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The purpose of this study is to investigate the challenges before India for electric vehicle (EV) adoption by 2030. The study further looks into the measures taken by the Government of India (GOI) to promote research and development in EV sector and what is yet to be done.

In the present study, the challenges are identified allied to the commercialization of EVs in India. The data are collected, analyzed and compiled through secondary sources. The secondary data give a concise insight and comprehensive information regarding what is occurring around the globe as well as in the Indian context. Further, the challenges are investigated through a focus group study consisting of 11 participants from industry and academia.

The findings from the study are the critical roles of sharing economy and public utilities in the promotion of EV adoption, given the high cost of EV, lack of infrastructure and poor purchasing power of Indian customers. The sharing economy perspective provides various opportunities for the government to manage the resources (electric-powered transport system) optimally. Further, the study compares the global perspective in assigning the target figures.

The study highlights the facilitating role of the shared format in EV technology promotion but ignores the hurdles that can come in its implementations. Also, the focus group study has its limitation as it relies more on participants' perceptions and opinions.

The present study assists GOI and various stakeholders in having a realistic plan rather than daydreaming with overambitious goals. The diffusion of technology as a shared format (especially in the context of EV) has not been academically approached in the past literature.

This study aims to develop an automatic lane-change mechanism on highways for self-driving articulated trucks to improve traffic safety.

The authors proposed a novel safety lane-change path planning and tracking control method for articulated vehicles. A double-Gaussian distribution was introduced to deduce the lane-change trajectories of tractor and trailer coupling characteristics of intelligent vehicles and roads. With different steering and braking maneuvers, minimum safe distances were modeled and calculated. Considering safety and ergonomics, the authors invested multilevel self-driving modes that serve as the basis of decision-making for vehicle lane-change. Furthermore, a combined controller was designed by feedback linearization and single-point preview optimization to ensure the path tracking and robust stability. Specialized hardware in the loop simulation platform was built to verify the effectiveness of the designed method.

The numerical simulation results demonstrated the path-planning model feasibility and controller-combined decision mechanism effectiveness to self-driving trucks. The proposed trajectory model could provide safety lane-change path planning, and the designed controller could ensure good tracking and robust stability for the closed-loop nonlinear system.

This is a fundamental research of intelligent local path planning and automatic control for articulated vehicles. There are two main contributions: the first is a more quantifiable trajectory model for self-driving articulated vehicles, which provides the opportunity to adapt vehicle and scene changes. The second involves designing a feedback linearization controller, combined with a multi-objective decision-making mode, to improve the comprehensive performance of intelligent vehicles. This study provides a valuable reference to develop advanced driving assistant system and intelligent control systems for self-driving articulated vehicles.

This paper studies the lateral stability regulation of intelligent electric vehicle (EV) based on model predictive control (MPC) algorithm.

Firstly, the bicycle model is adopted in the system modelling process. To improve the accuracy, the lateral stiffness of front and rear tire is estimated using the real-time yaw rate acceleration and lateral acceleration of the vehicle based on the vehicle dynamics. Then the constraint of input and output in the model predictive controller is designed. Soft constraints on the lateral speed of the vehicle are designed to guarantee the solved persistent feasibility and enforce the vehicle’s sideslip angle within a safety range.

The simulation results show that the proposed lateral stability controller based on the MPC algorithm can improve the handling and stability performance of the vehicle under complex working conditions.

The MPC schema and the objective function are established. The integrated active front steering/direct yaw moments control strategy is simultaneously adopted in the model. The vehicle’s sideslip angle is chosen as the constraint and is controlled in stable range. The online estimation of tire stiffness is performed. The vehicle’s lateral acceleration and the yaw rate acceleration are modelled into the two-degree-of-freedom equation to solve the tire cornering stiffness in real time. This can ensure the accuracy of model.

The purpose of this paper is to investigate problems in performing stable lane changes and to find a solution to reduce energy consumption of autonomous electric vehicles.

