Electromobility is gaining importance in the courier, express, and parcel (CEP) sector, as parcel service providers increasingly rely on zero-emission vehicles to improve their CO₂ footprint. A common disadvantage of battery electric vehicles is their reduced range under cold operating conditions, due to the increased energy demand for cabin heating. Another CEP-specific factor influencing both energy consumption and cabin comfort is the frequent opening of doors during parcel delivery. Additionally, during delivery phases, the cabin cools down in the driver’s absence, as the heating is deactivated. However, a sufficient level of thermal comfort must be maintained during the driving phases between delivery stops. This paper presents an optimization-based strategy for the cabin heating of battery electric CEP vehicles. The objective is to maximize cabin comfort during driving phases while maintaining a predefined level of energy consumption. For this purpose, a nonlinear model predictive control approach is developed. Characteristic CEP load cases are identified using a k-Means clustering analysis of field data to evaluate the optimization approach. Assuming that the phases of parcel delivery can be accurately predicted, Model-in-the-Loop simulations indicate significant potential for improving comfort. The optimization potential depends on the underlying CEP load cases, particularly the stop characteristics, and the accepted energy consumption. For CEP load cases with low stop density, the simulation results indicate a 16 % reduction in energy consumption and a 21 % increase in comfort level compared to the baseline heating strategy. The energy consumption reduction and comfort improvement are achieved by optimizing the air mass flow rate and the heating power trajectory. In contrast, for load cases with high delivery density, a significant improvement in cabin comfort can only be achieved with increased energy consumption. In these load cases, an additional consumption of 30 % leads to an increase in comfort of 44 %.