated real-time torque vectoring, vehicle diagnostic tools, electric vehicle powertrain software

## Chapters

1. **Rimac Automobili company history and technology focus** (00:09) — Rimac evolved from electric vehicle garage conversions into an automotive component supplier and direct hypercar manufacturer.
1. **Concept and specifications of the Rimac Nevera hypercar** (04:49) — Engineers built the modern Nevera hypercar architecture entirely from scratch to achieve record-breaking electric acceleration performance metrics.
1. **In-vehicle and off-vehicle software control architecture components** (07:32) — A high-level structural network communicates between numerous electronic control units and dedicated domain controllers operating across the vehicle.
1. **Custom domain controllers and vehicle communication networks** (11:49) — Automotive engineers employ C and MATLAB programming stacks to execute calculations against vehicle control components via dedicated area networks.
1. **Fusing sensor data for the autonomous driver coach** (14:03) — Real-time sensor fusion and Nvidia computing platforms drive a bespoke track-only machine learning coaching mode for competitive racers.
1. **Delivering power performance with intelligent torque vectoring systems** (17:14) — Intelligent algorithms manage continuous physical power distribution to specific wheels based on active driving modes and real-time surface grip.
1. **In-vehicle infotainment systems and graphical functional safety validation** (22:49) — Embedded Yocto Linux and the Qt framework power performant internal interfaces verified by isolated functional safety microcontrollers.
1. **Connectivity platforms and robust telemetry cloud backend architecture** (30:30) — The connectivity backbone relies on continuous MQTT transmissions and scalable Kafka message brokering to persist live cloud metrics.
1. **Tracking remote firmware health with the engineering dashboard** (33:53) — Engineers utilize internal React applications to monitor real-time automotive test data streams and track historical diagnostic engine faults.
1. **Empowering customers with native mobile vehicle metric applications** (36:23) — A native mobile app infrastructure enables vehicle owners to monitor detailed driving analytics and securely dispatch remote operational commands.
1. **Orchestrating over-the-air firmware updates for vehicle modules** (38:45) — Specialized deployment systems orchestrate safe wireless firmware payload downloads across a strict dependency sequence of vehicle control modules.
1. **Electronic diagnostic software tools and factory production flashing** (41:05) — Custom .NET desktop applications facilitate factory floor component flashing and assist technicians with deep software diagnostics in regional repair centers.
1. **Transforming modern hypercars into connected digital network platforms** (43:55) — The overarching automotive industry demonstrates an ongoing philosophical shift migrating from purely mechanical engineering towards aggressively integrated software platforms.
1. **Approaching vehicle connectivity, offline telemetry, and software cybersecurity** (46:48) — Securing consumer vehicles relies on continuously iterating behavioral threat models and enforcing encrypted signed image installations to prevent unauthorized access.
1. **Hardware integration testing suites and autonomous track operations** (52:03) — Validating complex automotive software heavily relies on iterative mock hardware environments before authorizing physical road tests alongside professional track drivers.

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