Voltage Tracking Research Articles

Model migration based battery power capability evaluation considering uncertainties of temperature and aging

Uncertainties of cell temperature and aging are two challenges for the power management of battery-integrated systems. To evaluate the maximum power capability of batteries with uncertain degree of degradation and internal temperature, a temperature-compensated battery model is first established as a base model in this paper. Then the linear migration with particle filtering is employed to adjust the developed base model so that the migrated model can be adaptive to the uncertainties of aging and internal temperature. Moreover, a numerical seeking method is proposed for state of power (SoP) calculation to avoid direct handling of the complex, highly nonlinear battery model. After that, the multiple constraints such as current, state of charge (SoC), and voltage limitations are considered for SoP estimation. Experimental results show that for the cases of capacity degradation up to 15%, temperature variation up to 40 °C, and the root-mean-square error (RMSE) of the voltage measurement noise up to 50 mV, the RMSE of the voltage tracking for SoP calculation can still be limited to 8.4 mV, and the RMSE of the SoC estimation is better than 1.64%. In addition, the computational efficiency of the proposed seeking algorithm is stable with particle filters using different configurations.

Simulation and experiment of algorithm and circuit design for UPQC

ABSTRACTPower quality issues have become one of the most important issue for researchers to concern. In this paper, simulation and experiment of algorithm and circuit design of Unified Power Quality Conditioner (UPQC) are provided. Control algorithm and topology design of one UPQC which includes active power filter (APF) and dynamic voltage restorer (DVR) are introduced. Stability condition of the filter unit is deduced and proved by Routh stability criterion. Simulation for APF and DVR is carried out in PSCAD to show the proposed control strategy. Experiments such as current tracking, harmonic detection and compensation and voltage drop compensation are provided in details. Experimental results show that the proposed control method and the designed topology are effective and practical.

Fault ride-through capability of star-connected cascaded multilevel converter based hybrid energy storage system under unbalanced grid failure

This paper proposes a fault-tolerant control method for star-connected cascaded multilevel converter (CMC) based hybrid energy storage system (HESS) to enhance its fault ride-through capability under unbalanced grid failure. In this topology, battery and capacitor are used as two types of dc sources. Unbalanced grid will lead to uneven power flow among three-phase links, so it's challenging to distribute active power between different types of converter cells to perform voltage balancing control. With proposed control method, battery cells and capacitor cells respectively perform unbalanced voltage tracking and zero sequence voltage (ZSV) injection. The system can maintain dc-side voltages, allowing system to ride through faulty situations and enhance its reliability. Proposed method is implemented in the DSP and verified by a 5 MW/35 kV system based on RT-LAB HIL (hardware-in-loop) platform, experimental results validate the reliability of system has been enhanced.

Robust adaptive H‐infinity based controller for islanded microgrid supplying non‐linear and unbalanced loads

This study introduces a proposed control method for microgrids (MGs) in islanded (off-grid) mode. The proposed control method is developed by modifying the droop control method using H-infinity controller. In this control method, the droop control loop, current and voltage control loops are adjusted to respond to system load variation. The proposed method is an adaptive control one as it regulates the system voltage and frequency to their nominal values after system load variations. Also, it is a repetitive control method as it depends on the internal model principle that provides good performance for voltage and current error tracking. To prove the applicability and effectiveness of the proposed method, it is applied to a test system using MATLAB/Simulink under three different loading conditions. The results are compared with those of droop control and they prove the effectiveness of the proposed method in adjusting MGs under the off-grid mode of operation. Also, a system stability analysis is performed based on root locus and system step response. Robustness analysis is performed to prove the ability of the proposed controller to restore the system performance after the fault clearance.

Multivariable integral linear quadratic Gaussian robust control of islanded microgrid to mitigate voltage oscillation for improving transient response

AbstractA novel robust integral linear quadratic Gaussian (ILQG) controller is presented in this paper to control the voltage of islanded microgrid and improves its transient response. Microgrid is a small grid that consists of number of distributed generator units, power‐electronic components with inductor‐capacitor (LC) filters and loads. The loads are parametrically uncertain and unknown that produces the voltage or power oscillation. The ILQG controller is capable to compensate for the voltage oscillation and exhibits the tracking of grid voltage against the different load dynamics. The design of ILQG controller is carried out by augmenting the plant dynamics with an integrator. The robustness of the ILQG controller is studied by considering a number of uncertainties within the plant model. The performance of ILQG controller is compared with linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) controller in terms of rise time, settling time, bandwidth and tracking error. The comparison results ensure the high bandwidth and tracking performance of ILQG controller as compared to other controllers.

