The rapid consumption of fossil fuel and increased environmental damage caused by it have given a strong impetus to the growth and development of fuel-efficient vehicles. Hybrid electric vehicles (HEVs) have evolved from their inchoate state and are proving to be a promising solution to the serious existential problem posed to the planet earth. Not only do HEVs provide better fuel economy and lower emissions satisfying environmental legislations, but also they dampen the effect of rising fuel prices on consumers. HEVs combine the drive powers of an internal combustion engine and an electrical machine. The main components of HEVs are energy storage system, motor, bidirectional converter and maximum power point trackers (MPPT, in case of solar-powered HEVs). The performance of HEVs greatly depends on these components and its architecture. This paper presents an extensive review on essential components used in HEVs such as their architectures with advantages and disadvantages, choice of bidirectional converter to obtain high efficiency, combining ultracapacitor with battery to extend the battery life, traction motors’ role and their suitability for a particular application. Inclusion of photovoltaic cell in HEVs is a fairly new concept and has been discussed in detail. Various MPPT techniques used for solar-driven HEVs are also discussed in this paper with their suitability.

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A comprehensive review on hybrid electric vehicles: architectures and components

To reduce the dependence on oil and environmental pollution, the development of electric vehicles has been accelerated in many countries. The implementation of EVs, especially battery electric vehicles, is considered a solution to the energy crisis and environmental issues. This paper provides a comprehensive review of the technical development of EVs and emerging technologies for their future application. Key technologies regarding batteries, charging technology, electric motors and control, and charging infrastructure of EVs are summarized. This paper also highlights the technical challenges and emerging technologies for the improvement of efficiency, reliability, and safety of EVs in the coming stages as another contribution.

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Technology development of electric vehicles: A review

A direct-drive permanent magnet synchronous generator (PMSG) with a three-level neutral-point-clamped back-to-back power converter is an attractive configuration for high-power wind energy conversion systems. For such a topology, finite-control-set model-predictive control (FCS-MPC) has emerged as a promising alternative. However, due to its fully model-based concept, variation of system parameters (in particular, the stator and grid filter inductance and rotor permanent-flux linkage) will (seriously) affect the system control performances when using the classical FCS-MPC. In this work, a robust FCS-MPC method with revised predictions is proposed and validated for such a system. With the proposed solution, not only the system robustness against parameter variations is improved, but also the control variable ripples are evidently reduced. The proposed method has been implemented with a fully field-programmable-gate-array-based real-time hardware. Its performance improvements in comparison with the conventional solutions are validated with experimental data.

Robust Predictive Control of Three-Level NPC Back-to-Back Power Converter PMSG Wind Turbine Systems With Revised Predictions

To reduce the steady-state torque ripples for permanent-magnet synchronous motor drives with predictive torque control (PTC), this paper proposes a modified PTC algorithm based on the extended control set (ECS-PTC). In the proposed algorithm, more candidate voltage vectors are extended to the control set, which forms the ECS, and then, the torque control precision could be improved and the torque ripples will be reduced. More attractive thing is that a new voltage vector synthesis method is deigned in ECS-PTC, and the corresponding predictive model and cascaded predictive algorithm are set up on the basis of this method. With the help of them, the optimal vector can be selected from ECS in a shorter control period of time, and its amplitude is also optimized at the same time to achieve high-precision control effects for torque and flux. In addition, the three-phase duty ratios of the output vector can be determined in ECS-PTC directly, without the help of space vector pulse width modulation. The experimental results show that ECS-PTC has excellent dynamic torque performance, and it also has more stable torque control performance and better execution efficiency at the same time.

Torque Ripple Minimization of Predictive Torque Control for PMSM With Extended Control Set

The conventional rotor flux estimation method has issues of dc offset and harmonics, which are caused by initial rotor flux, detection errors, etc. To eliminate these defects, one improved nonlinear flux observer is proposed for sensorless control of permanent magnet synchronous machine (PMSM). First, the rotor position estimation method based on PMSM rotor flux observation is studied. Meanwhile, the limitations of the traditional rotor flux estimators, i.e., the saturation of pure integrator, phase shift, and amplitude attenuation of a low-pass filter are analyzed. Then, two novel flux observers, second-order generalized integral flux observer (SOIFO) and second-order SOIFO, are designed for the rotor flux estimation of PMSM. Based on second-order generalized integrator (SOGI) structure, the SOIFO can limit the dc component to a certain value. Furthermore, the second-order SOIFO is developed from the SOGI, which is characterized with effective dc and harmonics attenuation capability. With the second-order SOIFO, even without magnitude and phase compensation, the dc offset and harmonics of estimated rotor flux could be well eliminated. Therefore, the speed and rotor position can be estimated accurately. All the performances of the four methods are analyzed by transfer functions and Bode diagrams. Finally, the new sensorless control strategy is validated by comprehensive experimental results.

