Step Load Change Research Articles

SIMULATION OF TORQUE VARIATIONS IN A DIESEL ENGINE FOR LIGHT HELICOPTERS USING PI CONTROL ALGORITHMS

This article presents the results of simulation research of a diesel engine for a light helicopter. The simulations were performed using the 1D software AVL Boost RT. The engine model includes elements such as cylinders, turbine, compressor, inlet and outlet valves, ambient environment definition, and fuel injection control strategy. The simulations aimed to evaluate the engine's response to step changes in the main rotor load, both increasing and decreasing power demands. Parameters analyzed included power deviation, torque, engine rotational speed, and stabilization time of the main rotor rotational speed. All tests were conducted using a single set of PI controller settings. The results demonstrate that these parameters are dependent on the magnitude of the step change in the main rotor load demand. The study compares the maximum engine rotational speed deviation from the nominal value for both increasing and decreasing main rotor load demands. The findings indicate that using PI regulator to control rotational speed in the diesel engine in a light helicopter significantly depends on the change in the load torque on the rotor.

Data‐driven predictive control of perturbed buck converters using a modified iterative feedback tuning algorithm

AbstractThe most challenging aspect of utilizing model predictive controllers (MPCs), particularly those involving power electronic applications, is the extraction of a model that accurately represents the behavior of the studied system. Concerning the use of power electronic applications, as long as an MPC is used, adjusting the controller parameters brings difficulties. In addition, as the number of elements increases, it becomes harder to get the best control law out of the model. To do away with the need for model extraction, this study presents an offline data‐driven approach in conjunction with the MPC that can optimally adjust the MPC parameters based on the iterative feedback tuning (IFT) algorithm called the iterative feedback predictive controller (IFPC). The proposed method eliminates concerns regarding selecting an optimal number of algorithm iterations, thereby reducing operating costs, by introducing a modified IFT called feedback‐based IFPC (FIFPC) while simultaneously achieving optimal MPC parameters. The proposed method is applied to a constant voltage load (CVL) connected less‐than‐ideal buck converter, that is, one with perturbed filter elements and variable loads. A robust stability analysis (RSA) is performed under normal operating conditions to investigate the robustness behavior of the proposed controller. Simulation studies are presented to evaluate the proposed controller under different scenarios, such as step and abrupt load changes and measurement noise, compared with the well‐known model‐based and data‐enabled predictive controller (DeePC) approaches in the MATLAB/Simulink environment.

Study of dynamic performance of PEMFC-based CCHP system in a data center based on real-time load and a novel synergistic control method with variable working conditions

In this paper, the dynamic performance of Proton Exchange Membrane Fuel Cell-based Combined Cooling Heating and Power (PEMFC-based CCHP) system combined with a data center real-time load is studied. A novel synergistic control method is proposed to achieve optimization of energy flow between system units under fluctuating load. First, the off-design working condition models of PEMFC-based CCHP system are constructed. The delay in the changes of data center temperature is considered because of the thermal inertia under dynamic conditions. Second, the dynamic performance of PEMFC-based CCHP system to step changes of data center load is analyzed. Third, to further reveal the energy flow between units, the units output under varying load conditions are compared under the constraints of power and refrigeration supply. Finally, the dynamic performance of PEMFC-based CCHP system under the traditional control method of following electric load are revealed. A novel synergistic control method for the PEMFC-based CCHP system is proposed by refining the traditional method to optimize the energy flow between units. The result presents that the average energy efficiency reaches 78.29 %. Compared with the following electric load method, the energy efficiency is increased by 6.02 %. The response time of synergistic control method is 27.0 ms. Improved energy efficiency and fast response have been achieved.

