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The introduction of advanced control algorithms may improve considerably the efficiency of wind turbine systems. This work proposes a high order sliding mode (HOSM) control scheme based on the super twisting algorithm for regulating the wind turbine speed in order to obtain the maximum power from the wind. A robust aerodynamic torque observer, also based on the super twisting algorithm, is included in the control scheme in order to avoid the use of wind speed sensors. The presented robust control scheme ensures good performance under system uncertainties avoiding the chattering problem, which may appear in traditional sliding mode control schemes. The stability analysis of the proposed HOSM observer is provided by means of the Lyapunov stability theory. Experimental results show that the proposed control scheme, based on HOSM controller and observer, provides good performance and that this scheme is robust with respect to system uncertainties and external disturbances.

In this document it is presented and experimentally validated a new linear predictive regulator to control the mechanical speed and the rotor flux of induction motor (IM). The regulator is developed in the synchronous reference frame and it provides a very good dynamic performance and guarantees fulfilment with the current constraints, to avoid over currents in stator windings. This predictive controller employs the minimum necessary dynamic model of the motor to get minor computational cost, in which the rotor flux and the load torque are estimated, and in spite of important parametric uncertainties, the performance is excellent. Moreover, the predictive regulator anticipates the response and compensates the mechanical dead time of the speed induction motor drive, getting better results than the classic speed PI control scheme. This control scheme incorporates the space vector pulse width modulation (SVPWM) with two proportional–integral​ (PI) current controllers, where the rest of dynamics of motor (stator) is controlled and voltage constraints are implemented, ensuring that the modulator always works in the linear area, to prevent distortion in the resulting stator currents. From the experimental tests that have been carried out, it can be concluded that the presented controller provides an effective and robust mechanical velocity and rotor flux tracking, from low to high speed range, with a high accuracy.

The increasing use of lithium batteries and the necessary integration of battery management systems (BMS) has led international standards to demand functional safety in electromobility applications, with a special focus on electric vehicles. This work covers the complete design of an enhanced automotive BMS with functional safety from the concept phase to verification activities. Firstly, a detailed analysis of the intrinsic hazards of lithium-based batteries is performed. Secondly, a hazard and risk assessment of an automotive lithium-based battery is carried out to address the specific risks deriving from the automotive application and the safety goals to be fulfilled to keep it under control. Safety goals lead to the technical safety requirements for the next hardware design and prototyping of a BMS Slave. Finally, the failure rate of the BMS Slave is assessed to verify the compliance of the developed enhanced BMS Slave with the functional safety Automotive Safety Integrity Level (ASIL) C. This paper contributes the design methodology of a BMS complying with ISO 26262 functional safety standard requirements for automotive lithium-based batteries.

Oscillating water column (OWC) systems are water power generation plants that transform wave kinetic energy into electrical energy by a surrounded air column in a chamber that changes its pressure through the waves motion. The chamber pressure output spins a Wells turbine that is linked to a doubly fed induction generator (DFIG), flexible devices that adjust the turbine speed to increase the efficiency. However, there are different nonlinearities associated with these systems such as weather conditions, uncertainties, and turbine stalling phenomenon. In this research, a fuzzy logic controller (FLC) combined with an airflow reference generator (ARG) was designed and validated in a simulation environment to display the efficiency enhancement of an OWC system by the regulation of the turbine speed. Results show that the proposed framework not only increased the system output power, but the stalling is also avoided under different pressure profiles. This research was funded by the Basque Government, through the project EKOHEGAZ (ELKARTEK KK-2021/00092), Diputación Foral de Álava (DFA) through the project CONAVANTER, and to the UPV/EHU through the project GIU20/063.

