Validity Assessment and Calibration Approach for Simulation Models of Energy Efficiency of Light-Duty Vehicles 2020-01-1441
Software tools for simulations of vehicle fuel economy/energy efficiency play an important role strategic decision-making in advanced powertrains. In general, there is a trade-off between the level of detail in a numerical model of a vehicle (higher detail provides better simulation accuracy), and the computational time resources to run the model. However, even with detailed models of a vehicle, there remains some uncertainty about how the vehicle performs in the real-world. Calibration of simulation models versus real-world data is a challenging task due to variations in vehicle usage by different owners. This work utilizes datasets of real-world driving in vehicles that have been equipped with OBD/GPS loggers. The loggers record at fairly high frequency the vehicle speed, road slope, cabin heating/air-conditioning loads, as well as energy/fuel consumption. For six advanced powertrain vehicle models (Bolt, Leaf, Model S, C-Max Energi, Prius Prime, Volt), an assessment is made regarding the accuracy of window-sticker ratings derived from standard dynamometer tests. One key observation is that while window-sticker ratings can be reasonably accurate when considering many trips across different vehicle owners, individual trips and/or averages for individual owners can vary quite a bit from the window-sticker ratings. Next, simulation accuracy/validity assessment is conducted for baseline version of FASTSim, which is an open-source software tool originally developed by NREL. Lastly, a calibration approach via mass and power adjustment terms is proposed. Results show success at improving the fidelity of FASTSim simulations.
Citation: Hamza, K., Chu, K., Favetti, M., Benoliel, P. et al., "Validity Assessment and Calibration Approach for Simulation Models of Energy Efficiency of Light-Duty Vehicles," SAE Technical Paper 2020-01-1441, 2020, https://doi.org/10.4271/2020-01-1441. Download Citation
Karim Hamza, Kang-Ching Chu, Matthew Favetti, Peter Benoliel, Vaishnavi Karanam, Ken Laberteaux, Gil Tal
Toyota Motor North America Inc., University of California Davis
WCX SAE World Congress Experience
Simulation and modeling
Computer software and hardware
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