Voltage Error Research Articles

A novel parameter adaptive method for state of charge estimation of aged lithium batteries

The state of charge (SOC) of lithium battery is an important evaluation index for battery management system (BMS) in electric vehicles. In this study, a novel parameter adaptive method adapted to battery aging has been proposed for SOC estimation. In order to accurately estimate the SOC, the Thevenin model was firstly to established. Model parameters were then identified based on the recursive least square (RLS) method. In order to improve the accuracy and the self-update ability of the RLS method, an improved RLS method with an activation zone (RLS-AZ) was developed. The activation zone refers to an interval according to the error between the predicted value and measured value of the terminal voltage. When the error is in the interval, the covariance matrix of RLS is reset to the pre-defined value. In order to consider the influence of battery aging on the evolution of open circuit voltage (OCV), a back-propagation neural network (BPNN) between OCV and the SOC and capacity was established. Based on the identified parameters above, the unscented Kalman filter (UKF) was applied to estimate the SOC under degradation. The robustness and accuracy of the proposed method was verified, and the results show that the error of terminal voltage estimated by improved RLS method is reduced to one order of magnitude compared with the original RLS method. The SOC estimation error for the aged battery is less than 0.8% even if given an inaccurate initial value for estimator.

Adaptive linear neuron control of three-phase shunt active power filter with anti-windup PI controller optimized by particle swarm optimization

In the present paper, particle swarm optimization technique (PSO) is used to tune anti-windup PI controller gains for DC bus voltage control of the shunt active power filter by offline simulation. The main advantage of the PSO tuning algorithm is to accurately estimate PI controller parameters and overcome the complexity of analytical calculation approaches as well as classical tuning methods. The sum of the total harmonic distortion of source currents and the DC bus's voltage error are used as a fitness function. The reference current is obtained using an artificial neural network named adaptive linear neuron (ADALINE). Three ADALINEs are trained online using the least mean square algorithm (LMS). The proposed system is designed by MATLAB/Simulink and validated experimentally through the dSPACE DS1104 platform. The analysis is done for various conditions, and the obtained results demonstrate the effectiveness of the controller in terms of performance, efficiency, and power quality enhancement.

Load-Independent Voltage Balancing of Multi-Level Flying Capacitor Converters in Quasi-2-Level Operation

Quasi-2-level (Q2L) operation of multi-level bridge-legs, especially of flying-capacitor converters (FCC), is an interesting option for realizing single-cell power conversion in applications whose system voltages exceed the ratings of available power semiconductors. To ensure equal voltage sharing among a Q2L-FCC’s switches, the voltages of a Q2L-FCC’s minimized flying capacitors (FCs) must always be balanced. Thus, we propose a concept for load-independent FC voltage balancing: For non-zero load current, we use a model predictive control (MPC) approach to identify the commutation sequence of the individual switches within a Q2L transition that minimizes the FC or cell voltage errors. In case of zero load current, we employ a novel MPC-based approach using cell multiple switching (CMS), i.e., the insertion of additional zero-current commutations within a Q2L transition, to exchange charge between the FCs via the charging currents of the switches’ parasitic capacitances. Experiments with a 5-level FCC half-bridge demonstrator confirm the validity of the derived models and verify the performance of the proposed load-independent balancing concept.

State-of-charge estimation for Lithium-Ion batteries using Kalman filters based on fractional-order models

The accuracy of state of charge estimation results will directly affect the performance of battery management system. Due to such, we focus in this article on the SOC estimation of Lithium-Ion batteries based on a fractional second-order RC model with free noninteger differentiation orders. For such an estimation, three Kalman filters are employed: the adaptive extended Kalman filter (AEKF), extended Kalman filter (EKF), and Unscented Kalman Filter (UKF). The Fractional-Order Model (FOM) parameters and differentiation orders are identified by the Particle Swarm Optimization (PSO) algorithm, and a pulsed-discharge test is implemented to verify the accuracy of parameter identification. The output voltage error of the FOM model is much less than that of the Integer-Order Model (IOM). The FOM model has lower root-mean square error (RMSE), the mean absolute error (MAE), and the maximum absolute error (MAXAE) of SOC estimation than the IOM model during the SOC estimation regardless of AEKF, EKF or UKF. Experimental results show that the FOM can simulate the polarisation on effect and charge–discharge characteristics of the battery more realistically, demonstrating that the SOC estimation based on FOM is more accurate and promising than the one based on the IOM when using the same Kalman filters.