Thermal Management of Proton‐Exchange Membrane Fuel Cells with Enhanced Fuzzy Control via an Improved Whale Optimization Algorithm

Proton exchange membrane fuel cells (PEMFCs) require an appropriate operating temperature to achieve high performance and longevity. In addressing the critical need for effective thermal management in PEMFCs for vehicle propulsion systems, this study has developed and introduced a novel thermal management system model equipped with dual‐cooling loops. Addressing the issues of slow response and poor dynamic performance inherent in traditional control strategies, as well as the computational complexity that hinders the practical application of existing advanced control strategies, this research proposes a fuzzy proportional‐integral‐derivative (PID) controller optimizing the improved whale optimization algorithm (IWOA‐FPID) aimed at enhancing fan side control. By simulating step changes in current load and designing dynamic operating conditions based on the most basic and simple energy management system, the performance of IWOA‐FPID in temperature control is validated. The final results indicate that the IWOA‐FPID strategy significantly outperforms existing control methods, notably reducing adjustment time and minimizing temperature overshoot to ≈0.5 K. The proposed framework achieves efficient temperature control, highlighting its potential for broader application in vehicular fuel cells and offering a promising solution to the challenges of PEMFC thermal management.

Design of Fuzzy Logic based Adaptive Active Power Controller to Enhance Power sharing among DGs in an Autonomous Microgrid

This paper presents the design of an adaptive active power controller to enhance the power-sharing capabilities of distributed generators (DGs) in an autonomous microgrid. Each DG in an autonomous microgrid consists of a droop-controlled inverter to control active and reactive power by regulating frequency and voltage correspondingly. The high droop gain can be used in the power controller to encourage faster power sharing among the DGs. However, high droop gain can cause undamped growing oscillations during load fluctuations or generation losses. During such events, attaining faster power-sharing between DGs using high droop gains is difficult. So, the problem with an autonomous microgrid is the conflict between faster power sharing and stability. Stability needs to be compromised to attain quicker power sharing and vice versa. Hence, to achieve power-sharing swiftly with high droop gain and to diminish the growing oscillations caused, this paper proposes a fuzzy logic-based adaptive active power controller (FLAPC). The proposed FLAPC is adaptive and easy to implement. It offers faster power sharing for different values of droop gains and step change in load. The FLAPC is developed in MATLAB 2018a/Simulink environment, and time domain simulations are performed to see the efficacy of the proposed controller. The results of time domain simulations are compared with a droop controller without any additional controller, conventional lead-lag power system stabilizer, and proposed controller for step change in load at different droop gains. The results show that the proposed controller enhances the power-sharing performance and also ameliorates the system’s stability by reducing the settling time and overshoot in active power responses of DGs.

Comparison of the MPPT command based on the PSO, P&O, and IncCond algorithm implemented in Dspace

Several algorithms have been offered to track the maximum power point when we have one maximum power point. In this paper, we will propose an improved maximum power point tracking method for the photovoltaic system that utilizes a modified PSO algorithm. The main advantage of the method is the decreasing of the steadystate oscillation (to practically zero) once the maximum power point is located. moreover, the proposed method has the ability to track the maximum power point under extreme environmental conditions. To evaluate the effectiveness of the proposed method, MATLAB simulations are carried out under very challenging circumstances, namely step changes in irradiance and step changes in load. Finally, its performance is compared with the «perturbation and observation” and incremental conductance. The results obtained were validated by a PIL (Processor In the Loop) co-simulation using the DSpace 1104 card.

Analysis, Modeling and Cascade Operation of Wind Energy Fed Dual Active Bridge Converter Operating in Extended Phase Shift and Single Phase Shift Modes: A Comparative Study

In this work, cascade control of wind energy conversion System (WECS) fed Dual Active Bridge (DAB) converter is presented. The Permanent Magnet Synchronous Generator (PMSG) is used to feed the DAB. The real time wind speed data of Muppandal, Tamilnadu, India is fed to the PMSG. The DAB is operated in Extended Phase Shift (EPS) and Single-Phase Shift (SPS) control modes. An outer voltage controller in cascade with an inner current controller is used for closed loop operation of the DAB. The proposed controller is tested for small wind speed variations (13 m/s to 10 m/s) with a step load change and wide changes in wind speed (13 m/s to 8 m/s) accompanied with a step load change. DAB controls the power flow from the WECS to resistive load and its power carrying capability when controlled via the proposed controller is exhibited in the presented work. The proposed configuration controlled via the new cascade EPS controller draws lower power (100 Watts) and offers superior efficiency (85.10%) when compared with cascade SPS controlled microgrid configuration. The cascade controller is tested in MATLAB/Simulink environment and a prototype of DAB is developed in lab for which the cascade controller is tested through the TI-Piccolo-F280049 microcontroller.

