A5005838900- Vehicle emissions and performance
- Vehicle Dynamics and Control Systems
- Advanced Battery Technologies Research
- Traffic control and management
- Electric Vehicles and Infrastructure
- Autonomous Vehicle Technology and Safety
- Transportation and Mobility Innovations
- Transportation Planning and Optimization
University of Zagreb
2022-2025
The paper presents a novel approach for predicting battery energy consumption in electric city buses (e-buses) by means of trip-based data-driven regression model. model was parameterized based on the data collected running physical experimentally validated e-bus simulation model, and it consists powertrain heating, ventilation, air conditioning (HVAC) system submodels. main advantage proposed is its reliance readily available trip-related data, such as travel distance, mean velocity,...
The authors of this paper propose a Markov-chain-based method for the synthesis naturalistic, high-sampling-rate driving cycles based on route segment statistics extracted from low-sampling-rate vehicle-tracking data. In considered case city bus transport system, segments correspond to sections between two consecutive stations. include lengths and maps average velocity, station stop time, station-stopping probability, all given along day an hourly basis. process cycle synthesis, transition...