Multi-goal balancing is a core demand in long-distance electric vehicle (EV) driving, where time and energy objectives are coordinated in a dynamic environment. The present study is grounded in control-loop models of self-regulation, conceptualizing that drivers iteratively compare perceived states to reference values and adjust speed or charging strategies accordingly. Within this regulatory process, effective goal balancing depends on how drivers interpret task-relevant information and translate these appraisals into action. Two determinants are particularly relevant: informational support and subjective competence. Informational support is understood as system- or environment-provided cues that are timely, interpretable, and task-aligned within action-regulation processes. Subjective competence refers to drivers’ self-appraisal of their capability to meet task demands, grounded in task knowledge and usable strategies. An online survey of EV drivers (N = 57) assessed Perceived Support of Action Regulation (PSAR), Subjective Range Competence (SRC), and Subjective Goal-Balancing Competence (SGBC). Results showed that both PSAR and SRC were positively associated with SGBC, indicating that perceived informational support and range-related subjective competence systematically co-occur with higher subjective competence to coordinate time and energy goals under constraints. The findings highlight the relevance of driver-centered feedback as regulatory support for managing time-energy trade-offs.