A route aware predictive energy management framework for solar integrated electric bus transportation systems

Abstract

The electrification of urban public transportation systems is essential for reducing greenhouse gas emissions and improving energy sustainability. Solar integrated electric buses offer an additional opportunity to reduce grid dependency by utilizing renewable energy during vehicle operation. However, conventional rule based energy management strategies are unable to adapt effectively to route dependent variations in solar availability and traffic conditions. This study proposes a route aware predictive solar energy management strategy for electric buses operating on heterogeneous urban routes. A comprehensive modelling framework integrating vehicle dynamics, photovoltaic power generation, battery energy storage, and predictive energy management control is developed. The proposed approach incorporates route specific parameters such as traffic congestion, solar irradiance, and shading effects to optimize the power distribution between the photovoltaic system and the battery. Simulation studies are conducted for five representative urban routes including high congestion, IT corridor, peripheral solar exposure, dense urban, and bus rapid transit corridors. Results demonstrate that the predictive strategy reduces battery energy consumption by an average of 10.18% compared with the conventional rule based controller while improving solar energy utilization and vehicle driving range. Furthermore, fleet level analysis for a system of 300 buses shows a total energy saving of 378.70 kWh per trip and an annual energy saving of approximately 1.38 GWh. These results highlight the effectiveness of predictive energy management strategies in improving the operational efficiency and sustainability of solar electric bus fleets.