The successful implementation and upkeep of a HIL rig depends not only on initial capital but also on access to a mix of specialized skills
The development of vehicles is complicated. In the past, we built prototype versions to learn the scope of the system and gather details on its functionality and performance. Hardware-in-the-loop testing is a vital enabler for safe, reliable and cost-effective development. Besides helping to define systems, it is used to test a system long before all the constituent components have been made.
HIL testing is an essential component within the broader framework of model-based development, particularly for engineering complex control systems, embedded software and safety-critical applications. It integrates physical hardware components (such as ECUs or sensors) with simulated components in a real-time simulated environment. Unlike pure software simulation or physical road tests, HIL provides a hybrid, highly controlled setting. We can simulate missing components under development and exercise a hybrid of actual and simulated components under simulated operation.
Vehicles are increasingly loaded with ECUs, ADAS and intricate software. Developing multiple ECUs takes time, often starting with prototype parts that represent some of the attributes of the specific system. Although prototype creation is much faster than it used to be, it still takes time to lay out boards and write software for features. HIL provides the ability to explore multiple system designs and functional apportionment early in the development effort.
Systems include ECUs, electrical components and sensors that are part of the entire system. A system may also include models of other elements or simulated components. The design of the hardware portions of the system that emulate other components will require low latency – that is, propagation of signals and component broadcasts via communication. This will include an emulation of the system environment, where high-fidelity component models emulate ECU responses, vehicle dynamics, road conditions, sensor inputs and fault conditions. Real-time computers and interfaces connect hardware and simulation for instantaneous interaction.
Designing and managing high-fidelity simulation environments requires specialized expertise. There is a need for expertise in electronics and electrical hardware, software and real-time simulation, which is not often found in one person.
Setting up HIL systems requires specialized, often expensive, hardware and simulation tools. This can limit adoption, especially for smaller teams or startups. The initial HIL setup, for example, will need to be on a platform that does not introduce undue latency beyond the expectations of the vehicle system. Hardware that can coordinate multiple ECUs and communication protocols while avoiding timing mismatches is critical. Even minor latency issues or signal desynchronization can skew test results and mask actual faults.
Simulation of modern vehicle systems requires high-fidelity models for subsystems such as motors, sensors and ECUs. The models are only as good as the hardware they mimic, which is reflected in the initial setup costs. Capturing second- and third-order effects or dynamic behaviors makes models complex and demands powerful simulation hardware. Inaccurate or incomplete models lead to misleading test outcomes, undermining the value of HIL validation.
Sensors, actuators and other hardware used in HIL may have physical or signal constraints, meaning some aspects of real-world behavior can’t be fully replicated in the lab without investing in engineering time to uncover and adequately address them. This requires engineering talent to understand the gap, work to close it where possible, and note the limitations in simulating the system. This is but one level of specialized skill required for success.
Generating realistic sensor data and simulating all relevant physical phenomena (including edge cases and faults) is challenging. Advanced use cases such as ADAS require vast, high-quality scenario libraries, which are time-consuming to build.
As vehicle features grow in complexity and new standards emerge, HIL test benches need frequent updates to remain relevant and support continuous integration and version control. Scalability to accommodate new hardware or test scenarios can be a logistical challenge. The tool itself will need to fall under configuration management for two reasons. First, there will be a need to address specific system incarnations if the HIL rig is used to model more than one vehicle platform or a variety of vehicle incarnations. Second, we will need to be able to go back to previous versions of the test tool.
Automating scenario generation, software reflashing and repeated validation while maintaining reproducible and valid ‘golden’ test data is challenging, especially across development cycles. The test and verification of the test fixture becomes more difficult with the complexity of the HIL. Ultimately, we must be able to make tangible statements of the quality of any test fixture, but it takes time and effort to understand the veracity and limits of the HIL.
Some aspects may not be testable with HIL, so human-in-the-loop or vehicle-in-the-loop stages are still necessary.
Hardware-in-the-loop testing has been a vital pillar of auto engineering for probably a decade, and with increasing complexity, its value has increased. With HIL rigs, we can explore design incarnations and test them in a simulated environment – well in advance of material availability.
