Anti-disturbance control of oxygen feeding for vehicular fuel cell driven by feedback linearization model predictive control-based cascade scheme

The accurate control of automotive fuel cell oxygen excess ratio (OER) is necessary to improve system efficiency and service life. To this end, an anti-disturbance control driven by a feedback linearization model predictive control (MPC)-based cascade scheme is proposed. It considers strong nonlinear coupling and disturbance injection of fuel cell oxygen supply. A six-order nonlinear fuel cell oxygen feeding model is presented. It is further formulated using an extended state observer to rapidly reconstruct the OER, to overcome the slow response and interference errors of sensor measurements. In the proposed cascade control, the outer loop is the anti-disturbance control which is used to realize the optimized OER tracking and the inner loop via the feedback linearization to linearize the oxygen feeding behaviors conducts MPC to regulate the air compressor output mass flow. The feedback linearization demonstrates a robust tracking performance of nonlinear outputs, and the integral absolute error of anti-disturbance control is 0.3021 lower than that of PI control under a custom test condition. Finally, the numerical validation on a hybrid driving cycle indicates that the proposed cascade control can regulate the fuel cell OER with an average absolute error of 0.02313 in the high air compressor operation efficiency zone.     

Adaptive maximum power point tracking control of fuel cell power plants

A fuel cell's output power depends nonlinearly on the applied current or voltage, and there exists a unique maximum power point (MPP). This paper reports a first attempt to trace MPPs by an extremum seeking controller. The locus of MPPs varies nonlinearly with the unpredictable variations in the fuel cell's operation conditions. Thus, a maximum power point tracking (MPPT) controller is needed to continuously deliver the highest possible power to the load when variations in operation conditions occur. A two-loop cascade controller with an intermediate converter is designed to operate fuel cell power plants at their MPPs. The outer loop uses an adaptive extremum seeking algorithm to estimate the real-time MPP, and then gives the estimated value to the inner loop as the set-point, at which the inner loop forces the fuel cell to operate. The proposed MPPT control system provides a simple and robust control law that can keep the fuel cell working at MPPs in real time. Simulation shows that this control approach can yield satisfactory results in terms of robustness toward variations in fuel cell operation conditions.     

Powertrain control of a solar photovoltaic-battery powered hybrid electric vehicle

This paper proposes a powertrain controller for a solar photovoltaic battery powered hybrid electric vehicle (HEV). The main objective of the proposed controller is to ensure better battery management, load regulation, and maximum power extraction whenever possible from the photovoltaic panels. The powertrain controller consists of two levels of controllers named lower level controllers and a high-level control algorithm. The lower level controllers are designed to perform individual tasks such as maximum power point tracking, battery charging, and load regulation. The perturb and observe based maximum power point tracking algorithm is used for extracting maximum power from solar photovoltaic panels while the battery charging controller is designed using a PI controller. A high-level control algorithm is then designed to switch between the lower level controllers based on different operating conditions such as high state of charge, low state of charge, maximum battery current, and heavy load by respecting the constraints formulated. The developed algorithm is evaluated using theoretical simulation and experimental studies. The simulation and experimental results are presented to validate the proposed technique.     

A novel prediction algorithm for solar angles using solar radiation and Differential Evolution for dual-axis sun tracking purposes

This paper deals with a dual-axis sun tracking system for a photovoltaic system. Its trajectories are determined by an optimization procedure. The optimization goal is the maximization of the electrical energy production within a photovoltaic system, by considering the tracking system consumption. The procedure used for determining the tilt angle and azimuth angle trajectories is described as a nonlinear and bounded optimization problem. Since an explicit form of the objective function is unavailable, a stochastic search algorithm called Differential Evolution is applied as the optimization tool. In order to evaluate the objective function, models for calculating the available solar radiation and tracking system consumption are applied together with the efficiencies of solar cells, a DC/DC converter and inverter. A new algorithm is introduced for the time dependent prediction of available solar radiation. It is based on the length of a sunbeam’s path through the atmosphere and the statistical data of a pyranometer measured total and diffuse solar radiation at a given location on the Earth. The optimization bounds are given in the form of angular speed, lower and upper bounds for both angles and angle quantization. The results presented in this paper show, that the optimal trajectories can help to increase the electrical energy production within photovoltaic systems by sun tracking.     