Holistic 1D Electro-Thermal Model Coupled to 3D Thermal Model for Hybrid Passive Cooling System Analysis in Electric Vehicles

Thermal management is the most vital element of electric vehicles (EV) to control the maximum temperature of module/pack for safety reasons. This paper presents a novel passive thermal management system (TMS) composed of a heat sink (HS) and phase change materials (PCM) for lithium-ion capacitor (LiC) technology under the premise that the cell is cycled with a continuous 150 A fast charge/discharge current rate. The experiments are validated against numerical analysis through a computational fluid dynamics (CFD) model. For this purpose, a comprehensive electro-thermal model based on an equivalent circuit model (ECM) is designed. The designed electro-thermal model combines the ECM model with the thermal model since the performance of the LiC cell highly depends on the temperature. Then, the robustness of the model is evaluated using a precise second-order ECM. The extracted parameters of the electro-thermal model are verified by the experimental results in which the voltage and temperature errors are less than ±5% and ±4%, respectively. Finally, the thermal performance of the HS-assisted PCM TMS is studied under the fast charge/discharge current rate. The 3D CFD results exhibit that the temperature of the LiC when using the PCM-HS as the cooling system was reduced by 38.3% (34.1 °C) compared to the natural convection case study (55.3 °C).

Efficiency Maximization of Grid-Connected Tidal Stream Turbine System: A Supervisory Energy-Based Speed Control Approach with Processor in the Loop Experiment

Permanent magnet synchronous generator (PMSG) with a back-to-back power converter is one of the commonly used technologies in tidal power generation schemes. However, the nonlinear dynamics and time-varying parameters of this kind of conversion system make the controller computation a challenging task. In the present paper, a novel intelligent control method based on the passivity concept with a simple structure is proposed. This proposed strategy consists of passivity-based speed control (PBSC) combined with a fuzzy logic method to address the robustness problems faced by conventional control techniques such as proportional-integral (PI) control. The proposed method extracts the maximum power from the tidal energy, compensates for the uncertainty in a damped way where the entire dynamics of the PMSG are considered when designing the control law. The fuzzy logic controller is selected, which makes the proposed strategy intelligent to compute the damping gains to make the closed-loop passive and approximate the unstructured dynamics of the PMSG. Thus, the robustness property of the closed-loop system is considerably increased. The regulation of DC voltage and reactive power to their desired values are the principal objectives of the present work. The proposed method is used to control the machine-side converter (MSC), while a conventional PI method is adopted to control the grid-side converter (GSC). Dynamic simulations show that the DC voltage and reactive power errors are extremely reduced with the proposed strategy; ±0.002 for the DC-link voltage and ±0.000015 in the case of the reactive power. Moreover, the lowest steady-state error and better convergence criterion are shown by the proposed control (0.3 × 10−3 s). Generally, the proposed candidate offers high robustness, fast speed convergence, and high efficiency over the other benchmark nonlinear strategies. Moreover, the proposed controller was also validated in a processor in the loop (PIL) experiment using Texas Instruments (TI) Launchpad.

Air flow and pressure optimization for air supply in proton exchange membrane fuel cell system

To study the air supply of proton exchange fuel cell (PEMFC) system to avoid air starvation, a proton PEMFC system model mainly including the stack (30 kW, 240 cells, 190 cm2 activation area) and air supply system is developed. Model's average relative errors of output mass flow and pressure are 2.9% and 0.756% respectively. Model' saverage relative error of output voltage is 2.678%. Subsequently, the influence of operating parameters (air excess ratio and air pressure) on output performance (dynamic response of stack voltage and on net output power of PEMFC system) is analyzed. When air excess ratio is 4 and pressure is 1.7 bar respectively, voltage's dynamic response reaches the best level. Optimal pressure to output maximum net power is always located in lower value region and optimal flow shows a tendency to be gradually larger as current increases. Then the optimization model to determine working points of each parameter aiming at comprehensively improve voltage's dynamic response and net output power of PEMFC system simultaneously is presented. Based on this, an optimized air supply strategy of replenishing air upon loading is innovatively proposed. This research can be further used to guide the development of control strategy of air supply.

