Adoption Of Hybrid Electric Vehicles Research Articles

Which state is the cleanest of them all? Pricing long run heterogeneity in carbon abatement costs across America

Electric vehicles (EVs) feature prominently in the United States' efforts to decarbonize the light-duty vehicle fleet and mitigate climate change. To spur EV adoption, public policy offers procurement incentives for individuals willing to purchase an EV instead of an internal combustion engine vehicle (ICEV). How cost-effective are such policies? To what extent does their efficiency vary across states? We address these questions using state-level data on projected electric grid carbon intensity and fuel prices, as well as models of vehicle utilization. Our approach focuses on comparable vehicle models that enable us to jointly estimate the lifecycle emissions and total cost of ownership (TCO) associated with ICEVs, hybrid electric vehicles (HEVs), and EVs. Our findings are fourfold. First, although EVs offer the largest emissions benefit relative to ICEVs, there exists significant state-level heterogeneity. Compared to HEVs' emissions advantage of 20.54 tons of CO2e, EVs' emissions advantage ranges from 10.18 to 58.83 tons of CO2e across states. Second, HEVs offer a more favorable cost-to-emissions advantage nationwide, with an average cost of $59/ton CO2e reduced compared to $192/ton CO2e reduced via EVs. Third, state-level variation in fuel prices and grid carbon intensity enable HEVs to offer emissions reductions at a minimum cost of $3/ton CO2e reduced, while EVs' minimum cost is $76/ton CO2e reduced. Fourth, envisioned grid decarbonization efforts are insufficient for EVs to deliver economically efficient cost-to-emissions advantages due to EVs' relatively high TCO. If EVs produced zero emissions in totality, realizing cost-effective emissions reductions would still necessitate lowering their TCO by an average of at least $3200. We conclude that favorable abatement cost realization necessitates better targeting of procurement incentives at both the federal and state level. We demonstrate that this outcome can be achieved by incentivizing the adoption of HEVs and high-utilization EVs in the short run and by improving EVs’ cost and continuing to invest in EV battery longevity in the long run.

Greening the roads: Assessing the role of electric and hybrid vehicles in curbing CO[formula omitted] emissions

The transportation sector is the largest contributor to greenhouse gas (GHG) emissions, and electric and hybrid vehicles (EHVs) are among many solutions that can help reduce the consumption of fossil fuels and their resulting GHG emissions. This study addresses the significant and understudied question of how EHVs’ adoption influences CO2 emissions using panel U.S. state-level data over the 2016-2019 period and fixed effects. The study finds no statistically significant relationship between the adoption of hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and plug-in electric vehicles (PEVs) and CO2 emissions. These findings could be explained by adoption rates of HEVs and PHEVs that are too low to manifest statistically significant reductions in CO2 emissions from the potential displacement of internal-combustion engine vehicles (ICEVs). The findings also align with observations indicating that PEVs, although emission-free, are frequently adopted as supplementary rather than primary vehicles by multi-vehicle households in the U.S. The complexities surrounding EHVs and their impact on CO2 emissions highlight the importance of further research in understanding the role these vehicles play in the larger context of sustainable transportation as well as more nuanced research into adoption patterns, potential policy interventions, and broader environmental implications.

Recent Progress in Energy Management of Connected Hybrid Electric Vehicles Using Reinforcement Learning

Review Recent Progress in Energy Management of Connected Hybrid Electric Vehicles Using Reinforcement Learning Min Hua 1, Bin Shuai 1,2, ∗ , Quan Zhou 1, Jinhai Wang 1, Yinglong He 3, and Hongming Xu 1 1 School of Engineering, University of Birmingham, Birmingham B152TT, UK 2 School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China 3 School of Mechanical Engineering Sciences, University of Surrey, Guildford, GU27XH, UK * Correspondence: shuaib@mail.tsinghua.edu.cn Received: 29 August 2023 Accepted: 11 December 2023 Published: 19 December 2023 Abstract: The growing adoption of hybrid electric vehicles (HEVs) presents a transformative opportunity for revolutionizing transportation energy systems. The shift towards electrifying transportation aims to curb environmental concerns related to fossil fuel consumption. This necessitates efficient energy management systems (EMS) to optimize energy efficiency. The evolution of EMS from HEVs to connected hybrid electric vehicles (CHEVs) represent a pivotal shift. For HEVs, EMS now confronts the intricate energy cooperation requirements of CHEVs, necessitating advanced algorithms for route optimization, charging coordination, and load distribution. Challenges persist in both domains, including optimal energy utilization for HEVs, and cooperative eco-driving control (CED) for CHEVs across diverse vehicle types. Reinforcement learning (RL) stands out as a promising tool for addressing these challenges. Specifically, within the realm of CHEVs, the application of multi-agent reinforcement learning (MARL) emerges as a powerful approach for effectively tackling the intricacies of CED control. Despite extensive research, few reviews span from individual vehicles to multi-vehicle scenarios. This review bridges the gap, highlighting challenges, advancements, and potential contributions of RL-based solutions for future sustainable transportation systems.

