Fixed Step Method Research Articles

Photovoltaic Maximum Power Point Tracking Technology Based on Improved Perturbation Observation Method and Backstepping Algorithm

Photovoltaic power generation systems mainly use the maximum power tracking (MPPT) controller to adjust the voltage and current of the solar cells in the photovoltaic array, so that the photovoltaic array runs at the maximum power point (MPP) to achieve the purpose of maximum power output. At present, photovoltaic power stations mainly adopt the traditional method to track the maximum power point, but this fixed step method easily causes output power oscillation of the photovoltaic array when tracking the maximum power point, and it easily falls into the local extreme point under partial shadow conditions. In order to solve these problems, this paper proposes an improved perturbation observation method and backstepping method (IP&O-backstepping) to replace the traditional method applied to the MPPT controller to optimize the operating state of the solar cell, thereby improving the output power point of the photovoltaic array and increasing the output power of the photovoltaic array. The algorithm first uses the improved perturbation and observation (IP&O) method to search the maximum power point of the photovoltaic array and output the reference voltage. Secondly, the reference voltage is input into the backstepping algorithm for voltage tracking. Finally, the algorithm tracks the reference voltage and makes the photovoltaic array operate at the maximum power point. The simulation is carried out by using MATLAB/Simulink. The IP&O-backstepping algorithm is compared with the intelligent algorithm and the traditional method, and the results show that compared to the above algorithm, the IP&O-backstepping algorithm can not only track the maximum power point of the photovoltaic array, but also has a faster tracking speed, and the output power has almost no oscillation when the photovoltaic array runs at the maximum power point.

The Long-term Error Estimation Method for the Numerical Integrations of Celestial Orbits

Numerical methods have become a very important type of tool for celestial mechanics, especially in the study of planetary ephemerides. The errors generated during the computation are hard to know beforehand when applying a certain numerical integrator to solve a certain orbit. In that case, it is not easy to design a certain integrator for a certain celestial case when the requirement of accuracy were extremely high or the time-span of the integration were extremely large. Especially when a fixed-step method is applied, the caution and effort it takes would always be tremendous in finding a suitable time-step, because it is about whether the accuracy and time-cost of the final result are acceptable. Thus, finding the best balance between efficiency and accuracy with the least time cost appeared to be a major obstruction in the face of both numerical integrator designers and their users. To solve this problem, we investigate the variation pattern of truncation error and the pattern of rounding error distributions with time-step and time-span of the integration. According to those patterns, we promote an error estimation method that could predict the distribution of rounding errors and the total truncation errors with any time-step at any time-spot with little experimental cost, and test it with the Adams-Cowell method in the calculation of circular periodic orbits. This error estimation method is expected to be applied to the comparison of the performance of different numerical integrators, and also it can be of great help for finding the best solution to certain cases of complex celestial orbits calculations.

Maximum efficiency control and predictive-speed controller design for interior permanent magnet synchronous motor drive systems

Improving the efficiency of home appliances is an important area of research these days, especially for global warming and climate change. To achieve this goal, in this paper, a new method to improve the maximum efficiency control of an interior permanent magnet synchronous motor (IPMSM) drive system, which includes an IPMSM and an inverter, is investigated. By suitably controlling the d-axis current, the IPMSM drive system can quickly reach its maximum efficiency. A steepest ascent method is used to obviously reduce the searching steps of the maximum efficiency tracking control for an IPMSM. According to experimental results, by using the traditional fixed step method, 14 steps are required to reach the maximum efficiency operating point. By using the proposed steepest ascent method, however, only 4 steps are needed to reach the maximum efficiency operating point. In addition, according to the experimental results, during the transient dynamics, the predictive controller obtains faster responses and 2% lower overshoot than the PI controller. Moreover, during adding external load, the predictive controller has only a 10 r/min speed drop and 0.1 s recover time; however, the PI controller has a 40 r/min speed drop and 0.3 s recover time. Experimental results can validate theoretical analysis. Several measured results show when compared to the fix-step searching method with a PI controller, the proposed methods provide quicker searching maximum efficiency ability, quicker and better dynamic transient responses, and lower speed drop when an external load is added.

