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Predictive errors restrict high performance of finite control set model predictive control (FCS-MPC) in the cascaded H-bridge multilevel inverter.In order to solve this problem, the influence mechanisms of parameter mismatch, model discretization, and sampling error on voltage and current prediction errors are analyzed in this article. A hierarchical multifactorial error correction method is proposed. The known voltage prediction errors of the previous adjacent prediction periods are first fed back to calculate the voltage predictive error factors and self-correct the next voltage prediction errors. And then the current prediction errors are calibrated by the corrected voltage and the calculated current predictive error factor. This proposed method involves a simple structure and a good inhibitory ability on multifactorial prediction errors. Finally, experimental results in a three-phase five-level cascaded H-bridge multilevel inverter support the theoretical analysis and the proposed method. [ABSTRACT FROM AUTHOR]

The extensive application of vector phase shift modulation method in permanent magnet synchronous motor drive systems with single dc-link current sensor results in obvious current ripple in the low-speed region. The patterns of these ripples vary greatly in different sectors, leading to nonnegligible phase current reconstruction errors. In this article, an estimation of the local average current change rate (ELAC2R) based reconstruction error suppression method within the switching cycle is proposed to resolve this problem. By comparing the actual and the ideal sampling points, the increase of current ripple and the reconstruction error caused by the combination of the vector phase shift and the single current sensor sampling in the low-speed region are modelled and analyzed. Then according to equivalent modelling of the current ripple between the ideal and the actual sampling points, the more accurate phase current information can be quickly obtained based on the sampling value. The compensation process is significantly simplified and the computation burden of the processor is reduced. Experimental results show that the performance of current reconstruction can be improved effectively with less harmonic content with the proposed method. [ABSTRACT FROM AUTHOR]

Due to the unbalanced three-phase currents and the torque ripples and speed fluctuations to the drive caused by the current sampling errors of three-phase current sensors and corresponding signal processing circuits, the estimation on current sampling errors is of great importance to eliminate these adverse effects. The observer-based methods, however, present two defects: first, they could increase the computational burden to the drives, thus limiting their practical applications; second, their high dependence on the system speed or position feedback information might degrade the estimation accuracy. To solve these problems, this article proposed a fixed-point sampling method of lower branch flows and three phase-currents, which adopts the relations between the measured currents, rather than any complex algorithm, to estimate the current sampling errors. To coordinate with the proposed strategy, a fixed-point sampling scheme was accordingly rolled out. Compared with the observer-based methods, as a fixed-point one, much applicable to actual digital controllers, it could reduce the computational burden of the drive. Meanwhile, its effectiveness was verified by experimental results on a 1.5-kW IPMSM prototype, which showed accurate estimated current sampling errors and the effectively eliminated torque ripples and speed fluctuations. [ABSTRACT FROM AUTHOR]

Because of the time-sharing sampling logic, the three-phase currents reconstructed by single dc-link shunt present significant errors in the permanent magnet synchronous motor drives. A traceback-prediction current correction method for sampled currents is proposed in this article to eliminate the reconstruction errors. According to the analysis of time-sharing sampling errors, the concept of equivalent current change rate during one pulsewidth modulation (PWM) period is introduced, and the phase current characteristic model based on state observer is established. Both the equivalent and instantaneous current change rates can be obtained by the observer-based calculation method. In order to improve the current reconstruction precision, the ultimate values of three-phase currents can be predicted by adopting the proposed traceback-prediction current correction method, which does not require major computation and is easy to implement with no restrictions on the PWM strategy. The effectiveness of the proposed method is verified by experimental results. [ABSTRACT FROM AUTHOR]