A photovoltaic powered electrolysis converter system with maximum power point tracking control

One of the main problems for renewable and other innovative energy sources is the storage of energy for sustainability. This study focuses on two different scenarios to benefit from solar energy more efficiently. Photovoltaic (PV) energy is converted to the desired voltage level using a buck converter for generating hydrogen with electrolysis process. A maximum power point tracking (MPPT) algorithm is used to benefit from the photovoltaic sources more efficiently. The basic electrolysis load for hydrogen production needs low voltage and high current and controlled sensitively to supply these conditions. The photovoltaic powered buck converter for electrolysis load was simulated in MATLAB/Simulink software using a perturb and observe (P and O) MPPT algorithm and PI controller. The simulation results show that in normal, short circuit and open circuit working conditions the PV and load voltages are stabilized. The efficiency of the proposed system is reached more than 90% for high irradiance levels.     

Robust maximum power point tracking method for photovoltaic cells: A sliding mode control approach

Due to nonlinear I-V characteristics of photovoltaic cells, an maximum power point tracking algorithm is adopted to maximize the output power. In this paper, an approach for peak power tracking using the sliding mode control is proposed. The proposed controller is robust to environment changes and load variations. The stability and robustness of the controller are addressed. The performance of the controller is verified through simulations and experiments. It demonstrated that the proposed approach can be implemented effectively and economically.     

Optimization of a fuzzy logic controller for PV grid inverter control using S-function based PSO

This paper presents implementation of particle swarm optimization (PSO) algorithm as a C-Mex S-function. The algorithm is used to optimize a 9-rule fuzzy logic controller (FLC) for maximum power point tracking (MPPT) in a grid-connected photovoltaic (PV) inverter. The FLC generates DC bus voltage reference for MPPT. A digital PI current control scheme in rotating dq-reference frame is used to regulate the DC bus voltage and reactive power. The proposed technique simplifies optimal controller design and ensures fast simulation speeds due to seamless integration with the simulation platform. Validity of the proposed method was verified using co-simulation in PSIM and MATLAB/Simulink. Simulation results show that the optimized FLC gives a better performance compared to fixed-step MPPT.     

不平衡电网电压下T型三电平光伏并网逆变器的有限集模型预测控制

为实现电网电压不平衡时对T型三电平光伏并网系统输出功率和电流质量的控制,以达到入网功率平稳或电流正弦为控制目标,结合光伏阵列输出功率前馈,在两相静止坐标系下提出一种直流母线电压外环PI控制、并网电流内环有限集模型预测控制的控制策略,并在电压外环中引入2倍频陷波器以获得平滑的入网功率参考值。仿真结果表明:当电网电压不对称时,采用所提控制策略能够实现对入网有功、无功功率2倍频脉动及负序电流的分别抑制或协调控制,且并网电流谐波畸变小、入网电能质量高,同时实现T型三电平逆变器的中点电位平衡。     

基于复合控制的塔式太阳能跟踪控制装置设计

针对塔式太阳能热发电站中定日镜跟踪装置的跟踪精度不高、构建成本较大等问题,提出采用将遗传算法的选择机制与吸热塔能量变化的反馈机制相结合的方式对光热电站的太阳能跟踪控制系统进行改进.在光热电站的少数几台定日镜上配备光电检测元件,并以其控制角度为基准控制其他定日镜的角度调整.采用DSP(digital signal processing)为控制核心,完成了跟踪控制器的通讯框架及控制系统的硬件电路设计.实验表明,该方案在保证光热电站整体控制精度的基础上,减少了光电检测元件安装数量和电站构建成本,并保证了视日轨迹跟踪控制时的自动调整能力.     

采用电流寻优的MPPT光伏阵列并网逆变器的研究

针对光伏阵列模型之特点,提出了一种具有最大功率点跟踪（MPPT）的新型光伏阵列正弦波并网逆变器控制方案,该方案一改并网逆变器常规的双环（电压外环,电流内环）控制模式,而采而由MPPT控制器输出直接进行电流控制的新模式,使控制结构更加简单,动态性能更加优越,基于80C196MC控制的电流预估控制策略,实现了网侧电流正弦化,且为单位为功率因数。     

SMC-DPC based active and reactive power control of grid-tied three phase inverter for PV systems

In this paper, sliding mode control (SMC) – direct power controller (DPC) based active and reactive power controller for three-phase grid-tied photovoltaic (PV) system is proposed. The proposed system consists of two main controllers: the DC/DC boost converter to track the possible maximum power from the PV panels and the grid-tied three-phase inverter. The Perturb and Observe (P&O) algorithm is used to transfer the maximum power from the PV panels. Control of the active and reactive powers is performed using the SMC-DPC strategy without any rotating coordinate transformations or phase angle tracking of the grid voltage. In addition, extra current control cycles are not used to simplify the system design and to increase transient performance. The fixed switching frequency is obtained by using space vector modulation (SVM). The proposed system provides very good results both in transient and steady states with the simple algorithms of P&O and SMC-DPC methods. Moreover, the results are evaluated by comparing the SMC-DPC method developed for MPPT and the traditional PI control method. The proposed controller method is achieved with TMS320F28335 DSP processor and the system is experimentally tested for 12 kW PV generation systems.     

