Vehicle Motion Control Allocation Including Tire Wear Minimization

Tire wear is a major source of microplastic emissions, adversely affecting soil, water, air quality, and ecosystems, while also representing a non-negligible operational cost for road vehicles. This paper proposes a unified, monetary-cost-based control allocation framework for distributed-drive electric vehicles that jointly minimizes electric energy consumption and tire wear. Both objectives are expressed in a common economic unit (e.g., cost rate per time or distance), enabling explicit and transparent trade-offs between propulsion efficiency and tire wear within a single optimization problem. A mixed-integer, optimization-based control allocation strategy is developed to distribute wheel forces and motor torques across multiple axles and wheels, implicitly managing tire slip while prioritizing actuators based on both electrical efficiency and wear-related economic costs. To enable wear-aware control, an empirical tire wear model is introduced that accounts for longitudinal and lateral slip contributions and captures axle-specific wear behaviour. The model is calibrated using real vehicle measurement data and extends existing slip-based wear formulations. Simulation results demonstrate that vehicles equipped with multiple driven axles-particularly heavy-duty electric vehicles-benefit from cost-aware torque distribution, achieving a more balanced utilization of driveline components. Across different driving cycles, the proposed approach reduces the combined cost of electrical energy consumption and tire wear on average by 2.7% and up to 6$\%$ compared to energy-focused control allocation strategies.