METHOD OF COMPROMISE CHOICE OF INTERVAL OF MODEL TIME CHANGE IN IMITATION MODEL

The process of simulation is considered as one of the main means for studying the dynamics of functioning of real systems, in particular, complex ones. The system can be represented by a set of components. The functioning of a component is represented by the implementation of a set of functional actions, which are represented by the corresponding activities in the form of a pair: algorithm for performing a functional action - duration of execution. The problem of displaying the simultaneous or parallel nature of the functioning of all components of a complex system in the MI is solved by introducing model or system time. The main methods for introducing model time are the fixed step method and the variable step method. In the fixed-step method, an important problem is the choice of the value of the model time variation interval. The existing recommendations for choosing the value of the interval for changing the model time are of a qualitative nature and their use makes it possible to increase the accuracy of modeling, but at the same time the consumption of the computer time resource increases. It is proposed to use quantitative estimates of the values of quality criteria - the accuracy and expenditure of the computer time resource when choosing the value of the model time change interval. The generalized criterion is represented as a weighted sum of transformations of local criteria. The values of the coefficients by which the corresponding transformations are multiplied express the preferences of the decision-maker for the local optimality criteria. A geometric interpretation of the process of determining a compromise alternative on a set of effective alternatives for various cases of the importance of local criteria is given. These estimates make it possible to substantiate the nature of the change in the quality criteria for various variants of the values of the interval of change in the model time and to use them to select a compromise option among the effective ones by minimizing the generalized criterion. The choice of the compromise value of the model time variation interval is implemented in the control simulation program.

Fractional-Order SIR Epidemic Model for Transmission Prediction of COVID-19 Disease

In this paper, the fractional-order generalization of the susceptible-infected-recovered (SIR) epidemic model for predicting the spread of the COVID-19 disease is presented. The time-domain model implementation is based on the fixed-step method using the nabla fractional-order difference defined by Grünwald-Letnikov formula. We study the influence of fractional order values on the dynamic properties of the proposed fractional-order SIR model. In modeling the COVID-19 transmission, the model’s parameters are estimated while using the genetic algorithm. The model prediction results for the spread of COVID-19 in Italy and Spain confirm the usefulness of the introduced methodology.

Variable Step Size Solution of Standard Parabolic Equation in Complex Environment

Aiming at the problem that it is difficult to balance the accuracy and velocity of the fixed-step solution of standard parabolic equation in the study of radio wave propagation in a wide range of complex environments, a variable-step solution method of standard parabolic equation is proposed. Firstly, after deducing the relationship between the error of SSFT solution and step size, frequency and other factors; And the basic selection range of step size for SPE variable step size solution is given. Secondly, the action mechanism of different environmental factors and the requirement of changing trend for step size are expounded through simulation, and the complex environment of SPE application is classified according to the requirement of error. Finally, the method is used to simulate the characteristics of the typical complex environment. The simulation results show that the method can save up to 71.4% of the time compared with the fixed-step method of parabolic equation under the condition of ensuring the calculation accuracy. The reliability and efficiency of the proposed method are verified, and the calculation efficiency of the parabolic equation radio wave prediction can be greatly improved. Therefore, the parabolic equation method with variable step size can ensure the accuracy of calculation, reduce the memory and time required for calculation, greatly improves the efficiency of calculation, and has practical significance in the application of real-time prediction of electromagnetic wave propagation in a wide range of complex environments.

A Line Integral Convolution Method With Dynamically Determining Step Size and Interpolation Mode for Vector Field Visualization

The line integral convolution method can obtain a continuous and dense vector streamline texture. The traditional fixed step size gets larger texture noise, while the exact calculation step method (such as the Runge-Kutta method) is time-consuming. In the process of generating streamline texture, if using bilinear interpolation calculation, we can get the method of calculating the point vector value, and it is also time-consuming. To address the above-mentioned problems, the line integral convolution method for dynamically determining integral step size and interpolation mode is proposed. The effect of streamline drawing mainly depends on the size of the integration step and the interpolation mode. The method proposed in this paper gives the rules for determining the integration step size and interpolation mode according to the vector speed size and the angle between two vectors. The experimental results show that compared with the previous fixed step method and the bilinear interpolation method, the proposed method not only has faster computation speed but also clearer texture and stronger contrast.

