World Electr. Veh. J., Volume 16, Issue 3 (March 2025) – 6 articles

With the escalating environmental issues, the imperatives to mitigate greenhouse gas emissions and advance energy products through innovation, energy production, and consumption frequently result in environmental externalities. Conventional markets frequently struggle to address these external factors, resulting in market failures. Consumers are more aware of the environmental repercussions, regulatory mandates, and potential economic benefits of new energy vehicles (NEVs). Consequently, there has been a substantial surge in the demand for NEVs as alternatives to conventional vehicles. This study analyses the method by which innovative technology moves from the stage of purchase intention dissemination toward market adoption and explores strategies to expedite this process. Moreover, it examines how the intentions of customers to purchase ecologically friendly energy goods and their receptiveness to such products affect the expansion of the market. Further analysis indicates that the factors influencing consumers’ attitudes towards NEVs include the adoption of ecological innovation, awareness of environmental product knowledge, and perceived value of innovative, environmentally friendly energy products. The purpose of this study is to expand upon the existing literature on consumer demand, examining the influential factors that extend the Theory of Planned Behaviour (TPB) to enhance consumer intention through internal mechanisms. It explicitly focuses on these aspects, as well as perceived risk (PR) and perceived value (PV), to identify gaps in the literature and contribute to intentions to purchase NEVs in China. This study presents a thorough research framework for efficiently examining customer demand for comparable eco-friendly energy products. It investigates the potential influence of attitudes, subjective norms, perceived behavioural control, and environmental perceptions, specifically those concerning environmental knowledge and concerns. Moreover, personal factors such as attitude, normative beliefs, and perceived control beliefs were found to impact consumer attitudes towards NEVs. The key factor influencing purchasing intention was the attitude towards NEVs. Simultaneously, subjective norms did not have a direct effect on purchase intentions. However, social influence played a significant role in the decision-making process, with perceived behavioural control and subjective norms exerting considerable influence. Full article

This study investigates the impacts of autonomous vehicles (AVs) on the insurance industry from the viewpoint of insurance companies, highlighting the necessity for adaptation due to technological advancements. The research is motivated by the gap in understanding between traditional insurers and automaker-backed insurance services regarding AV implications. The purpose is to identify potential impacts, evaluate the level of concern among diverse insurance companies, and examine their differing perspectives. The methodology includes a literature review, the Analytic Hierarchy Process (AHP), and Spearman correlation analysis. The literature review clarifies the definition of AVs and their impacts on traditional insurance. The AHP assesses the level of concern among insurance companies, and Spearman correlation analysis explores the similarities and differences in perspectives. The findings show that insurance companies largely agree on the transformative impacts of AVs. The primary effects are in “Updates in Insurance Business Operations” and the “Emergence of New Risks”, with less impact on “Changes in the Insurance Market”. A major concern is the complexity of multi-party liability claims. Companies differ in their focus on specific impacts like legal frameworks or system malfunctions, but share concerns about multi-party liability, system malfunctions, and legal gaps. The study anticipates minor impacts on market dynamics and traditional insurance models. The conclusions emphasize that AVs will significantly impact the insurance industry, requiring innovation and adaptation to maintain competitiveness. This includes developing new products, optimizing processes, and collaborating with stakeholders. The study has several implications: customized insurance products, optimized no-fault claims processes, collaborations with automakers and tech firms, data-driven risk assessments, enhanced risk management, and adapting traditional models. Recommendations include building loss experience databases, adopting no-fault insurance, strategic partnerships, developing customized products, strengthening risk management and cybersecurity, monitoring regulations, adjusting traditional models, focusing on product liability insurance, and training professionals. Full article