Adaptive On-Time Control Buck Converter with a Novel Virtual Inductor Current Circuit

This study presents a new virtual inductor current circuit to reduce circuit complexity, which is not necessary to sense inductance current directly. The buck converter was designed to produce an output voltage of 1.0–2.5 V for a 3.0–3.6 V input voltage. The load current range was from 100 mA to 500 mA. It was simulated and verified by SIMPLIS and MathCAD. The simulation results of this buck converter show that the voltage error is within 1%, and the recovery time is smaller than 2 ms for step-up and step-down load transients. Additionally, it achieves less than 26 mV overshoot at full-load step transient response. The circuit topology would be able to fabricate using TSMC 0.35 mm 2P4M CMOS technology. The control mechanism, implementation, and design procedure are presented in this paper.

Adaptive current harmonics suppression strategy for grid-tie inverters

Since the observed angle of a phase-locked loop (PLL) is relatively accurate even under distorted grid conditions, the mathematical model of the voltage errors caused by the switching modulation and the dead-time effect are derived as a function of the grid voltage angle in this paper. Based on the model analysis, an adaptive compensation algorithm is proposed to suppress the grid-side current harmonics in three-phase converters. The proposed algorithm fits the unmeasurable voltage errors by a truncated Fourier series expansion, and then takes it as an equivalent disturbance in the current control loop to achieve harmonic compensation. By the feed-forward compensation, the design and tuning of the controller parameters are simplified and separated from the dynamic performance. In addition, the controller can adapt to the grid frequency variation by updating the grid voltage angle with the PLL block. To reduce the computational burden, a simplified version of the proposed method is also presented. Simulation and experiment results show that the proposed methods can suppress the current harmonics and achieve better performance in terms of total harmonic distortion, strong robustness and insensitivity to the grid frequency variations, compared with the traditional PI control or repetitive control strategy.

Inverter Nonlinearity Compensation Through Deadtime Effect Estimation

This article proposes a method to compensate for the nonlinearity of an inverter through the estimation of the deadtime effect. The deadtime effect varies with the manufacturing tolerance of the inverter circuit itself and operating conditions, such as conducting current, dc-link voltage, and temperature. For the accurate compensation of the nonlinearity, the effect of the deadtime should be estimated in realtime. That effect on the control of the inverter is significantly affected by the pulsewidth modulation (PWM) scheme because the deadtime occurs only at the switching instant of the inverter, and the PWM scheme solely decides the switching. The proposed method exploits the difference of voltage error from the deadtime effect according to different PWM schemes. By comparing the effects with two different PWM schemes, namely continuous PWM and discontinuous PWM, the voltage error to a specific inverter caused by the deadtime can be identified. Several experimental tests are carried out to verify the validity of the proposed method. The results reveal that the voltage error due to the deadtime can be identified in the range of 100 mV at 300-V dc link. It is equivalent to 30 ns resolution in deadtime.

Improving battery thermal behavior and consistency by optimizing structure and working parameter

• An electro-thermal model for an air-cooled pack is established. • Effect of temperature difference on the branch current distribution is included. • Effect of pack thermal behavior on its SOC difference is considered. • Prediction precision of the proposed model is validated. • Thermal behavior and consistency of pack are raised by optimizing structure and air speed. Improving battery consistency is the one of the main goals of battery management system (BMS). As its subsystem, the battery thermal management system (BTMS) should try to accomplish this aim. However, the traditional design of the BTMS considers only the battery temperature and temperature difference, and does not considers their influence on the battery consistency. This study establishes an electro-thermal model for an air-cooled pack. The coupled model can accurately predict the electrical and thermal behavior of the pack. At the pack level, the maximum prediction error of the terminal voltage is 0.58 V, and the maximum average relative error of temperature is only 1.73%. The coupled model is used to optimize the air channel and air speed. In order to improve consistency of the battery, the difference of state of charge (SOC) is added as the evaluation parameter in the optimization of the air channel and air velocity. The optimization process of the structure is divided into two phase and the dual DOEs (design of experiment) are applied. The DOE results are analyzed by the range and variance to select the structure with the best comprehensive performance. Compared with the original air channel and air velocity, the optimized air channel with the new air velocity reduces the maximum cell temperature and temperature difference by 2.67 °C and 1.11 °C respectively, makes the SOC difference falls from 0.37% to 0.29% in a discharging process, under the severest design condition. Moreover, the optimized pack is proved to have a better performance under other conditions.

Enhancement of Disturbance Rejection Capability in Dual Three-Phase PMSM System by Using Virtual Impedance

Dual three-phase permanent magnet synchronous machine systems usually suffer from small impedance to voltage disturbance such as inverter voltage errors and back EMF harmonics. This article proposes a virtual impedance technique to increase the machine equivalent impedance and, thus, enhance the disturbance rejection capability of the system. This enhancement can contribute to current harmonic suppression in a wide range of frequencies. In addition, the introduction of virtual impedance can also reduce the system sensitivity to parameter variation, which helps to suppress the dynamic current overshoot, pulsating, and cross-coupling effect caused by the parameter mismatch. Simulation and experimental results have verified the effectiveness of the proposed control strategy.