Rule-based fuzzy control method for static pressure reset using improved Mamdani model in VAV systems

In variable air volume air(VAV) conditioning systems, conventional methods for static pressure reset depends on accurate mathematics models which are often difficult to be built. On the contrary, controls, which are based on a series of control rules derived from the operating and commissioning experience, have the capacity to achieve better effects. A rule-based fuzzy control method (RBFCM) for static pressure reset is proposed using improved Mamdani model and functioning fuzzy subset inference method, which reflects the physical characteristics of the controlled object and is convenient for the engineers to understand and use. The development and implementation of the proposed RBFCM are necessary to demonstrate in detail. Through comparative experiments, the proposed RBFCM is compared with the conventional fixed-step method and itself with different actual domain in a control experiment platform for the VAV air conditioning system. Experimental results indicate that the proposed RBFCM has better control performances and outstanding energy-saving potential if the actual domain can be selected reasonably. A minimum of 33% energy saving rate of the proposed RBFCM with the optimal actual domain is shown through experimental study.

Research on MPPT Algorithm Based on Mixed Strategy

Based on the mathematical model of PV array and its output characteristics, a hybrid control strategy combining fixed step method and variable coefficient approximation method is proposed. The method is followed by a fixed step in the search of the maximum power point. When the slope of the PU curve changes for the first time, the search interval is fixed in an initial step, and then the search is gradually approximated to maximum power point in the section. The method is analyzed theoretically and modeled in Matlab / Simulink environment, and compared with the variable step perturbation observation method. The simulation results show that the proposed method can quickly and accurately track the maximum power point under the standard condition and the sudden change of light intensity, and has faster tracking speed.

COUNTER FLOW ADIABATIC REGENERATOR AND COMPARATIVE STUDY

Liquid desiccant air conditioning systems have recently been attracting attention due to their capability of handling the latent load without super-cooling and then reheating the air, as happens in a conventional compression-type air conditioning system. This paper presents the results from a performance study of the simultaneous heat and mass transfer between air and liquid desiccant in an adiabatic, counter flow, structured packed regenerator. A heat and mass transfer numerical model has been developed, based on the Runge-Kutta non-stiff fixed step method, to predict the performance of the device under various operating conditions. Good agreement was found between the theoretical model and experimental tests from previous studies, with the deviation range being ±6.2% in air outlet temperature, ±8.1% in air outlet humidity ratio and ±1.4% in solution outlet temperature. Important design variables are also defined. The effects of air and desiccant flow rates, air humidity ratio, desiccant temperature and concentration have been reported on the regeneration rate and regeneration effectiveness. A detailed sensitivity analysis has been implemented to indicate which input variables mostly affect the output conditions. The three most commonly used liquid desiccant solutions, namely LiCl, LiBr and CaCl2 were evaluated against each other. The results show that high regeneration efficiency could be achieved under high desiccant mass flow rates, high air mass flow rate, high desiccant inlet temperature, low desiccant inlet concentration and CaCl2 as the desiccant solution.

Modeling of the Potential Pit and Force Field to Limit the Motion of the Plasma Particles

Paper is devoted to development of the potential barrier model allowing to take into account the interaction between elastic reflection of particles and plasmatron walls. The coaxial magneto-plasma accelerator which has been put into practice is considered.Plasma clot change of speed and weight depending on the coordinate determined by both power characteristics and gas dynamic regularities of hypersonic jet currents in the cylindrical channel was investigated in the accelerator. Potential function and force field type modeling spatial restriction of plasma particles scattering is presented. Dynamics ofcharged particles distribution in electromagnetic field andthe plot of energy balance taking into account the erosion of channel walls have been presented. The developed model of the coaxial magneto-plasma accelerator taking into account an erosion caused by particles distribution on a low-frequency helixhas been shown.Low-frequency helixpath motion is presented as superposition of longitudinal and transverse motions. Differential equations were solved using the fourth-order Runge-Kutta fixed-step method.