Detailed Controller Synthesis and Laboratory Verification of a Matching-Controlled Grid-Forming Inverter for Microgrid Applications

Grid-forming inverters are the essential components in the effort to integrate renewable energy resources into stand-alone power systems and microgrids. Performance of these inverters directly depends on their control parameters embodied in the controller. Even the most conscientiously designed controller will exhibit suboptimal performance upon implementation due to the presence of parasitic elements in the existing hardware. Hence, the controller has to be tuned and optimized. In the present article, the process of implementation, laboratory verification, and tuning of a matching-controlled grid-forming inverter is presented. In order to assess the efficiency of the grid-forming controller, its operation has been tested and analyzed in blackstart, steady state, and transient operation. For this purpose, a systematic sensitivity analysis has been conducted and the control parameters have been tuned in laboratory tests. The laboratory results verify proper operation of a 7 kW grid-forming inverter in all three test scenarios. After applying the proposed method on the tested grid-forming inverter in steady state operation, total harmonic distortion (THD) of the output voltage is less than 0.5% for its practical loading range (maximum THD is less than 1% in no-load condition). The system is able to blackstart and supply the loads. Finally, the studied grid-forming inverter is stable in the presence of severe step load changes and disturbances, i.e., voltage overshoot is managed well and compensated for with a low settling time using this approach.

An improved transient performance boost converter using pseudo-current hysteresis control

This paper introduces an enhanced low transient voltage and fast transient response boost converter. It uses a hysteresis-controlled circuit fed by a voltage signal from a rail-to-rail current sensor, resulting in improved efficiency, and transient response. The converter is designed using Taiwan semiconductor manufacturing company (TSMC) 0.18 µm CMOS 1P6M technology, delivers an output voltage of 1.8 V while operating with an input voltage range of 0.5 V to 1 V and supports an output load current range of 10 to 100 mA. The key contributions of this paper are: i) introducing a new boost converter architecture employing pseudo-current hysteresis-controlled (PCHC) techniques, ii) incorporating voltage and current loops into the proposed architecture, and iii) demonstrating superior transient performance. Experimental measurements reveal a peak power efficiency of 98.6% at 10 mA and transient times of 15.4 µs and 11.8 µs for a step load change from 10 to 100 mA and back to 10 mA, respectively, with transient voltages of 51 mV. The presented boost converter outperforms in terms of performance, compared to previous works using the figure of merit (FOM) formula.

A Consensus-Based Distributed Secondary Control Optimization Strategy for Hybrid Microgrids

In this paper, a new consensus-based distributed secondary control (DSC) strategy is proposed for frequency control, dc-voltage regulation, and optimal dispatch (OD) in isolated hybrid ac/dc-microgrids (HMGs). At the same time, all the units are maintained within limits. The proposed control scheme dispatches the distributed generators (DGs) within the microgrid in compliance with the Karush-Kuhn-Tucker (KKT) conditions of a linear optimal power flow (OPF) formulation. Furthermore, the power through the interlinking converters (ICs) is also dispatched to help minimize the total operation cost of the microgrid. The controllers rely on local measurements and information from neighbouring devices at both sides of the microgrid (DGs and ICs). Thus, unlike conventional methods, the microgrid is considered a single entity and not as three independent systems interacting with one another, and the OD is calculated considering both the ac-DGs and dc-DGs. Extensive simulations demonstrate a good performance of the controller amid load step changes and unit congestion, driving the system to an optimal economic operation.

Fuzzy logic based vector control of multi-phase permanent magnet synchronous motors

This paper presents a fuzzy-logic-based vector control for a five-phase permanent-magnet synchronous motor (PMSM). The high-performance of the proposed fuzzy logic control (FLC)-based PMSM drive are investigated and compared with the conventional proportional-integral (PI) controller at different conditions, such as step change in command speed and load, and robustness against machine parameter variations. Finally, Simulation results shows that FLC presents better performances and high robustness compared to the conventional PI controller.