Nowadays, the increase in solar energy installations as a source of energy is growing considerably. The connection to the grid of these installations generally injects all the power obtained from the panel as active power, making zero the reactive power. The same power injection system can be used to achieve a unit power factor if the active filter feature is integrated in it. In this paper, an active power filter (APF) that can control both, the MPP (maximum power point) of a photovoltaic system (PV) and the power factor of a nonlinear load connected to the grid using a three phase DC/AC power inverter with new sliding mode controllers is presented. Perturbation–observation (P&O) is the used MPPT algorithm and three Sliding Mode Controllers (SMC) are used to regulate the DC voltage of the PV and the current d and q components of the active filter using the PQ theory. With a SMC, no exact knowledge of the model parameters is required and it offers good behavior against unmodeled dynamics, insensitivity to parameter variations and good rejection of external disturbances. The space vector pulse wide modulation (SVPWM) of 7 and 5 segments is implemented in order to check the efficiency and grid current ripple. Several experimental tests have been carried in different conditions, concluding that the presented system provides an efficient maximum power tracking and a good power filter characteristic.

This work proposes a robust controller for a variable speed wind turbine system with a doubly feed induction generator. The controller aims at tracking the optimal speed of the wind turbine so that extracts the maximum power from the wind. Also, a robust aerodynamic torque observer is proposed in order to avoid the use of wind speed sensors. This torque observer allows to estimate the aerodynamic torque to be used by the controller in order to calculate the value of the optimal reference speed for the wind turbine. The vector control theory is applied in the present approach, and thereby the stator flux-oriented control is used for controlling the speed of the wind turbine generator. The proposed robust control law is based on sliding mode control theory, which has proved to provide good performance under system uncertainties. The stability of the proposed controller under disturbances and parameter uncertainties has been analyzed using the Lyapunov stability theory. Finally, real time experimental results show that, on the one hand, the proposed controller provides high-performance dynamic characteristics, and on the other hand, this scheme is robust with respect to the uncertainties that usually appear in this kind of systems.

This document studies torque degradation of an internal permanent magnet motor due to an incorrect rotor angle measurement when low rotor angle resolution sensors are used. The performance of the control with different rotor angle resolution is also analysed to determine the torque error due to the use of an incorrect synchronous rotating reference system. To address torque degradation due to the low resolution of Hall sensors, a new method of estimating the rotor angle is proposed that incorporates the information from Hall sensors. In this way, good resolution is achieved, allowing the machine to be controlled over a wide speed range even with rated torque. This method is validated through simulations and real experiments.

Wind-generated energy is a fast-growing source of renewable energy use across the world. A dual-feed induction machine (DFIM) employed in wind generators provides active and reactive, dynamic and static energy support. In this document, the droop control system will be applied to adjust the amplitude and frequency of the grid following the guidelines established for the utility&rsquo, s smart network supervisor. The wind generator will work with a maximum deloaded power curve, and depending on the reserved active power to compensate the frequency drift, the limit of the reactive power or the variation of the voltage amplitude will be explained. The aim of this paper is to show that the system presented theoretically works correctly on a real platform. The real-time experiments are presented on a test bench based on a 7.5 kW DFIG from Leroy Somer&rsquo, s commercial machine that is typically used in industrial applications. A synchronous machine that emulates the wind profiles moves the shaft of the DFIG. The amplitude of the microgrid voltage at load variations is improved by regulating the reactive power of the DFIG and this is experimentally proven. The contribution of the active power with the characteristic of the droop control to the load variation is made by means of simulations. Previously, the simulations have been tested with the real system to ensure that the simulations performed faithfully reflect the real system. This is done using a platform based on a real-time interface with the DS1103 from dSPACE.

This paper aims to study some of the functional safety standard technical requisites, namely IEC61508 or ISO26262, regarding the Battery Management Systems. A Hazard and Risk Analysis has been carried out to identify the critical aspects of lithium-based batteries, aiming to find the necessary risk reduction and the applicable safety functions with an assigned Safety Integrity Level for a vehicle application.