This paper proposes an effective sliding mode controller (SMC) for a grid-connected 7-level packed U-cell (PUC7) inverter. The aim is to design a simple controller that deals effectively with the complex control problem of the PUC7 inverter (multiobjective control problem). The selection of the control actions is achieved according to the system state error at every sampling time, regardless of the previous values, which makes the control technique model-independent. The control algorithm evaluates online two cost functions (one for each state error), which are derived on the basis of sliding mode theory, and it selects the optimal control input in order to satisfy the reaching conditions of the two cost functions. Compared with the existing solutions, the proposed SMC technique ensures lower average switching frequency by tuning the hysteresis bandwidth of the capacitor-voltage error. The fast implementation, needless of gains tuning, and simple design procedure are the main features of the proposed algorithm. Simulation and experimental results are presented to prove the effectiveness of the proposed technique in controlling the PUC7 inverter with high dynamic performance and robustness against disturbances and parameters mismatch. [ABSTRACT FROM AUTHOR]

In the control of permanent magnet synchronous machines (PMSMs), predictive controllers have received considerable attention due to the enhanced dynamic responses. However, periodic disturbances caused by dead-time effects and sampling errors deteriorate the performances of PMSMs. In order to suppress periodic disturbances, one typical control structure is to adopt several corresponding resonant controllers connected in parallel with the main controller. Even though excellent steady-state performances can be obtained, coupling effects between reference tracking and periodic disturbance attenuation can be observed, leading to significant transient oscillations under the situation of a reference step change. In order to realize decoupling between reference tracking and disturbance attenuation, this paper proposes a dual-loop predictive control structure, in which the reference tracking is only determined by the primary predictive controller. Periodic disturbance attenuation is achieved through an embedded disturbance rejection loop. By applying the proposed controller, periodic disturbances are strongly attenuated while smooth and fast transient performances are simultaneously guaranteed. Furthermore, a wide range of low frequency harmonics can be successfully suppressed, including but not limited to the main periodic harmonics. The steady-state performance, dynamic responses, and robustness against parameter variations of the proposed controller are verified through experiments based on a 2.3-kW PMSM. [ABSTRACT FROM AUTHOR]

Droop control is broadly used in dc power distribution systems, e.g., dc microgrids. Implementing droop control for switch mode power supplies requires the measurement of average current. Synchronous sampling is used in digital control systems to obtain the average of a triangular inductor waveform. However, the dead time, semiconductor turn-on and turn-off delays, and signal conditioning delays shift the sensed waveform and change the effective duty cycle, resulting in a misalignment and measurement error from the average value. This paper proposes a duty cycle weighted averaging method based on double sampling. By sampling twice per switching period and averaging the results using duty cycle as the weighting factor, the error due to waveform misalignment is theoretically eliminated. The result always equals the average value of the triangle. This method does not rely on the knowledge of circuit delays, making it easy to implement and robust to parameter variations. Simulations and experimental measurements validate the superior performance compared with conventional single and double sampling methods. The experiment on a droop-controlled dc–dc converter demonstrates a more accurate droop characteristic. [ABSTRACT FROM AUTHOR]

To solve the problem of poor robustness due to the high dependence of model predictive control (MPC) on the three-phase inverter model, the influence mechanism of the mismatch of circuit parameters R and L, the model discretization error, and sampling errors on MPC prediction error are analyzed in this paper. A feedback self-correction is proposed, which the next current errors are predicted and used to modify the model, based on the previous prediction errors. This proposed method involves simple structure and a small amount of calculation. Steady-state effects of the proposed method are quantized to prove a good inhibitory ability on multifactorial prediction errors. Finally, experimental results in a three-phase inverter are presented to support the theoretical analysis and demonstrate the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

The current reconstruction strategies using single current sensor in the motor drives are widely researched. However, the sampled currents do not represent the average values within the modulation period, especially for the asymmetric modulation or asymmetric sampling solutions. This is due to the following two reasons: 1) The detected current values obtained at different sampling points are utilized to calculate the three-phase currents; and 2) the detected instantaneous currents are applied to estimate the average current values. In this letter, the current change rates under different action vectors are estimated to compensate these errors in a three-phase four-switch interior permanent magnet synchronous motor (IPMSM) drive with single current sensor. The effectiveness of the proposed strategy is verified by experimental results on a 5-kW IPMSM motor prototype, which shows that the current reconstruction errors are reduced after compensation. [ABSTRACT FROM AUTHOR]

