Range prediction and extension for automated electric vehicles with fail-operational powertrain: Optimal and safety based torque distribution for multiple traction motors

With the introduction of robocabs and automated shuttles new requirements for vehicle powertrain arise requiring fail-operational system behavior. Redundancy in powertrain components can be used for the increase of driving efficiency, but requires also new strategies for controlling powertrain topologies with independent traction batteries. This paper presents a new concept and algorithm for the optimal torque distribution based on multi-objective optimization problem. The first objective of the optimization problem is to increase the driving energy efficiency by torque distribution between front and rear axle as well as between left and right side motors. A symmetrical discharge of the independent batteries is considered as a second objective. Using the runtime powertrain diagnostics, the torque distribution strategy covers also possible failure case operation. An optimal torque distribution profile as well as required propulsion energy are predicted for the entire driving cycle online. This information is then used for safety based range extension allowing to arrive at the safest possible location for the passengers also in case of a failure. Simulation results for different normal and failure case scenarios show a significant increase of driving efficiency while ensuring symmetrical discharge of the independent traction batteries.