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In critical healthcare units, such as operation theaters and intensive care units, healthcare workers require specific temperature environments at different stages of an operation, which depends upon the condition of the patient and the requirements of the surgical procedures. Therefore, the need for a dynamically controlled temperature environment and the availability of the required heating/cooling electric power is relatively more necessary for the provision of a better healthcare environment as compared to other commercial and residential buildings, where only comfortable room temperature is required. In order to establish a dynamic temperature zone, a setpoint regulator is required that can control the zone temperature with a fast dynamic response, little overshoot, and a low settling time. Thus, two zone temperature regulators have been proposed in this article, including double integral sliding mode control (DISMC) and integral terminal sliding mode control (ITSMC). A realistic scenario of a hospital operation theater is considered for evaluating their responses and performance to desired temperature setpoints. The performance analysis and superiority of the proposed controllers have been established by comparison with an already installed Johnson temperature controller (JTC) for various time spans and specific environmental conditions that require setpoints based on doctors' and patients' desires. The proposed controllers showed minimal overshoot and a fast settling response, making them ideal controllers for operation theater (OT) zone temperature control. [ABSTRACT FROM AUTHOR]

Machine Learning (ML) is one of the major driving forces behind the fourth industrial revolution. This study reviews the ML applications in the life cycle stages of biofuels, i.e., soil, feedstock, production, consumption, and emissions. ML applications in the soil stage were mostly used for satellite images of land to estimate the yield of biofuels or a suitability analysis of agricultural land. The existing literature have reported on the assessment of rheological properties of the feedstocks and their effect on the quality of biofuels. The ML applications in the production stage include estimation and optimization of quality, quantity, and process conditions. The fuel consumption and emissions stage include analysis of engine performance and estimation of emissions temperature and composition. This study identifies the following trends: the most dominant ML method, the stage of life cycle getting the most usage of ML, the type of data used for the development of the ML-based models, and the frequently used input and output variables for each stage. The findings of this article would be beneficial for academia and industry-related professionals involved in model development in different stages of biofuel's life cycle. [ABSTRACT FROM AUTHOR]

To enhance the move towards a sustainable society, the solar Photovoltaic (PV) industry and its applications are progressing at a rapid rate. However, the associated issues need to be addressed when connecting PV to the grid. Advanced and efficient controllers are required for the DC link to control the second harmonic ripple and current controllers to inject quality active and reactive power to the grid in the grid-connected PV system. In this paper, DC-link voltage, active power, and reactive power are successfully controlled in stationary reference using Adaptive-PI (A-PI) and Adaptive-Sliding Mode Controller (A-SMC) for a 3 kW single-phase two-stage transformerless grid-connected inverter. A Resonant Harmonic Compensator (RHC)-based Proportional Resonant (PR) controller is employed in the current-controlled loop. The magnitude, phase, and frequency information of the grid voltage are provided by Second-Order General Integral (SOGI)-based PLL that has harmonic immunity, fast-tracking accuracy, and a rapid-dynamic response. MATLAB®/Simulink®/Simscape R2017b were used for the test bench implementation. Two scenarios were considered: in the first case, the input PV power feedforward loop was avoided, while in second case, it was included. The feedforward loop of input PV power improved the overall system dynamics. The results show that the designed controller improves both the steady-state and dynamic performance as compared with a proper-regulated PI-controller. The proposed controllers are insensitive to active and reactive power variations, and are robust, stable, faster, and fault tolerant, as compared to controllers from prior studies. [ABSTRACT FROM AUTHOR]