An optimization algorithm, model predictive control (MPC) and Karush–Kuhn–Tucker (KKT) conditions are adopted to resolve the problems of obtaining optimal lane time, tracking dynamic reference and energy-efficient allocation. In this paper, the dynamic constraints of vehicles during lane change are first established based on the longitudinal and lateral force coupling characteristics and the nominal reference trajectory. Then, by optimizing the lane change time, the yaw rate and lateral acceleration that connect with the lane change time are limed. Furthermore, to assure the dynamic properties of autonomous vehicles, the real system inputs under the restraints are obtained by using the MPC method. Based on the gained inputs and the efficient map of brushless direct-current in-wheel motors (BLDC IWMs), the nonlinear cost function which combines vehicle dynamic and energy consumption is given and the KKT-based method is adopted.

The effectiveness of the proposed control system is verified by numerical simulations. Consequently, the proposed control system can successfully achieve stable trajectory planning, which means that the yaw rate and longitudinal and lateral acceleration of vehicle are within stability boundaries, which accomplishes accurate tracking control and decreases obvious energy consumption.

This paper proposes a solution to simultaneously satisfy stable lane change maneuvering and reduction of energy consumption for autonomous electric vehicles. Different from previous path planning researches in which only the geometric constraints are involved, this paper considers vehicle dynamics, and stability boundaries are established in path planning to ensure the feasibility of the generated reference path.

The purpose of this paper is to investigate the effects of gamification on connections between consumers’ self-image congruence in relation to the purchasers of an environmentally friendly product electric vehicles (EVs) and their possession of a stereotype of EV owners as being “unconventional”, and their attitudes towards EVs, having regard to their levels of environmental concern and prior knowledge of EVs. Additionally, the research explored the link between attitudes towards and willingness to purchase EVs.

Participants completed a questionnaire and an Implicit Association Test (IAT) both before and after playing a computer game wherein the player assumed the identity of an EV driver. A structural equation model was constructed to predict attitude to EVs. The relationship between attitude and willingness to purchase was examined via a conditional process analysis.

The experience of playing the game improved the favourability of the respondents’ stereotype of EV owners by an average of 19 per cent, and their attitude towards EVs by 17 per cent. Self-image congruence in relation to EV ownership increased on the average by 14 per cent and reported EV product knowledge by 8 per cent. However, willingness to purchase an EV was not substantially affected. The link between attitude and willingness to purchase was weak, but was significantly moderated by stereotype favourability and self-image congruence with EV owners.

As with any IAT study, it was necessary to pre-specify a particular form of stereotype. Future research could employ alternative stereotypes. The investigation took place in a single country and involved a single environmentally friendly product.

Gamification has much potential for helping manufacturers and government agencies to stimulate the mass market for EVs. To negate unfavourable images of EV owners, marketing communications promoting EVs might usefully employ celebrities, sports personalities and/or leading political figures as exemplars of the types of people who drive electric cars.

The research is the first to explore the effects of gamification on product user self-image congruence and stereotype formation. It is novel both in its employment of an IAT to measure the consumer stereotype of an environmentally friendly product and in its examination of the moderating influences of stereotype and product user self-image congruence on the attitude-willingness to purchase link.

With the UK’s accelerating plans to transition to electric mobility, this paper aims to highlight the need for policies to prepare for appropriate management of electric vehicle (EV) lithium-ion batteries (LIBs) as they reach the end of their life.

This is a regulatory review based on projections of EV LIBs coming off the market and associated problems of waste management together with the development of a servitisation model.

Circular economy in EV LIBs is unlikely to shape itself because LIB recycling is challenging and still in development. LIB volumes are insufficient for recycling to be currently profitable, and a circular economy here will need to be driven by regulatory intervention. Ignoring the problem carries potentially high environmental and health costs. This paper offers potential solutions through new EV ownership models to facilitate a circular economy.

The authors suggest a new EV ownership model. However, despite environmental benefits, re-shaping the fundamentals of market economies can have disruptive effects on current markets. Therefore, further exploration of this topic is needed. Also, the data presented is based on future projections of EV markets, battery lifespan, etc., which are uncertain at present. These are to be taken as estimates only.

The paper proposes regulatory interventions or incentives to fundamentally change consumer ideas of property ownership for EVs, so that EV automotive batteries remain the property of the manufacturer even when the consumer owns the car.

The conventional two-level inverter suffers from harmonics, higher direct current (DC) link voltage requirement, higher dv/dt and heating of the rotor. This study aims to overcome by using a multilevel inverter for brushless DC (BLDC) drive.

