In-wheel motor vibration control for distributed-driven electric vehicles:A review

Efficient, safe, and comfortable electric vehicles (EVs) are essential for the creation of a sustainable transport system. Distributed-driven EVs, which often use in-wheel motors (IWMs), have many benefits with respect to size (compactness), controllability, and efficiency. However, the vibration of IWMs is a particularly important factor for both passengers and drivers, and it is therefore crucial for a successful commercialization of distributed-driven EVs. This paper provides a comprehensive literature review and state-of-the-art vibration-source-analysis and -mitigation methods in IWMs. First, selection criteria are given for IWMs, and a multidimensional comparison for several motor types is provided. The IWM vibration sources are then divided into internally-, and externally-induced vibration sources and discussed in detail. Next, vibration reduction methods, which include motor-structure optimization, motor controller, and additional control-components, are reviewed. Emerging research trends and an outlook for future improvement aims are summarized at the end of the paper. This paper can provide useful information for researchers, who are interested in the application and vibration mitigation of IWMs or similar topics

Loss-minimizing control of synchronous reluctance motors — A review

This paper reviews state-of-the-art loss-minimizing control strategies for synchronous reluctance motors. Methods can be categorized as loss-model controllers (LMCs) and search controllers (SCs). For LMCs, different loss models and the corresponding optimal solutions are summarized. The effects of the core losses and magnetic saturation on the optimal stator current are investigated; magnetic saturation is a more important factor than the core losses. For SCs, different search algorithms are presented and compared. The SCs are evaluated based on their convergence speed, parameter sensitivity, accuracy, and the torque ripple caused by the search process.Peer reviewe

A general magnetic-energy-based torque estimator: validation via a permanent-magnet motor drive

This paper describes the use of the current–flux-linkage ($i{-}psi$ ) diagram to validate the performance of a general magnetic-energy-based torque estimator. An early step in the torque estimation is the use of controller duty cycles to reconstruct the average phase-voltage waveform during each pulsewidth-modulation (PWM) switching period. Samples over the fundamental period are recorded for the estimation of the average torque. The fundamental period may not be an exact multiple of the sample time. For low speed, the reconstructed voltage requires additional compensation for inverter-device losses. Experimental validation of this reconstructed waveform with the actual PWM phase-voltage waveform is impossible due to the fact that one is PWM in nature and the other is the average value during the PWM period. A solution to this is to determine the phase flux-linkage using each waveform and then plot the resultant $i{-}psi$ loops. The torque estimation is based on instantaneous measurements and can therefore be applied to any electrical machine. This paper includes test results for a three-phase interior permanent-magnet brushless ac motor operating with both sinusoidal and nonsinusoidal current waveforms

Adaptive Feedback Linearization Control of SynRM Drives With On-Line Inductance Estimation

This article proposes an adaptive input-output Feedback Linearization Control ( FLC ) techniques for Synchronous Reluctance Motor ( SynRM ) drives, taking into consideration the iron losses. As a main original content, this work proposes a control law based on a new dynamic model of the SynRM including iron losses as well as the on-line estimation of the static inductances. The on-line estimation of the SynRM static inductances permits to inherently take into consideration the magnetic saturation phenomena occuring on both axes. As a major result, it permits a null stator current steady state tracking error even with a proportional derivative controller. The estimation law is obtained thanks to a Lyapunov-based analysis and thus the stability of the entire control system, including the estimation algorithm, is intrinsically guaranteed. The proposed adaptive FLC technique, has been tested experimentally on a suitably developed test set-up, and compared experimentally with its non-adaptive versions in both tuned and detuned working conditions. Moreover, a sensitivity analysis of the performance of the adaptive FLC to the variations of the stator resistance at low speed has been made. Finally, an analysis of the effects of the iron losses on the control performance and stability at high speed in the field weakening region at medium/high loads has been made

Feedback Linearization Based Nonlinear Control of SynRM Drives Accounting for Self- and Cross-Saturation

This article proposes a nonlinear controller based on feedback linearization (FL) for synchronous reluctance motor (SynRM) drives which takes into consideration the magnetic saturation. The proposed nonlinear FL control based control technique has been developed starting from the theoretical definition of an original dynamic model of the SynRM taking into consideration both the self- and the cross-saturation effects. Such a control technique permits the dynamics of both the speed and axis flux loops to be maintained constant independently from the load and the saturation of the iron core in both constant flux and variable direct axis flux operating conditions. Finally, sensitivity of the performance of the proposed FL control versus the variation of the main motor parameters has been verified. The proposed technique has been tested experimentally on a suitably developed test setup. The proposed FL control has been further compared with the classic field-oriented control (FOC) in both constant flux and variable flux working conditions

Field Oriented Sliding Mode Control of Surface-Mounted Permanent Magnet AC Motors: Theory and Applications to Electrified Vehicles