An efficient dynamic power management model for a stand-alone DC Microgrid using CPIHC technique

The power generation using solar photovoltaic (PV) system in microgrid requires energy storage system due to their dilute and intermittent nature. The system requires efficient control techniques to ensure the reliable operation of the microgrid. This work presents dynamic power management using a decentralized approach. The control techniques in microgrid including droop controllers in cascade with proportional-integral (PI) controllers for voltage stability and power balance have few limitations. PI controllers alone will not ensure microgrid’s stability. Their parameters cannot be optimized for varying demand and have a slow transient response which increases the settling time. The droop controllers have lower efficiency. The load power variation and steady-state voltage error make the droop control ineffective. This paper presents a control scheme for dynamic power management by incorporating the combined PI and hysteresis controller (CPIHC) technique. The system becomes robust, performs well under varying demand conditions, and shows a faster dynamic response. The proposed DC microgrid has solar PV as an energy source, a lead-acid battery as the energy storage system, constant and dynamic loads. The simulation results show the proposed CPIHC technique efficiently manages the dynamic power, regulates DC link voltage and battery’s state of charge (SoC) compared to conventional combined PI and droop controller (CPIDC).

Aggregation of Radial Distribution System Bus with Volt-Var Control

The high penetration of the distributed energy resources (DERs) encourages themselves to implement grid-supporting functions, such as volt-var control. The quasi-static time-series (QSTS) simulation is an essential technique to evaluate the impact of active DERs on the grid. Meanwhile, the increase of complexity on the circuit model causes a heavy computational burden of QSTS simulation. Although circuit reduction methods have been proposed, there have been few methods that can appropriately handle the distribution system (DS) with multiple voltage control devices, such as DERs implementing volt-var control. To address the remaining issues, this paper proposes an offline bus aggregation method for DS with volt-var control. The method determines the volt-var curve for the aggregated bus on the basis of historical data to reduce error in the aggregated model, and its offline process solves the computational convergence issue concerned in the online one. The effectiveness of the proposed method is validated in the simulation using a Japanese low-voltage DS model. The simulation results show that the proposed method can reduce the voltage error and computational time. Furthermore, the versatility of the proposed method is verified to show the performance does not heavily depend on how to select historical data for model-building.

Effects analysis on active equalization control of lithium-ion batteries based on intelligent estimation of the state-of-charge

In this paper, the characteristics analysis results of lithium-ion battery show that the essence of the inconsistency of lithium-ion battery is State-Of-Charge (SOC) inconsistency. Therefore, the disparity of SOC can be used to describe the battery inconsistency degree and investigate the equalization control strategy of lithium-ion battery. Firstly, Extended Kalman Filter (EKF) algorithm is proposed to estimate the SOC on the basis of the Ampere-Hour integral and open circuit voltage. Then, the Simscape battery model is established to estimate battery parameters, and the HPPC experiment is employed to verify the SOC estimation precision. Moreover, based on the battery SOC inconsistency laws, the battery equalization control strategy is presented. Finally, the experimental bench is set up to validate the effectiveness of the equalization strategies. Simulation results depict that with the active equalization, the dispersion of SOC drops from 9.4% to 0.84% during charging phase, while the dispersion of SOC drops from 7.4% to 4.12% and the dispersion of voltage drops from 8.54% to 0.71% during discharging phase. The experimental results show that the maximum SOC estimation error is about 4%, so this SOC estimation method meets the accuracy requirement; the 6 batteries are fully charged at the same time with charging equalization, the voltage error is within 15 mV and the voltage variance is within 2%; discharging processes of the 6 batteries are over at the same time with discharging equalization, voltage error is below 15 mV and the voltage variance is below 2%. These results indicate that active equalization control in this paper not only can improve cell inconsistency but also can improve the energy utilization of the battery pack in the process of charging and discharging.

