Multi-objective optimization of electric vehicle powertrain using scalable saturated motor model

This paper presents a methodology for optimal sizing of the electric powertrain based on vehicle level objective functions. The design variables gear ratio, rated torque and rated speed of the motor are size dependant on the objective functions energy demand over a driving cycle, powertrain mass, and high speed gradeability. Multi-objective optimization handles these conflicting objective functions simultaneously and produces the Pareto-optimal solutions in both objective function and design variable domains. The novelty of the proposed approach is the utilization of analytical scalable saturated flux-linkage and loss motor model which is used for fast and accurate calculation of drive cycle energy consumption and motor mass. The concept is demonstrated on an example of in-wheel motor electric powertrain with four synchronous permanent magnet outer rotor machines.