Design and Analysis of a Novel Converter Topology for Photovoltaic Pumps Based on Switched Reluctance Motor

In order to improve the performance of switched reluctance motor (SRM) systems for photovoltaic (PV) pumps, this paper introduces a new converter topology for SRM with controllable multiple power sources. Only simple switching components need to be added at the front end of the asymmetric half-bridge converter in this topology, which enables the control of multiple power sources. The new PV pump system has four operating modes, which are the PV panel driven mode, battery bank driven mode, dual-source driven mode, and battery charging mode. By adjusting the state of the front-end converter switch, the voltage tracking of PV panel can be achieved, providing a stable bus voltage for the SRM system. By controlling the battery bypass switch, the bus voltage of SRM system can be increased, thereby increasing the system power level. Simulations and experiments based on a four-phase 8/6 SRM demonstrate the effect of the novel converter proposed in this paper.

A Method to Enhance the Global Efficiency of High-Power Photovoltaic Inverters Connected in Parallel

Central inverters are usually employed in large photovoltaic farms because they offer a good compromise between costs and efficiency. However, inverters based on a single power stage have poor efficiency in the low power range, when the irradiation conditions are low. For that reason, an extended solution has been the parallel connection of several inverter modules that manage a fraction of the full power. Besides other benefits, this power architecture can improve the efficiency of the whole system by connecting or disconnecting the modules depending on the amount of managed power. In this work, a control technique is proposed that maximizes the global efficiency of this kind of systems. The developed algorithm uses a functional model of the inverters’ efficiency to decide the number of modules on stream. This model takes into account both the power that is instantaneously processed and the maximum power point tracking (MPPT) voltage that is applied to the photovoltaic field. A comparative study of several models of efficiency for photovoltaic inverters is carried out, showing that bidimensional models are the best choice for this kind of systems. The proposed algorithm has been evaluated by considering the real characteristics of commercial inverters, showing that a significant improvement of the global efficiency is obtained at the low power range in the case of sunny days. Moreover, the proposed technique dramatically improves the global efficiency in cloudy days.

A novel adaptive state of charge estimation method of full life cycling lithium‐ion batteries based on the multiple parameter optimization

AbstractThe state of charge (SoC) estimation is the safety management basis of the packing lithium‐ion batteries (LIB), and there is no effective solution yet. An improved splice equivalent modeling method is proposed to describe its working characteristics by using the state‐space description, in which the optimization strategy of the circuit structure is studied by using the aspects of equivalent mode, analog calculation, and component distribution adjustment, revealing the mathematical expression mechanism of different structural characteristics. A novel particle adaptive unscented Kalman filtering algorithm is introduced for the iterative calculation to explore the working state characterization mechanism of the packing LIB, in which the incorporate multiple information is considered and applied. The adaptive regulation is obtained by exploring the feature extraction and optimal representation, according to which the accurate SoC estimation model is constructed. The state of balance evaluation theory is explored, and the multiparameter correction strategy is carried out along with the experimental working characteristic analysis under complex conditions, according to which the optimization method is obtained for the SoC estimation model structure. When the remaining energy varies from 10% to 100%, the tracking voltage error is <0.035 V and the SoC estimation accuracy is 98.56%. The adaptive working state estimation is realized accurately, which lays a key breakthrough foundation for the safety management of the LIB packs.

Solar Optiverter—A Novel Hybrid Approach to the Photovoltaic Module Level Power Electronics

In this paper, the concept of an Optiverter is proposed as a novel class of photovoltaic (PV) module level power electronics systems. Functionally, the Optiverter is a hybrid technology that combines the ultrawide maximum power point tracking (MPPT) voltage window of the PV power optimizers with the direct ac connectivity and inherent safety of the PV microinverters. Thanks to the advanced multimode control with variable dc-link and the shade-tolerant MPPT algorithm, the proposed Optiverter ensures efficient energy harvest from the PV module in different shading scenarios. To justify the superiority of the concept, the performance of a 300 W prototype of the PV Optiverter is experimentally compared to that of the industrial microinverters in different operation conditions, including an extreme case with opaque shading of two out of three substrings of the PV module.