This document presents an efficient proportional derivative (PD) position controller for three-phase motor drives. The regulator has been designed in frequency domain, employing the direct&ndash, quadrature (d&ndash, q) synchronous rotating reference frame and the indirect vector control. The presented position regulator is easy to tune and incorporates a feed forward (FF) term to compensate effectively the effect of the load disturbance. This position controller has been validated experimentally by using two industrial three-phase motors: an induction motor (IM) of 7.5 kW and a permanent magnet synchronous motor (PMSM) of 3.83 kW. The inner proportional integral (PI) current loops of both machines have also been designed in the frequency domain. Each machine has connected in its shaft an incremental encoder of 4096 pulses per revolution, to measure the position. Several simulations and experimental tests have been carried out with both motors, in favorable conditions and also with various types of adversities (parametric uncertainties, unknown load disturbance and measurement noise in the position and current loops), getting very good results and suggesting that this controller could be used in the research area and also in the industry.

Due to the nonlinear dynamics and uncertainties usually present in wave energy conversion systems, the efficiency of these devices can be enhanced employing a robust control algorithms. Wave energy converters are constructed using electric generators of variable velocity, like double feed induction generator (DFIG) since they may improve the system efficiency to generate power when compared to fixed speed generators. The main reason is that this generators with variable speed may adapt the speed of the turbine in order to maintain the optimal flow coefficient values which improves the efficiency of the Wells turbine. However, a suitable speed controller is required in these systems first in order to avoid the stalling phenomenon and second in order to track the optimal turbine reference velocity that optimizes the power generation. In this paper a real time sliding mode control scheme for wave energy conversion systems that incorporate a Wells turbine and a DFIG is proposed. The Lyapunov stability theory is used to analyse the stability of this control scheme under parameter uncertainties and system disturbances. Next, the proposed control scheme is validated first by means of some simulation examples using the Matlab/Simulink software and second using a real-time experimental platform based on a dSPACE DS1103 control board.

This paper presents the design and experimental validation of a new Sliding Mode Controller (SMC) for a single-phase grid-tie inverter in a photovoltaic (PV) Maximum Power Point Tracking (MPPT) application. The number of PV modules required in the string is determined to meet the voltage requirements of the grid-connected inverter, this way the PV modules are connected directly to the DC link of the inverter in a centralized topology and the high step-up power converter of the conventional systems is avoided, obtaining a higher efficiency. The used MPPT algorithm is the hill climbing or perturbation–observation (P&O) and a new Sliding Mode Controller is used to regulate the desired inverter voltage according to the MPPT algorithm. SMC allows to avoid the need of an exact knowledge of the system parameters and offers many desirable properties, such as good performance against no modelled dynamics, insensitivity to parameter variations, and an excellent external disturbance rejection. The inverter control has been designed in the d-q rotating reference frame after use a virtual bi-phase system. Several experimental tests have been carried out in suitable and adverse conditions, concluding that the presented system provides an efficient maximum power tracking.

This publication describes a safety concept for an automotive domain battery management system in compliance with ISO 26262. First, Lithium-based battery hazards and risks are assessed, associated safety goals are defined to reduce previously identified risks and automotive safety integrity levels are assigned. Then, a safety architecture that meets previous safety goals and requirements is described at system and subsystem level. This safety architecture describes the overall technical safety concept, diagnosis strategy and measures to reduce the probability of systematic and random faults.

As most of PV systems, CPV systems are also affected by mismatching losses, particularly due to misalignment of optics and receivers. As a result, module level power electronics can help to increase their energy yield by making every CPV module deliver it maximum power at the output. Among the different alternatives, solutions based on DC power optimizers exhibit higher conversion efficiencies and lower costs than microinverters. However, while microinverters ensure optimal operation independently from the operating conditions, system design with DC power optimizers must be carefully examined to avoid potential underperformance. This paper describes not only the customized design and validation of a high-efficiency and economical DC power optimizer for HCPV systems, but also a comprehensive analysis of the whole system design to optimize its production under expected working conditions. Main design specifications (electrical parameters of module and number of modules per tracker), as well as supporting information for mismatching losses estimation, have been provided by ASSE within CPVMatch project. This work has received funding from the European Union’s Horizon 2020 research and innovation programme within the project CPVMatch under grant agreement No 640873.

