Sangshin Kwak

Predictive-Control-Based Direct Power Control With an Adaptive Parameter Identification Technique for Improved AFE Performance

This paper proposes predictive-control-based direct power control (DPC) with an adaptive online parameter identification technique for ac-dc active front ends (AFEs) to overcome model mismatch and parameter uncertainty. Based on least-squares estimation, the input inductance and input resistance of the AFE are calculated every sampling period using sampled input currents and input voltages. Because the online-tuned input inductance and resistance are updated for the controller, the proposed predictive-control-based DPC with the adaptive parameter identification technique can mitigate performance degradation resulting from the model uncertainty of the model predictive controller without any additional sensors. Therefore, the AFE generates sinusoidal input currents with a unity power factor despite parameter uncertainty.

Switching Strategy Based on Model Predictive Control of VSI to Obtain High Efficiency and Balanced Loss Distribution

This paper proposes the switching strategy based on finite control set model predictive control (FCS-MPC) method, to reduce switching losses and obtain balanced loss distribution of the voltage-source inverters (VSIs). Unlike the conventional FCS-MPC method with no explicit information of the reference voltage, the developed voltage-based FCS-MPC scheme produces the future reference voltage vector with the Lyapunov function every sampling period. With information of both the future reference voltage and the future load current vectors, the proposed switching strategy instantaneously determines one optimum clamped phase among the three legs in the VSI every sampling period. By optimally determining the clamping phase and its duration on the basis of every sampling period, the proposed switching strategy can successfully reduce the VSI switching losses. In addition, the proposed switching method can yield a balanced loss distribution among the switches in the VSI, contrary to the conventional FCS-MPC. The balanced loss generation as well as the switching loss reduction by the proposed method, which is optimal at the sampling period scale, is directly incorporated with the platform of the FCS-MPC algorithm, since the FCS-MPC operates on the basis of the sampling period. Thus, the proposed switching operation based on the voltage-based FCS-MPC algorithm enables the future VSI output currents to track the future reference current vector, as well as results in the reduced switching losses and the balanced loss performance.

Suboptimal Control Scheme Design for Interior Permanent-Magnet Synchronous Motors: An SDRE-Based Approach

This paper designs a suboptimal speed controller as well as a suboptimal load torque observer based on state-dependent Riccati equation (SDRE) approach for interior permanent-magnet synchronous motor (IPMSM) servo systems. First, dynamic equations of the IPMSMs are transformed to a suitable form that makes an SDRE-based control technique applicable. Moreover, the maximum torque per ampere (MTPA) control is incorporated to improve the torque generation in the constant torque region. The asymptotic stabilities of the proposed controller and load torque observer are fully guaranteed through an extended linear quadratic regulator (LQR) theory. This proposed method is simple to implement because the SDRE solutions are approximated off-line. The proposed observer-based suboptimal control scheme can ensure faster dynamic response, smaller steady-state error, and more robust response than the LQR and proportional-integral (PI) controller under the system parameter variations and load torque disturbances. The effectiveness of the proposed control strategy is verified via experiment.

Model-Predictive Direct Power Control With Vector Preselection Technique for Highly Efficient Active Rectifiers

This paper proposes a novel method to reduce switching losses on the basis of a model-predictive direct power control (MPDPC) method for ac-dc active rectifiers. The main idea is to preselect voltage vectors to decrease switching losses at the next sampling period, and then select one optimum voltage vector among only the preselected voltage vectors to perform direct power control (DPC). The proposed vector preselection scheme enables a predefined cost function to consider only four vectors to control the real and the reactive power at every sampling period. The proposed MPDPC method using only the four preselected vectors stops switching operation of one leg exposed to the largest input current at every sampling period. On the basis of the preselected vectors at each sampling period, the proposed method can effectively reduce the switching losses, as well as accurately perform power control of the active rectifier.

Predictive Control Method With Future Zero-Sequence Voltage to Reduce Switching Losses in Three-Phase Voltage Source Inverters

This paper proposes a predictive control method with zero-sequence voltage injection to efficiently reduce the switching losses of three-phase voltage source inverters (VSIs). In the proposed predictive control method, three-phase future voltage references modified by a zero-sequence voltage injection are generated to clamp one of the three legs with the largest load current. Furthermore, the future zero-sequence voltage, which is produced online with the future voltage and current references in every sampling period, optimally adjusts the clamping duration on each leg, depending on the load angle. In addition, the proposed method selects the zero vector on the basis of the polarity of the future zero-sequence voltage to reduce the switching losses. Using a predefined cost function, the proposed predictive control scheme chooses one optimal voltage state closest to the future voltage references modified by the zero-sequence voltage injection. Therefore, the proposed predictive control method can perform load current control and minimize the switching losses of the VSI under any load condition regardless of the load angle.

