Towards optimal route planning for solar-powered battery electric vehicles

Abstract

Given the recent advances in battery technologies, Battery Electric Vehicles (BEVs) are more in demand since they are considered a better option than Internal Combustion Engine Vehicles (ICEVs). There are some drawbacks to using BEVs; for example, driving ranges are shorter compared to ICEVs, and limited charging station infrastructure may be available in certain parts of the world. Furthermore, batteries mounted in BEVs are the leading cause of high acquisition costs, and there are also some technical limitations since the maximum battery capacity degrades over time. These disadvantages negatively affect the adoption of BEVs. There is expected to be an increase in BEV adoption around the world since they require less expensive and less frequent maintenance than ICEVs. A significant problem with BEVs is range anxiety, and route planning may help mitigate this. BEVs need frequent recharging during trips, which renders existing route planning methods used for ICEVs infeasible. Limited driving range, lack of charging stations and possible long charging times of BEVs affects the route choices significantly. BEV route planning may also lower BEVs’ energy consumption and, consequently, the travel-cost. In the thesis, Mixed Integer Linear Programming (MILP) models are proposed to address route planning for BEVs. Multiple factors such as wind speed and -direction, solar irradiation in the case of a solar panel mounted on the vehicle, vehicle acceleration and drive-train efficiency are incorporated to determine optimal routes. As part of this thesis’s case study, the models are adapted to race strategies for competing in the Sasol Solar Challenge. The Sasol Solar Challenge is a biennial competition where multiple teams worldwide design and build solar-powered vehicles to travel across South Africa over eight days. In recent years, the Sasol Solar Challenge has drawn considerable awareness to the development of solar-powered vehicles. In the past years, most of the effort focused on the cars’ mechanical quality and efficiency, but teams gave little attention to the race strategy. An important task is to determine at which stages of the route an automobile should accelerate, decelerate, or maintain speed to use available energy efficiently. When considering a solar-powered car, accessible weather- and elevation data for the whole route is a requirement when determining a race strategy. The solar-powered vehicle is simulated, using vehicle characteristics, weather- and elevation data, and an optimisation model to determine the best strategy for a given solar-powered automobile and route. These simulation- and optimisation models can also help with decisions regarding the design of solar-powered vehicles. A short-term advantage of this approach is the connection with current vehicle technologies regarding energy efficiency when travelling a known route, i.e. a strategy to assist a driver in obtaining better fuel economy