Stochastic Dynamic Programming (SDP) has shown promising results for sequential decision problems of the route optimisation for an Electric Vehicle (EV) with the presence of stochastic variables in the travel cost. However, in studies, the optimisation problem formulation for EVs has been lacking in detail. For example, possible waiting times at a Charging Station (CS) have been neglected. This thesis uses SDP to formulate a more holistic optimisation problem for EVs moving through a road network where travel speeds and charging station availability are stochastic. The goal is to optimise the travel costs, which consists of, e.g., the journey time and the charging cost, for an EV on long-haul trips.

In this thesis, four simulation-based case studies are conducted: (1) comparison of conventional navigation system with the proposed method; (2) speed optimisation in order to improve the travel costs; (3) charging platform selection in order to improve the travel cost; (4) uncertainty influence on the travel costs. The case studies are conducted to create insight into how the travel costs of an EV can be optimised. In these case studies, the influence of multiple factors has been taken into account and investigated. For example, cabin climate control, which is dependent on the ambient temperature, has a significant influence on the energy consumption of the EV resulting in higher travel costs.

The simulation results have shown interesting results. Compared to a Min algorithm, which uses a strategy to minimise the travel and charging time, the proposed method can find an optimal policy that is in some cases 5% shorter in terms of journey time. It is profitable for certain ambient temperatures and maximum allowable driving speeds in terms of journey time and charging cost to optimise the driving speed below the maximum allowed driving speed on highways. This results in a shorter journey time and saving charging costs. For example, for a maximum speed of 120 (km/h) and an ambient temperature of 20 ◦C, 3% of journey time advantage can be achieved by optimising the driving speed.