This work presents a novel abc-based model applicable to surface-mounted permanent magnet AC (SM-PMAC) machines with sinusoidal and non-sinusoidal back-emf. It is capable of predicting the electromagnetic performance metrics such as torque waveforms, machine inductances, flux linkages and back-emf. The closed form expressions of the model, which can be evaluated with a high computational efficiency, are derived from basic geometric and winding parameters. Validation of the model is carried out numerically and experimentally with a very good match in results. Finally, the computational efficiency of the model is highlighted by considering a multi-objective evolutionary optimization design of SM-PMAC machine with a relatively large number of design parameters, where results are presented and discussed.