Data-Driven Optimal Power Flow Management in an Electric Dual-Drive Topology for Vehicle Electrification

The limited operating range on a single charge can be seen as an important detriment to contemporary vehicular technology, necessitating regular charging of the battery pack. Due to the high load variability during driving, incorporating two different electric motors in the drive can provide significant improvements in terms of energy consumption. A data-driven approach towards optimal power flow management in such configuration is proposed. Computationally expensive dynamic models are translated into an equivalent power flow-based representation, taking into account peak start-up losses. Optimal synchronization of both machines is then assessed over a given drive cycle, providing an optimal actuation policy for all embodied subsystems. Modifications to a standard dynamic programming formulation are introduced, reducing the computation time by a factor 125. The dual-drive topology furthermore offers the capability of cutting down energy consumption by 19.9%. Notable range extensions can thus be achieved by intelligently formulating and tackling the power flow management problem in a dual-drive topology.