Master Thesis: Power management of BEVs with distributed propulsion

Battery electric heavy vehicles (BEVs) usually have limited driving range mainly because limitations of battery capacity and charging infrastructure. In addition, BEVs also appear with multiple axles and actuator configurations. Hence, all approaches to improve energy efficiency are being explored. Among these approaches, one method is by exploiting the flexibility, cost neutrality and modularity of electric machines allowing physical installation on different axles or wheels and thereby utilising the overactuation capabilities. Distributed powertrain architecture using optimal control has shown potential in balancing driving range, vehicle performance features and safety [1] [3]. In [2], different algorithms to optimally distribute control effort among the actuators instantaneously while minimising power losses were explored conceptually. An energy management strategy for a multi-motor passenger vehicle using mixed integer programming is also explored in [4].


Suitable background


The thesis work will include vehicle dynamics, control theory 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 main goals of this master thesis are the following:
Evaluate the energy savings possible for BEVs (4X4 Tractor) using distributed propulsion and power loss minimisation algorithm including idle / clutch related losses.
Develop a model framework and algorithm for mixed integer programming using MPC for the optimal control exploiting the advantage of minimisng idle and other losses (rolling resistance, slip losses etc.). Verify the framework using relevant test cases representing vehicle application scenarios.
Propose a strategy to control the switching of actuators namely electric machine or clutch for actual vehicle operations and real-time application.
Present a modular scheme of the algorithm of axle control to aid distributed e-axles concept, which could be extended to other vehicle configurations like 6X4, 8X4, 8X8 etc.

[1] 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.
[2] Janardhanan S, “On power loss minimisation for heavy vehicles with axle-wise and modular electrical propulsion and friction braking”, Licentiate thesis, Feb 2023.
[3] 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.
[4] A. Ganesan, N. Murgovski, D. Yang and S. Gros, "Real-Time Mixed-Integer Energy Management Strategy for Multi-Motor Electric Vehicles," 2023 IEEE Transportation Electrification Conference & Expo (ITEC), Detroit, MI, USA, 2023, pp. 1-6, doi: 10.1109/ITEC55900.2023.10186957.


Thesis Level: Master
Language: English
Starting date: Jan 2024
Number of students: 2
Tutor:
Sachin Janardhanan, Vehicle analyst, sachin.janardhanan@volvo.com
Esteban Gelso, Expert control engineer, esteban.gelso@volvo.com
Prof. Bengt Jacobson, Chalmers University, bengt.jacobson@chalmers.se - (Academic supervisor)


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