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Identifying electric vehicle charging styles among consumers: a latent class cluster analysis

Elham Hajhashemi, Patrícia Sauri Lavieri, Neema Nassir

2024Transportation Research Interdisciplinary Perspectives15 citationsDOIOpen Access PDF

Abstract

• Heterogeneous charging styles exist among current and prospective EV users. • Five distinct charging styles were identified using a latent class cluster model. • Charging styles are applied to guide targeted policy recommendations. • Charging styles can add behavioural realism to charging demand models. The market share of electric vehicles (EVs) is growing rapidly, making it crucial to understand the charging behaviour of current and prospective users. Such understanding is essential for designing policies that positively influence consumers’ charging behaviour and facilitate EV adoption. In this study, we examined the heterogeneity in charging preferences of 994 respondents across Australia using a latent class cluster model that considers indicators of charging behaviour as outcomes of interest. We used sociodemographic characteristics, travel needs, and EV adoption status as covariates to predict class membership. Our findings indicate five segments of consumers with distinct charging preferences: routine-focused frugals, cost-oriented deliberators, range seekers, flexibility seekers, and indifferent late adopters . These segments differ in the importance they attach to charging attributes, their coping strategies with limited battery resources, and their risk attitude. Our results suggest that a uniform approach to EV-related policies is not appropriate, as each consumer segment has unique charging preferences and requirements. Furthermore, the study emphasizes the significance of accounting for charging behaviour heterogeneity in demand modelling, as assumptions in current models may not accurately represent the decision-making of most segments.

Topics & Concepts

Latent class modelCluster (spacecraft)Electric vehicleClass (philosophy)AdvertisingComputer sciencePsychologyStatisticsBusinessMathematicsArtificial intelligencePhysicsQuantum mechanicsProgramming languagePower (physics)Electric Vehicles and InfrastructureAdvanced Battery Technologies ResearchEnergy, Environment, and Transportation Policies
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