Department of Mechanical engineering

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Author: search.filters.author.Digalwar, Abhijeet KumarSubject: search.filters.subject.Electric vehicles (EVs)

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Now showing 1 - 6 of 6
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    A comprehensive framework for analysis and evaluation of factors responsible for sustainable growth of electric vehicles in India
    (Elsevier, 2022-12) Digalwar, Abhijeet Kumar
    The Indian transport sector powered by fossil fuels is primarily responsible for creating severe issues like greenhouse gas emissions, foreign fuel dependency, economic burden, and chronic health effects. To mitigate these severe issues, electric vehicles (EVs) are positioned as an alternate green and clean technology, which can potentially enable the efficient transition to a sustainable low-carbon emission transportation system and preservation of natural scarce resources. Despite announcing favorable policy measures to encourage EV adoption, the multiplicity of potential factors with mutual interaction has resisted its penetration in several countries. Though researchers have identified the critical factors, the question “How do these factors mutually interact among themselves?” has remained largely unanswered in empirical research. Unpacking the relationship between the factors will empower manufacturers and policymakers in strategic planning, and devising suitable measures in controlling the factors. The primary goal of this research is to undertake a thorough assessment and give a brief understanding of the various factors responsible for sustainable growth of EVs market in India. Factors are identified from past academic literature and experts' interviews. Study further empirically validated the identified factors. Then integrated Decision-Making Trial and Evaluation Laboratory (DEMATEL) – Interpretive Structural Modeling (ISM) approach has been used to demonstrate the interrelationship and hierarchal structure of the factors. The present study will be useful to the manufacturers, policymakers to focus on the gray area so that they can expedite the growth of EVs deployment in India.
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    Modeling the supply chain risk and barriers to electric vehicle technology adoption in India
    (Springer, 2023-12) Digalwar, Abhijeet Kumar
    The Electric Vehicle (EV) technology is believed to be the most effective to reduce dependency on petrol and diesel vehicles and thereby achieve clean environmental objectives. In pursuit of achieving emission net zero by 2070, central government and state governments are putting substantial efforts to drive the EV technology growth in India. The central and state governments in India through various schemes such as Faster Adoption and Manufacturing of Hybrid and Electric Vehicles (FAME-II), Production Linked Incentive Scheme (PLI), Swapping policy for batteries, Special Electric Mobility Zone, and subsidies such as tax rebate on EVs. Yet the complete switch to the EVs from petrol and diesel vehicles, still has significant technology and supply chain barriers. This research paper identifies the risks and barriers with respect to supply chain, technology, finance, and policy for the growth of EV technology in India. The research paper using an Interpretive Structural Model (ISM) demonstrates the critical supply chain barriers. Based on the analysis carried out in this research paper, the barriers such as availability of battery packs, raw materials, charging network, and interoperability of batteries are the most critical supply chain barriers to implementing EV technology in India. The research findings will enable policymakers to develop a sustainable EV supply chain in India and in similar developing countries.
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    Modelling factors influencing charging station location selection to accelerate ev adoption in India: an ISM-MICMAC analysis
    (Springer, 2023-12) Digalwar, Abhijeet Kumar; Routroy, Srikanta
    Electric vehicles (EVs) are rising fast to prominence as a key component of the effort to meet sustainable energy goals. The research and mass manufacturing of new energy vehicles, especially electric vehicles, offer several benefits over conventional energy vehicles, such as zero exhaust emissions, zero pollution, cleanliness, and low cost. As a result, more and more nations are paying attention and placing importance over the development of EV-fleet, but EV sales are still a modest part of all vehicle sales. The protruding reason highlighted by the literature and researchers is underdeveloped charging infrastructure. To get the most out of an EV, an appropriate charging station with optimum configuration needs to be placed in a specific location with all the infrastructure to make it supportive and sustainable hotspot for EVs. This study aims to identify all the factors that needs to be considered while selecting a location for setting up a sustainable charging station for EVs in semi-urban areas. A deeper understanding of factors is explored, using interpretive structural modelling (ISM) and MICMAC analysis. A total of 17 factors are considered for the analysis which are crucial in developing the configurations for an EV charging station. The outcomes of the paper will support the policymakers to locate, determine and decide the suitable locations, and configuration for constructing EV charging stations and escalate the EV adoption.
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    A data-driven framework for optimizing multi-period ev charging infrastructure deployment
    (IEEE, 2024-12) Digalwar, Abhijeet Kumar; Routroy, Srikanta
    The rise of electric vehicles represents a transformative shift in the automotive industry, signaling the dawn of a new era of clean, sustainable transportation, but their operation requires a distributed rapid-charging infrastructure. Building such rapid charging networks is currently capital-intensive and therefore, requires careful planning and the development of the charging infrastructure must be maintained. However, infrastructure construction is not a one-off investment but a multi-period plan. A multi-period location and capacity expansion model of the charging stations will be needed. This study proposes a novel data-driven framework for deploying suitable rapid-charging infrastructure for EVs in large urban areas. This study combines an iterative clustering technique with a geographical information system analysis tool to determine the suitable regions for developing an optimized EV charging service. The analysis intends to plan a case study for Gurugram City of India and suggest the locations that should be the potential points for consideration of charging station development.
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    Assessments of social factors responsible for adoption of electric vehicles in India: a case study
    (Emerald, 2023-01) Digalwar, Abhijeet Kumar
    Environmental crisis and energy security concerns forced researchers, environmentalists and industrialists to look for a cleaner mode of transportation. Rigorous efforts have been made to make electric vehicles (EVs) feasible for commercial use. However, despite of many efforts by the Government of India, the rate of adoption of EVs in India has not been up to the mark. To bridge this gap, present study understands the social acceptability and sustainability of EVs and identifies the social factors, builds inferences from the results obtained and helps in orienting the manufacturers and decision makers towards faster adoption of the EVs.
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    Assessment of EVs Adoption in India Using AHP-BWM Approach
    (Routledge, 2023) Routroy, Srikanta; Digalwar, Abhijeet Kumar
    The deployment of electric vehicles (EVs) is considered as one of the potential solutions for addressing the issues like climate change, energy security and air pollution. At present, for most of the people, pollution has become an alarming concern. Pollution free environment is what everyone is aiming for, but the actions are taking apart from the goal of sustainable and environment friendly surroundings. Among various factors for pollution in India, the transportation sector holds a significant share of approximately 21% of CO2 emissions. While, the pacing numbers of registrations of automobiles in India, needs an immediate direction which must result into sustainable and environmentally friendly modes of transportation. The possible solution to this current dilemma is shifting on EVs. However, EV acceptance is not taking place at a desirable rate, although it is intended to grow in the coming years. This qualitative study incorporates exploration of various factors necessary for the adoption of EVs. Although, a big set of complex factors are tangled when considering the adoption of EVs in a developing country like India. The purpose of this study is to catalyse the adoption of EVs in India by highlighting the crucial factors, and validating them using hybrid multi-criteria decision-making method, including best-worst method (BWM), and analytic hierarchy process (AHP).