Causal-and-effect Relation Between Trip Chaining Pattern and Charging Choice in Different Scenarios
To comparatively study the heterogeneity of charging demand generation process of battery electric vehicle(BEV)users in different scenarios,the working days and non-working days were selected as the study objects.The cause-and-effect relation between trip chaining pattern(travel structure)and charging choice of BEV users in two scenarios were studied by using the recursive simultaneous bivariate probit(RSBP)model respectively.One scenario was that trip chaining pattern affects charging choice;and the other was that charging choice affects trip chaining pattern.The data on trip chaining and charging choice were used to calibrate and verify the model.The result indicates that in working days and non-working days scenarios,the model fitting results are different.The dominant relation between trip chaining pattern and charging choice is different.The generation mechanism of charging demand is heterogeneous.During working days,the trip chaining pattern affects the charging choice,indicating that the generation of user charging demand depends on the travel chaining and activity agenda.In this scenario,the residents'travel habits should be fully considered.The key attributes,e.g.,travel purpose,parking point type,travel time,and state of charge,should be combined to predict and schedule the urban charging demand.During non-working days,the charging choice affects trip chaining pattern,indicating that the charging decision is prior to the trip decision,and the charging demand is less affected by the trip plan.The charging preferences should be analyzed based on the individual socio-economic attributes,BEV attributes,and charging station ownership.The demand forecasting and scheduling should be carried out based on the charging choices.Therefore,there are two types of charging demand generation mechanism during working days and non-working days.The study result has certain guiding significance for predicting and scheduling the urban charging demand.
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