Power generated from wind is a fast growing renewable source of the world energy consumption. A double feed induction generator (DFIG) used in wind turbines, provides dynamic and static active and reactive power support. In this paper, the droop control technique is used to regulate the grid amplitude and frequency according to the criteria defined for the smart grid supervisor. Wind turbine will operate in an unloaded maximum power curve, and according to the reserved active power to correct the frequency deviation, the limit of the reactive power or voltage amplitude correction will be explained. In addition, the offset adjustment of the encoder and the stator synchronization and connection to the grid will be explained. The connection process to the grid and the regulation of a real 7.5kW DFIG is performed controlling the active and reactive powers to their reference values. For that, a platform based on a real-time interface with the DS1103 board is used.

The incorporation of the full dynamics of the different conversion stages of wave energy converters (WECs), from ocean waves to the electricity grid, is essential for a realistic evaluation of the power flow in the drive train. WECs with different power take-off (PTO) systems, including diverse transmission mechanisms, have been developed in recent decades. However, all the different PTO systems for electricity-producing WECs, regardless of any intermediate transmission mechanism, include an electric generator, linear or rotational. Therefore, accurately modelling the dynamics of electric generators is crucial for all wave-to-wire (W2W) models. This paper presents the models for three popular rotational electric generators (squirrel cage induction machine, permanent magnet synchronous generator and doubly-fed induction generator) and a back-to-back (B2B) power converter and validates such models against experimental data generated using three real electric machines. The input signals for the validation of the mathematical models are designed so that the whole operation range of the electrical generators is covered, including input signals generated using the W2W model that mimic the behaviour of different hydraulic PTO systems. Results demonstrate the effectiveness of the models in accurately reproducing the characteristics of the three electrical machines, including power losses in the different machines and the B2B converter. This material is based on works supported by the Science Foundation Ireland under Grant No. 13/IA/1886.

Robust control algorithms may improve the efficiency of wave power conversion systems since they present intrinsic nonlinear dynamics and the system uncertainties. Sometimes, the generators that can operate al variable speed (e.g. double feed induction generator) are used at wave power generation plants, since they may improve the system efficiency to generate power when compared to fixed speed generators. The main reason is that this generators with variable speed may adapt the speed of the turbine in order to maintain the optimun flow coefficient value which improving its efficiency. This paper proposes a sliding mode controller for wave power plants based on a double feed induction generator. Also, the presented robust control scheme introduces an adaptive sliding gain that avoids calculating the upper bound for the uncertainties of the system, facilitating its application. The stability of the proposed control scheme is analyzed by means of the Lyapunov stability theory. Finally, the proposed control scheme is validated through some simulation examples.

This article proposes a neural network model reference adaptive system for the rotor angle and speed estimation of the doubly fed induction generator used in wind turbines. The model reference adaptive system reference signal is the measured rotor current. The adaptive neural network adjusts the weights minimizing the rotor current vector squared error using the steepest descent algorithm. The neural network maximum stable learning rate will be determined for this application. The validity of the proposed neural network model reference adaptive system is verified and analyzed in a real prototype of 7.5-kW doubly fed induction generator. To validate the proposed estimator, the estimated rotor angle and speed in the process of connecting the doubly fed induction generator to the grid and the sensorless regulation according to a random wind speed profile are presented.

This paper presents an effective Proportional Derivative (PD) position controller of induction motor drives. A new procedure for controller design in frequency domain and the d-q synchronous rotating reference frame is presented, where the indirect vector control has been used. This position controller is validated experimentally using an industrial induction motor of 7.5 kW and an incremental encoder of 4096 impulses per revolution. The position regulator includes an effective FeedForward (FF) term instead of the Integral action (I), reducing drastically the undesirable effect of the unknown load disturbance on the position tracking. The presented algorithm has been tested using several simulation and real experiments, in suitable conditions and also in adverse conditions employing the unknown load disturbance, parameter uncertainties and measurement noise in the position and stator current loops signals, where its functional robustness is clearly demonstated. The obtained results are very satisfactory, suggesting its use in industry and in the research area to be used as a reference with other advanced position regulators. The stability of the controlled system is demonstrated in frequency domain and also by discretization of poles.