Integrated modeling and analysis of dynamics for electric vehicle powertrains

Powertrain of an electric vehicle (EV) is a compound system with an electrical sub-system, such as batteries, inverters, and electrical motors, as well as a mechanical sub-system, including transmissions, differential, and wheels. Since the electrical systems directly affect the vehicle driving performance and dynamics of an EV, integrated modeling considering both the mechanical and electrical systems is essential to assess ultimate kinetic and dynamic characteristics of an EV in terms of input electrical quantities. In this paper, an entire analytic model for the powertrain of EVs is developed to describe EV dynamics with respect to electrical signals, in consideration of both mechanical and electrical systems. Theoretical models based on mathematical expressions, combining the mechanical power system and the electrical power systems, are derived for predicting the final vehicle driving performance as a function of electrical quantities. In addition, a Matlab model of an EV is developed to verify the derived mathematical analysis model. Based on the theoretical model of the powertrain, a variety of relationships between electrical quantities and vehicle dynamics, such as velocity, acceleration, and forces of the EVs, are finally investigated and analyzed.

Optimal Design and Performance Analysis of Permanent Magnet Assisted Synchronous Reluctance Portable Generators

In this paper, design and performance analysis of robust and inexpensive permanent magnet-assisted synchronous reluctance generators (PMa-SynRG) for tactical and commercial generator sets is studied. More specifically, the optimal design approach is investigated for minimizing volume and maximizing performance for the portable generator. In order to find optimized PMa-SynRG, stator winding configurations and rotor structures are analyzed using the lumped parameter model (LPM). After comparisons of stator windings and rotor structure by LPM, the selected stator winding and rotor structure are optimized using a differential evolution strategy (DES). Finally, output performances are verified by finite element analysis (FEA) and experimental tests. This design process is developed for the optimized design of PMa-SynRG to achieve minimum magnet and machine volume as well as maximum efficiency simultaneously.

Predictive Current Control Methods With Reduced Current Errors and Ripples for Single-Phase Voltage Source Inverters

This paper proposes two model predictive current control (MPCC) methods utilizing two output voltages with variable application durations in one sampling period to control the output currents of single-phase voltage source inverters (VSIs). In the proposed methods, the application durations of the two voltages, as well as the selection of two output voltages used in the future sampling period, are determined by an optimization process to minimize current error inside the future sampling period and to eliminate current error at the end of the future sampling instant. By utilizing the two voltages with variable durations, the two proposed MPCC methods can reduce steady-state current errors and decrease output current ripples without increasing the sampling frequency in comparison with the conventional MPCC method, despite only three distinctive output voltages being allowed in the single-phase VSI. The two proposed methods along with the conventional MPCC method are compared in terms of current errors and total harmonic distortion. The effectiveness of the two proposed methods for the single-phase VSIs is verified with both simulation and experimental results.

Simple Space Vector PWM Scheme for 3-level NPC Inverters Including the Overmodulation Region

This paper proposes a simple space vector PWM (SVPWM) scheme including overmodulation operation for 3-level NPC (Neutral Point Clamped) Inverters. The proposed scheme features a simple decision and calculation procedure for determining switching times in the overmodulation range by utilizing the duty calculation method used in 2-level inverters and the minimum phase error projection method widely employed in motor drive systems. The proposed scheme does not need to detect the angle of the reference vector or calculate trigonometric functions to determine the magnitude of the voltage vector. The magnitude of the angle of the new reference voltage vector is decided in advance with the help of the Fourier Series Expansion to extend the linearity of the output voltage of 3-level inverters in the overmodulation region. Experimental results demonstrate the validity of the proposed SVPWM scheme including overmodulation operation for 3-level NPC inverters.

Fault diagnosis algorithm based on switching function for boost converters

A fault diagnosis algorithm, which is necessary for constructing a reliable power conversion system, should detect fault occurrences as soon as possible to protect the entire system from fatal damages resulting from system malfunction. In this paper, a fault diagnosis algorithm is proposed to detect open- and short-circuit faults that occur in a boost converter switch. The inductor voltage is abnormally kept at a positive DC value during a short-circuit fault in the switch or at a negative DC value during an open-circuit fault condition until the inductor current becomes zero. By employing these abnormal properties during faulty conditions, the inductor voltage is compared with the switching function to detect each fault type by generating fault alarms when a fault occurs. As a result, from the fault alarm, a decision is made in response to the fault occurrence and the fault type in less than two switching time periods using the proposed algorithm constructed in analogue circuits. In addition, the proposed algorithm has good resistivity to discontinuous current-mode operation. As a result, this algorithm features the advantages of low cost and simplicity because of its simple analogue circuit configuration.