This paper presents a comparative analysis of the conventional two-level and three-level multilevel inverter for electric vehicle (EV) application using BLDC drive.

A three-level Active Neutral Point Clamped Multilevel inverter (ANPCMLI) is proposed in this paper which provides DC link voltage control. Simulation studies of the multilevel inverter and BLDC motor is carried out in MATLAB.

The ANPCMLI fed BLDC simulation results shows that there is the significant reduction in the BLDC motor torque ripple, switching stress and harmonic distortion in the BLDC motor fed ANPCMLI compared to the conventional two-level inverter. A prototype of ANPCMLI fed BLDC drive along with field programmable gate array (FPGA) control is built and MATLAB simulation results are verified experimentally.

This research examines the drivers of electric vehicle (EV) acceptance in the Kingdom of Saudi Arabia (KSA) by applying the unified theory of acceptance and use of technology (UTAUT) model, contextualized for the EV setting. The study aims to provide insights supporting the transition to sustainable transportation and identifying consumer perceptions and behavioral intentions toward EV adoption.

Based on survey data from a convenience sample collected from undergraduate and MBA students in a major university of KSA, the authors use seemingly unrelated regressions to provide novel insights on electric vehicle acceptance.

The study shows UTAUT constructs influence purchase intentions and attitudinal outcomes. Results indicate that perceived EV sustainability plays an important role in the relationship between UTAUT constructs and purchase intention alongside attitudes toward EV technology. Technological innovativeness enhances the impact of EV attitude and weakens the effect of perceived EV sustainability on purchase intention.

The study benefits researchers on sustainable technology acceptance and stakeholders facilitating sustainable transportation shifts. The insights guide the promotion of eco-friendly transportation solutions.

The research contextualizes and extends the UTAUT model constructs to understand drivers of EV acceptance. The study contributes to understanding sustainable innovation acceptance, considering the mediating role of perceptions of EV sustainability and the moderating role of technological innovativeness in driving purchase intentions.

Electric cars have very little market share in developing countries despite their environmental benefits. Thus, governments have started promoting electric cars by providing financial incentives to consumers. The current article aims to examine the direct and indirect effects of government financial incentives on consumer electric car adoption in India.

The study followed a quantitative research method that employed a self-administered survey questionnaire. Structural Equation Modelling and Multi-Group Analysis were followed for data analysis.

The study revealed that financial incentives have an indirect effect on electric car adoption intention rather than a direct effect. In addition, financial incentives were found to have a direct effect on attitude and Perceived Behavioural Control (PBC). Attitude and PBC positively influenced consumer adoption intention.

The insights and implications from the present study would help policymakers and marketers to formulate better incentive policies and market strategies to increase consumer acceptance of electric cars in developing countries.

The study contributes to the literature by analysing the underlying mechanism that links government financial incentives to electric car adoption intention. This study also explored the direct effect of financial incentives on attitude and PBC, which are less investigated in electric vehicle literature. In addition, the present article also assessed the moderating role of age in electric car adoption, which has mixed evidence in the literature, and such studies are scarce in the Indian context.

The cutting process of the electric machine laminations causes residual mechanical stress in the soft magnetic material. A local magnetic deterioration can be observed and the resulting local and global iron losses increase. A continuous local material model for the consideration of the changing magnetization properties has been introduced in a previous work as well as an a priori assessment of iron losses. A local iron loss calculation considering both a local magnetization and local loss parameters misses yet. The purpose of this study is to introduce a local iron loss calculation model considering both a local magnetization and local loss parameters.

In this paper, an approach for local iron loss simulation is developed and a comparison to the cut-edge length-dependent loss model is given. The comparison includes local loss distribution in the lamination as well as the impact on the overall motor efficiency and vehicle range in an electric vehicle driving cycle.

For an analysis of the resulting local iron loss components, both the local magnetization and iron loss parameters must be considered using physically based models. Consistently, a local iron loss model is presented in the work. The developed model can be used to gain detailed information of the local loss distribution inside the machine. The comparability of this local iron loss with the cut-edge length approach for overall system characteristics, e.g. efficiency or driving range, is shown.

A local iron loss simulation approach is a physical accurate model to describe the influence of cutting techniques on electric machine characteristics. A comparison with the less complicated a priori assessment gives detailed information about the necessity of the local model under consideration of the given problem.