Minimising operational cost while ensuring safe motion for heavy vehicles with modular electric axles

Doctoral thesis, 2026

The electrification of heavy commercial vehicles offers opportunities beyond replacing conventional powertrains with batteries and electric machines. In particular, electric axles enable propulsion, braking, and motion control to be distributed and coordinated across the vehicle. This thesis investigates how modular electric axle powertrains can be designed and controlled to reduce operational costs while maintaining safe, robust, and predictable vehicle behaviour.

A modular powertrain architecture is proposed in which different axles or axle groups can be assigned distinct functions. A dedicated cruise axle is tailored for efficient steady-state highway operation, while a startability axle provides high traction at low speeds and on demanding grades. The joint selection of motor ratings and gear ratios, together with coordinated axle operation, is investigated to identify powertrain configurations that satisfy vehicle motion requirements while improving energy efficiency and driving range.

Building on this modular electric axle architecture, the thesis then addresses the coordination of multiple electric powertrains and friction brakes. Control allocation methods are developed to distribute wheel-torque demands among redundant actuators while achieving the requested vehicle motion and minimising operational losses. In contrast to conventional heuristic weighting, the proposed formulations represent actuator losses as physically based cost rates, providing a direct connection between control decisions and vehicle operating cost. Tyre-friction constraints are incorporated to account for the coupled longitudinal and lateral demands during vehicle manoeuvres.

For demanding driving conditions, vehicle-level motion control is combined with lower-level actuator coordination. A model predictive control-based force generator regulates longitudinal and yaw responses within prescribed operating limits, while subsequent control allocation distributes the required forces among the available actuators. The developed methods are evaluated under conditions including low-friction surfaces and combined braking and cornering, with emphasis on stability, path tracking, and predictable vehicle response.

Finally, the optimisation framework is extended beyond energy consumption by incorporating tyre wear alongside actuator losses. The results demonstrate that modular electric axles, combined with optimisation-based design and control, can provide new means of improving energy efficiency, reducing operating costs, and maintaining safe and predictable motion in heavy electric vehicles