Model predictive control of mixing controlled compression ignition operation for low reactivity fuels

Using gasoline or other low reactivity fuels with a pilot injection or port fuel injection in a compression ignition engine has shown great potential in reducing NOx emissions while keeping high thermal efficiency compared to diesel. However, excessive combustion noise is caused by a high maximum pressure rise rate in the cylinder due to the higher fractions of premixed charge of the low-reactivity fuel. This noise can result in structural damage to engine components and as such, combustion noise limits the range of the operating parameters and makes the control of such engines challenging. In this study, a simulation environment was built up in MATLAB/Simulink leveraging a physics-based zero-dimension combustion model to capture the in-cylinder pressure time traces as well as metrics relevant to thermal efficiency and combustion noise. In order to also facilitate the control of emissions, machine learning models were investigated to capture NOx emissions. A kernel-based extreme learning machine (K-ELM) performed best and had a coefficient of correlation (R-squared) of 0.998. The combustion and NOx emission models are valid for not only conventional gasoline fuel but also oxygenated alternative fuel blends at three different pilot injection strategies. In order to track key combustion metrics while keeping noise and emissions within constraints, a model predictive control (MPC) was applied for a compression ignition engine operating with a range of potential fuels and fuel injection strategies. The MPC is validated under different scenarios, including a load step change, fuel type change, and injection strategy change, with proportional–integral (PI) control as the baseline. The simulation results show that MPC reduces about 26% of ringing intensity in the transient process and 17% at the steady state for E30. Generally, MPC can optimize the overall performance through modifying the main injection timing, pilot fuel mass, and exhaust gas recirculation (EGR) fraction.

Model predictive temperature control of a closed-loop spray cooling system

A dynamic model of a closed-loop spray cooling system was proposed, and a model predictive temperature control algorithm was presented. The presented algorithm could quantitively estimate sudden changes in heat load, and then plan an optimized control path along which the temperature trajectory was numerically predicted to be the most stable. Then, the presented algorithm was integrated into a closed-loop spray cooling system, and its control performance was numerically studied. The results showed that, following a 20 W downward step change in heat load, the temperature was re-stabilized in 4 s, with its oscillation less than 0.14 K. Under identical conditions, the presented algorithm outperformed PID in terms of temperature stability, with its peak time shorter by 25–55%, settling time shorter by 38–51%, and average temperature offset smaller by 50–60%. This advantage was mainly because the presented algorithm compensated for hydraulic and thermal lags, two sources of control nonlinearity, by excessive regulation in advance. Unexpectedly, temperature overshoots of the presented algorithm and PID did not differ significantly, seemingly due to the algorithm-inherent estimation lag. From a system design perspective, the length of pump pipeline should be as short as possible, which proved to help reduce overshoot and settling time. Similarly, addition in heat load’s mass also helped reduce overshoot, but would result in an unfavorable long settling time, and vice versa. The simulation results were validated by experimental data, with error less than 10%.

Dynamic modelling and control system design of micro-high-temperature gas-cooled reactor with helium brayton cycle

It is possible to use the micro-high-temperature gas-cooled reactor with helium Brayton cycle (Mi-HTR) as a mobile micro-nuclear power source to provide a stable power supply. Because the Mi-HTR is a highly integrated system, the devices involved are highly coupled and mutually constrained. Therefore, the dynamic model of 5 MW Mi-HTR was established through theoretical derivation. Compared with the design value, the maximum error of steady-state calculation results is less than 2%, and the temperature error is less than 1 K. The transient behaviour is consistent with the experimental trend. The maximum relative error of flow is less than 1.5%, and the maximum relative error of pressure is less than 2.8%. On this basis, the characteristics of Mi-HTR such as large time delay, nonlinear, strong coupling and parameter time-varying are obtained by analysing the dynamic characteristics. The steady-state operation scheme of Mi-HTR is proposed. The reactor outlet helium temperature control, the electric power/rotor speed control, and the precooler/intercooler outlet helium temperature control are designed. A dynamic control model for Mi-HTR is established. The designed control system can cope with the 33% step change of external load.

