881 resultados para Active and reactive power control


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In the early stages of the development of Japan’s environmental policy, sulfur oxide (SOx) emissions, which seriously damage health, was the most important air pollution problem. In the second half of the 1960s and the first half of the 1970s, the measures against SOx emissions progressed quickly, and these emissions were reduced drastically. The most important factor of the reduction was the conversion to a low-sulfur fuel for large-scale fuel users, such as the electric power industry. However, industries started conversion to low-sulfur fuel not due to environmental concerns, but simply to reduce costs. Furthermore, the interaction among the various interests of the electric power industry, oil refineries, the central government, local governments, and citizens over the energy and environmental policies led to the measures against SOx emissions by fuel conversion.

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Data centers are easily found in every sector of the worldwide economy. They are composed of thousands of servers, serving millions of users globally and 24-7. In the last years, e-Science applications such e-Health or Smart Cities have experienced a significant development. The need to deal efficiently with the computational needs of next-generation applications together with the increasing demand for higher resources in traditional applications has facilitated the rapid proliferation and growing of Data Centers. A drawback to this capacity growth has been the rapid increase of the energy consumption of these facilities. In 2010, data center electricity represented 1.3% of all the electricity use in the world. In year 2012 alone, global data center power demand grep 63% to 38GW. A further rise of 17% to 43GW was estimated in 2013. Moreover, Data Centers are responsible for more than 2% of total carbon dioxide emissions.

