Optimized Operating Strategy for the Thermal Management of a Battery Electric City Bus Using Bayesian Optimization

Electrified propulsion systems offer the potential to reduce global CO2 emissions in the transportation sector, particularly in the field of urban mobility. Electric city buses combine the benefits of public transport systems with locally emission-free mobility. To ensure sufficient range for daily duty cycles, energy efficiency is crucial. Thermal management has a significant impact on the energy demand of battery electric vehicles. Therefore, efficiency can be improved by employing an integrated thermal management architecture that interconnects the individual coolant circuits and enables system-wide optimization. This study proposes an approach to optimize the operating strategy for the thermal management of a battery electric city bus. The important thermal components, including the drive system, battery system and HVAC system, are investigated. Experiments were carried out using a test setup of the system to identify the thermal behavior of the components. The study develops a simulation model of the thermal system of a BEV bus and subsequently uses this model to optimize the operating strategy by means of Bayesian optimization. The goal is to minimize energy demand under representative driving and environmental conditions in the city of Hamburg. The simulation-based analyses highlight potential gains resulting from the optimization of coolant temperatures and the flow rates of the components. Finally, a route- and temperature-based operating strategy is recommended.