IKs ion-channel pore conductance can result from individual voltage sensor movements

The IKs current has an established role in cardiac action potential repolarization, and provides a repolarization reserve at times of stress. The underlying channels are formed from tetramers of KCNQ1 along with one to four KCNE1 accessory subunits, but how these components together gate the IKs complex to open the pore is controversial. Currently, either a concerted movement involving all four subunits of the tetramer or allosteric regulation of open probability through voltage-dependent subunit activation is thought to precede opening. Here, by using the E160R mutation in KCNQ1 or the F57W mutation in KCNE1 to prevent or impede, respectively, voltage sensors from moving into activated conformations, we demonstrate that a concerted transition of all four subunits after voltage sensor activation is not required for the opening of IKs channels. Tracking voltage sensor movement, via [2-(trimethylammonium)ethyl]methanethiosulfonate bromide (MTSET) modification and fluorescence recordings, shows that E160R-containing voltage sensors do not translocate upon depolarization. E160R, when expressed in all four KCNQ1 subunits, is nonconducting, but if one, two, or three voltage sensors contain the E160R mutation, whole-cell and single-channel currents are still observed in both the presence and absence of KCNE1, and average conductance is reduced proportional to the number of E160R voltage sensors. The data suggest that KCNQ1 + KCNE1 channels gate like KCNQ1 alone. A model of independent voltage sensors directly coupled to open states can simulate experimental changes in IKs current kinetics, including the nonlinear depolarization of the conductance-voltage (G-V) relationship, and tail current acceleration as the number of nonactivatable E160R subunits is increased.

Experimental Investigation on Buck Converter Using Neuro - Fuzzy Controller

Buck type DC-DC converter circuit topology is non-linear due to their switched circuit structure. Conventional control systems are insufficient to control non-linear systems. Neural Networks have important abilities such as learning, optimizing and adaptability. Fuzzy logic and neural networks are used as an adaptive structure based on the fuzzy logic controller. This adaptive structure adjusts the properties of the fuzzy rules and the characteristics of the control system so that the Neuro-Fuzzy controller can be adapted to all different system conditions. In this study, experimental studies were carried out on the dSPACE experiment platform to show the dynamic performance of the Neuro-Fuzzy controller and the conventional PI controller in different system conditions (such as reference voltage tracking and output load change) of buck type DC-DC converter.

Sliding Mode Output Regulation for a Boost Power Converter

This work deals with the novel application of the sliding mode (discontinuous) output regulation theory to a nonlinear electrical circuit, the so-called boost power converter. This theory has excelled due to the fact that trajectory tracking plays a central role. The control of a boost power converter for the output tracking of a DC biased sinusoidal signal is a challenging problem for control engineers. The main difficulties are the computation of a proper reference signal for the inductor current, and the stabilization of the inductor current dynamics or to guarantee the correct output tracking of the capacitor voltage. With the application of the discontinuous output regulation these problems are solved in this work. Simulations and real time experiments were carried out with an unknown variation of the DC input voltage, where the good output tracking of the capacitor voltage was verified along with the stabilization of the inductor current. The discontinuous output regulation theory has proven to be a suitable tool in the output tracking for the boost power converter.

A 1-MHz-Bandwidth Gm-C-Based Quadrature Bandpass Sigma-Delta Modulator Achieving −153.7-dBFS/Hz NSD With Background Calibration

This paper presents a fifth-order continuous-time Gm-C-based quadrature bandpass sigma-delta ( $\Delta \Sigma$ ) modulator for Internet-of-Things applications. In the presented $\Delta \Sigma $ modulator, a reconfigurable full-scale input amplitude assists the $\Delta \Sigma $ modulator, achieving a wide dynamic range (DR) and a low-noise floor. A following system-level supply voltage and temperature background tracking technique stabilizes the frequency response of the Gm-C-based quadrature bandpass $\Delta \Sigma $ modulator. Furthermore, the 1.5-bit feedback current DAC employs a PN-based semi-self-swapping logic to relax the matching requirement. The prototype $\Delta \Sigma $ modulator was fabricated in a 180-nm CMOS process with an active area of 0.28 mm2. The $\Delta \Sigma $ modulator achieves a total DR of 93.7 dB with the reconfigurable full-scale input amplitude, resulting in a noise spectral density of −153.7 dBFS/Hz with a bandwidth of 1 MHz. The presented $\Delta \Sigma $ modulator consumes 2.0 mW with a power supply of 1.8 V and a sampling frequency of 32 MHz.