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Los Centros de Datos se encuentran actualmente en cualquier sector de la economía mundial. Están compuestos por miles de servidores, dando servicio a los usuarios de forma global, las 24 horas del día y los 365 días del año. Durante los últimos años, las aplicaciones del ámbito de la e-Ciencia, como la e-Salud o las Ciudades Inteligentes han experimentado un desarrollo muy significativo. La necesidad de manejar de forma eficiente las necesidades de cómputo de aplicaciones de nueva generación, junto con la creciente demanda de recursos en aplicaciones tradicionales, han facilitado el rápido crecimiento y la proliferación de los Centros de Datos. El principal inconveniente de este aumento de capacidad ha sido el rápido y dramático incremento del consumo energético de estas infraestructuras. En 2010, la factura eléctrica de los Centros de Datos representaba el 1.3% del consumo eléctrico mundial. Sólo en el año 2012, el consumo de potencia de los Centros de Datos creció un 63%, alcanzando los 38GW. En 2013 se estimó un crecimiento de otro 17%, hasta llegar a los 43GW. Además, los Centros de Datos son responsables de más del 2% del total de emisiones de dióxido de carbono a la atmósfera. Esta tesis doctoral se enfrenta al problema energético proponiendo técnicas proactivas y reactivas conscientes de la temperatura y de la energía, que contribuyen a tener Centros de Datos más eficientes. Este trabajo desarrolla modelos de energía y utiliza el conocimiento sobre la demanda energética de la carga de trabajo a ejecutar y de los recursos de computación y refrigeración del Centro de Datos para optimizar el consumo. Además, los Centros de Datos son considerados como un elemento crucial dentro del marco de la aplicación ejecutada, optimizando no sólo el consumo del Centro de Datos sino el consumo energético global de la aplicación. Los principales componentes del consumo en los Centros de Datos son la potencia de computación utilizada por los equipos de IT, y la refrigeración necesaria para mantener los servidores dentro de un rango de temperatura de trabajo que asegure su correcto funcionamiento. Debido a la relación cúbica entre la velocidad de los ventiladores y el consumo de los mismos, las soluciones basadas en el sobre-aprovisionamiento de aire frío al servidor generalmente tienen como resultado ineficiencias energéticas. Por otro lado, temperaturas más elevadas en el procesador llevan a un consumo de fugas mayor, debido a la relación exponencial del consumo de fugas con la temperatura. Además, las características de la carga de trabajo y las políticas de asignación de recursos tienen un impacto importante en los balances entre corriente de fugas y consumo de refrigeración. La primera gran contribución de este trabajo es el desarrollo de modelos de potencia y temperatura que permiten describes estos balances entre corriente de fugas y refrigeración; así como la propuesta de estrategias para minimizar el consumo del servidor por medio de la asignación conjunta de refrigeración y carga desde una perspectiva multivariable. Cuando escalamos a nivel del Centro de Datos, observamos un comportamiento similar en términos del balance entre corrientes de fugas y refrigeración. Conforme aumenta la temperatura de la sala, mejora la eficiencia de la refrigeración. Sin embargo, este incremente de la temperatura de sala provoca un aumento en la temperatura de la CPU y, por tanto, también del consumo de fugas. Además, la dinámica de la sala tiene un comportamiento muy desigual, no equilibrado, debido a la asignación de carga y a la heterogeneidad en el equipamiento de IT. La segunda contribución de esta tesis es la propuesta de técnicas de asigación conscientes de la temperatura y heterogeneidad que permiten optimizar conjuntamente la asignación de tareas y refrigeración a los servidores. Estas estrategias necesitan estar respaldadas por modelos flexibles, que puedan trabajar en tiempo real, para describir el sistema desde un nivel de abstracción alto. Dentro del ámbito de las aplicaciones de nueva generación, las decisiones tomadas en el nivel de aplicación pueden tener un impacto dramático en el consumo energético de niveles de abstracción menores, como por ejemplo, en el Centro de Datos. Es importante considerar las relaciones entre todos los agentes computacionales implicados en el problema, de forma que puedan cooperar para conseguir el objetivo común de reducir el coste energético global del sistema. La tercera contribución de esta tesis es el desarrollo de optimizaciones energéticas para la aplicación global por medio de la evaluación de los costes de ejecutar parte del procesado necesario en otros niveles de abstracción, que van desde los nodos hasta el Centro de Datos, por medio de técnicas de balanceo de carga. Como resumen, el trabajo presentado en esta tesis lleva a cabo contribuciones en el modelado y optimización consciente del consumo por fugas y la refrigeración de servidores; el modelado de los Centros de Datos y el desarrollo de políticas de asignación conscientes de la heterogeneidad; y desarrolla mecanismos para la optimización energética de aplicaciones de nueva generación desde varios niveles de abstracción. ABSTRACT Data centers are easily found in every sector of the worldwide economy. They consist of tens of thousands of servers, serving millions of users globally and 24-7. In the last years, e-Science applications such e-Health or Smart Cities have experienced a significant development. The need to deal efficiently with the computational needs of next-generation applications together with the increasing demand for higher resources in traditional applications has facilitated the rapid proliferation and growing of data centers. A drawback to this capacity growth has been the rapid increase of the energy consumption of these facilities. In 2010, data center electricity represented 1.3% of all the electricity use in the world. In year 2012 alone, global data center power demand grew 63% to 38GW. A further rise of 17% to 43GW was estimated in 2013. Moreover, data centers are responsible for more than 2% of total carbon dioxide emissions. This PhD Thesis addresses the energy challenge by proposing proactive and reactive thermal and energy-aware optimization techniques that contribute to place data centers on a more scalable curve. This work develops energy models and uses the knowledge about the energy demand of the workload to be executed and the computational and cooling resources available at data center to optimize energy consumption. Moreover, data centers are considered as a crucial element within their application framework, optimizing not only the energy consumption of the facility, but the global energy consumption of the application. The main contributors to the energy consumption in a data center are the computing power drawn by IT equipment and the cooling power needed to keep the servers within a certain temperature range that ensures safe operation. Because of the cubic relation of fan power with fan speed, solutions based on over-provisioning cold air into the server usually lead to inefficiencies. On the other hand, higher chip temperatures lead to higher leakage power because of the exponential dependence of leakage on temperature. Moreover, workload characteristics as well as allocation policies also have an important impact on the leakage-cooling tradeoffs. The first key contribution of this work is the development of power and temperature models that accurately describe the leakage-cooling tradeoffs at the server level, and the proposal of strategies to minimize server energy via joint cooling and workload management from a multivariate perspective. When scaling to the data center level, a similar behavior in terms of leakage-temperature tradeoffs can be observed. As room temperature raises, the efficiency of data room cooling units improves. However, as we increase room temperature, CPU temperature raises and so does leakage power. Moreover, the thermal dynamics of a data room exhibit unbalanced patterns due to both the workload allocation and the heterogeneity of computing equipment. The second main contribution is the proposal of thermal- and heterogeneity-aware workload management techniques that jointly optimize the allocation of computation and cooling to servers. These strategies need to be backed up by flexible room level models, able to work on runtime, that describe the system from a high level perspective. Within the framework of next-generation applications, decisions taken at this scope can have a dramatical impact on the energy consumption of lower abstraction levels, i.e. the data center facility. It is important to consider the relationships between all the computational agents involved in the problem, so that they can cooperate to achieve the common goal of reducing energy in the overall system. The third main contribution is the energy optimization of the overall application by evaluating the energy costs of performing part of the processing in any of the different abstraction layers, from the node to the data center, via workload management and off-loading techniques. In summary, the work presented in this PhD Thesis, makes contributions on leakage and cooling aware server modeling and optimization, data center thermal modeling and heterogeneityaware data center resource allocation, and develops mechanisms for the energy optimization for next-generation applications from a multi-layer perspective.