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Improved Nonlinear Flux Observer-Based Second-Order SOIFO for PMSM Sensorless Control

This paper investigates torque ripple minimization for permanent-magnet synchronous machine (PMSM), and proposes a closed-loop fuzzy-logic-based current controller by using the magnitude of the speed harmonic as the feedback control signal. The speed harmonic can be obtained from machine speed measurement, so the proposed approach does not require accurate machine parameters and is not influenced by the nonlinearity of the machine and drive. The torque harmonic can produce the speed harmonic of the same order, so their relation is investigated, which shows that the magnitude of the speed harmonic is proportional to the magnitude of the torque harmonic of the same order, so it can be used as a measure of torque harmonic for torque ripple minimization. Then, the torque harmonic model is developed to facilitate the design and analysis of the current controller. Afterward, a novel fuzzy-logic-based current controller is proposed to minimize the dominant torque harmonics. The proposed current controller is evaluated on a laboratory PMSM drive system under different load conditions and operation speeds.

A Closed-Loop Fuzzy-Logic-Based Current Controller for PMSM Torque Ripple Minimization Using the Magnitude of Speed Harmonic as the Feedback Control Signal

To develop a high-performance and reliable permanent-magnet synchronous machine (PMSM) drive for electric vehicle (EV) applications, accurate knowledge of the PMSM parameters is of significance. This paper investigates online estimation of PMSM parameters and voltage source inverter (VSI) nonlinearity using current injection method in which magnetic saturation is also considered. First, a novel dc component-based current injection model considering VSI nonlinearity is proposed, which employs the dc components of dq -axis currents and voltages for PMSM parameter and VSI-distorted voltage estimation. This method can eliminate the influence of rotor position error on VSI nonlinearity estimation. Second, a simplified linear equation is employed to model the cross- and self-saturation of the dq -axis inductances during current injection, which can facilitate the estimation of the inductance variations induced by magnetic saturation. Third, a novel current compensation strategy is proposed to minimize the torque ripples caused by current injection, which contributes to making our approach applicable to both surface and interior PMSMs. Therefore, the proposed online parameter estimation approach can estimate the winding resistance, rotor flux, VSI-distorted voltage, and the varying dq -axis inductances under different operating conditions. The proposed approach is experimentally validated on a down-scaled laboratory interior PMSM prototyped for direct-drive EV powertrain.

Current Injection-Based Online Parameter and VSI Nonlinearity Estimation for PMSM Drives Using Current and Voltage DC Components

Vector space decomposition (VSD) model is widely used for dual three-phase permanent magnet synchronous machine (dual-PMSM) control, in which two direct-quadrature (DQ) frames, DQ1 and DQ2, are introduced to facilitate the controller design. Existing studies show that harmonic current injection in DQ2 frame can increase the output torque for a given peak phase current, which is referred as maximum torque per peak current (MTPPC) control. However, the injected harmonic current will induce a small dc torque and the harmonic torque. This paper first proposes a comprehensive torque model considering the harmonics in PM flux linkages, inductances and stator currents to investigate the induced torque components, which are neglected in existing approaches. These torque components are then considered in the harmonic current design to improve the MTPPC control performance. The harmonic current design results in a multiobjective optimization problem, and genetic algorithm (GA) is employed to optimize the harmonic current to maximize the output torque with minimal torque harmonic. Compared with existing approaches, the proposed approach is applicable to both surface-mounted and interior dual-PMSMs. Experimental investigations on a laboratory interior dual-PMSM show that the output torque of the test motor can be increased by more than ten percent with a negligible increase in torque ripple.

Dual Three-Phase PMSM Torque Modeling and Maximum Torque per Peak Current Control Through Optimized Harmonic Current Injection

This paper studies the online parameter estimation of permanent magnet synchronous motor (PMSM) with the consideration of magnetic saturation and proposes a novel current injection method to estimate parameters, including winding resistances, $dq$ -axis inductances, and rotor flux. During the current injection, the inductances will vary due to magnetic saturation, neglecting which will cause great estimation error especially in the inductance estimation. This paper proposes to use simplified equations to model the self- and cross-saturation effects during the current injection. By incorporating this saturation model into the PMSM steady-state equations, the varying $dq$ -axis inductances due to magnetic saturation as well as the rotor flux can be accurately estimated. In addition, the estimation of winding resistance is independent of other parameters and does not get affected by the magnetic saturation. The proposed approach is validated through both the numerical and experimental studies on a laboratory interior PMSM.

A Novel Current Injection-Based Online Parameter Estimation Method for PMSMs Considering Magnetic Saturation

Falls are a major health risk for the elderly, decreasing their ability to live independently. This article proposes a novel feature-specific floor pressure imaging system that uses a smart floor embedded with fiber sensors. The potential applications include indoor human-activity analysis for intelligent surveillance. In particular, the authors focus on the application of fall detection in a bathroom scenario. Their fall detection method consists of two steps: floor pressure imaging for target posture classification and the fall event decision based on the classified target postures. Fall detection experiments validated the proposed method. This article is part of a special issue on domestic pervasive computing.

Guodong Feng

Papers

A Closed-Loop Fuzzy-Logic-Based Current Controller for PMSM Torque Ripple Minimization Using the Magnitude of Speed Harmonic as the Feedback Control Signal

Current Injection-Based Online Parameter and VSI Nonlinearity Estimation for PMSM Drives Using Current and Voltage DC Components

Dual Three-Phase PMSM Torque Modeling and Maximum Torque per Peak Current Control Through Optimized Harmonic Current Injection

A Novel Current Injection-Based Online Parameter Estimation Method for PMSMs Considering Magnetic Saturation

Floor Pressure Imaging for Fall Detection with Fiber-Optic Sensors