Master's Thesis - AI-Assisted Automation of EMS Test Developmentcable

Master's Thesis - AI-Assisted Automation of EMS Test Development

A Master's thesis is an excellent opportunity to get to know Scania and TRATON and build relationships for the future. Many of today's employees began their Scania career with their degree project.

The Engine Management System (EMS) controls and monitors important engine functions, including sensors, actuators, communication signals, diagnostics and fault reactions. Reliable testing is essential to verify that EMS functions behave correctly under normal and faulty conditions.

Within EMS System Test Base Engine, we are investigating how artificial intelligence and test automation can improve the development and execution of EMS test cases.

Background and objective

EMS test cases are developed from requirements and FMEA information. They must then be converted into executable test scripts, executed in suitable environments and evaluated against expected results. This process can require significant manual effort.

The objective of this thesis is to develop and evaluate an automated workflow that combines:

• AI-assisted conversion of structured EMS test cases into executable HIL test scripts.
• INCA-FLOW automation for executing and evaluating selected test cases.

The work will investigate how automation can improve test efficiency, repeatability, traceability and overall test quality.

Job description

The thesis work may include:

• Analysing selected EMS test cases, FMEA information and existing engineer-written test scripts.
• Investigating how AI can convert structured test cases into executable HIL test scripts.
• Developing or evaluating a proof of concept for AI-assisted test-script generation.
• Developing INCA-FLOW workflows for test execution, measurement, data collection and result evaluation.
• Comparing AI-generated scripts with engineer-written scripts.
• Evaluating correctness, completeness, test coverage, traceability, repeatability and engineering effort.
• Identifying limitations and recommending methods for reviewing and improving the automated workflow.

Selected tests may be executed in a HIL, vehicle or laboratory test environment, depending on the available setup.

The intended workflow is:

The final scope will be agreed with the student based on their background, interests, available tools and test environments.

Expected results

The expected results include:

• A proof of concept for AI-assisted EMS test-script generation.
• Automated INCA-FLOW workflows for selected test cases.
• An evaluation of the combined workflow against the current manual approach.
• Recommendations for improving and scaling automated EMS test development.

Education and profile

Master's student in Computer Science, Software Engineering, Electrical Engineering, Automotive Engineering, Embedded Systems, Mechatronics or a related field.

Experience or interest in the following is beneficial:

• Python or other programming languages
• Artificial intelligence and machine learning
• Automated software testing
• CAN and automotive communication
• Embedded systems

We are looking for an analytical, structured and curious student who can work independently and collaborate with engineers.

Practical information

Number of students: One or two

Start date: To be agreed

Duration: Approximately 20 weeks

Scope: 30 credits / 30 ECTS

Location: Södertälje, Sweden

Workplace: On-site or hybrid, depending on the test activities

Contact and application

Hiring manager: Kajsa Forslund, Head of TGRPSTE System Test Base Enginer kajsa.x.forslund@scania.com

Your application must include a CV, personal letter and transcript of grades. Please describe your relevant experience and interest in AI, automated testing, EMS or automotive systems.

A background check might be conducted for this position. Interviews may be held continuously, and the recruitment may close before the application deadline. The thesis may involve confidential technical information, and publication conditions will be agreed with the student and university.

Requisition ID: 34964

Number of Openings: 1.0

Part-time / Full-time: Full-time

Permanent / Temporary: Temporary

Country / Region: SE

Location(s):
Södertälje, SE, 151 38

Required Travel: 0%

Workplace: Hybrid