Key points are not available for this paper at this time.
The electrification of vehicle power systems has become a dominant trend worldwide. However, with current technologies, range anxiety is still a major obstacle to the popularization of battery electric vehicles (BEVs). Previous research has found that users' trust in the BEVs' range estimation system (RES) is associated with their range anxiety. However, influential factors of trust in RES have not yet been explored. Thus, a questionnaire was designed to model the factors that are directly (i.e., implicit factors) and indirectly (i.e., explicit factors) associated with BEV users' trust in RES. Following the three-layer automation trust framework (i.e., dispositional trust, situational trust, and learned trust), a questionnaire was designed and administrated online. In total, 367 valid samples were collected from BEV users in mainland China. A mixed approach combining Bayesian network (BN) and regression analyses (i.e., BN–regression mixed approach) was proposed to explore the potential topological relationships among factors. Four implicit factors (i.e., sensitivity to BEV brand, knowledge of RES, users' emotional stability, and trust in the battery estimation system of their phones) have been found to be directly associated with BEV users' trust in RES. Furthermore, four explicit factors (i.e., users' highest education, regional charging infrastructure development, BEV brand, and household income) were found to be indirectly associated with users' trust in RES. This study further demonstrates the effectiveness of using a BN–regression mixed approach to explore topological relationships among social–psychological factors. Future strategies aiming to modulate trust in RES can target toward factors in different levels of the topological structure.
Wang et al. (Mon,) studied this question.