Modeling the dynamic behavior of electrical machines involves several fields of physics, such as electromagnetics, electronics, mechanics, thermodynamics and acoustics. Multi-physics lumped models are applied to an inverter-fed permanent magnet synchronous machine. These models are coupled and fully parameterized to optimize the machine for traction applications. A particle swarm optimization algorithm is used to obtain general tendencies and different design rules. The objective is to provide a decision-making tool using lumped models to design permanent magnet synchronous motors. In this paper, we focus on electromagnetic noise, and average and ripple electromagnetic torque. The magnetic model, a permeance network, provides a good compromise between accuracy and computing time.