Predicting Usage Cycles for Electric Vehicles

Cleo is taking the lead in developing additional functionalities within its smart platform for clients operating electric school bus fleets. This innovative platform provides users with the necessary tools to optimize vehicle charging schedules, ensuring reliable charging for planned routes while minimizing energy costs and reducing demand on the grid. The primary goal of the project is to predict bus usage cycles, enabling the efficient utilization of its charging plan optimization model. To achieve this, Cleo’s smart platform leverages historical trip data and external factors such as weather forecasts and academic calendars using unsupervised machine learning techniques. Key outputs include automatic trip detection, prediction of trip start and end times, energy consumption estimates, and an assessment of the likelihood of irregular trips occurring. The fact that Cléo is a subsidiary of Hydro-Québec further strengthens its commitment to sustainable electrification solutions.