This letter proposes a structured approach for accurate estimation of diode reverse-recovery characteristics using datasheet specifications. Considering a conductance model of a diode, the entire reverse-recovery process is divided into four operating modes. The state equations for each mode are derived taking the circuit nonidealities, viz., device capacitance and parasitic inductances, into account. Analytical expressions for reverse-recovery charge, reverse-recovery time, and diode current are derived and numerically solved to estimate the diode conductance directly from manufacturer's data. An empirical model is proposed to characterize the effects of temperature variation on the diode conductance. Numerical simulation and experimental results are presented for antiparallel diodes of three MOSFETs having different current and voltage ratings and also for a discrete p-n diode at different junction temperatures. The maximum estimation error with the proposed approach is 5.1% for peak reverse-recovery current and less than 8% for reverse-recovery time, peak voltage, and energy loss. [ABSTRACT FROM AUTHOR]

In the square-wave voltage signal injection sensorless drive of the interior permanent-magnet synchronous machine, the injection voltage can be distorted by the inverter nonlinearity effects especially when the injection voltage is low. If that happens, a high-frequency (HF) current signal which contains the rotor position information could be also distorted, which directly leads to an error in the position estimation. This paper analyzes the effects of the inverter nonlinearity on injection voltage, on induced current ripple, and on the position estimation performance in sequence and proposes a voltage injection method to minimize the impact of the inverter nonlinearity by the regulation of the HF current ripple. By simulations and experiments, the performance of the proposed method has been verified. The experimental results show 19.7% reduction of position estimation error under 15% of rated voltage signal injection without increasing the current ripple at a certain operating condition. Moreover, the performance of position estimation is kept uniform regardless of the loading condition. [ABSTRACT FROM AUTHOR]

In this paper, a novel scheme for the estimation of the equivalent series resistance (ESR) of the dc-link electrolytic capacitor in three-phase ac/dc pulsewidth-modulation converters is proposed for condition monitoring. First, a controlled ac current component is injected into the input. Then, it induces ac voltage ripples on the dc output. By manipulating these ac voltage and current components with digital filters, the value of the ESR can be calculated, where the recursive least squares algorithm is used for reliable estimation results. In addition, the value of the ESR is corrected by considering the temperature effect, for which a simple temperature-sensing circuit has been designed. The simulation and experimental results show that the estimation error of the ESR is within a reasonable range, thereby enabling the determination of the appropriate time for the replacement of the capacitor. [ABSTRACT FROM PUBLISHER]

Modern gasoline internal combustion engines use a variety of technologies to enhance the efficiency of fresh air induction. These technologies, which include variable valve timing and variable intake geometry systems, also make it more difficult to predict the mass of fresh air that is trapped during the induction stroke of the engine because they not only affect the residual gas fraction of the trapped air charge, but also the wave dynamics of the system. As the number of controllable actuators increases, this estimation problem becomes even more difficult. As these technologies continue to develop, the importance of robustness in air-to-fuel ratio control continues to grow. This paper presents an air-to-fuel ratio control algorithm based on a switching frequency regulator that has favorable robust stability properties in the presence of both input and model errors. Instead of modeling the air path system with a simplified model, this control architecture considers the air estimate as a control input. As a result, air estimation errors behave like input errors, not modeling errors. By using the rich-to-lean and lean-to-rich air-to-fuel ratio switching frequencies of the pre-catalyst exhaust gas oxygen sensor as the primary feedback signal, the control laws are completely independent of the parameters of the plant model. The performance of this controller is demonstrated both with a robust stability analysis and through a vehicle-based experimental validation. [ABSTRACT FROM PUBLISHER]