A parameter-optimised rule-based control strategy for front-rear torque vectoring in electric vehicles with multiple motors and disconnect clutches

Applying a proper front/rear torque distribution in electric vehicles with multiple motors leads to battery energy consumption reduction. The energy efficiency can further be enhanced by equipping the e-motors with disconnect clutches, because the drag loss can be avoided by disconnecting and stopping the inactive motors. In this paper, a practical parameter-optimised rule-based (RB) torque vectoring control strategy is proposed, which manipulates front/rear torque distribution ratio and clutch state control inputs to minimise the energy consumption. The strategy accounts for clutch connect transient losses and a requirement on limiting the dog clutch switching frequency for improved durability. It relies on a set of two-wheel drive/all-wheel drive switching curves with associated hysteresis and corresponding control rules. The RB strategy is verified against a more sophisticated model predictive control (MPC) strategy and a globally optimal, dynamic programming (DP)-based offline optimisation benchmark. The DP results reveal that the energy consumption reduction achieved through the disconnect clutch functionality is around 6%, on top of up to 5% reduction achieved by torque distribution itself. The RB strategy closely approaches the DP benchmark, it outperforms the MPC strategy fed by realistic, error-prone vehicle velocity predictions, and is robust with respect to driving cycle features.