Future electric vehicle (EV) traction motors require high power density, high efficiency, wider speed range, lower torque ripple, and lower weight and volume. Hairpin (HP) windings are a favored option for traction motor windings; however, their efficiency tends to degrade due to AC losses at high operating speeds. Therefore, HP winding designs that offer higher EM performances, including higher efficiencies in the full operational region, and lower winding weight are necessary for future EVs. In this regard, this paper investigated the arrangement of the HP windings within the stator slot, considering different phases, and utilized an improved winding function-based model and analytical AC loss estimation to propose an optimal concentric winding (CW) configuration for a commercially available 140 kW, 15000 rpm induction machine (IM). According to the results, except for the similar torque capacity in the maximum torque per ampere (MTPA) region, the proposed optimal CW IM configuration demonstrated superior overall performance and characteristics, including output power, torque, and efficiency, across a wide speed range; both MTPA and field weakening regions compared to the IM with distributed windings (DW). Additionally, the proposed CW configuration reduces winding weight by 12.96% compared to the IM with conventional DW, which is a significant advantage in terms of weight and volume reduction.

Multi–motor electric vehicles (MMEVs) have been identified as a solution to the inherent disadvantages of current electric vehicles (EVs) in energy consumption and driving range. These improvements are achieved by operating each motor in its peak efficiency region, as appropriate for the driving scenario. However, an MMEV’s increased efficiency is highly dependent on the sizes of the motors. Existing studies focus mostly on improving overall system efficiency through improved energy management control strategies. The few studies that do seek to size the powertrain, introduce additional components, and alter the power capabilities of the vehicle, often resulting in increased cost and reduced dynamic performance. This paper investigates electric motor sizing methodologies used in these studies and restructures their implementation without adding new components to the existing powertrain. The optimal torque split ratio is determined using a Non–Dominated Sorting Genetic Algorithm (NSGA–II) for achieving improved overall system efficiency while preserving dynamic performance. Furthermore, using the proposed methodology, the optimal torque–split ratio is determined for a 2021 Ford Mustang Mach–E EV case study. Improved system efficiency through the optimization does not require redesign of the Mach–E’s powertrain as no additional components are introduced thus avoiding additional manufacturing costs.

As a computationally efficient tool for the machine’s steady–state performance prediction, equivalent circuit model (ECM) of induction machines (IMs) has been an established option in literature. The results and performance predictions obtained from ECM are significantly affected by: (i) the leakage reactances as the function of the geometry of the machine’s rotor and stator slots (ii) the skin, proximity, and slotting effects and (iii) the saturation of the core. Simultaneous consideration of these effects has been ignored in conventional ECM of IMs for simplicity. In this paper, a novel permeance-based ECM is proposed and developed based on the dimensions of the stator and rotor slots to simultaneously incorporate leakage zig–zag, tooth top and overhang reactances into modeling steps. Saturation, slotting, proximity and skin effects are also fully taken into account to improve the accuracy of the modeling and performance prediction compared to the conventional ECM. Finite element analysis is used to verify the accuracy of the proposed ECM when compared to the conventional ECM based on the steady state performance characteristics such as torque, electromagnetic loss, and efficiency predictions.

Asymmetrical star-delta winding interior permanent magnet synchronous motor (IPMSM) is introduced as a capable option in supporting higher torque and lower torque ripple characteristics compared to the symmetrical star-delta winding IPMSM. This is at the expense of having higher radial electromagnetic (EM) force and potential vibration-related concerns including high acceleration. EM force and vibration reduction in the asymmetrical star-delta winding IPMSMs have not been well addressed in the literature so far. In order to improve the EM force and acceleration characteristics of the asymmetrical star-delta winding IPMSM while keeping its developed torque within the desired ranges, various stator and rotor geometrical parameters are defined and are changed individually. A sensitivity analysis is utilized to introduce the most effective geometrical design variables for the highlighted objectives. The reduction in the EM force, through the Maxwell-Stress tensor method, and the acceleration on the outer surface of the motor housing of the improved asymmetrical star-delta winding IPMSM structure over a base asymmetrical star-delta winding IPMSM model are investigated and reported via EM and structural simulations.

