## 1 Introduction  
A permanent magnet synchronous machine (PMSM) has the merits of high torque density, high efficiency, and dynamic performance [1; 2; 3; 4; 5]. It has been widely applied in manufacturing and the electric vehicle (EV) driving system [6; 7; 8; 9], and traction applications [10]. In this paper, a 130 kW 12-pole/72-slot internal PMSM (IPMSM) is designed for traction vehicles applied in port transportation, where a heavy-load torque-output capability and good start performances are required. In this paper, more attention is paid to the torque ripple, since it can generate vibration and radial electromagnetic force fluctuations [11; 12; 13], and consequently degrade the reliability and stability of the machine's system, and the start and brake performances of the traction vehicle, which are critical to port transportation.  
The methods to reduce the motor torque ripple are mainly based on optimizations of motor design and control strategy, respectively. In reference [14], a PMSM model was established, and motor parameters were studied by finite element analysis (FEA). The structural parameters which affect the maximum efficiency of PMSMs were obtained. A training sample method based on a depth learning neural network algorithm was proposed to analyze the PMSM output characteristics. This method can effectively narrow the time required for performance analysis and optimization. In order to reduce torque ripple, a stator with an odd number of slots per pole pair and an IPM rotor with multiple layersof flux barriers were studied in [15]. It has been demonstrated that torque ripple can be reduced to less than 5%, by using a stator with an odd number of slots per pole pair, and an IPM rotor with optimized barrier configurations, without using stator/rotor skewing or rotor pole shaping. In [16], a non-parametric optimization technique to find a new magnetic circuit which minimized a torque ripple and maximized the driving torque of IPMSM was examined. Reference [17] proposes a new optimization method by employing hybrid rear-earth and Ferrite magnets. The torque performance of the optimal rotor design provided a decrease in the torque ripple from 56.2% to 2.8% by being consistent with almost 20% increases to the average torque. The computationally efficient FEA is introduced in [18], and after optimization of the rotor topology, a 37% increase of the average torque was obtained. In addition, the cogging torque was significantly reduced when the machine was optimized. In reference [19], a novel technique was adopted to reduce cogging torque and torque ripple by using an asymmetrical V-type rotor configuration; the proposed model contains the peak-to-peak value 0.43 Nm, which is reduced by 66.67%, compared with that of the conventional version (1.29 Nm). Moreover, a harmonic current optimization design method based on experimental harmonics was proposed in reference [20]. By injecting two test signals into the machine, the optimal harmonic current can be found by comparing the two schemes to obtain the minimum mechanical loss and torque ripple. The proposed scheme has advantages in computational efficiency and simple implementation. Along with the optimization of topologies, the advanced control schemes were also introduced to reduce the torque ripple of the permanent magnet machines [21; 22; 23; 24].  
The main contribution of this paper to give a comprehensive optimization of the rotor topology, considering multi-variable parameters. The influence of the rotor surface shape, the location of the permanent magnet and the iron bridge on the torque ripple were considered. The sensitive factors affecting the output torque ripple of the machine were obtained. Finally, the prototype was manufactured and tested to validate the FEA results.