Challenges of the Electric Vehicle Markets in Emerging Economies

Mészáros, Ferenc; Shatanawi, Mohamad; Ogunkunbi, Gabriel Ayobami

doi:10.3311/pptr.14037

Cited by 23 publications

(18 citation statements)

References 14 publications

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“…There is a broad consensus on the large-scale employment of EVs globally. The electricity prices vary across all countries of the world majorly because many countries face problems with reliable and sufficient electricity generation and transmission (Meszaros et al, 2021). Due to rise in ecommerce market throughout the world, there has been a significant rise of two-wheeler transport for commercial purposes, affecting the sustainability of the transport (Anosike et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Analyzing the blockades to electric vehicle mobility in an emerging economy: Toward a triple bottom line sustainable development

Gahlaut

Dwivedi

2023

Sustainable Development

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The emerging economies are moving toward electric vehicles (EVs), which are much sustainable means of transportation. However, many social, economic, and technological blockades of EV mobility remain to be addressed. The study investigates social, economic, and technological blockades for e‐mobility in an emerging economy and simultaneously concentrating on their existing and future business implications. Identification of e‐mobility blockades is obtained through literature review and consensus of the experts. Kappa analysis is used to strain the priority map of the mentioned blockades on the basis of developing consensus among experts. Thereafter, a multi criteria decision making approach that is, best‐worst method is adopted to rank the identified potential blockades. The study models the social, economic, and technological blockades of EV mobility in context of emerging economy. To cater blockades in a desired sequence, the study further suggests the ranking sequence of blockades to enhance e‐mobility toward sustainable development. The findings from the study reveals that “costs associated with EVs and “the lack of government policies, standards, and regulations” are the most important blockades to sustainable EV adoption. Thus, the organizations and the Government need to find ways to reduce the cost of EVs and simultaneously should plan and develop policies to enhance EV adoption and to reduce the usage of gasoline vehicles. The third most important blockade that is, “low demand due to undetermined sustainable benefits” indicates that there is an urgent need to spread awareness among the consumers about the sustainable benefits for the adoption of EVs. Further, the sensitivity analysis reveals that sensitivity range for weightage of the group of academicians lies between 0.3 and 0.7 on a scale of 1. If more weightage is provided to the practical scenario, it is discovered that “location of charging station (BEV4)” is more important than “lack of flexible distribution network (BEV2)” to enhance the amount of EV adoption in India. The study provides insights to practitioners dealing with e‐mobility in emerging economies, showing the appropriate sequence of the blockades to help them build up strategies to mitigate these blockades.

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Section: Introductionmentioning

confidence: 99%

Analyzing the blockades to electric vehicle mobility in an emerging economy: Toward a triple bottom line sustainable development

Gahlaut

Dwivedi

2023

Sustainable Development

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“…The most promising technology came out to be electric propulsion which is widely analyzed in the research (Berton and Haller, 2014; Epstein and O’Flarity, 2019). Electric propulsion do not produce emissions during operation and thus is assumed as environmentally friendly (Meszaros et al , 2020). However, storing the electric energy onboard the aircraft with current battery technology creates additional weight problems to be dealt (Pornet et al , 2014).…”

Section: Introductionmentioning

confidence: 99%

Analyzing well-to-pump emissions of electric and conventional jet fuel for aircraft propulsion

Yildiz

Kale

Nagy

2022

AEAT

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Purpose The purpose of this study is to show the emissions related to electric consumption in electric aviation. Aviation, being one of the main transportation and economical driver of global trade and consumerism, is responsible for an important ratio of anthropogenic emissions. Electric energy use in aircraft propulsion is gaining interest as a method of providing sustainable and environmentally friendly aviation. However, the production of electricity is more energy and emission sensitive compared to conventional jet fuel. Design/methodology/approach A well-to-pump (WTP) energy use and emission analysis were conducted to compare the electricity and conventional jet fuel emissions. For the calculations, a software and related database which is developed by Argonne’s Greenhouse gas, Regulated Emissions, and Energy use in Transportation (GREET®) model is used to determine WTP analysis for electricity production and delivery pathways and compared it to baseline conventional jet fuel. Findings The WTP results show that electricity production and transmission have nine times higher average emissions compared to WTP emissions of conventional jet fuel. The future projection of emission calculations presented in this paper reveals that generating electricity from more renewable sources provides only a 50% reduction in general emissions. The electricity emission results are sensitive to the sources of production. Originality/value The main focus of this study is to analyze the WTP emissions of electric energy and conventional jet fuel for use on hybrid aircraft propulsion.

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“…They are necessary for cell phones, consumer electronic devices, hybrid and electrical vehicles and sustainable energy production. Especially the last two mentioned markets are emerging quickly and therefore the need for permanent magnets will grow significantly in the future [1,2,3]. The state of the art intermetallic phase of high performance permanent magnets is Nd 2 Fe 14 B. Neodymium (Nd) is considered a critical element because of high demand and possible supply risks [4].…”

Section: Introductionmentioning

confidence: 99%

Description of collective magnetization processes with machine learning models

Kornell¹,

Exl²,

Breth³

et al. 2022

Preprint

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This work introduces a latent space method to calculate the demagnetization reversal process of multigrain permanent magnets. The algorithm consists of two deep learning models based on neural networks. The embedded Stoner-Wohlfarth method is used as a reduced order model for computing samples to train and test the machine learning approach. The work is a proof of concept of the method since the used microstructures are simple and the only varying parameters are the magnetic anisotropy axes of the hard magnetic grains. A convolutional autoencoder is used for nonlinear dimensionality reduction, in order to reduce the required amount of training samples for predicting the hysteresis loops. We enriched the loss function with physical information about the underlying problem which increases the accuracy of the machine learning approach. A deep learning regressor is operating in the latent space of the autoencoder. The predictor takes a series of previously encoded magnetization states and outputs the next magnetization state along the hysteresis curve. To predict the complete demagnetization loop, we apply a recursive learning scheme.

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Challenges of the Electric Vehicle Markets in Emerging Economies

Cited by 23 publications

References 14 publications

Analyzing the blockades to electric vehicle mobility in an emerging economy: Toward a triple bottom line sustainable development

Analyzing the blockades to electric vehicle mobility in an emerging economy: Toward a triple bottom line sustainable development

Analyzing well-to-pump emissions of electric and conventional jet fuel for aircraft propulsion

Description of collective magnetization processes with machine learning models

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