Developing a multipurpose sun tracking system using fuzzy control

The present work demonstrates the design and simulation of time controlled step sun tracking systems that include: one axis sun tracking with the tilted aperture equal to the latitude angle, equatorial two axis sun tracking and azimuth/elevation sun tracking. The first order Sugeno fuzzy inference system is utilized for modeling and controller design. In addition, an estimation of the insolation incident on a two axis sun tracking system is determined by fuzzy IF-THEN rules. The approach starts by generating the input/output data. Then, the subtractive clustering algorithm, along with least square estimation (LSE), generates the fuzzy rules that describe the relationship between the input/output data of solar angles that change with time. The fuzzy rules are tuned by an adaptive neuro-fuzzy inference system (ANFIS). Finally, an open loop control system is designed for each of the previous types of sun tracking systems. The results are shown using simulation and virtual reality. The site of application is chosen at Amman, Jordan (32° North, 36° East), and the period of controlling and simulating each type of tracking system is the year 2003.     

On-line implementation of model free controller for oxygen stoichiometry and pressure difference control of polymer electrolyte fuel cell

This paper proposes and validates a model free controller to improve the real time operating conditions of Proton Exchange Membrane Fuel Cells (PEMFC). This approach is based on an ultra-local model that does not depend on a precise knowledge of the system. It is perfectly adapted to a complex system such as the fuel cell, while benefiting from the ease of online implementation and low computational cost. The designed controller is used to regulate both the oxygen stoichiometry and the membrane inlet pressure, which are crucial operating conditions for the fuel cell's lifetime. The objectives of the proposed control strategy are twofold: preventing the starvation failure, and limiting the potential for mechanical degradation of the membrane during a large pressure difference. The performance of the proposed control strategy is initially evaluated by a simulation environment for both oxygen stoichiometry and inlet pressure difference control of fuel cell stack. An online validation on 1.2 KW fuel cell stack is conducted to control the membrane pressure drop. Two case studies are comprehensively investigated in relation to stoichiometry control: set point tracking and rejection of unmeasured disturbances caused by current variations. Simulations and experimental results reveal that the proposed controller provides significantly better performance in terms of fast trajectory tracking, and ensures less overshoot compared to the Fuzzy PID and PID controller. This efficiency is proven using the Integral Absolute Error (IAE), Integral Squared Error (ISE) and Integral of the Square input (ISU) performance indexes.     

Evaluation of a photovoltaic energy mechatronics system with a built-in quadratic maximum power point tracking algorithm

The historically high cost of crude oil price is stimulating research into solar (green) energy as an alternative energy source. In general, applications with large solar energy output require a maximum power point tracking (MPPT) algorithm to optimize the power generated by the photovoltaic effect. This work aims to provide a stand-alone solution for solar energy applications by integrating a DC/DC buck converter to a newly developed quadratic MPPT algorithm along with its appropriate software and hardware. The quadratic MPPT method utilizes three previously used duty cycles with their corresponding power outputs. It approaches the maximum value by using a second order polynomial formula, which converges faster than the existing MPPT algorithm. The hardware implementation takes advantage of the real-time controller system from National Instruments, USA. Experimental results have shown that the proposed solar mechatronics system can correctly and effectively track the maximum power point without any difficulties.     

Development and performance analysis of a two‐axis solar tracker for concentrated photovoltaics

This study presents a two‐axis solar tracking system equipped with a small concentrator module for electricity generation through a multijunction solar cell. The system can accurately track the sun without the need of calibration for an extended period and operate as a stand‐alone system. High‐precision solar tracking was achieved by a combination of open‐loop and closed‐loop controls. A camera tracking sensor was introduced as a feedback device in closed‐loop control. Two different types of solar concentrator modules were designed and fabricated. Their concentration ratios were analyzed against solar tracking errors by means of ray tracing software. One is made up of a paraboloidal primary concentrator and a paraboloidal secondary reflector, whereas the other has a paraboloidal primary concentrator and a hyperboloidal secondary reflector. Both modules showed an almost identical concentration ratio of 610 provided that the solar tracker is pointing perfectly at the sun. However, their performance differs considerably when tracking error is present. The maximum power output was obtained near solar noon with multijunction cells, whose average solar conversion efficiency was 21%, much higher than that of conventional photovoltaic systems. Copyright © 2015 John Wiley & Sons, Ltd.     

