Physical test system
Last updated
Last updated
While virtualization and shift-left strategies significantly reduce physical testing overheads, physical testing remains irreplaceable to ensure real-world performance, safety, and durability. Real-world environments introduce variables like vibrations, wear-and-tear, and edge-case conditions that cannot be fully replicated in simulations. Physical testing also validates complex integrations between hardware and software under real operational stress. By combining virtual and physical testing, manufacturers can ensure not only faster development cycles but also the robustness and reliability required for safe, high-quality vehicles on the road.
In automotive testing, physical test systems ensure real-world validation of vehicle components and systems. The primary types include:
Component HIL (Hardware-in-the-Loop): Real hardware components (e.g., ECUs, sensors, actuators) are tested in virtual environments simulating vehicle behavior and conditions.
System HIL: Integrates multiple components into sub-systems (e.g., powertrain or ADAS) for end-to-end validation.
Development Vehicles: Pre-production prototypes used to test real-world performance and integration across systems.
Engineering Mules: Modified test vehicles combining new components with existing platforms to assess feasibility.
Fleet-Based Testing: Real-world driving of multiple vehicles to collect data over time for reliability and performance analysis.
Each of these systems plays a critical role in bridging the gap between simulation and real-world conditions, ensuring robust vehicle performance.
Hardware-in-the-Loop (HIL) is a testing method where real hardware components, such as ECUs and sensors, are integrated into a virtual environment. This virtual environment simulates the rest of the vehicle, its subsystems, or real-world operating conditions like driving scenarios. HIL testing allows systems to be validated in near-real conditions without requiring a fully built physical car. This significantly accelerates development, reduces costs, and ensures safety-critical components are thoroughly tested before integration into physical prototypes.
The introduction of High-Performance Computing (HPC) and Software-Defined Vehicles (SDVs) is transforming HIL testing in significant ways:
Increased Complexity: HPC enables centralized computing and domain integration, meaning HIL systems must simulate entire zones or vehicle domains, not just isolated ECUs. This requires more processing power and advanced virtual environments.
Scalability: HIL setups now need to scale for SDV architectures, where software can continuously evolve. Virtualization and cloud support allow hardware to be integrated with virtual components for modular and agile testing.
Real-Time Requirements: HPC-powered systems and SDVs demand synchronized testing across virtualized ECUs, real hardware, and connected systems to ensure functional safety (ASIL) and performance.
Software-Centric Focus: SDVs rely on frequent software updates. HIL systems are evolving to validate over-the-air (OTA) updates, dynamic software configurations, and real-world scenarios rapidly.
Enhanced Simulation Integration: Combining HIL with virtual environments enables hybrid testing, where virtual and physical components interact seamlessly. This is crucial for validating AI-driven features, ADAS, and autonomous functions.
In essence, HIL is transitioning from isolated, static setups to dynamic, integrated platforms that accommodate evolving SDV architectures, high-performance computing, and real-time software development.
System-HIL (System Hardware-in-the-Loop) represents an advanced level of HIL testing where entire vehicle systems—spanning powertrain, infotainment, ADAS, and body controls—are integrated into a single testing environment. Unlike component-level HIL, System-HIL focuses on realistic system-level interactions to simulate full-vehicle behavior under near-real conditions.
A House of HIL is an advanced test environment that integrates numerous Hardware-in-the-Loop (HIL) systems to validate the full vehicle. It consists of multiple component HILs, each dedicated to testing individual ECUs, sensors, or actuators, and combines them to form a complete system-level testing setup.
For a single vehicle, a House of HIL setup typically includes:
Dozens of Component HILs: Each HIL tests specific ECUs (e.g., ADAS, infotainment, braking). A modern car may have 30-70 ECUs, requiring corresponding HIL systems.
Physical Space: HIL test racks, power supplies, and cooling infrastructure require dedicated labs. For a full vehicle, this can span several rooms, often over hundreds of square meters.
The number of Component HILs depends on vehicle complexity:
Modern SDVs: Up to 50+ component HILs for individual ECUs.
Each HIL tests functions like powertrain, ADAS, climate control, and body electronics independently before integrating into the system.
The House of HIL combines these systems, ensuring synchronization and enabling end-to-end validation for complex vehicles.
The introduction of High-Performance Compute and SDVs will have a significant impact on System-HIL, including:
System Integration With HPC and centralized SDV architectures, multiple domains (powertrain, ADAS, infotainment) need integrated testing. System-HIL ensures realistic interaction across interconnected systems, enabling validation of complex dependencies.
Data Management and Processing Power SDVs generate massive amounts of real-time data. System-HIL relies on HPC to manage, process, and simulate this data efficiently, ensuring accurate testing of time-sensitive systems like braking and steering.
