Master Thesis: Optimisation of lateral performance of BEVs

Battery electric heavy vehicles appear with different axle and actuator configurations. The cost neutrality, modularity and flexible features of electric machines allows physical installation on different axles. Distributed powertrain architecture has shown improvement in driving range, vehicle performance features and safety [1] [3]. In [1] [2], the concept of steer by propulsion (torque vectoring) for a 4X4 truck, with distributed propulsion was explored and their effects of vehicle performance were analysed.

Suitable background

The thesis work will include vehicle dynamics, control theory (MPC) and real time optimization. Interest in programming of real time systems is seen as a merit. The thesis is recommended for one or two students with control system major with good mathematical skills.

Description of thesis work
The aim with Master thesis is to extend on the previous work in [1] of steer by propulsion for a different vehicle configuration 6X4 (Tag axle with steering and propulsion).
  • Exemplify the influence of torque vectoring on lateral vehicle performance for low speed and high-speed operations on different road friction conditions. Based on the results formulate the use cases where torque vectoring can improve and decrease lateral performance for the specific vehicle configuration.
  • Torque vectoring algorithm – Modelling the dynamics and enhancing the MPC algorithm with axle level side slip control constraints, defining stable boundaries for safe operation of the vehicle, non-linear constraints etc. Comparison with the yaw control scheme implemented previously.
  • Analysis the combined influence of power steering and torque vectoring on vehicle lateral performance. Evaluation of the total power consumption would also be beneficial.
  • Proposal of a modular scheme of the algorithm of axle control to aid distributed e-axles concept, which could be extended to other vehicle configurations like 4X4, 6X6, 8X4, 8X8 etc.
[1] Persson.J, Åkesson.J, “On torque vectoring to improve steering predictability while minimising power loss in heavy electric vehicles using model predictive control”, Master Thesis, Chalmers University of Technology, June 2023.
[2] Fahlgren. E, Söderberg. D, “Torque vectoring using e-axle configuration for 4WD battery electric truck utilizing control allocation for motion control and steer by propulsion”, Master Thesis, Chalmers University of Technology, June 2022.
[3] Janardhanan S., Laine L., Jonasson M., and Jacobson B., and Alaküla M., “Concept design of electric cruise and startability axles for long haul heavy vehicles to maximise driving range”, Vehicle Propulsion and Power Conference, October 2021.
[4] Janardhanan S, “On power loss minimisation for heavy vehicles with axle-wise and modular electrical propulsion and friction braking”, Licentiate thesis, Feb 2023.

Thesis Level: Master

Language: English

Starting date: Jan 2024

Number of students: 2


Sachin Janardhanan, Vehicle analyst,
Jonas Persson, Function developer,
Mats Jonasson, Senior Researcher - Chalmers University,

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