A Vehicle-to-Grid System for Controlling Parameters of Microgrid System.

The power system for large-scale adoption of hybrid electric vehicles can benefit from a distributed reserve provided by the vehicle-to-grid (V2G) concept. This study suggests a V2G technology that can effectively control frequency on a microgrid throughout a 24-h cycle. When usage is at its lowest in the spring or fall, a microgrid is intended to be large enough to simulate a community of 2000 households. A 1:5 ratio of cars to households is realized by modelling 400 electric vehicles (EVs) as a basic model, indicating a typical case in the future. An in-depth analysis of the voltage, current, reactive, and active power is carried out for a microgrid. By coordinating control of diesel generation, renewable energy source (RES) generation, power exchange, and EV generation, the system frequency of a microgrid can be managed by regulating load demand with V2G devices. The proposed microgrid with V2G effectively manages energy and reduces the uncertain and variable nature of RES power generation with enhanced performance. System parameter variations have been investigated for various operating scenarios, and it has been discovered that error is confined to less than 5%.

Co-Optimization of Eco-Driving and Energy Management for Connected HEV/PHEVs near Signalized Intersections: A Review

Currently, road transport constitutes a considerable proportion of global fossil fuel consumption, as well as CO2 and pollutant emissions. To mitigate transportation energy consumption, two primary approaches have emerged: the large-scale adoption of Hybrid Electric Vehicles (HEVs) and Plug-In Electric Vehicles (PHEVs), as well as the implementation of eco-driving strategies, which present an immediate and low-cost solution. In this context, this paper provides a comprehensive review of these two technologies and their integration for connected HEV/PHEVs. We summarize the framework of recent approaches to incorporate fusion road information in single-vehicle and multi-vehicle scenarios, respectively, wherein we compare their advantages, their disadvantages, and their effectiveness in reducing energy consumption. Additionally, we reflect on the future development directions of cooperative optimization in EMS and eco-driving strategies from various perspectives. This comprehensive review underscores the importance and potential impact of these approaches in addressing environmental challenges in transportation systems, thereby offering useful insights for new researchers and practitioners in this area.

Exploration of the drivers influencing the growth of hybrid electric vehicle adoption in the emerging economies: Implications towards sustainability and low-carbon economy

The heavy reliance of the transportation and power generation sector on fossil fuels is seriously impacting the environment. Transitioning towards more sustainable transportation modes is necessary to reduce this dependency on fossil fuels. Even though shifting toward electric vehicles (EVs) can reduce harmful emissions, due to the lack of adequate charging infrastructures, underdeveloped power transmission systems, and increased cost of power generation, it is difficult for a developing country to adopt and rely heavily on EVs. However, developing countries like Bangladesh can adopt a different strategy to address this issue. Harmful emission reduction is also possible by transitioning from conventional internal combustion engine (ICE) vehicles to hybrid electric vehicles (HEVs). The drivers that can promote the expansion of HEV adoption have not been extensively studied to date, which inspired the proposed study. This study explores the drivers for the growth of HEV adoption in emerging economies. First, the study identifies seventeen drivers from the literature review and expert feedback. Then the identified drivers were assessed using the Bayesian Best-Worst method (BWM). The study findings indicate that no requirement for a charging station, incentivizing consumers through policy measures, and enhanced fuel efficiency are the top three drivers influencing the growth of HEV adoption in developing or emerging economies. This study can help the decision-makers and end users in developing counties to gradually shift towards a low-carbon emission-based economy and ensure a greener and more sustainable future.

