User-preference-aware charging scheduling for electric vehicles based on motivation-hygiene theory

User preferences play a crucial role in shaping electric vehicle (EV) charging behavior. These preferences cover various aspects, such as charging time requirements, cost considerations, and low-carbon responsiveness. However, most existing charging strategies often overlook the combined impact of these multifaceted preferences, leading to suboptimal outcomes between user satisfaction and charging costs. To address this gap, this paper proposes a novel framework based on motivation-hygiene theory, integrating EV users’ hygiene and motivation sub-models. The hygiene sub-model incorporates expected charging completion time and departure state of charge as key determinants, capturing user anxieties related to time and range. Meanwhile, the motivation sub-model utilizes carbon trading revenue and electricity cost to reflect low-carbon and economic preferences. Then, EVs are classified into three aggregator types, i.e., hygiene-driven, motivation-driven, and hygiene-motivation-balanced. Each type is associated with a customized scheduling strategy. Simulation results show that the proposed approach effectively mitigates user anxiety, reduces charging costs, enhances local renewable energy utilization, and meets spatiotemporally differentiated charging demands.