Mohammad Hossain Mohammadi

A Computationally Efficient Algorithm for Rotor Design Optimization of Synchronous Reluctance Machines

A generalizable algorithm is proposed for the design optimization of synchronous reluctance machine rotors. Single-barrier models are considered to reduce the algorithms computational complexity and provide a relative comparison for rotors with different slots-per-pole combinations. Two objective values per sampled design (average and ripple torques) are computed using 2-D finite-element analysis simulations. Non-linear regression or surrogate models are trained for the two objectives through a Bayesian regularization backpropagation neural network. A multi-objective genetic algorithm is used to find the validated Pareto front solutions. An analytical ellipse constraint is then suggested to encapsulate optimal solutions. Compared with a direct sampling approach, this restriction captures an optimal region within the double-barrier space for further torque ripple reduction.

Design and optimization of fractional slot concentrated winding permanent magnet machines for class IV electric vehicles

The design, optimization and application of a number of surface mounted fractional slot concentrated winding (FSCW) electric machines for application to Class IV electric vehicles have been considered. Four FSCW motors with nominal power ratings of 50, 65, 75 and 100 kW have been designed. The motors were optimized using a novel multi-objective optimization strategy which allows a large numbers of objectives to be considered while ensuring computational efficiency and Pareto optimality. Vehicle simulations were carried out using the optimized motors for some typical drive cycles. The gear ratio of the drive train was optimized for each motor with respect to the drive cycle and the vehicle performances were calculated. The methodology and results presented provide a novel and improved framework for considering the trade-offs between the motor size, gear ratio and vehicle performance for Class IV and other vehicle classes.

Comparison of fractional-slot concentrated winding and PM-assisted synchronous reluctance motors for class IV electric vehicles

The design and comparative analysis of three 100 kW motors, a fractional-slot concentrated winding machine (FSCW) surface mounted permanent magnet and two permanent magnet-assisted synchronous reluctance machines (PMa SynRMs), were considered for a Class IV step van electric vehicle application. The electromagnetic, thermal, demagnetization, and acoustic performances of each machine have been presented as well as vehicle dynamic simulations for various urban drive cycles. The results show that all three motors are suitable for a Class IV electric vehicle. The advantages and the disadvantages of the machines with respect to their application for Class IV vehicles have been highlighted in this work.

Human motion energy harvesting by design of handheld Linear PM Synchronous Generator

The authors present the experimental procedure to build a high power handheld-sized Linear Permanent Magnet Synchronous Generator (LPM SG) powered by human motion. This generator produces maximum energy for charging small-scale electronic devices such as mobile phones. Two different generator prototypes are compared through the presented theoretical and experimental results based on parallel charging of two 5V Li-ion battery supplies. The systematic choice of rare earth material PM, magnetization direction, solenoid wire diameter and number of turns have increased the generated power by more than tenfold between the discussed prototypes.

A Computational Study of Efficiency Map Calculation for Synchronous AC Motor Drives Including Cross-Coupling and Saturation Effects

After designing and optimizing an electric machine, efficiency maps are needed to predict a vehicle’s performance in a dynamic simulation. Calculating efficiencies at various torque and speed points, however, requires prior knowledge of the input excitation conditions, such as the current magnitude and advance angle, in an electromagnetic finite-element analysis simulation. Hence, this paper derives and uses nonlinear motor control equations (MTPA, FW, MTPV) in the study of efficiency map calculation while accounting for both saturation and cross-coupling effects. Two synchronous ac motors are considered in this paper, including the 2010 Prius IPM and a PM-assisted synchronous reluctance machine, with all procedure steps outlined in detail.

A computational study of efficiency map calculation for synchronous AC motor drives including cross coupling and saturation effects

This work studies the calculation of efficiency maps for synchronous motors using nonlinear flux linkages. The computational effort needed to find a reasonably accurate map is investigated along with comparisons of different fitting functions.

Analysis and design of electrical machines with material uncertainties in iron and permanent magnet

Purpose Manufacturing processes, such as laminations, may introduce uncertainties in the magnetic properties of materials used in electrical machines. This issue, together with magnetization errors, can cause serious deterioration in the performance of the machines. Hence, stochastic material models are required for the study of the influences of the material uncertainties. The purpose of this paper is to present a methodology to study the impact of magnetization pattern uncertainties in permanent magnet electric machines. Design/methodology/approach The impacts of material uncertainties on the performances of an interior permanent magnet (IPM) machine were analyzed using two different robustness metrics (worst-case analysis and statistical study). In addition, two different robust design formulations were applied to robust multi-objective machine design problems. Findings The computational analyses show that material uncertainties may result in deviations of the machine performances and cause nominal solutions to become non-robust. Originality/value In this paper, the authors present stochastic models for the quantification of uncertainties in both ferromagnetic and permanent magnet materials. A robust multi-objective evolutionary algorithm is demonstrated and successfully applied to the robust design optimization of an IPM machine considering manufacturing errors and operational condition changes.

A neural network based surrogate model for predicting noise in synchronous reluctance motors

This paper proposes a neural network (NN) based noise prediction model for electric machines, applied to the case of synchronous reluctance motors (SynRMs). The natural frequencies of various vibration modes for a SynRM stator with generalized tooth geometry and slot numbers have been obtained using structural FEA based computations and then used to build a NN based surrogate model. The accuracy of the surrogate model has been tested and applied to predict the noise level in SynRMs. Also, varying trends in the noise levels for single-barrier SynRMs have been analyzed as a function of the rotors flux carrier and barrier widths using the natural frequency prediction model.

Finding optimal performance indices of synchronous AC motors

The design optimization of electrical machines involves both design and control variables. Finding optimal control variables, however, requires the solution of another optimization problem. Due to high computational cost, the design process is usually carried out with suboptimal values which may lead to suboptimal designs. Thus, in this paper, we propose an optimization framework that emulates the control strategy, in order to find optimal performance indices for each candidate solution. Both the efficacy of the proposed method and a comparison among different “control strategy emulators” are demonstrated for the rotor design optimization of an interior permanent magnet motor and a synchronous reluctance motor.

Incorporating Control Strategies Into the Optimization of Synchronous AC Machines: A Comparison of Methodologies

This paper presents a comparison of methodologies to incorporate control parameters into the design optimization of synchronous ac machines. A metric is used to quantify the conflict level between the average torque and torque ripple for an interior permanent magnet machine and a synchronous reluctance machine. Using 2-D finite-element analysis simulations, the results demonstrate that the traditional approach of lumping the control and design variables together can lead to poor designs, especially when the conflict is high.