Thesis worker - Look Ahead Energy - Optimal Control Of An Integrated Thermal Management System

Master Thesis worker 30hp - Look-Ahead Energy-Optimal Control of an Integrated Thermal Management System for Battery-Electric Heavy-Duty Vehicles

Introduction

Thesis work is an opportunity to work closely with Scania and build relationships for the future. Many of today’s employees began their Scania careers with a degree project.

Background

Thermal management consumes a significant amount of energy in a battery-electric heavy-duty vehicle, particularly during cold starts, fast charging, high-load driving, and overnight cab heating. Conventional controllers largely react to current temperatures and fixed thresholds. Information about the route, expected driving demand, charging plans and ambient conditions could instead help the vehicle prepare for future heating and cooling needs.

For example, the vehicle could pre-cool the battery before a demanding drive or use available waste heat before switching on an electric heater. Waste heat from power electronics could also be stored temporarily in the cab coolant circuit and used to warm the battery during a later stop.

These decisions must be made at system level. Using heat in one part of the vehicle can reduce the thermal margin available elsewhere, and moving or rejecting heat also consumes energy. A look-ahead controller must account for these interactions while respecting temperature and component limits.

Objective

The objective is to develop and evaluate a predictive strategy for coordinating the vehicle’s integrated thermal-management system. The thesis should:

· describe the relevant thermal circuits, operating modes and available control actions;

· develop and validate a reduced-order model suitable for look-ahead control;

· compare the predictive strategy with a reference rule-based controller across representative driving, charging and parking scenarios;

· quantify when heat recovery, temporary heat storage, electric heating, heat-pump operation and heat rejection are beneficial; and

· assess the effects of forecast errors and model mismatch, as well as the feasibility of real-time implementation.

Job description

You will investigate how forecasts can help the vehicle decide when to heat, cool, recover, store or reject heat. You will build a reduced-order model of the coupled thermal system and develop a supervisory controller that plans its operation while maintaining required temperature and safety limits.

You will evaluate the approach in scenarios such as cold starts, uphill driving, fast charging and planned stops. An important part of the work is to investigate whether waste heat stored in the cab coolant circuit can reduce later battery-heating energy. You will compare the results with the reference controller and explain both the scenarios that benefit from look-ahead control and those that do not.

Finally, you will assess how sensitive the strategy is to inaccurate forecasts and model errors, define a fallback when a planned solution is infeasible, and identify any system or measurement limitations that would need to be addressed before further development.

Education/program/focus

Indicate education, program or focus:

Number of students: 1

Start date for the thesis work: 1st of February 2027

Estimated time required: 5 month

Contact persons and supervisors

Contact Name: Göran Lissel Function: Head of TGRBTEA – Electrification Management control – Thermal & Aux

Phone: +46 8 553 51937

Mobile: +46 70 086 0984 e-Mail: goran.lissel@scania.com

Supervisor Name: Karim Mohammed Razaul

Function: Software Development Engineer – Thermal & Aux

Mobile: +46767225137 e-Mail: mohammed.razaul.karim@scania.com

Application:

Your application must include a CV, personal letter and transcript of grades

A background check might be conducted for this position. We are conducting interviews continuously and may close the recruitment earlier than the date specified.

Publication date from - to.

2026-10-22 – 2026-11-22