Modern Industrial Electronics (4th Edition Pdf Free Download)

[Janne Evers]

LinearSystems Theory (EE 550) L-T-P-C : 3-0-0-6

Course Contents:

Maths Preliminaries: Vector Spaces, Change of Basis, Similarity Transforms, Introduction: Linearity, Differential equations, Transfer functions, State Space representations, Evolution of State trajectories Time Invariant and Time Variant Systems, Controller Canonical Form, Transformation to Controller Canonical form SI, MI, State Feedback Design SI, MI, Discrete time systems representation, reachability and state feedback design, Observability: Grammian, Lyapunov Equation, Output Energy, Observability matrix Observer canonical form (SO, MO), Unobservable subspace, Leunberger Observer (SO, MO), State Feedback with Leunberger Observers, Minimum order observers, Stabilizability and Detectability.

Modern Power Systems (EE 570) L-T-P-C : 3-0-0-6

Course Contents:

Introduction to modern power system: interconnected power system, main objective in operation of power system, structure of Indian power system; Power Component static and dynamic modeling: static modeling of transmission lines, transformer, and capability curve of generator ; Power flow analysis: Gauss-Seidel, Newton-Raphson (polar and rectangular form), decoupled load flow, fast decoupled power flow, DC load flow, Distribution system power flow ; Contingency analysis: contingency ranking, DC and AC sensitivity analysis ; Power system stability: equal area criteria, rotor angle and voltage stability, energy function approach towards transient stability prediction; Power system Operation and Control: Economic load dispatch, load frequency control.

Insulation and High Voltage Engineering (EE 571) L-T-P-C : 3-0-0-6

Course Contents:

Introduction to HV engineering course and challenges & opportunities in electric power equipment industry; Insulation engineering: Insulation materials, Stresses on power apparatus insulation & insulation systems of various power apparatus; Fundamentals of Insulation Breakdown: Electrical breakdown in gases, liquid and solid dielectrics; Stress Control: Principles of stress control, Stress distribution in multiple dielectrics, Stress calculation; Generation of high voltages in laboratory: Generation of High voltage AC by cascading and series resonant system, High DC voltages, Multistage impulse generator circuits, Impulse current generator; Measurement of High Voltages : AC voltage, DC voltage, Impulse voltages; Non-Destructive Insulation Assessment: Schering bridge, Ampere turns bridge, Standard Capacitor, Partial discharge; Testing of Power apparatus: Non-destructive tests to check integrity of insulation of on various power apparatus, Impulse test of transformers.

Power Electronics Applications in Power Systems (EE 562) L-T-P-C : 3-0-0-6

Course Contents:

Power electronic converters, Basic power system operation, Role of power electronics in power systems; High Voltage DC Transmission and Flexible AC Transmission Systems (FACTs), Principles of series and shunt compensators, Various FACTs devices; Power Quality Requirements, types of loads, harmonics, Active and Passive filters, Shunt, series and hybrid filters, Power Quality Conditioners; Uninterruptible Power Supplies, Power electronics in domestic and industrial loads; Power conditioning units for renewable power generation and distributed generation systems.

Electrical Machines and Drive Systems (EE 580) L-T-P-C : 3-0-0-6

Course Contents:

Introduction to generalized theory of electrical machines, Reference-frames, modeling of dc machines, Induction machine modeling in various reference frames, Per-unit system, Synchronous machine modeling, Steady-state and transient analysis, Field-oriented control of induction motor drives, Sensorless control and estimation, Permanent magnet synchronous motor and brushless dc motor drives.

Electronics is everywhere in modern Western societies, but so is its environmental impact. Electronic devices and components enable and embed some of the most innovative technologies that are reshaping our world, from robotics to domotics, from electric mobility to artificial intelligence (Rasmussen et al. 2020). The electrical and electronic equipment (EEE) sector is a key enabler of the transitions to renewable energy systems, new modes of circular production and climate-resilient economies (European Commission 2020). However, the growth in the EEE industry comes with a heavy and increasing environmental footprint (De Felice et al. 2014). The production and consumption of EEE face two core problems in terms of environmental sustainability: first, its reliance on scarce minerals and rare metals (Bressanelli et al. 2021), whose extraction causes a wide range of environmental spillovers, and second, the production of a stream of e-waste, as also called WEEE (waste of EEE), containing hazardous substances and potentially valuable materials (Forti et al. 2020; Man et al. 2012).