Permanent magnet ac motors have been extensively utilized for adjustable-speed traction motor drives, due to their inherent advantages including higher power density, superior efficiency and reliability, more precise and rapid torque control, larger power factor, longer bearing, and insulation life-time. Without any proportional-and-integral (PI) controllers, this paper introduces novel first- and higher-order field-oriented sliding mode control schemes. Compared with the traditional PI-based vector control techniques, it is shown that the proposed field oriented sliding mode control methods improve the dynamic torque and speed response, and enhance the robustness to parameter variations, modeling uncertainties, and external load perturbations. While both first- and higher-order controllers display excellent performance, computer simulations show that the higher-order field-oriented sliding mode scheme offers better performance by reducing the chattering phenomenon, which is presented in the first-order scheme. The higher-order field-oriented sliding mode controller, based on the hierarchical use of supertwisting algorithm, is then implemented with a Texas Instruments TMS320F28335 DSP hardware platform to prototype the surface-mounted permanent magnet ac motor drive. Last, computer simulation studies demonstrate that the proposed field-oriented sliding mode control approach is able to effectively meet the speed and torque requirements of a heavy-duty electrified vehicle during the EPA urban driving schedule

An Advanced Model Predictive Current Control of Synchronous Reluctance Motors

Synchronous reluctance motors (SynRMs) have, in recent years, attracted much attention due to their high-efficiency output and nature of their construction denoted by the lack of expensive magnetic materials, thus cheapening the overall cost whilst increasing in robustness. These benefits have made the SynRM a strong contender against other established electric motors in the market. Similarly, model predictive current control (MPCC) has recently become a powerful advanced control technology in industrial drives, being, therefore, a suitable choice for SynRM drives granting overall high control performance and efficiency. However, current prediction in MPCC requires a high number of voltage vectors (VVs) synthesizable by the converter, being therefore computationally demanding. Accordingly, the main goal of this work is the development and analysis of a more efficient and advanced MPCC for SynRMs whilst reducing the computational burden and delivering good control performance in contrast with the standard MPCC. Therefore, to achieve the intended levels of efficiency and control performance in SynRM drives, a combination of two control strategies is developed, which combines hysteresis current control (HCC) and MPCC, dubbed in this work HCC-MPCC. Furthermore, the SynRM dynamic model equations comprising the magnetic saturating effects and iron losses are presented through a detailed theoretical and computational analysis of the drive’s control. Conclusively, the developed HCC-MPCC for SynRM drives is analyzed through thorough and rigorous experimental tests alongside the standard MPCC, whose obtained results are detailed comprehensively.Os motores síncronos de relutância (SynRMs) têm, nos últimos anos, atraído muita atenção devido às suas características construtivas, designadamente pela falta de materiais magnéticos caros, depreciando assim o custo em geral; e simultaneamente pelo aumento em robustez. Esses benefícios tornaram o SynRM num forte concorrente face a outros motores elétricos existentes no mercado. Da mesma forma, o modelo preditivo de controlo de corrente (MPCC) tornou-se recentemente numa poderosa estratégia de controlo avançado em acionamentos industriais, sendo, portanto, uma escolha adequada para acionamentos envolvendo SynRMs, garantindo elevado desempenho e eficiência de controlo. No entanto, a previsão da corrente no MPCC requer um grande número de vetores de tensão (VVs) sintetizáveis pelo conversor, sendo, portanto, exigente computacionalmente. Consequentemente, o objetivo principal deste trabalho é o desenvolvimento e análise de um MPCC mais eficiente e avançado para SynRMs, reduzindo a carga computacional e, simultaneamente, demonstrando um bom desempenho de controlo em contraste com o MPCC clássico. Portanto, para atingir os níveis pretendidos de eficiência e desempenho de controlo em acionamentos com SynRMs, uma combinação de duas estratégias de controlo é desenvolvida, combinando o controlo de corrente de histerese (HCC) e MPCC, denominado neste trabalho HCC-MPCC. Além disso, as equações do modelo dinâmico do SynRM, compreendendo os efeitos de saturação magnética e as perdas de ferro, são apresentadas através de uma análise teórica e computacional detalhada do controlo do acionamento. Conclusivamente, o HCC-MPCC desenvolvido para acionamentos com SynRMs é analisado por meio de testes experimentais conjuntamente com o MPCC padrão, sendo os resultados obtidos detalhados de forma abrangente

Minimizing losses of a synchronous reluctance motor drive taking into account core losses and magnetic saturation

This paper proposes a loss-minimizing controller for synchronous reluctance motor drives. The proposed method takes core losses and magnetic saturation effects into account. The core-loss model consists of hysteresis losses and eddy-current losses. Magnetic saturation is modeled using two-dimensional power functions considering cross coupling between the d- and q-axes. The efficiency optimal d-axis current is calculated offline using the loss model and motor parameters. Instead of generating a look-up table, an approximate function was fitted to the loss-minimizing results. The loss-minimizing method is applied in a motion-sensorless drive and the results are validated by measurements.Peer reviewe

Torque ripple minimization in non-sinusoidal synchronous reluctance motors based on artificial neural networks

This paper proposes a new method based on Artificial Neural Networks for reducing the torque ripple in a non-sinusoidal Synchronous Reluctance Motor. The Lagrange optimization method is used to solve the problem of calculating optimal currents in the d-q frame. A neural control scheme is then proposed as an adaptive solution to derive the optimal stator currents giving a constant electromagnetic torque and minimizing the ohmic losses. Thanks to the online learning capacity of neural networks, the optimal currents can be obtained online in real time. With this neural control, each machine’s parameters estimation errors and current controller errors can be compensated. Simulation and experimental results are presented which confirm the validity of the proposed method.Bourse de l'Ambassade de France au Vietna