Design and implementation of FPGA-based Taguchi-chaos-PSO sun tracking systems

The field-programmable gate array (FPGA) based intelligent sun tracking system proposed in this paper uses an NI 9642 controller to integrate the dual-axis sun tracking system with a Maximum Power Point Tracker (MPPT), so as to effectively increase the output power of solar panels. Furthermore, it is provided with multiple intelligent functions, so that the system can start up the sun tracking function automatically in the daytime, and automatically return to its initial position at night. It has a delay function to reduce the electric power consumed by the motor in rotation. Moreover, it can be switched to dual-axis or one-axis sun tracking freely as required by the user, and the solar panel inclination can be operated directly. The dual-axis sun tracking system uses the Particle Swarm Optimization (PSO) method to look for the parameters of the PI controller. The Taguchi Method and Logistic Map are proposed to enhance the steady state convergence of PSO in seeking the optimal solution. The MPPT uses Fuzzy Logic to adjust the step length of the incremental conductance method, so as to remedy the defects in the traditional fixed step method, and to make the solar panel output reach the maximum power point position rapidly and stably.

MPPT Strategy of PV System Based on Adaptive Fuzzy Control

In order to use photovoltaic cell effectively and improve its photoelectric conversion efficiency, the maximum power point of photovoltaic generation system should be tracked rapidly and stably [1]. Taking into account the solar PV systems are often affected by external factors,it is difficult to determine system parameters, and has a strong non-linear,so this paper,a adaptive fuzzy logic control technology for STP0950S-36 type of independent photovoltaic systems to a adaptive fuzzy controller design method, and using MATLAB/SIMULINK,fuzzy logic toolbox for simulation tools such as maximum power point control,adaptive fuzzy control simulation results of MPPT with fixed step method compared to fixed-step method was found to reach steady there is a certain state after the fluctuation,The results show that the method can quickly and correctly track change of MPP in different light intensity and the system has excellent stability performance.

Thermodynamic analysis of a counter flow adiabatic dehumidifier with different liquid desiccant materials

Liquid desiccant systems have been proposed as energy saving alternatives to the conventional vapor compression systems for handling the latent load. This paper presents the results from a study of the performance of a counter flow liquid desiccant dehumidifier. A heat and mass transfer theoretical model of an adiabatic packed column has been developed, based on the Runge-Kutta fixed step method, to predict the performance of the device under various operating conditions. Good agreement was found between experimental tests and the theoretical model, with the maximum deviation being ±2.9% in air outlet temperature, ±15.9% in air outlet humidity ratio and ±2.8% in solution outlet temperature. Following the model validation, the rate and the efficiency of the dehumidification process were assessed under the effects of variables, such as air temperature and humidity, desiccant temperature and humidity and air and desiccant flow rates. The three most commonly used liquid desiccant solutions, namely LiCl, LiBr and CaCl2 were evaluated against each other. The results show that high absorber efficiency and system efficiency could be achieved under humid conditions, low air mass flow rates and LiCl as the desiccant solution.

Study on UAV Path Planning Approach Based on Fuzzy Virtual Force

This article proposes a novel fuzzy virtual force (FVF) method for unmanned aerial vehicle (UAV) path planning in complicated environment. An integrated mathematical model of UAV path planning based on virtual force (VF) is constructed and the corresponding optimal solving method under the given indicators is presented. Specifically, a fixed step method is developed to reduce computational cost and the reachable condition of path planning is proved. The Bayesian belief network and fuzzy logic reasoning theories are applied to setting the path planning parameters adaptively, which can reflect the battlefield situation dynamically and precisely. A new way of combining threats is proposed to solve the local minima problem completely. Simulation results prove the feasibility and usefulness of using FVF for UAV path planning. Performance comparisons between the FVF method and the A* search algorithm demonstrate that the proposed approach is fast enough to meet the real-time requirements of the online path planning problems.

Trellis-based power control for direct sequence CDMA in a Rayleigh fading environrnent

A mobile user's signal strength fluctuates significantly and rapidly due to Rayleigh fading. Unless the time gap in adjusting the transmitting power to an ideal level is eliminated, either the signal-to-interference ratio is too low to meet the minimum requirement, or excessive interference to other users occurs. In the paper, the time gap is reduced by devising a trellis-based prediction method that adjusts the transmitting power strength based on the similarity of the power control states, such that the signal strengths of all mobile users at the base station are nearly identical. In the performance evaluation, the power control events are modelled by a sequence of 0s and 1s, which can be either periodic or aperiodic. The number of users that can be supported in the system using the proposed power control method is computed for both the average case and the worst case. The analytical results, verified by simulation runs, show that the drop in capacity is small compared to that of transmission environment with ideal power control, and that the proposed scheme increases capacity over that of the fixed step method, by as much as 50%.