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Response inhibition is the ability to suppress inadequate but automatically activated, prepotent or ongoing response tendencies. In the framework of motor inhibition, two distinct operating strategies have been described: “proactiveandreactivecontrol modes. In the proactive modality, inhibition is recruited in advance by predictive signals, and actively maintained before its enactment. Conversely, in the reactive control mode, inhibition is phasically enacted after the detection of the inhibitory signal. To date, ample evidence points to a core cerebral network for reactive inhibition comprising the right inferior frontal gyrus (rIFG), the presupplementary motor area (pre-SMA) and the basal ganglia (BG). Moreover, fMRI studies showed that cerebral activations during proactive and reactive inhibition largely overlap. These findings suggest that at least part of the neural network for reactive inhibition is recruited in advance, priming cortical regions in preparation for the upcoming inhibition. So far, proactive and reactive inhibitory mechanisms have been investigated during tasks in which the requested response to be stopped or withheld was an “overt” action execution (AE) (i.e., a movement effectively performed). Nevertheless, inhibitory mechanisms are also relevant for motor control during “covert actions” (i.e., potential motor acts not overtly performed), such as motor imagery (MI). MI is the conscious, voluntary mental rehearsal of action representations without any overt movement. Previous studies revealed a substantial overlap of activated motor-related brain networks in premotor, parietal and subcortical regions during overtly executed and imagined movements. Notwithstanding this evidence for a shared set of cerebral regions involved in encoding actions, whether or not those actions are effectively executed, the neural bases of motor inhibition during MI, preventing covert action from being overtly performed, in spite of the activation of the motor system, remain to be fully clarified. Taking into account this background, we performed a high density EEG study evaluating cerebral mechanisms and their related sources elicited during two types of cued Go/NoGo task, requiring the execution or withholding of an overt (Go) or a covert (MI) action, respectively. The EEG analyses were performed in two steps, with different aims: 1) Analysis of the “response phase” of the cued overt and covert Go/NoGo tasks, for the evaluation of reactive inhibitory control of overt and covert actions. 2) Analysis of the “preparatory phase” of the cued overt and covert Go/NoGo EEG datasets, focusing on cerebral activities time-locked to the preparatory signals, for the evaluation of proactive inhibitory mechanisms and their related neural sources. For these purposes, a spatiotemporal analysis of the scalp electric fields was applied on the EEG data recorded during the overt and covert Go/NoGo tasks. The spatiotemporal approach provide an objective definition of time windows for source analysis, relying on the statistical proof that the electric fields are different and thus generated by different neural sources. The analysis of the “response phase” revealed that key nodes of the inhibitory circuit, underpinning inhibition of the overt movement during the NoGo response, were also activated during the MI enactment. In both cases, inhibition relied on the activation of pre-SMA and rIFG, but with different temporal patterns of activation in accord with the intended “covert” or “overt” modality of motor performance. During the NoGo condition, the pre-SMA and rIFG were sequentially activated, pointing to an early decisional role of pre-SMA and to a later role of rIFG in the enactment of inhibitory control of the overt action. Conversely, a concomitant activation of pre-SMA and rIFG emerged during the imagined motor response. This latter finding suggested that an inhibitory mechanism (likely underpinned by the rIFG), could be prewired into a prepared “covert modality” of motor response, as an intrinsic component of the MI enactment. This mechanism would allow the rehearsal of the imagined motor representations, without any overt movement. The analyses of the “preparatory phase”, confirmed in both overt and covert Go/NoGo tasks the priming of cerebral regions pertaining to putative inhibitory network, reactively triggered in the following response phase. Nonetheless, differences in the preparatory strategies between the two tasks emerged, depending on the intended “overt” or “covert” modality of the possible incoming motor response. During the preparation of the overt Go/NoGo task, the cue primed the possible overt response programs in motor and premotor cortex. At the same time, through preactivation of a pre-SMA-related decisional mechanism, it triggered a parallel preparation for the successful response selection and/or inhibition during the subsequent response phase. Conversely, the preparatory strategy for the covert Go/NoGo task was centred on the goal-oriented priming of an inhibitory mechanism related to the rIFG that, being tuned to the instructed covert modality of the motor performance and instantiated during the subsequent MI enactment, allowed the imagined response to remain a potential motor act. Taken together, the results of the present study demonstrate a substantial overlap of cerebral networks activated during proactive recruitment and subsequent reactive enactment of motor inhibition in both overt and covert actions. At the same time, our data show that preparatory cues predisposed ab initio a different organization of the cerebral areas (in particular of the pre-SMA and rIFG) involved with sensorimotor transformations and motor inhibitory control for executed and imagined actions. During the preparatory phases of our cued overt and covert Go/NoGo tasks, the different adopted strategies were tuned to the “how” of the motor performance, reflecting the intended overt and covert modality of the possible incoming action.

