Reduced order field-circuit modeling of squirrel cage induction machines for automotive applications

Purpose The aim of the paper is to investigate the impacts of simplifications of a reduced-order simulation model of squirrel cage induction machines (SCIMs) by numerical experiments. Design/methodology/approach Design of setups to isolate the main influences on the results of the reduced-order model of SCIMs. Results of time-stepping finite element calculations are used as benchmark. Findings Whereas neglecting eddy current effects and the assumption of a sinusoidal rotor current distribution leads to acceptable deviations in regular inverter operation, the sampling and interpolation of the machine parameters in a two-axis coordinate system considerably deteriorate the model accuracy. Using a polar coordinate system for this purpose is expected to significantly improve the model quality. Originality/value Preparing the ground for a successful, both fast and accurate simulation model of SCIMs as parts of electrified drivetrains.

Aquila Optimization Based Harmonic Elimination in a Modified H-Bridge Inverter

Multilevel inverters (MLIs) are capable of producing high-quality output voltage and handling large amounts of power. This reduces the size of the filter while also simplifying the circuitry. As a result, they have a wide range of applications in industries, particularly in smart grids. The input voltage boosting feature is required to use the MLI with renewable energy. Moreover, many components are required to get higher output voltage levels that add weight and cost to the circuit. Numerous MLI topologies have been identified to minimize the losses, device count, and device ratings. A seven-level modified H-bridge inverter with a reduced component count, and reduced THD is presented in this paper. Two DC sources with six IGBTs have been used to generate a seven-level output voltage, and the Aquila Optimizer (AO) has been implemented to get the regulated output. MATLAB/Simulink environment has been used for designing the simulation model. Furthermore, the simulation result has been validated in the laboratory on a hardware setup using the DSP-TMS320F28335 Launchpad. With the reduced number of switching devices as well as the dc supply, the size of the inverter is compacted and becomes more economical.

Visual Dynamic Simulation Model of Unstructured Data in Social Networks

Social networks contain a large amount of unstructured data. To ensure the stability of unstructured big data, this study proposes a method for visual dynamic simulation model of unstructured data in social networks. This study uses the Hadoop platform and data visualization technology to establish a univariate linear regression model according to the time correlation between data, estimates and approximates perceptual data, and collects unstructured data of social networks. Then, the unstructured data collected from the original social network are processed, and an adaptive threshold is designed to filter out the influence of noise. The unstructured data of social network after feature analysis are processed to extract its visual features. Finally, this study carries out the Hadoop cluster design, implements data persistence by HDFS, uses MapReduce to extract data clusters for distributed computing, builds a visual dynamic simulation model of unstructured data in social network, and realizes the display of unstructured data in social network. The experimental results show that this method has a good visualization effect on unstructured data in social networks and can effectively improve the stability and efficiency of unstructured data visualization in social networks.

Design and Simulation of Manufacturing Organizations Based on a Novel Function-Based Concept

Historically, researchers and managers have often failed to consider organizations as a sum of functions leading to a set of capabilities that produce a product that can serve society’s needs. Furthermore, functions have increased with the development of industrial revolutions, however, many manufacturing organizations have not realized their full potential. As a result, many industrial organizations do not know why, where, and when the existing functions and projects for implementing new functions fail where tactical and strategic functions of a manufacturing organization are commonly over-seen. Thus, the aim of this research was to propose a holistic approach for manufacturing organizations in order to model their functions enabling the assessment, design, management, and control of operations and performance as well as to identify improvement potentials. For this purpose, a conceptual model was developed based on the evolution of functions along with the industrial revolutions. Moreover, using the conceptual model, manufacturing organizations can be modeled, considering common organizational functions in the respective areas of production, maintenance, and quality, etc., in the three planning horizons—strategic, tactical, and operative. As a result, the model serves as a basis for the integral management and control of manufacturing organizations. Moreover, it can be also used as a basis framework for a digital twin model for organizations. Thus, a system dynamics simulation model based on the conceptual model was developed for a generic organization. The goal of the simulation model is to provide an exemplary digital model of a manufacturing organization in which the different functions are applied with different methods, systems, and/or individuals along the development phases.