A sliding mode position control for high-performance real-time applications of induction motors is developed in this work. The design also incorporates a sliding mode based flux and load torque observers in order to avoid this sensors, that increases the cost and reduces the reliability. Additionally, the proposed control scheme presents a low computational cost and therefore can be implemented easily in a real-time applications using a low cost DSP-processor. The stability analysis of the controller under parameter uncertainties and load disturbances is provided using the Lyapunov stability theory. Finally simulated and experimental results show that the proposed controller with the proposed observer provides a good trajectory tracking and that this scheme is robust with respect to plant parameter variations and external load disturbances.

In this paper, a real time sliding mode control scheme for a variable speed wind turbine that incorporates a doubly feed induction generator is described. In this design, the so-called vector control theory is applied, in order to simplify the system electrical equations. The proposed control scheme involves a low computational cost and therefore can be implemented in real-time applications using a low cost Digital Signal Processor (DSP). The stability analysis of the proposed sliding mode controller under disturbances and parameter uncertainties is provided using the Lyapunov stability theory. A new experimental platform has been designed and constructed in order to analyze the real-time performance of the proposed controller in a real system. Finally, the experimental validation carried out in the experimental platform shows, on the one hand that the proposed controller provides high-performance dynamic characteristics, and on the other hand that this scheme is robust with respect to the uncertainties that usually appear in the real systems.

14 p. This paper presents and validates a new proposal for effective speed vector control of induction motors based on linear Generalized Predictive Control (GPC) law. The presented GPC-PI cascade configuration simplifies the design with regard to GPC-GPC cascade configuration, maintaining the advantages of the predictive control algorithm. The robust stability of the closed loop system is demonstrated by the poles placement method for several typical cases of uncertainties in induction motors. The controller has been tested using several simulations and experiments and has been compared with Proportional Integral Derivative (PID) and Sliding Mode (SM) control schemes, obtaining outstanding results in speed tracking even in the presence of parameter uncertainties, unknown load disturbance, and measurement noise in the loop signals, suggesting its use in industrial applications. The authors are very grateful to the UPV/EHU for its support throughout the project GUI07/08 and the Basque Government for the support to this work throughout the project S-PE09UN12

Power generated from wind is a fast growing renewable source of the world energy consumption. A test bench for comprehensive research on the doubly fed induction generator (DFIG) used as wind turbine is implemented. The wind energy is emulated with a synchronous machine according to the wind profile specified in the computer. Two inverters in a back to back configuration between the rotor and the grid are used to control the DFIG. The space vector pulse width modulation (SVPWM) technique is used in both inverters. Special attention has been placed in the offset adjustment of the encoder and the stator synchronization and connection to the grid. Finally, the regulation of the DFIG is performed controlling the active and reactive power to their reference values.

In this paper, a sensorless induction motor parameter identification is presented. Sensorless control employs a variety of estimators and observers of motor speed, torque and fluxes, and accurate information about motor parameters is crucial to obtain a high performance control. The parameters of the induction motor equivalent circuit are obtained by means of DC an AC tests using the voltage-source inverter. When these parameters are estimated a closed loop flux estimator and an open loop speed estimator are implemented to determine the mechanical parameters of the machine. The parameter estimation procedure has been simulated and tested in a 7.5 kW induction motor. With the obtained parameters a sensorless control was implemented.

In this paper, the multiple period speed measurement is compared with the classical frequency and/or period methods used. The proposed speed method is used to examine the quality of the three implemented speed estimators. These estimators get the information from measured stator currents and from motor stator voltage. Open loop estimators or observers are used to estimate rotor or stator flux and rotor speed to use as feedback signals. An improved open loop estimator, an MRAS, and an EKF observer are tested utilizing a 7.5 kW induction motor. They have different accuracy, robustness and sensitivity against parameter variations and all of them have the same problem when the rotor speed is around zero.