A Load-Independent Controllable Z-Source Circuit Breaker With an Intrinsic Fault Detection Method

The Z-source circuit breaker using thyristor as the main switch benefits from its low cost, low conduction loss, and high ruggedness. However, the fault protection of the conventional Z-source circuit breakers only relies on the change of the load. In this paper, a load-independent controllable Z-source circuit breaker (CZCB) with an intrinsic fault detection circuit is proposed. It will not be protected by mistake during any load step change, and an accurate fault current detection can be achieved with a specific threshold. Meanwhile, the fault current is monitored by the on-state voltage of the main thyristor, so no additional sensor is needed. An auxiliary thyristor is used to turn off the main thyristor reliably when an overcurrent is detected. In addition, only one inductor is needed in the CZCB, and the <i>L-C</i> parameter is much smaller than the conventional Z-source breakers, leading to lower size and cost. The performance of the proposed CZCB is verified by simulation and experiment. The results show that the fault current can be cleared within a few microseconds, and the total fault isolation time is only about 38 <i>&#x03BC;</i>s.

A new generalized floor function based high switching frequency modulation and control technique: Multilevel inverters

SummaryA new generalized floor function (F2) based single carrier pulse width modulation (F2SC‐PWM) technique has been proposed in this paper by considering a single‐phase 9‐level T‐type packed U‐cell (PUC) inverter topology. In literature, the conventional level‐shifted PWM technique requires (level‐1) carriers, and the unipolar phase disposition (UPD) PWM technique requires (level‐1)/2 carriers to produce a particular level of output. To reduce the complexity of control, the authors have developed single‐carrier‐based PWM techniques. However, these are not generalized in a simple manner and are especially applicable only to particular inverter topologies. In this paper, a new F2SC‐PWM technique with a single modulating signal has been introduced that is applicable to any multilevel inverter (MLI) topology. This technique is very simple to implement, and it does not internally require any large number of mathematical operations and if‐else loops. Finally, a laboratory prototype has been used to verify the operation of the 9L‐TPUC topology considering R and RL loads with respect to step change of load, step change of modulation index (MI), and step change of modulation frequecy (MF) via with new proposed control technique (PCT).

Active hybrid energy storage management in a wind-dominated standalone system with robust fractional-order controller optimized by Gases Brownian Motion Optimization Algorithm

Accessibility to sustainable and reliable electrical energy for remote area power supply (RAPS) systems under high penetration levels of wind energy requires adopting appropriate technologies and controllers. In recent years, energy storage has gained significant attention for smoothing inherent voltage and power fluctuations of standalone systems. This paper presents a filtration-based fractional-order PI (FOPI) controller optimized by Gases Brownian Motion Optimization (GBMO) algorithm to manage an active battery-supercapacitor hybrid energy storage system (HESS) in a wind-dominated RAPS system. The GBMO algorithm has a high accuracy and convergence rate among optimization algorithms introduced in recent years. Moreover, a fuzzy logic controller (FLC) guarantees the wind turbine generator's maximum power point tracking (MPPT) at any wind condition while mitigating its fluctuating torque. The proposed RAPS system uses the advantages of the FOPI controller, the GBMO optimization algorithm, the FLC-based MPPT algorithm, and a high-pass filter to manage precise coordination between different components of the RAPS system. The high-pass filter decouples high and low-frequency voltage oscillations to modify the HESS performance and relieve battery stress, thereby extending its lifespan. The proposed controller's performance and robustness are verified in comparison with an optimal PI controller based on GBMO under turbulent wind speed and load step changes in a detailed model of the system. The results demonstrate the superiority of the optimal FOPI controller over the optimal PI controller.

