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Model-Based testing framework for Automotive Systems

QAC EmTech
QAC Emerging Technologies Quality Assurance

This monthly newsletter will focus on QAC’s activities regarding R&D, Connected Vehicles, Cognitive Autonomous Systems, Artificial Intelligence, Internet of Things, and Blockchain Quality Assurance Services


Leading the way
Welcome to the sixteenth edition of the EmTech newsletter. In this edition, we’ll review the recently completed technical project by EmTech. In the previous newsletter, we provided a short overview of EmTech accomplishments covering R&D, Solutions, Dissemination, etc. This newsletter will provide a short overview of the developed and tested Model-Based testing framework for Automotive Systems.
Welcome to our 16th edition of our EmTech Quality Assurance Newsletter

Keeping you informed


Our emerging technologies quality assurance workstreams

R&D and Grant Projects
Research and development of new technologies that position QAC to become a world leader in quality assurance services.
Connected Vehicles
Testing and Quality Assurance services exclusively developed to provide integration testing services for highly connected vehicles.
Cognitive Autonomous Systems
Fully automation of testing and quality Assurance services exclusively developed for Cognitive Autonomous Systems
Cybersecurity, IoT, AI, and Blockchain
Focus on developing new technologies that utilizes AI to address QA challenges on Cybersecurity, IoT, and Blockchain domains

Model-based testing of automotive systems

QAC, in partnership with Ontario Tech University (OTU), The Automotive Centre of Excellence (ACE), and the National Research Council of Canada, have completed a 28-month highly technical project. The purpose was to test a complete meta-model of a vehicle fully automated to trigger components, listen, and measure (one or several) responding components. This could be achieved over many different network protocols found both within the vehicle and outside the vehicle i.e., CAN, MOST, Bluetooth, 5G.

The project exceeded expectations. As the project evolved, it became clear that the advancements in technology were endless. Such knowledge brought QAC to the forefront of the automotive world. As a result, the team created a state-of-the-art service that addressed industry concerns.This solution automated the testing of hundreds of components produced by different suppliers, automatically testing the vehicle’s full or subsystems. Our service demonstrations received positive feedback and garnered interest from our technical partners.

Vehicle communication

This project was not an easy task. Modern vehicles have very complex integrated communication systems that speak over one or multiple communication protocols (CAN, Flexray. Ethernet, LIN, MOST). These protocols can be triggered by complex detection systems such as LiDAR, camera, and human-triggered components such as acceleration, braking etc. These communication methods send encrypted messages to communicate with Electronic Control Units (ECU’s). In turn, these messages control mechanical components (sensors), and electronic features (warning alarms etc.). Even braking, steering, and acceleration could be automatically controlled, hence the evolution of autonomous vehicles.

There are external factors to consider outside the composition of vehicles. Modern vehicles communicate to external devices such as mobile phones, tablets, and laptops. These three channels can connect through wires or wirelessly for multimedia functions, third-party applications, and mapping purposes. The evolution of 5G, smart devices, infrastructure, and the continuous evolvement of vehicle technologies would change modern life.

Eventually, cars would communicate with traffic lights, emergency vehicles, points of interest, and even with other cars. Today, there are several terms being used such as V2V (Vehicle to Vehicle), V2I (Vehicle to Infrastructure), and V2X (Vehicle to everything). The combination of communication components is virtually endless, hence the need for advanced testing techniques to ensure both functionally and security.

For our test framework, we deconstructed a vehicle into a set of components and proceeded to map the relationships between each of the components within the vehicle. This provided a representation (meta-model). Based on that model, 1 million test cases were generated and executed. These cases did not include external factors! During test execution, which can be run entirely automated, our solution selects each test case and sets the components’ initial state. At that point, the components “listen” to other components and compare final states to the expected states and record a pass or fail result. For example, when a vehicle is switching gears from parking to reverse, this action might affect several components such as the back camera, back sensor, or multimedia volume, etc. The team also developed a different approach for detecting the current state of each component. CAN bus messages and Listener scan identify and interpret device source code or driver state without having access.

To summarize

  1. Our automotive SIT solution focused on system integration testing across vehicle architecture pillars (infotainment, instrument cluster, heads-up display, telematics, and AUTOSAR)
  2. The test framework provided verification of all devices and components, part of the automotive ecosystem, and test scenarios. This test ensured various parts worked together correctly
  3. The test framework includes both the internal communications and relationships of trigger components, responding components, the change of state, and external components that communicate to the vehicle
  4. The test framework includes all communication bus or networks that data must travel through
  5. The team conducted connectivity testing for head units, IoT components, and devices in a vehicle according to ISO 26262 guidelines based on ASIL levels
  6. The test execution can be performed on a HiL bench, through simulation, on an assembled vehicle, and as a combination of all three

Testing for edge

This framework leveraged the automated process to prioritize automotive test cases and focused on high-risk test execution scenarios. Our solution made it easy to edit and maintain test case adaptability when adding components to create new listeners for specific products and vehicles.

During the test, execution we triggered vehicle components (actual, simulated, or extracted onto a HiL test bench) and listened to the expected responding components. This operation alone could use several communication protocols. Tests were automatically generated by modeling the vehicle, prioritized by leveraging ISO 26262 ASIL levels, and automatically executed as a whole or specific subsection depending on the test focus.

From August 2020 to October 2020, QAC partnered with the National Research Council (NRC) to conduct a test on a fully disassembled Ford Edge. The test focused on the vehicle’s hardware in the loop test bench. Even with Covid-19 restrictions in place, the team was able to connect and test the components on the bench successfully calling CAN messages and communicating with the expected components. All work was done from a remote location.

The project was completed in December 2020. The QAC EmTech team was proud that the project resulted in three patent applications. This achievement spoke to the excellent overall viability to the EmTech team’s unique capabilities and vision. Overall, it was a huge success.


Coming next month
To learn more please visit our EmTech page at More topics to come soon! Stay tuned to our next newsletter.

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