LMI-based robust voltage tracking control for a class of renewable energy systems

ABSTRACTThis paper introduces a method of robust voltage tracking control for a class of renewable energy systems, which uses a linear matrix inequality (LMI)-based approach. A remodeling method is introduced where the nonlinear model of the renewable energy system is represented as a nonlinear combination of linear subsystems with state-dependent parameters (the so-called linear state-dependent parameter system model, LSDPM). Next, the remodeling method is applied to a boost converter, a photovoltaic (PV) system, and a wind energy conversion system as examples. A robust output voltage tracking approach is proposed based on the LSDPM. Using Lyapunov’s direct method, controller stability analyses are expressed as LMI formulations. Powerful numerical toolboxes then solve for the controller gains. The advantages of this approach include: i) the generalized remodeling technique is applicable to a wide variety of renewable energy systems; ii) it creates a unified LMI-based design framework for multiple control objectives; iii) it provides numerically solved control gains; and iv) it provides robust tracking control for the multiple objectives of renewable energy systems. Using an LMI-based robust voltage tracking controller is an accurate and effective method of control for many types of renewable energy systems. Finally, practical DSP-based experiments are carried out using the buck converter as an example. The satisfactory results of these experiments verify the theoretical derivations for this control method.

Data-driven multi-inverter cooperative control for voltage tracking and current sharing in islanded AC microgrids

A data-driven cooperative control scheme utilizing additional local and network sensor information is proposed for voltage tracking and current sharing under a cyber-physical system framework. An information-based inverter controller is developed as a replacement for the physical mechanism or model-based method because of uncertainties related to the inverter application scenario, system structure and specifications. To overcome the disadvantages of the reference voltage set-point strategy, an integrated cascade controller is adopted in which the outer loop is a learning controller with a noncausal filter, used to achieve high-precision voltage tracking, and the inner loop is a current consensus regulator implemented by means of nonlinear proportional–integral–derivative (PID) control, used to realize instantaneous value smoothing and output current consensus among a number of inverters. The designed controller does not rely on the plant model, structure or parameters and does not use the droop mechanism; it relies on fully data-driven and distributed (without root nodes or leaders) techniques. This controller design scheme can be uniformly applied for different kinds of distributed generation unit to achieve flexible and expandable microgrid deployment. Plug-and-play and load change capabilities, as well as tolerance to communication constraints, are also verified on the MATLAB/Simulink platform.

Particle filter-based state-of-charge estimation and remaining-dischargeable-time prediction method for lithium-ion batteries

Battery state of charge is a crucial indicator of battery management systems since an accurate estimated state of charge is critical to ensure the safety and reliability of the battery. However, polarization during the discharge process can affect the dischargeable capacity in the state-of-charge definition. Moreover, a nonlinear drop of the state-of-charge may lead to misjudgment of the remaining-dischargeable-time. To address these issues, the voltage-based state of charge is defined to reduce the effects of polarization and reflect the upper bound of the remaining capacity of the battery. This paper proposes a particle filter based open circuit voltage online estimation method to achieve the voltage-based state of charge. On this basis, an open-loop remaining-dischargeable-time prediction algorithm using the voltage-based state of charge is introduced. Static and dynamic tests are presented to identify battery model parameters as well as the relationship between available capacity and voltage-based state of charge. Two definitions of the state of charge definition are applied in the prognostics architecture. Results are compared and evaluated concerning the accuracy of the voltage tracking and the relative error of the remaining-dischargeable-time prediction. The comparison results show that prognostics via voltage-based state of charge has a lower prediction relative error under different current and temperature conditions. Therefore, the voltage-based state of charge is more suitable for the remaining-dischargeable-time forecast.