Active voltage balancing strategy of asymmetric stacked multilevel inverter

Multilevel inverters (MLI) play an important role in AC applications and are undergoing continuous development in topology and control. In higher levels inverters, conventional MLIs have high components count which calls for modification of these topologies to obtain the same number of levels with fewer components to reduce cost and size. Balancing of the capacitors voltages is crucial for the operation of the MLI and it becomes more challenging in higher levels. This paper presents an active voltage balancing strategy for a reduced switch count five-leve topology which is the asymmetric stacked multilevel inverter (ASMLI). The ASMLI uses fewer components than the conventional MLIs when used in their five-levelconfiguration. The proposed active voltage balancing strategy uses simple measurements and logic to assure a balanced capacitors voltages during steady state and transients. The performance was examined and compared based on two modulation techniques with LCL filter and RL load using MATLAB/Simulink. The results show that the active voltage balancing strategy can trace all capacitors voltages to the reference value simultaneously with less than 1% voltage error, fast dynamic response, and an acceptable total harmonic distortion (THD) which allows the proposed setup to be an available option for medium voltage applications.<br /><div> </div>

Three-Phase Induction Motor Controller Design Based on Hysteresis Voltage Control

This paper describes a controller for Three-Phase Induction Motor. Induction motor is an electromechanical actuator widely used due to its reliability and relatively low maintenance cost. However, the control problem of an induction motor is complex due to nonlinearities, load torque perturbation, and parameter uncertainties. An element included in this study is voltage source control, which is to control the voltage fed from three-phase inverter to Three-Phase Induction Motor. Hysteresis Controller was proposed in this paper to minimize voltage error. Hysteresis controller is seen as an input – output phase lag corrector. The implementation of the designed hysteresis controller is performed in simulation using MATLAB/Simulink. The result proved that the proposed controller design can minimize the line voltage error of the induction motor, preventing the line voltage from being kept low hence avoiding excess current at low speeds.

Design of sliding mode adaptive DC-DC converter based on function approximation

The output power and voltage of solar photovoltaic power generation are easily affected by climate and load changes, so it is necessary to use DC-DC converter at its output to provide stable output voltage. DC-DC converter is a time-varying nonlinear system. When the output load of the converter varies widely, the output waveform distortion and dynamic response speed of the DC-DC converter will slow down. The essence of sliding mode control is a kind of switch control method, and the DC-DC converter needs the switch of switch tube to realize voltage regulation. In this paper, a sliding mode adaptive control strategy based on orthogonal polynomial function approximation is proposed, and Laguerre polynomial is selected as the basis function of DC-DC transformation system. The output voltage error and its first derivative of the system are taken as the input of the network, and the output of the network is taken as the approximation term of the system uncertainty, and the network weight is updated according to the adaptive law. Through simulation and comparison, the adaptive controller designed in this paper is superior to the ordinary sliding mode controller in reducing chattering, adaptive load change and reducing the influence of system interference.

Fault Location and Restoration of Microgrids via Particle Swarm Optimization

This aim of this work was to develop an integrated fault location and restoration approach for microgrids (MGs). The work contains two parts. Part I presents the fault location algorithm, and Part II shows the restoration algorithm. The proposed algorithms are implemented by particle swarm optimization (PSO). The fault location algorithm is based on network connection matrices, which are the modifications of bus-injection to branch-current and branch-current to bus-voltage (BCBV) matrices, to form the new system topology. The backward/forward sweep approach is used for the prefault power flow analysis. After the occurrence of a fault, the voltage variation at each bus is calculated by using the Zbus modification algorithm to modify Zbus. Subsequently, the voltage error matrix is computed to search for the fault section by using PSO. After the allocation of the fault section, the multi-objective function is implemented by PSO for optimal restoration with its constraints. Finally, the IEEE 37-bus test system connected to distributed generations was utilized as the sample system for a series simulation and analysis. The outcomes demonstrated that the proposed optimal algorithm can effectively solve fault location and restoration problems in MGs.

Lithium-Ion Battery SOC Estimation Based on Adaptive Forgetting Factor Least Squares Online Identification and Unscented Kalman Filter

In order to improve the estimation accuracy of the battery state of charge (SOC) based on the equivalent circuit model, a lithium-ion battery SOC estimation method based on adaptive forgetting factor least squares and unscented Kalman filtering is proposed. The Thevenin equivalent circuit model of the battery is established. Through the simulated annealing optimization algorithm, the forgetting factor is adaptively changed in real-time according to the model demand, and the SOC estimation is realized by combining the least-squares online identification of the adaptive forgetting factor and the unscented Kalman filter. The results show that the terminal voltage error identified by the adaptive forgetting factor least-squares online identification is extremely small; that is, the model parameter identification accuracy is high, and the joint algorithm with the unscented Kalman filter can also achieve a high-precision estimation of SOC.