In this context, the ecological transition to carbon neutrality, circular economy models and systemic improvements in sustainability offer companies in this industry new opportunities for competitiveness, but the process is not without barriers (Rizos and Bryhn 2022). Some companies operating in EEE supply chains are attempting to achieve tangible improvements in the sustainability of their products and processes, but they are facing numerous challenges deriving from the high complexity that reigns over this industry (Menon and Ravi 2021a). One of the most well-studied dimensions of complexity in this sector is in terms of its supply chain. The global scope of electronics supply chains, in fact, exposes companies to the propagation of systemic risks and disruptive events (Jttner and Maklan 2011; Ponis and Koronis 2012; Tukamuhabwa et al. 2015), which represent both a challenge and an opportunity for complexity management and, ultimately, for improving environmental, social and financial sustainability (Donadoni et al. 2018).

Given the increasing number of international shocks recently affecting the global economy, with the COVID-19 pandemic and ensuing supply chain disruptions as some of the most prominent examples, companies are directing increasing efforts toward developing their resilience strategies, by prioritizing management tools and innovations that support preparedness and long-term stability (Orlando et al. 2022; Pellegrino and Gaudenzi 2023). Consequently, complexity management has the potential to boost resilience and, in turn, competitiveness and sustainability (e.g., Donadoni et al. 2018; Lger et al. 2022; Luo et al. 2017). Moreover, recent studies have provided ample empirical evidence of the growing importance of complexity management in organizations (Pavlov and Micheli 2023; Reeves et al. 2020). For example, among a set of senior executives, a majority perceive the level of complexity within their organizations as excessive and do not have access to appropriate complexity management (Shey and Roesgen 2012). Another study highlights how most managers interviewed believe that, in future, complexity will become an increasingly crucial factor in corporate administration (Jger et al. 2014). However, more evidence is required on how complexity management is linked to corporate sustainability management and competitiveness, to better characterize how it can strengthen long-term resilience (Bianchi et al. 2022; Espinosa and Porter 2011; Wiedmer et al. 2021).Footnote 1

Overall, our contribution to the existing literature is twofold. First, since the relationship between complexity and corporate sustainability management is not univocal, we want to investigate precisely how complexity management is linked to corporate sustainability in this specific setting and thus build a novel framework on the relationship between different types of complexity and Corporate Sustainability Management (CSR). Second, we explore how the identified dimensions of complexity management can impact the adoption of sustainable innovations that increase long-term resilience in the EEE industry. By implementing an in-depth longitudinal case study methodology, our research analyzes how complexity is perceived by practitioners, what difficulties it poses, how it is managed and whether it can open new business opportunities, thus enhancing the competitiveness and resilience of an organization.

Finally, answering these research questions with our case study allows us not only to build a conceptual framework that relates sustainability and complexity management with organizational resilience, but also provides practical managerial implications highlighting how to exploit complexity to incorporate green innovations to handle sustainability as a business opportunity rather than a cost. We find that one key activity that enables the creation of comparative advantage in the joint management of sustainability and complexity is the capacity to effectively transfer innovations, new methodologies and know-how regarding greener solutions across products or clients within a complex system.

The remainder of the paper is organized as follows. Section 2 presents the theoretical background on managing complexity, corporate sustainability and resilience. Section 3 illustrates the methodological approach of the article. Section 4 examines the results of the supporting case study and the emerging conceptual framework. Finally, Sect. 5 concludes with some further discussion, while Appendix shows unstructured questionnaire used for the interviews.

Our research contributes to the literature on complexity management, corporate sustainability strategies and their link with resilience and long-term competitiveness. We examine the most relevant findings for each of these areas of research in the following sections.

Complexity is an elusive construct that is often placed at the center of corporate management and strategy, whose interpretation and conceptualization can vary according to the specific research field (Jacobs and Swink 2011). In particular, since the 1960s, complexity has been a dominant concept in the organization research arena (Anderson 1999). A complex system responds to the classic definition of being made of a large number of parts that have multiple interactions (Simon 1962). The level of complexity of the organization tends to grow with increasing abundance (the number of elements that influence each other), correlation (the strength of mutual relationships) and diversity (Osbert-Pociecha 2013). From this definition, it is possible to classify two different types of complexity. The first one is structural complexity, which refers to the number of different elements constituting the system; the second one is dynamic complexity, which refers to the number of interactions within the system (Bode and Wagner 2015).

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