Hardware-Software Synchronization High-performance computing allows for better synchronization between physical hardware components and virtual systems. For SDVs, this is critical to validate continuously evolving software configurations and over-the-air (OTA) updates.
Scalability and Modular Testing Modular testing of subsystems is integrated into a scalable System-HIL setup. For example, a full-vehicle simulation can test individual zones or domains while maintaining system-wide scalability.
Realistic Sensor and Actuator Emulation Advanced ADAS and autonomous functions rely on accurate sensor and actuator emulation. System-HIL integrates real hardware with virtual sensors to ensure realistic, safety-critical system validation.
Cost and Space Optimization While System-HIL requires substantial resources, virtualization and HPC reduce physical infrastructure by integrating virtual environments, minimizing costs and space needed for traditional hardware racks.
The figure below indicates how a System HIL should be designed to test our - by now famous - Open Door API.
System-HIL, evolving with HPC and SDVs, supports full-vehicle testing by combining real hardware with advanced simulations. It ensures scalable, modular, and synchronized validation while addressing the growing complexities of software-defined and high-performance vehicle systems.
Engineering Mules are early-stage test vehicles built by combining new development components with an existing production vehicle platform. They allow real-world testing of systems like powertrains, suspension, or new electronic architectures long before the final vehicle design is ready. Mules help validate critical functions under real driving conditions, bridging the gap between simulation and full vehicle prototypes. They reduce development risks by exposing design flaws early, allowing engineers to refine systems before committing to costly production tooling.
The A-D test samples represent progressive stages of prototype development in automotive testing:
A-Sample: Initial prototypes validate basic functionality and identify integration issues.
B-Sample: Enhanced prototypes refine subsystem interactions, optimize software, and test durability.
C-Sample: Pre-production prototypes undergo full regulatory, safety, and real-world deployment tests.
D-Sample: Production-intent prototypes confirm readiness for production, meeting all quality and compliance requirements.
In the past, non-connected vehicles in A-D sample phases had minimal issues with version compatibility, as systems were self-contained. However, in SDVs, cloud backends and Vehicle-to-Cloud (V2C) APIs are integral to vehicle operations. If these APIs or backend services evolve during development, it creates versioning challenges. Sample vehicles at various phases (A-D) need their on-board software and cloud services to remain synchronized. Misalignment can cause failures in functionality or testing, requiring strict version control, backward compatibility, and coordinated updates across all systems. This synchronization is critical for seamless integration and validation.
Vehicle-in-the-Loop (ViL) testing is a method that combines real vehicles with a simulated environment to validate vehicle systems under controlled and realistic conditions. The vehicle operates on test benches, like chassis dynamometers, while virtual inputs simulate road conditions, traffic, and sensor data.
ViL is particularly useful for validating advanced driver assistance systems (ADAS), autonomous driving, and energy management. It enables repeatable testing of complex scenarios without physical road tests, improving safety, cost efficiency, and development speed. This approach bridges simulation and real-world testing.
Test fleets are essential for validating vehicles under real-world conditions, evolving into production fleets as development progresses. Initially, small fleets (5-20 vehicles) validate core systems, focusing on functional testing and performance. As systems mature, mid-sized fleets (50-200 vehicles) capture diverse data, testing across environments, driver behaviors, and edge cases.
Test fleets generate terabytes of data daily, including sensor logs, V2C communication, and diagnostics. Production fleets scale up (thousands of vehicles), monitoring long-term reliability, OTA updates, and real-world user feedback to ensure readiness for market deployment.
For progressive OEMs, every production vehicle now also acts as a test vehicle for new feature updates delivered via Over-the-Air (OTA). While updates undergo rigorous validation and homologation, they enable continuous innovation post-production. This approach allows OEMs to experiment more dynamically, gradually introducing new features or improvements. Compared to the past, where vehicles were static once sold, today’s production vehicles serve as platforms for iterative development, leveraging real-world data and feedback to refine performance, safety, and user experience.
Fleet data offers numerous opportunities for OEMs and operators to optimize vehicle development and operations:
Product Development: By identifying patterns and real-world usage, fleet data helps refine features, improve vehicle performance, and address customer needs dynamically.
Continuous Homologation: It supports compliance by validating software updates to ensure regulatory alignment as vehicles evolve.
Fleet Management: Real-time data optimizes operations, reduces maintenance costs, and improves uptime.
Research & Innovation: Anonymized datasets power AI model development for autonomous driving and other advanced technologies.
Customer Support: Proactive issue detection enhances support and reduces customer disruptions.
Sustainability Efforts: Fleet data tracks emissions and promotes green initiatives, supporting environmental goals.