Consumer perceptions of hybrid electric vehicle adoption and the green automotive market: the Malaysian evidence

Compared to many developing countries, Malaysia has been far less successful in getting its citizen to embrace hybrid electric vehicles (HEVs). The study investigates the reasons behind this problem and offers a framework that could facilitate policymakers and stakeholders toward the electrification transition. Using the textual-based content analysis method, text-based articles and comments were extracted from a local reputable automotive news portal using a web scraper tool and analyzed using the open-coding technique. Surprisingly, environmental and greenhouse pollution issues did not emerge from our analysis—indicating that altruistic values and ecological consideration are not among the consumers' priorities when evaluating HEVs. Value proposition and risk aversion form the main themes, while national carmakers, competition, ambiguous policies, perceived unfairness in incentives distribution, and physical presentation constitute the minor themes. Overall, the consumers remain highly cautious and skeptical toward HEVs ownership proposition. This paper contributes to the existing literature by presenting a strategic framework for consumers' adoption of HEVs across Southeast Asian Nations (ASEAN). The main message is that HEV adoption requires a firm political resolution from ASEAN governments to promote a fairer playing field within the region by complementing (rather than competing with) each other. By removing non-tariff barriers and providing incentives, the gradual growth of a sizeable and sustainable HEV customer base will potentially dispel existing consumers' negative perceptions toward these cars.

Analyzing Factors of Hybrid Electric Vehicle Adoption Using Total Cost of Ownership

Around 20% of total greenhouse gas emissions occur in transportation, 85% of which takes place in road traffics. Environmentally friendly vehicles are a transport type which has less environment impacts compared to existing internal combustion engine vehicles. Among them hybrid electric vehicles (HEVs) have increased steadily in South Korea. This paper analyzes the sales of YF SONATA HEV and K5 HEV, which account for 85% of the domestic HEV market, compared to gasoline engine versions of the same models from Total Cost of Ownership (TCO) viewpoint. The relationship between the vehicle’s TCO and HEV sales share were analyzed as well as the consumer’s perception about the value associated with purchasing HEVs. This research conducts a quantitative study on the necessary government incentives on HEV sales for the expansion of HEV market in Korea. This work could contribute to the design of government policy to promote environmentally friendly vehicles. Additionally, this work can serve to analyze the effect of such incentive policies on environmental conservation and reduction of social expenses.

The joint effects of driving hedonism and trialability on the choice between internal combustion engine, hybrid, and electric vehicles

The low penetration rate of electric vehicles (EVs) is raising concern among policy makers and car designers who face risky decisions whether to invest in EV technology and promotion. Traditionally, battery electric vehicles (BEV) and hybrid electric vehicles (HEV) were considered successive technologies. Yet, it is becoming apparent that in the next few decades these technologies will co-exist, which revives the interest in the choice amongst them. This study focuses on normative and hedonic goals to understand the impact of innovativeness and driving hedonism and their interaction with user experience and pro-environmental attitudes of consumers choosing between conventional, hybrid and electric cars. The behavioral model challenges utility-based models of auto propulsion choices by integrating hedonic goal-framing and its interaction with product experience into Rogers’ diffusion of innovation model. In a discrete choice experiment informed by stated-preference Bayesian efficient design among 309 participants, we find that the interaction between driving hedonism and BEV 'trialability' is positively related to the adoption of HEVs rather than of BEVs. Compared to environmental consumers who lack driving hedonism, the segment of innovative-environmentalists act as BEV adoption pioneers and the segment of innovative-environmentalist-hedonists are HEV adoption pioneers.

Measuring the cost-effectiveness of electric vehicle subsidies

Despite the prevalence of plug-in electric vehicle (PEV) subsidies, research on improving their cost-effectiveness and impact remains limited. To assess the scope for improving their cost-effectiveness, we develop a vehicle choice model-based counterfactual simulation using a large-scale nationally representative sample of U.S. new car buyers. Results suggest that existing federal incentives are expensive, $36k per additional PEV, as every buyer gets the subsidy. The cost-effectiveness can be improved by twofold by targeting incentives by income, vehicle disposal, geography, and/or vehicle miles traveled. Preserving the federal policy's assignment of larger subsidies for PEVs with larger battery capacities results in greater battery electric vehicle (BEV) adoption, while policies not discriminating by battery capacity result in greater plug-in hybrid electric vehicle adoption. The reduction in gasoline consumption is the same in both the cases, with a slightly lower marginal cost for the latter.

Analysing consumer's perception comparatively on hybrid electric according to online comments

Hybrid electric vehicles (HEVs) are regarded as an available near-term green solution to reduce the greenhouse gas (GHG) emission in transportation sector, but they still do not play a dominant role in some auto market. In the view of consumer's perception, this paper investigates 1109 online comments to find out the reasons that cause large sale discrepancy. A framework including five aspects and nineteen factors is proposed, which help to analyse the consumer's perception on HEVs systematically. In addition, based on that framework, the difference on consumer's perception between China and America is investigated comparatively, which is also as a good case on HEVs for some other developing and developed countries. Finally, according to comparative result, three basic strategies, including cannikin strategy, suboptimum strategy and dominant strategy, are brought forward to boost the widespread adoption of HEVs in different markets.

