A Random Charging Decision Method for Electric Private Cars Considering Individual Heterogeneity of Users and Latent Attitudinal Variables

According to the charging decision behavior of electric private cars (EPC), a random charging decision method for EPCs is proposed with individual heterogeneity and latent attitude variables taken into account. Firstly, an analysis on the influencing factors of charging decision is conducted, and questionnaires for the different factors are designed. Secondly, to address the design problem of latent variables of attitude, a measurement index is derived to indirectly quantify latent variables of attitude. Additionally, the quality of the survey data is analyzed through an examination of questionnaire data reliability and validity. Then, considering the charging scene variables, attitude latent variables and individual socioeconomic attributes that affect individual charging decisions, the hybrid choice model (HCM) is employed to establish the charging utility, and the charging probability is subsequently determined. Through the investigation data, the model parameters are estimated, leading to the determination of specific expressions of charging utility and three types of influencing factors. Compared to the prediction results based on the mixed Logit model, the proposed method achieves higher prediction accuracy, and the error has been reduced by nearly 14% when adopting the proposed method.