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Reactive power is critical to the operation of the power networks on both safety aspects and economic aspects. Unreasonable distribution of the reactive power would severely affect the power quality of the power networks and increases the transmission loss. Currently, the most economical and practical approach to minimizing the real power loss remains using reactive power dispatch method. Reactive power dispatch problem is nonlinear and has both equality constraints and inequality constraints. In this thesis, PSO algorithm and MATPOWER 5.1 toolbox are applied to solve the reactive power dispatch problem. PSO is a global optimization technique that is equipped with excellent searching capability. The biggest advantage of PSO is that the efficiency of PSO is less sensitive to the complexity of the objective function. MATPOWER 5.1 is an open source MATLAB toolbox focusing on solving the power flow problems. The benefit of MATPOWER is that its code can be easily used and modified. The proposed method in this thesis minimizes the real power loss in a practical power system and determines the optimal placement of a new installed DG. IEEE 14 bus system is used to evaluate the performance. Test results show the effectiveness of the proposed method.

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Includes bibliographical references and index.

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Understanding the physiological and psychological factors that contribute to healthy and pathological balance control in man has been made difficult by the confounding effects of the perturbations used to test balance reactions. The present study examined how postural responses were influenced by the acceleration-deceleration interval of an unexpected horizontal translation. Twelve adult males maintained balance during unexpected forward and backward surface translations with two different acceleration-deceleration intervals and presentation orders (serial or random). SHORT perturbations consisted of an initial acceleration (peak acceleration 1.3 m s(-2); duration 300 ms) followed 100 ms later by a deceleration. LONG perturbations had the same acceleration as SHORT perturbations, followed by a 2-s interval of constant velocity before deceleration. Surface and intra-muscular electromyography (EMG) from the leg, trunk, and shoulder muscles were recorded along with motion and force plate data. LONG perturbations induced larger trunk displacements compared to SHORT perturbations when presented randomly and larger EMG responses in proximal and distal muscles during later (500-800 ms) response intervals. During SHORT perturbations, activity in some antagonist muscles was found to be associated with deceleration and not the initial acceleration of the support surface. When predictable, SHORT perturbations facilitated the use of anticipatory mechanisms to attenuate early (100-400 ms) EMG response amplitudes, ankle torque change and trunk displacement. In contrast, LONG perturbations, without an early deceleration effect, did not facilitate anticipatory changes when presented in a predictable order. Therefore, perturbations with a short acceleration-deceleration interval can influence triggered postural responses through reactive effects and, when predictable with repeated exposure, through anticipatory mechanisms.

