Internship Model based / Data Driven Control Strategies For Vehicle Motion Control

Job description

Internship Model based / Data Driven Control Strategies For Vehicle Motion Control Job ID 2026-5415 Belgium Brussels (Zaventem) R&D Internships About this job This internship involves developing an integrated motion control system for multi-actuated vehicles. You will design a high-level optimal controller, such as MPC, combined with a control allocation layer to coordinate actuators like brakes and steering. The role includes modeling vehicle dynamics, handling constraints, ensuring real-time feasibility, and validating performance in simulation using MATLAB/Simulink and Python to improve stability, robustness, and overall vehicle performance.

Get to know your team and responsibilities Team/division description The internship will be developed in TME R&D, Chassis group.

Chassis engineering division is responsible for the: Development of Chassis systems and components (Brake, Steering, Suspension, Tyre, Shift, Pedals, …) for local production, utilising European technologies and suppliers to achieve the highest driving performance and quality standards at competitive cost. Vehicle dynamic performance development through simulation and testing of systems and vehicles. Investigation and Predevelopment of new European technology for automotive chassis systems and components.

Research and application of state-of-the-art methodologies for chassis systems and chassis electronic systems’ design and validation, enabling most competitive performance and efficient development processes while securing our quality and safety standards. We are inspired by the Toyota Way precepts, and we challenge to provide final customers with best quality products with the continuous improvement mindset. Your project Integrated Optimal Motion Control and Allocation for Multi-Actuated Vehicles Objective The objective of this project is to develop an integrated vehicle motion control framework for a multi-actuated ground vehicle, based on optimal control and control allocation techniques, with explicit consideration of real-time implement-ability.

Scope and Contributions The work aims to: Investigate and critically review the state-of-the-art in vehicle motion control, including optimal control (e.g., MPC, MPPI), control allocation strategies, and integrated chassis control for multi-actuated systems Define a coherent control architecture combining to prioritize a high-level optimal controller for vehicle dynamics regulation but also lower-level actuator coordination and allocation layer.

Motion control architecture is to be compatible with both trajectory and manual drive inputs interfaces.

Formulate control strategies that explicitly account for: coupled vehicle dynamics (lateral, longitudinal, and roll) actuator constraints and redundancy stability and adherence limits Address real-time feasibility, including: model simplification and reduction strategies computational complexity analysis solver selection and timing considerations data driven approaches to control robustness and modelling

• Implement and validate the proposed framework in a high-fidelity simulation environment (potentially both offline and with DiLs), assessing: stability and performance improvements robustness to varying conditions (e.g., friction, manoeuvres) computational performance and real-time suitability
• Validate concept over multiple use cases (comfort, emergency, handling…) with necessary weight-scheduling through automations and pipelines to be developed.

Expected Outcome The internship is expected to deliver a system-level control framework demonstrating effective coordination of multiple actuators through optimal control and allocation, while ensuring practical feasibility for real-time automotive implementation. Who are we looking for? Your profile You are fluent in English (TME’s business language) You are student in last year of a Master’s degree in Mechatronics, Control Systems or related domain.

You have interest in Control Engineering, Vehicle Dynamics and Autonomous Vehicle systems. You have strong knowledge in Control Theory and Robust Control techniques as well in Dynamic and Vehicle Dynamics simulations and related tools (Matlab/Simulink, CarMaker and similar) You have strong coding skills (Python, Matlab) and highly knowledgeable in Data Science and Machine Learning. Knowledge on CAN protocol and CAN simulation with virtual prototyping (dSPACE) might be an asset.

You have good communication skills and can work in autonomous way within a multicultural team Starting date 1 September 2026 Duration 6 months Confidentiality Due to business requirement, not all performed projects can be reflected in the internship report. This issue needs to be discussed with candidate/school in advance. It is mandatory that applicants are students for the entire period of the internship. We can only accept students with an EEA or Swiss citizenship (not requiring a work permit or visa to be eligible to perform an internship in Belgium) Our offer We offer a dynamic multicultural work environment with broad opportunities to learn every day and exciting career pathways that help you explore different disciplines or areas of expertise.

Your benefits Flexible working hours and hybrid working (homeworking, 10 days from abroad); Company restaurant – Warm dishes, salads and desserts daily, including Japanese and traditional Belgian specialties, as well as a vegan/vegetarian option; Sport facilities – Tennis, squash, volleyball, football and softball pitches are available at various Toyota sites; Team building activities and other personnel related events; Programs to support your physical and social well-being.