Electric aviation (eViation) is a promising pathway for sustainability in General Aviation (GA), particularly pilot training. However, challenges such as limited aircraft models, low battery endurance, long charging times, and inadequate charging infrastructure at most airfields—exacerbated by a lack of charging standardization—hinder eViation adoption. This study explores key factors influencing the feasibility of establishing a fast-charging network for electric airplanes in Switzerland, addressing infra-structural, technological, and policy barriers, as well as stakeholder concerns. Using a sequential mixed-methods approach, we analyzed 7000+ electric flight records and conducted an online stakeholder survey (n = 44) and 21 qualitative expert interviews. The findings reveal strong interest in eViation but highlight critical gaps, including sparse charging infrastructure and the need for standardization. Stakeholders emphasize transitioning to the Combined Charging System (CCS), integrating renewable energy, and implementing policy measures like subsidies and operational privileges. However, a chicken-and-egg dilemma persists: limited infrastructure hampers aircraft adoption, yet investment is difficult without widespread use. Lessons from the automotive EV transition highlight the need for strategic infrastructure expansion and coordinated policies. Remarkably, stakeholders prioritize network density over charging speed. This study identifies key barriers and opportunities for eViation adoption, providing actionable recommendations for the sustainable GA transition. Full article

As of the end of 2024, there are only about 781 electric vehicles (EV) on the streets of Kuwait, ranking it at about the 0.03 percentile of the total car population and as the country with the lowest EVitization worldwide. In this study, we explore the reasons behind this ultra-low adoption rate from a variety of standpoints: 1. from a qualitative perspective based on deep interviews with 10 existing EV owners in Kuwait; 2. from the perspective of marketing and of capital and operational expenses by gathering the latest data from the common database of Kuwaiti automobile dealers; 3. from the perspective of governmental incentives and infrastructural development; and 4. from the technical perspective on how EVs perform in extreme heat conditions, such as those in Kuwait. From these four perspectives, we gather several reasons for the ultra-low adoption rate, and we provide a variety of possible solutions that are likely to increase the rate at which Kuwaiti residents replace their internal combustion engine automobiles with electric vehicles and, thus, lower their carbon footprint, which is one of the highest in the world. Full article

Battery parameter identification is a key challenge for battery management systems, as parameterizing lithium-ion batteries is resource-intensive. Electrical circuit models (ECMs) provide an alternative, but their parameters change with physical conditions and battery age, necessitating regular parameter identification. This paper presents two modular algorithms to improve data quality and enable fast, robust parameter identification. First, the dequantizer algorithm restores the time series generating the noisy, quantized data using the inverse normal distribution function. Then, the Linear Continuous-Time Regression (LCTR) algorithm extracts exponential parameters from first-order or overdamped second-order systems, deducing ECM parameters and guaranteeing optimality with respect to RMSE. The parameters have low sensitivity to measurement noise since they are continuous-time. Sensitivity analyses confirm the algorithms’ suitability for battery management across various Gaussian measurement noise, accuracy, time constants and state-of-charge (SoC), using evaluation metrics like root-mean-square-error (RMSE) (<2 mV), relative time constant errors, and steady-state error. If the coarseness of rounding is not extreme, the steady-state is restored within a fraction of a millivolt. While a slight overestimation in the lower time constants occurs for overdamped systems, the algorithms outperform the conventional benchmark for first-order systems. Their robustness is further validated in real-life applications, highlighting their potential to enhance commercial battery management systems. Full article

The variable-flux memory machine (VFMM) can perform flexible online PM flux adjustment by utilizing a magnetizing current pulse, effectively extending the machine operation range. However, the continuous flux adjustment (CFA) method generally suffers from sophisticated control effort due to frequent actions of the power converters. Thus, a new two-state magnetization state (TS-MS) manipulation method is developed to simplify the MS manipulation process, while maintaining almost the same operating envelope compared to the CFA method. In addition, for further extension of the operation region, this paper proposes a novel two-state linear FW (TS-LFW) strategy with simple implementation. In the TS-LFW strategy, piecewise linear approximations for FW are, respectively, planned at MS1 and MS2. Distinctively, the determination of the two working MS of all the two-state methods in this paper is discussed to avoid the unnecessary MS manipulations. Finally, the feasibility and effectiveness of the proposed TS-LFW strategy are verified through the experimental results on a hybrid magnetic circuit VFMM (HMC-VFMM) prototype. Full article