Why is the market for hybrid electric vehicles (HEVs) moving slowly?

Hybrid electric vehicles (HEVs) could be a good short term option to help achieve global targets regarding road transport greenhouse gas emissions. Several common and country-specific public policies based on price or tax rebates are established in order to encourage the adoption of HEVs. The present research empirically assesses market preferences for HEVs in Spain, looking at the role of subsidies. An interactive internet-based survey was conducted in a representative sample (N = 1,200) of Spanish drivers. Drivers are willing to pay an extra amount of €1,645 for a HEV model compared to a conventional vehicle, premium which is well below the price markup for these cars. Therefore, current levels of economic subsidies applied in isolation to promote these types of vehicles may have a quite limited effect in extending their use. Overall, it is found that drivers have clear misconceptions about HEVs, which affect their purchasing choices and perceptions. Therefore, a policy mix of various incentives (including informational campaigns) may be required in order to stimulate the demand for HEVs.

Design-space exploration of series plug-in hybrid electric vehicles for medium-duty truck applications in a total cost-of-ownership framework

The light-duty vehicle market has seen some adoption of hybrid electric vehicles that is not reflected in the heavy-duty market. The major challenges associated with the heavy-duty segment are: (i) greater emphasis on economic viability, (ii) reluctance to take on risk associated with new technologies, and (iii) numerous diverse applications that preclude a one-size-fits-all approach to hybrid-electric powertrain design. To overcome these challenges, a model-based framework is required that enables the exploration and optimal design of powertrain architectures for diverse applications while capturing the impact of hybridization on the economics of ownership under different economic scenarios. This paper demonstrates such a framework that incorporates powertrain simulation and battery degradation models to predict fuel consumption, electrical energy consumption, and battery replacements. These results are combined with economic assumptions to enable the exploration of a large design space (which spans powertrain design & control variables, noise variables, and economic scenarios) from a total cost-of-ownership perspective to provide better insights to vehicle integrators, component manufacturers, and buyers of heavy-duty hybrid electric vehicles. The methodology is applied to series plug-in hybrid electric and extended-range electric powertrain architectures for medium duty truck applications. The results show that under the assumptions made, economically favorable solutions for series plug-in hybrid electric medium-duty trucks exist in the 2020 time-frame for the NY Composite Truck drive cycle, while for the HTUF Refuse Truck and HTUF Class 6 P&D Truck drive cycles, feasible solutions are not obtained until 2025 and 2030 time-frames respectively.

Spatial effects on hybrid electric vehicle adoption

This paper examines spatial effects on hybrid-electric vehicle (HEV) adoption. This is in contrast to most existing analyses, which concentrate on analyzing socioeconomic factors and demographics. This paper uses a general spatial model to estimate the strength of ‘neighbor effects’ on HEV adoption—namely that each consumer’s HEV-adoption decision can be influenced by the HEV-adoption decisions of geographic neighbors. We use detailed census tract-level demographic data from the 2010 United States Census and the 2012 American Community Survey and vehicle registration data collected by the Ohio Bureau of Motor Vehicles. We find that HEV adoption exhibits significant spatial effects. We further conduct a time-series analysis and show that historical HEV adoption has a spatial effect on future adoption. These results suggest that HEVs may appear in more dense clusters than models that do not consider spatial effects predict.

An Overview of the Hybrid and Electric Systems R&D at the U.S.–DOE (FY 2015–2016)

The U.S. Department of Energy (DOE) through its Vehicle Technologies Office (VTO), often in close partnership with industry, has supported the development/deployment of cleaner, more efficient automotive technologies with electric drive systems. This paper provides an overview of efforts to promote market adoption of hybrid electric vehicles (HEVs) and electric vehicles (EVs) in the U.S. and the associated VTO R&D and Deployment initiatives for accelerating this adoption. It also highlights the many significant research breakthroughs resulting from R&D in the hybrid vehicle systems areas of research (with particular emphasis on advanced electric drive technologies) funded directly by or in collaboration with VTO.