In the 21st century, researchers have been showing keen interest in the areas of wireless networking and internet of things (IoT) devices. Conventionally, batteries have been used to power these networks; however, due to the limited lifespan of batteries and with the recent advancements in piezoelectric technology, there is a dramatic increase in renewable energy harvesting devices. In this research, an eco-friendly wind energy harvesting device based on the piezoelectric technique is analytically modeled, numerically simulated, and statistically optimized for low power applications. MATLAB toolbox SIMSCAPE is utilized to simulate the proposed wind energy harvester in which a windmill is used to produce rotational motion due to the kinetic energy of wind. The windmill's rotational shaft is further connected to the rotary to linear converter (RLC) and vibration enhancement mechanism (VEM) for the generation of translational mechanical vibration. Consequently, due to these alternative linear vibrations, the piezoelectric stack produces sufficient electrical output. The output response of the energy harvester is analyzed for the various conditions of piezoelectric thickness, wind speed, rotor angular velocity, and VEM stiffness. It is observed that the electrical power of the proposed harvester is proportional to the cube of wind speed and is inversely proportional to the number of rotor blades. Furthermore, an optimization strategy based on the full factorial design of the experiment is developed and implemented on MINITAB 18.0 for evaluating the statistical performance of the proposed harvester. It is noticed that a design with 3 rotor-blades, having 3 mm piezoelectric thickness, and 40 Nm−1 stiffness generates the optimum electrical response of the harvester. [ABSTRACT FROM AUTHOR]

Unlike the plug-in charging system, which has safety concerns such as electric sparks, wireless power transfer (WPT) is less-time consuming, is environmentally friendly and can be used in a wet environment. The inclusion of hybrid energy storage systems (HESSs) in electric vehicles (EVs) has helped to increase their energy density as well as power density. Combined with static wireless power transfer, a WPT–HESS system is proposed in this article. The HESS system includes a battery and supercapacitor (SC) connected to a WPT system through DC–DC converters. To ensure a stable DC bus voltage, an inductor–capacitor–capacitor series (LCC-S) compensation network has been implemented in the WPT system. Utilizing the two-port network theory, the design equations of the LCC-S compensation network are derived in order to realize the maximum efficiency point for the WPT system. To ensure that the WPT system operates at this maximum efficiency point and that the SC is charged to its maximum capacity, an energy management system (EMS) has been devised that generates reference currents for both the SC and battery. An integral terminal sliding mode controller (ITSMC) has been designed to track these reference currents and control the power flow between the energy storage units (ESUs) and WPT system. The stability of the proposed system is validated by Lyapunov theory. The proposed WPT–HESS system is simulated using the MATLAB/Simulink. The robustness of the ITSMC against the widely used proportional–integral–derivative (PID) and sliding mode controller (SMC) is verified under abrupt changes in the associated ESU resistance and reference load current. Finally, the simulations of the WPT–HESS system are validated by controller hardware-in-loop (C-HIL) experiments. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive nonlinear control strategy for the energy management of a polymer electrolyte membrane fuel cell and supercapacitor-based hybrid electric vehicle is proposed. The purpose of this work was to satisfy: (i) tight DC bus voltage regulation, (ii) good fuel cell reference current tracking, (iii) better supercapacitor reference current tracking (iv) global asymptotic stability of the closed-loop control system, and (v) better vehicle performance by catering to slowly-varying parameters. We have selected the power stage schematic of a hybrid electric vehicle and utilized adaptive backstepping and adaptive Lyapunov redesign-based nonlinear control methods to formally derive adaptive parametric update laws for all slowly-varying parameters. The performance of the proposed system has been tested under varying load conditions using experimental data from the "Extra Urban Driving Cycle." Mathematical analysis and Matlab/Simulink results show that proposed controllers are globally asymptotically stable and satisfy all the design requirements. The physical effectiveness of proposed system has been verified by comparing simulation results with the real-time controller hardware in the loop experimental results. Results show that proposed system shows satisfactory performance and caters for the time-varying parametric variations and the load requirements. [ABSTRACT FROM AUTHOR]