Dynamic Performance Improvement of a Single-Phase VSI with Digital Implementation of an On-Line Optimal Trajectory Control Algorithm

A single-phase voltage source inverter (VSI) still suffers from a long settling time and significant voltage overshoot/undershoot under the abrupt step-change of load current. This article analyzes the comprehensive large-signal dynamic process and limitation of the linear controller during step change in load current. The combination of linear and nonlinear control is presented which is a realistic, simple, and low-cost technique for enhancing the dynamic response of the single-phase VSI. A nonlinear controller based on the simplified capacitor charge balance algorithm is employed to drive the inductor current and capacitor voltage to attain the target value by precisely following the projected optimal trajectory during the transient process in a brief period. A linear PI controller is utilized during the steady-state operations such as input voltage variations, temperature drifts, and component ageing. The complete mathematical derivation as well as a design method is presented to guide the practical hardware implementation for the given main circuit parameters and identified load step change. Even though accurate time instants can be obtained using off-line numerical calculations, reasonable simplifications are provided for real-time practical engineering applications in DSP. Finally, simulation and experimental verifications prove that the single-phase VSI achieves a substantial settling time decrease and reduced voltage oscillations.

Frequency Support Studies of a Diesel–Wind Generation System Using Snake Optimizer-Oriented PID with UC and RFB

The present paper discusses the modeling and analysis of a diesel–wind generating system capable enough to cater to the electrical power requirements of a small consumer group or society. Due to high variations of the load demand or due to changes in the wind speed, the frequency of the diesel–wind system will be highly disturbed, and hence to regulate the frequency and power deviations of the wind turbine system, an effective controller design is a necessary requirement, and therefore this paper proposes a novel controller design based on PID scheme. The parameters of this controller is effectively optimized through a new snake optimizer (SO) in an offline manner to minimize frequency and power deviations of an isolated diesel–wind system. The performance of SO-PID for the diesel–wind system is evaluated by considering the integral of time multiplied absolute error (ITAE), integral absolute error (IAE), and integral of time multiplied square error (ITSE). The results were calculated for a step change in load, step change in wind speed, load change at different instants of time with diverse magnitude, and for random load patterns, and they were compared with some of the recently published results under similar working conditions. In addition, the effect of an ultracapacitor (UC) and redox flow battery (RFB) on SO-PID was investigated for the considered system, and the application results demonstrated the advantages of our proposal over other studied designs.

Performance evaluation of isolated three-phase voltage source inverter with LC filter adopting different MPC methods under various types of load

As the variety of loads in microgrids continues to grow rapidly, the drawbacks of using conventional voltage and current double closed-loop PI control are becoming increasingly intolerable. These disadvantages include poor static tracking of the output and the need for complicated tuning of optimal PI control parameters. Model predictive control (MPC) is widely studied in recent years and gradually applied to the inverter as a modern control strategy. Currently, the research on MPC mainly focuses on reducing the computational burden of algorithms and improving computing skills. In this paper, the control theory of continuous-control-set model predictive control (CCS-MPC), optimal switching vector model predictive control (OSV-MPC), quasi-sliding mode model predictive control (QS-MPC) and optimal switching sequence model predictive control (OSS-MPC) are elaborated. Also, the disadvantages of adopting conventional voltage and current double closed-loop PI control on microgrids are clarified. Moreover, aiming at evaluating the influence of connecting and/or removing the common loads, such as electric vehicles to the microgrid on the output performance of microgrids in practical engineering applications, single three-phase voltage source inverter with LC filter system with two-phase pure resistance load, three-phase diode rectifier bridge nonlinear load, constant power load and constant current source load applying four different MPC methods, are simulated. The simulation results show that under different types of load, system with nonlinear load applying OSV-MPC method has the biggest value of total harmonic distortion (THD) of the output voltage and the biggest steady state root mean square (RMS) tracking error of the output voltage, which are 1.33% and 2.1 V, respectively. The performances of the output voltage of the system adopting MPC are generally improved compared to the system using conventional voltage and current double close-loop PI control. Regarding the output voltage performance of a system under load step change, a system using the OSS-MPC method with a nonlinear load exhibits the smallest overshoot of the output voltage and the smallest root mean square value of the tracking error (RMSE) between the output voltage and the reference value within 20ms after the load step change. Specifically, the overshoot and RMSE are 2.804 V and 0.810 V, respectively. The simulation results provide valuable guidance for selecting the appropriate model predictive control strategy for microgrid integrating complex loads, such as electric vehicles in practical applications.