Hybrid simulation modelling of networks of heterogeneous care homes and the inter-facility spread of Covid-19 by sharing staff

Although system dynamics [SD] and agent-based modelling [ABM] have individually served as effective tools to understand the Covid-19 dynamics, combining these methods in a hybrid simulation model can help address Covid-19 questions and study systems and settings that are difficult to study with a single approach. To examine the spread and outbreak of Covid-19 across multiple care homes via bank/agency staff and evaluate the effectiveness of interventions targeting this group, we develop an integrated hybrid simulation model combining the advantages of SD and ABM. We also demonstrate how we use several approaches adapted from both SD and ABM practices to build confidence in this model in response to the lack of systematic approaches to validate hybrid models. Our modelling results show that the risk of infection for residents in care homes using bank/agency staff was significantly higher than those not using bank/agency staff (Relative risk [RR] 2.65, 95% CI 2.57–2.72). Bank/agency staff working across several care homes had a higher risk of infection compared with permanent staff working in a single care home (RR 1.55, 95%CI 1.52–1.58). The RR of infection for residents is negatively correlated to bank/agency staff’s adherence to weekly PCR testing. Within a network of heterogeneous care homes, using bank/agency staff had the most impact on care homes with lower intra-facility transmission risks, higher staff-to-resident ratio, and smaller size. Forming bubbles of care homes had no or limited impact on the spread of Covid-19. This modelling study has implications for policy makers considering developing effective interventions targeting staff working across care homes during the ongoing and future pandemics.

Performance Analysis of Integrated Photovoltaic-Thermal and Air Source Heat Pump System through Energy Simulation

The concept of zero energy buildings (ZEBs) has recently been actively introduced in the building sector, globally, to reduce energy consumption and carbon emissions. For the implementation of ZEBs, renewable energy systems, such as solar collectors, photovoltaic (PV) systems, and ground source heat pump (GSHP) systems, have been used. The system performance of solar collectors and PV systems are dependent on the weather conditions. A GSHP system requires a large area for boring machines and mud pump machines. Therefore, inhabitants of an existing small-scale buildings hesitate to introduce GSHP systems due to the difficulties in installation and limited construction area. This study proposes an integrate photovoltaic-thermal (PVT) and air source heat pump (ASHP) system for realizing ZEB in an existing small-scale building. In order to evaluate the applicability of the integrated PVT-ASHP system, a dynamic simulation model that combines the PVT-ASHP system model and the building load model based on actual building conditions was constructed. The heating and cooling performances of the system for one year were analyzed using the dynamic simulation model. As the simulation analysis results, the average coefficient of performance (COP) for heating season was 5.3, and the average COP for cooling season was 16.3., respectively. From April to June, the electrical produced by the PVT module was higher than the power consumption of the system and could realize ZEB.

Hybrid simulation model for navigation performance evaluation of the Three Gorges–Gezhouba Dams under novel regulations

As an important project on the golden waterway of the Yangtze River in China, the Three Gorges–Gezhouba Dams (TGGD) plays a pivotal role in the construction of the Yangtze River Economic Belt. To improve the efficiency and safety of ship traffic, some novel navigation regulations have been implemented that change the TGGD operation obviously. For example, a piecewise control strategy proposed in the regulations is applied to control the traffic flow of ships under a sectional manner. With the implementation of these regulations, how to understand the dynamic effects of new changes on TGGD has been an important problem. The purpose of this work is to evaluate the navigation performance of the TGGD via a data- and event-driven hybrid simulation model developed by multi-agent and discrete-event modeling theories. The model simulates the three significant navigable scenarios inherent in the actual operating environment: dry season, wet season, and flood season, reflecting the real situations. The input data come from the statistical analysis of the actual navigation data provided by the Three Gorges Navigation Administration. The validity and reliability of the model are verified by comparing the output results with actual data. Moreover, a set of test experiments are designed to explore the TGGD navigation limit and analyze the key factors that restrict the navigation capacity of the TGGD system. The work is expected to provide a certain decision support for the future cooperative scheduling optimization of the TGGD.