Parameter Co-optimization for Hybrid Electric Vehicles Powertrain System Leveraging V2V/V2I Information
A parameter tuning based co-optimization scheme for the hybrid electric vehicles (HEV) powertrain system is designed to maximize the fuel efficiency. The optimization controlled input parameters are chosen based on sensitivity study of powertrain control parameters. The vehicle to vehicle (V2V) and vehicle to infrastructure information is another optimization input, to have the driving conditions taking in to considerations for maximizing fuel efficiency. The catalyst temperature is considered as an additional constraint as the speed to reach light-off temperature should not decrease during optimized operation. Neural network is used to develop a simplified yet equivalent model for the optimization problem model. We have achieved an average of 9.22% fuel savings for a random driving cycle on a Toyota Prius test model.
- Research Organization:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-76RL01830
- OSTI ID:
- 1572780
- Report Number(s):
- PNNL-SA-145204
- Resource Relation:
- Conference: International Conference on Advanced Mechatronic Systems (ICAMechS 2019), August 26-28, 2019, Kusatsu, Shiga, Japan
- Country of Publication:
- United States
- Language:
- English
Similar Records
Co-Optimization Scheme for Hybrid Electric Vehicles Powertrain and Exhaust Emission Control System Using Future Speed Prediction
Impact of SiC Devices on Hybrid Electric and Plug-In Hybrid Electric Vehicles