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As a source or sink of reactive power, compensators can be made from a voltage sourced inverter circuit with the a.c. terminals of the inverter connected to the system through an inductive link and with a capacitor connected across the d.c. terminals. Theoretical calculations on linearised models of the compensators have shown that the parameters characterising the performance are the reduced firing angle and the resonance ratio. The resonance ratio is the ratio of the natural frequency of oscillation of the energy storage components in the circuit to the system frequency. The reduced firing angle of the inverter divided by the damping coefficient, β, where β is half the R to X ratio of the link between the inverter and the system. The theoretical results have been verified by computer simulation and experiment. There is a narrow range of values for the resonance ratio below which there is no appreciable improvement in performance, despite an increase in the cost of the energy storage components, and above which the performance of the equipment is poor with the current being dominated by harmonics. The harmonic performance of the equipment is improved by using multiple inverters and phase shifting transformers to increase the pulse number. The optimum value of the resonance ratio increases pulse number, indicating a reduction in the energy storage components needed at high pulse numbers. The reactive power output from the compensator varies linearly with the reduced firing angle while the losses vary as the square of it.

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The scope of this paper is to present the Pulse Width Modulation (PWM) based method for Active Power (AP) and Reactive Power (RP) measurements as can be applied in Power Meters. Necessarily, the main aim of the material presented is a twofold, first to present a realization methodology of the proposed algorithm, and second to verify the algorithm’s robustness and validity. The method takes advantage of the fact that frequencies present in a power line are of a specific fundamental frequency range (a range centred on the 50 Hz or 60 Hz) and that in case of the presence of harmonics the frequencies of those dominating in the power line spectrum can be specified on the basis of the fundamental. In contrast to a number of existing methods a time delay or shifting of the input signal is not required by the method presented and the time delay by n/2 of the Current signal with respect to the Voltage signal required by many of the existing measurement techniques, does not apply in the case of the PWM method as well.

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Permanent magnet synchronous motors (PMSMs) provide a competitive technology for EV traction drives owing to their high power density and high efficiency. In this paper, three types of interior PMSMs with different PM arrangements are modeled by the finite element method (FEM). For a given amount of permanent magnet materials, the V shape interior PMSM is found better than the U-shape and the conventional rotor topologies for EV traction drives. Then the V shape interior PMSM is further analyzed with the effects of stator slot opening and the permanent magnet pole chamfering on cogging torque and output torque performance. A vector-controlled flux-weakening method is developed and simulated in matlab to expand the motor speed range for EV drive system. The results show good dynamic and steady-state performance with a capability of expanding speed up to 4 times of the rated. A prototype of the V shape interior PMSM is also manufactured and tested to validate the numerical models built by the finite element method.

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With the advantages and popularity of Permanent Magnet (PM) motors due to their high power density, there is an increasing incentive to use them in variety of applications including electric actuation. These applications have strict noise emission standards. The generation of audible noise and associated vibration modes are characteristics of all electric motors, it is especially problematic in low speed sensorless control rotary actuation applications using high frequency voltage injection technique. This dissertation is aimed at solving the problem of optimizing the sensorless control algorithm for low noise and vibration while achieving at least 12 bit absolute accuracy for speed and position control. The low speed sensorless algorithm is simulated using an improved Phase Variable Model, developed and implemented in a hardware-in-the-loop prototyping environment. Two experimental testbeds were developed and built to test and verify the algorithm in real time.^ A neural network based modeling approach was used to predict the audible noise due to the high frequency injected carrier signal. This model was created based on noise measurements in an especially built chamber. The developed noise model is then integrated into the high frequency based sensorless control scheme so that appropriate tradeoffs and mitigation techniques can be devised. This will improve the position estimation and control performance while keeping the noise below a certain level. Genetic algorithms were used for including the noise optimization parameters into the developed control algorithm.^ A novel wavelet based filtering approach was proposed in this dissertation for the sensorless control algorithm at low speed. This novel filter was capable of extracting the position information at low values of injection voltage where conventional filters fail. This filtering approach can be used in practice to reduce the injected voltage in sensorless control algorithm resulting in significant reduction of noise and vibration.^ Online optimization of sensorless position estimation algorithm was performed to reduce vibration and to improve the position estimation performance. The results obtained are important and represent original contributions that can be helpful in choosing optimal parameters for sensorless control algorithm in many practical applications.^