A Compact, Voltage-Mode Type-I PLL With Gain-Boosted Saturated PFD and Synchronous Peak Tracking Loop Filter

Despite their inherent stability, area-efficient loop filters, and insensitivity to phase-frequency detector nonlinearity and dead-zone, type-I phase-locked loops (PLLs) are used infrequently because of two major limitations—limited lock-range and large reference spurs. This paper introduces a type-I PLL that takes advantage of the inherent benefits of the architecture, while tackling its limitations by means of gain boosting in the forward path for lock-range improvement and synchronous peak tracking of the voltage-controlled oscillator control voltage for reference spur reduction. Sampling in the loop filter changes the loop dynamics, and methods to accurately predict the closed-loop response, starting from state-space equations, are provided. A digital-friendly, voltage-mode topology is proposed that does not need charge pumps or opamps. A prototype 2.2–2.8-GHz PLL occupies a core area of 0.12 mm2 in 0.13- $\mu \text{m}$ CMOS and achieves −103.4 dBc/Hz in-band phase noise, −65-dBc reference spur, and 2.5- $\mu \text{s}$ worst-case lock-time while consuming 6.8 mW from a 1.2-V supply.

Advanced Drive System for DC Motor Using Multilevel DC/DC Buck Converter Circuit

This paper presents a new topology of clamped diode multilevel DC/DC buck power converter for a DC motor system. The proposed converter circuit consists of four cascaded MOSFET power switches with three clamping diodes and four voltage sources (voltage cells) connected in series. The main objective of the new topology is to reduce current ripples and torque ripples that are associated with hard switching of the traditional chopper circuit. When the voltage profile of this converter is applied on a DC motor, it positively affects the performance of the DC motor armature current and the generated dynamic torque. The output voltage of the proposed topology shows an adequate performance for tracking of reference voltage with small ripples that are normally reflected into smaller EMI noise. Moreover, it has been shown that the operation of the DC motor with the newly proposed chopper topology greatly decreases the motor armature current ripples and torque ripples by a factor equal to the number of the connected voltage cells. Both simulation and experimental results on a prototype of a DC motor are provided to validate the proposed chopper topology. The results prove that the mechanical vibration and acoustic noises have also been reduced roughly by 13 dBs with a continuous variable input voltage pattern.

Intermediate Voltage Regulation for Total Harmonic Distortion Reduction of Two-Stage Inverters Under Model Predictive Control Scheme via Observers

Two-stage inverters composed of the front DC-DC stage and the rear DC-AC stage are broadly employed for the current tracking. Structures vary according to the different control objectives and application occasions. The concerning structure in this paper is made up of the buck-boost converter stage and the single-phase inverter stage. The simulation results show that the intermediate voltage will affect the total harmonic distortion (THD) values. Moreover, under the same other conditions, a minimum THD can be attained by regulating the intermediate voltage. In this paper, a time-varying observer is introduced for the interface parameters identification based on the robustness of model predictive control (MPC) scheme. Combined with the input voltage, the reference current and grid voltage, the optimal intermediate voltage with lower THD can be determined. Besides, a cascaded proportional-integral (PI) MPC scheme is adopted for the intermediate voltage tracking without steady-state error. Meanwhile, based on the accurate interface parameters obtained by the observer, an adaptive MPC scheme is applied for the output current tracking. The simulation results on MATLAB/Simulink and experimental results on FPGA test bench validate the accuracy of the voltage determination and the effectiveness of the control scheme.

Robust control of mismatched buck DC–DC converters by PWM-based sliding mode control schemes

In this paper, two control methods are proposed to control mismatched dc–dc buck converters. In the first method, called Method I, a multiple surface sliding mode control is proposed to handle mismatched load uncertainty. A major problem associated with multiple surface sliding mode control viz. ‘explosion of terms’ is handled by a disturbance observer. Another method, Method II, based on simultaneous state and disturbance observer is proposed as a further improvement over Method I in terms of sensor requirement. The practical stability of the proposed schemes is proved. The performance of both the methods are assessed for regulation and tracking of output voltage under various uncertainties and is compared with a method based on extended state observer. It is shown by simulation and experimentation that the transient and steady state performance of both the controllers are satisfactory.