The problem of extracting maximum power from a photovoltaic (PV) system with negligible power loss is concerned with the power generating capability of the PV array and nature of the output load. Changing weather conditions and nonlinear behavior of PV systems pose a challenge in tracking of varying maximum power point. A robust nonlinear controller is required to ensure maximum power point tracking (MPPT) by handling nonlinearities of a system and making it robust against changing environmental conditions. Sliding mode controller is robust against disturbances, model uncertainties and parametric variations. It depicts undesirable phenomenon like chattering, inherent in it causing power and heat losses. In this paper, a supertwisting sliding mode algorithm based nonlinear robust controller has been designed for MPPT of a PV system which not only removes the chattering but also enhances the overall system's dynamic response. Moreover, supertwisting sliding mode controller is robust against changing environmental conditions like change in temperature and irradiance. Noninverting DC-DC Buck-Boost converter has been used as an interface between source and the load. The efficiency of MPPT of a PV system depends upon the accuracy of reference for peak power voltage, therefore an efficient mechanism for reference generation has also been proposed in this work. The reference for peak power voltage has been generated by using a trained artificial neural network, which is to be tracked by proposed nonlinear controllers. Sliding mode controller (SMC) and synergetic controllers have also been designed for MPPT of a PV system in order to compare them with supertwisting sliding mode controller (ST-SMC). Global asymptotic stability of the system has been ensured by using Lyapunov stability criterion. The performance of the proposed nonlinear controllers has been validated in MATLAB/Simulink ODE 45 environment. ST-SMC has also been compared with recently proposed integral backstepping controller and other conventional MPPT controllers given in the literature. The simulation results show the better performance of ST-SMC in terms of best dynamic response and robustness. [ABSTRACT FROM AUTHOR]

The crude distillation unit (CDU) is one of the most energy-intensive processes of a petroleum refinery. The composition of crude is subject to change on regular basis. The uncertainty in crude oil composition causes wastage of a substantial amount of energy in the CDU operation. In this study, a novel approach based on a multi-output artificial neural networks (ANN) model was devised to cope with variations (uncertainty) in crude composition. The proposed method is an extended version of another method of cut-point optimization based on hybridization of Taguchi and genetic algorithm. A data comprised of several hundred variations of crude compositions and their optimized cut point temperatures, derived from the hybrid approach, was used to train the ANN model. The proposed method was validated on a simulated CDU flowsheet for a Pakistani crude, i.e., Zamzama. The proposed method is faster and computationally less expensive than the hybrid method. In addition, it can efficiently predict optimum cut point temperatures for any variant of the crude composition. [ABSTRACT FROM AUTHOR]

°CThe research significance of various scientific aspects of photovoltaic (PV) systems has increased over the past decade. Grid-tied inverters the vital elements for the effective interface of Renewable Energy Resources (RER) and utility in the distributed generation system. Currently, Single-Phase Transformerless Grid-Connected Photovoltaic (SPTG-CPV) inverters (1–10 kW) are undergoing further developments, with new designs, and interest of the solar market. In comparison to the transformer (TR) Galvanic Isolation (GI)-based inverters, its advantageous features are lower cost, lighter weight, smaller volume, higher efficiency, and less complexity. In this paper, a review of SPTG-CPV inverters has been carried out. The basic operational principles of all SPTG-CPV inverters are presented in details for positive, negative, and zero cycles. A comprehensive analysis of each topology has been deliberated. A comparative assessment is also performed based on weaknesses, strengths, component ratings, efficiency, total harmonic distortion (THD), semiconductor device losses, and leakage current of various SPTG-CPV inverters schemes. Typical PV inverter structures and control schemes for grid connected three-phase system and single-phase systems are also discussed, described, and reviewed. Comparison of various industrial grids-connected PV inverters is also performed. Loss analysis is also performed for various topologies at 1 kW. Selection of appropriate topologies for their particular application is thoroughly presented. Then, discussion and forthcoming progress are emphasized. Lastly, the conclusions are presented. More than 100 research publications on the topic of SPTG-CPV inverter topologies, configurations, and control schematics along with the recent developments are thoroughly reviewed and classified for quick reference. [ABSTRACT FROM AUTHOR]