Identifying socio-demographically favourable area types for early hybrid electric vehicle adoption through mining of public sector data

In the coming years, the share of hybrid electric vehicles is expected to grow significantly in personal transportation. Vehicles that can be charged from the electrical grid, such as plug-in hybrids, could introduce problems for the distribution network, especially if the vehicle adoption is spatially concentrated and the charging happens unmanaged. Thus, where and when the hybrid vehicle adoption occurs is an important question for policy makers and planners. Currently, promoted by the European Union directives such as INSPIRE and PSI, there is a trend of public sector data being harmonised and opened for free usage across the Europe. The vast amount of information in the various registers of the society has a huge and largely untapped potential for modelling societal and environmental phenomena. To discover correlations and relationships from such large databases, data mining methods can be useful. In this paper, we utilise a data mining approach to identify relationships from public sector data between hybrid vehicle adoption and small area level socio-demography. Based on the discovered model, we assess how favourable each area type is for the adoption. The approach combines Self-Organizing Map based data compression, a feature selection using Genetic Algorithm and a linear regression model.

Predicting consumers’ intention to adopt hybrid electric vehicles: using an extended version of the theory of planned behavior model

China is a major energy-consuming country and is under great pressure to improve its energy efficiency as well as reduce its carbon emissions. Hybrid electric vehicles (HEVs), as an energy-efficient transport innovation, have the potential to reduce gasoline consumption, carbon emissions and alleviate environmental problems. Diffusion of HEVs’ adoption is a significant initiative. A sample of 433 respondents has been collected in China to predict the customers’ intention to adopt HEVs, using an extended model of the theory of planned behavior (TPB). The empirical results show that the attitude toward HEVs, subjective norm, perceived behavioral control (the three primary elements of the TPB model) and personal moral norm partially mediate the effect of consumers’ environmental concern on their intention to adopt HEVs. Consumers’ environmental concern affects the adoption intention indirectly and is significantly positively related to the attitude toward HEVs, subjective norm, perceived behavioral control and personal moral norm, which in turn influence the adoption intention positively. The results confirm the appropriateness of the TPB model and verify that the extended TPB model has good explanatory power in predicting consumers’ intention to adopt HEVs. Based on the empirical results, we discuss the implications for promoting the adoption of HEVs and provide suggestions for future study.

Incorporating social impact on new product adoption in choice modeling: A case study in green vehicles

While discrete choice analysis is prevalent in capturing consumer preferences and describing their choice behaviors in product design, the traditional choice modeling approach assumes that each individual makes independent decisions, without considering the social impact. However, empirical studies show that choice is social – influenced by many factors beyond engineering performance of a product and consumer attributes. To alleviate this limitation, we propose a new choice modeling framework to capture the dynamic influence from social networks on consumer adoption of new products. By introducing social influence attributes into a choice utility function, social network simulation is integrated with the traditional discrete choice analysis in a three-stage process. Our study shows the need for considering social impact in forecasting new product adoption. Using hybrid electric vehicles as an example, our work illustrates the procedure of social network construction, social influence evaluation, and choice model estimation based on data from the National Household Travel Survey. Our study also demonstrates several interesting findings on the dynamic nature of new technology adoption and how social networks may influence hybrid electric vehicle adoption.

The impact of federal incentives on the adoption of hybrid electric vehicles in the United States

Starting in 2004, the federal government in the United States offered several nationwide incentives to consumers to increase the adoption of hybrid electric vehicles. This study assesses the effectiveness of the Energy Policy Act of 2005 in this regard using econometric methods and data between 2000 and 2010. Our model accounts for network externalities by using lagged sales as an independent variable. This approach helps to capture the exponential initial growth associated with the diffusion of new technologies and avoids overestimating the effect of the policy incentives. Our results show that the Energy Policy Act of 2005 increased the sales of hybrids from 3% to 20% depending on the vehicle model considered. In addition, we find that this incentive is only effective when the amount provided is sufficiently large.

Geodemographic analysis and estimation of early plug-in hybrid electric vehicle adoption

Electric vehicles and hybrids are expected to become increasingly common in the coming years. The implications of growing adoption depend on its geographical extent. For instance, vehicles that are chargeable from the electrical grid, such as plug-in hybrids, can introduce problems for the distribution network especially if the vehicle adoption is spatially concentrated. In this paper, the adoption of hybrid electric vehicles is analysed in heterogeneous areas. The main purpose is to study the interrelationships between early hybrid electric vehicle adoption and different demographic and socio-economic characteristics of the areas. It is further discussed how the results can be applied to estimate the upcoming plug-in hybrid adoption. As there is a vast amount of information in the various registers of the society, slowly being opened for free usage but not fully utilised so far, it is also of interest to study and demonstrate the usability of public register data in this context. Our analysis suggests that certain characteristics of the areas strongly correlate with the hybrid electric vehicle adoption. The results of this study could be relevant, e.g., for electric distribution network planning, targeting policies to support cleaner vehicle adoption, marketing hybrid vehicles and locating charging stations.