Induction machines are a popular choice for tractive applications due to inherent cost savings and performance benefits driving industry to search for an optimal rotor bar design. Induction machines suffer from low torque densities due to larger size and increased losses incurred in the rotor bars making these the performance objectives to be improved through optimization. Communicating through objective functions (OFs), a performance model to rapidly evaluate design parameters coupled with genetic algorithm (GA) can be used to produce an optimal rotor bar; however, conventional OF modeling may introduce function bias or complex coefficient calculations leading to dominated objectives, stalling and premature convergence leading to an unoptimized solution. In this paper, the rotor bar of a squirrel cage induction machine (SCIM) is modeled by a permeance based equivalent circuit model (ECM) creating a link between the rotor slot geometry and equivalent circuit parameters. The model considering skin and slotting effect as well as slot, zigzag, tooth top and overhang leakage reactance effects coupled with a multi- objective GA through novel hyperbolic tangent based OFs to optimize the rotor bar geometry. The optimal rotor bar shape proposed offers increased output torque and reduced total machine losses resulting in a higher operating efficiency.

Weight, torque, and efficiency of induction machines (IMs) are directly affected by their stator winding configuration. To evaluate this, this paper presents the electromagnetic (EM) performance comparison of four squirrel cage IMs using different winding configurations, namely, integral slot distributed winding (ISDW), fractional slot concentrated winding (FSCW), integral slot concentrated winding (ISCW) and integer slot concentric winding (ISCW2). The same active volumes with identical electric and magnetic loading constraints were assigned for all IMs with the same materials. The weight, torque, EM losses, and efficiency values in both maximum torque per ampere (MTPA) and field weakening regions were assessed. The results indicate that the ISCW2 IM possessed the best overall performance and characteristics in terms of torque, torque density and efficiency in a wide speed range among the investigated IMs; except its lower developed torque compared to the ISDW IM in MTPA region. To resolve this issue, a winding layout optimization was carried out via a winding function-based analysis to improve the torque performance of the ISCW2 IM in MTPA region as well.

This paper proposes a novel gradient descent based maximum torque per ampere (MTPA) control algorithm for interior permanent magnet synchronous machines (IPMSMs) by using the measured speed harmonics. The proposed approach does not require machine parameters and thus is not influenced by the machine and drive nonlinearities. Hence, the proposed approach can ensure a robust MTPA control under different loading conditions. Specifically, in the proposed approach, a small q-axis harmonic voltage is injected into the machine to induce a small harmonic component in the machine speed. Based on the PMSM torque equation, the mathematical relation between the induced speed harmonic and the output torque is derived, which shows that the magnitude of the induced speed harmonic is proportional to the output torque of an IPMSM. Therefore, the speed harmonic is explored to seek the MTPA angle, in which the MTPA angle is found when the speed harmonic magnitude is maximized. In particular, the gradient descent algorithm is employed to detect the MTPA angle, which is computationally efficient and converges quickly. The proposed approach is evaluated with both simulations and experiments based on a laboratory IPMSM drive system.

Accurate information of permanent magnet (PM) flux linkage is of significance to high-performance control and condition monitoring of permanent magnet synchronous machines (PMSMs). During machine operation, the PM flux linkage can vary due to temperature rise and saturation. Thus, this paper investigates how temperature rise and saturation influence the PM flux linkage under different operation conditions. Under no-load condition, the PM flux linkage is estimated from the back-EMF test. Under load condition, a speed harmonic based PM flux linkage estimation approach is proposed, in which the PM flux linkage is estimated from the speed harmonic without requiring machine parameters. Thus, the proposed estimation approach is not affected by the machine and drive nonlinearities and thus can guarantee the estimation performance. The proposed approach is applied for PM flux linkage estimation under various loads and temperatures to investigate the influence of temperature rise and saturation on the PM flux linkage. Experimental results demonstrate that the PM flux linkage under no-load is larger than that under load due to magnetic saturation, the PM flux linkage under load decreases as the saturation level increases, and the one under both load and no-load decreases linearly as the PM temperature increases.