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The conventional control schemes applied to Shunt Active Power Filters (SAPF) are Harmonic extractor-based strategies (HEBSs) because their effectiveness depends on how quickly and accurately the harmonic components of the nonlinear loads are identified. The SAPF can be also implemented without the use of the load harmonic extractors. In this case, the harmonic compensating term is obtained from the system active power balance. These systems can be considered as balanced-energy-based schemes (BEBSs) and their performance depends on how fast the system reaches the equilibrium state. In this case, the phase currents of the power grid are indirectly regulated by double sequence controllers with two degrees of freedom, where the internal model principle is employed to avoid reference frame transformation. Additionally the DSC controller presents robustness when the SAPF is operating under unbalanced conditions. Furthermore, SAPF implemented without harmonic detection schemes compensate simultaneously harmonic distortion and reactive power of the load. Their compensation capabilities, however, are limited by the SAPF power converter rating. Such a restriction can be minimized if the level of the reactive power correction is managed. In this work an estimation scheme for determining the filter currents is introduced to manage the compensation of reactive power. Experimental results are shown for demonstrating the performance of the proposed SAPF system.

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A novel open-winding brushless doubly-fed generator (BDFG) system with two two-level bidirectional converters is proposed. This topology is equivalent to a three-level bidirectional converter connected to the typical BDFG, but solves the unbalanced-voltage-division problem of DC capacitor in the three-level converter, and has lower converter capacity, more flexible control mode, and better fault-tolerant ability. The direct power control (DPC) based on the twelve sections is adopted to implement the power tracking of the open-winding BDFG system, which is compared with the typical BDFG DPC system based on the six and twelve sections to verify the advantages of the proposed scheme.

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Mineral and chemical composition of alluvial Upper-Pleistocene deposits from the Alto Guadalquivir Basin (SE Spain) were studied as a tool to identify sedimentary and geomorphological processes controlling its formation. Sediments located upstream, in the north-eastern sector of the basin, are rich in dolomite, illite, MgO and KB2BO. Downstream, sediments at the sequence base are enriched in calcite, smectite and CaO, whereas the upper sediments have similar features to those from upstream. Elevated rare-earth elements (REE) values can be related to low carbonate content in the sediments and the increase of silicate material produced and concentrated during soil formation processes in the neighbouring source areas. Two mineralogical and geochemical signatures related to different sediment source areas were identified. Basal levels were deposited during a predominantly erosive initial stage, and are mainly composed of calcite and smectite materials enriched in REE coming from Neogene marls and limestones. Then the deposition of the upper levels of the alluvial sequences, made of dolomite and illitic materials depleted in REE coming from the surrounding Sierra de Cazorla area took place during a less erosive later stage of the fluvial system. Such modification was responsible of the change in the mineralogical and geochemical composition of the alluvial sediments.

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Permanent magnet synchronous motors (PMSMs) provide a competitive technology for EV traction drives owing to their high power density and high efficiency. In this paper, three types of interior PMSMs with different PM arrangements are modeled by the finite element method (FEM). For a given amount of permanent magnet materials, the V-shape interior PMSM is found better than the U-shape and the conventional rotor topologies for EV traction drives. Then the V-shape interior PMSM is further analyzed with the effects of stator slot opening and the permanent magnet pole chamfering on cogging torque and output torque performance. A vector-controlled flux-weakening method is developed and simulated in Matlab to expand the motor speed range for EV drive system. The results show good dynamic and steady-state performance with a capability of expanding speed up to four times of the rated. A prototype of the V-shape interior PMSM is also manufactured and tested to validate the numerical models built by the FEM.