基于改进径向基神经网络的风电叶片模温串级PID控制算法

针对风电叶片模具电加热系统中被控对象存在的大惯性、非线性、干扰多等问题,提出一种基于改进径向基(RBF)神经网络的串级PID温度控制方法.首先,采用RBF神经网络结构对常规PID串级控制主回路结构进行优化,在此基础上,引入双动量因子,对主控制回路的输出Jacobian信息进行系统辨识,进而实现对控制器参数的自适应整定;...     

Novel control algorithm for MPPT with Boost converters in photovoltaic systems

The great advances in efficiency and performance of photovoltaic modules would not be very useful if they do not work close to their maximum power point (MPP). In this paper a novel Sliding Mode Control (SMC) based algorithm is proposed to be implemented in a DC/DC converter in order to make an autonomous photovoltaic system to work at the MPP. Once that the design of the novel algorithm has been detailed (especially the novel part relative to the current reference signal) and its stability has been demonstrated, its performance has been compared with two of the most commonly used algorithms in this scope, i.e., Perturbation & Observation (P&O) and Incremental Conductance (IC) algorithms, in addition to a PI controller because it is one of the preferred controllers in industrial applications. This comparison has been carried out taking into account both simulated and experimental tests. The first focused on their behavior when sudden changes in irradiance and temperature, while the lasts analyzed them when the load resistance was varying arbitrarily in actual facilities (composed of a photovoltaic module Mitsubishi PV-TD185MF5, a Boost converter, a variable load and a real-time data acquisition card dSPACE DSP1104 used as the interface between the control algorithm implemented in Simulink/Matlab and the real photovoltaic module). After completing tests under different conditions, we found that the proposed SMC based algorithm outperforms the PI controller and the P&O and IC algorithms, especially in experiments carried out using actual facilities.     

Novel high efficient offline sensorless dual-axis solar tracker for using in photovoltaic systems and solar concentrators

In this study, a novel high accurate offline sensorless dual-axis solar tracker is proposed that can be widely used in photovoltaic systems and solar concentrators. The offline estimated data extracted from solar map equations are used by the tracker to find the sun direction where the maximum value of solar energy is captured. The solar tracker has been built, and it is experimentally verified that 19.1%–30.2% more solar energy can be captured depending on the seasons by utilizing the tracker. The contribution of this work is that the proposed offline sensorless dual-axis solar tracker not only has a very simple structure with a fabrication cost much less than sensor based solar trackers but also high accurately tracks the sun direction with a very small tracking error of only 0.43° which is less than the other sensorless and sensor based dual-axis solar trackers reported in the literature excluding the sensor based dual-axis solar trackers equipped with expensive sensors mounted on high accurate mechanical carriers. Furthermore, unlike all sensor based solar trackers, since the technique is offline, the proposed tracker does not use any feedback signal, and thus, its operation is independent from external disturbances and weather conditions such as cloudy sky.     

An algorithm for the computation of the solar position

A new algorithm for the determination of the solar position is proposed. The importance of tracking accurately the position of the sun is evident when considering high concentration thermal systems. In the literature are found many fast algorithms for the determination of the sun position within 0.01°, and complex astronomical algorithms that allow a precision of 0.0003° but at the price of a large amount of calculation. The algorithm proposed in this work has a precision that is half-way between the two cases (maximal error 0.0027°), that should be sufficient for all the applications in solar engineering, with a computational cost comparable to the cost of the fast algorithms.     

Assessment of a fuzzy logic based MRAS observer used in a photovoltaic array supplied AC drive

In this paper a fuzzy logic (FL) based model reference adaptive system (MRAS) speed observer for high performance AC drives is proposed. The error vector computation is made based on the rotor-flux derived from the reference and the adaptive model of the induction motor. The error signal is processed in the proposed fuzzy logic controller (FLC) for speed adaptation. The drive employs an indirect vector control scheme for achieving a good closed loop speed control. For powering the drive system, a standalone photovoltaic (PV) energy source is used. To extract the maximum power from the PV source, a constant voltage controller (CVC) is also proposed. The complete drive system is modeled in MATLAB/Simulink and the performance is analyzed for different operating conditions.