  Freight drivers of electric trucks need to design charging strategies for
where and how long to recharge the truck in order to complete delivery missions
on time. Moreover, the charging strategies should be aligned with drivers'
driving and rest time regulations, known as hours-of-service (HoS) regulations.
This letter studies the optimal charging problems of electric trucks with
delivery deadlines under HoS constraints. We assume that a collection of
charging and rest stations is given along a pre-planned route with known
detours and that the problem data are deterministic. The goal is to minimize
the total cost associated with the charging and rest decisions during the
entire trip. This problem is formulated as a mixed integer program with
bilinear constraints, resulting in a high computational load when applying
exact solution approaches. To obtain real-time solutions, we develop a
rollout-based approximate scheme, which scales linearly with the number of
stations while offering solid performance guarantees. We perform simulation
studies over the Swedish road network based on realistic truck data. The
results show that our rollout-based approach provides near-optimal solutions to
the problem in various conditions while cutting the computational time
drastically.
