The efficient operating parameter estimation for a simulated plug-in hybrid electric vehicle

Area of Science:

• Automotive Engineering
• Sustainable Transportation
• Battery Technology

Background:

• Hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs) are crucial for reducing greenhouse gas emissions and combating pollution.
• Battery replacement and fuel expenses represent major long-term costs for HEVs and PHEVs.
• Improving fuel economy is essential for wider adoption of these vehicles.

Purpose of the Study:

• To identify optimal operating parameters for battery state of charge (SoC), motor power, and fuel converter power in HEVs and PHEVs.
• To enhance battery lifespan and fuel economy without negatively impacting vehicle performance.
• To reduce the overall long-run expenditure associated with HEVs and PHEVs.

Main Methods:

• Simulations were conducted on a Ford C-Max Energi (2016) PHEV model.
• The Urban Dynamometer Driving Schedule (UDDS) and Highway (HWY) driving cycles were used for simulations.
• The Future Automotive Systems Technology Simulator (FASTSim) software from NREL was utilized.

Main Results:

• Analysis of battery SoC, fuel converter power, and motor power effects on driving range, battery life, fuel economy, cost, and charge-depleting range.
• Optimal parameter values were estimated, leading to a 4.3% increase in driving range and an 18% improvement in battery life.
• Minor trade-offs included a 1% decrease in charge-sustaining battery life and a 0.4-second increase in 0-60 mph acceleration time.

Conclusions:

• A novel and effective method was presented for optimizing XEV performance by adjusting existing design parameters.
• The study demonstrates that strategic parameter alterations can significantly improve key performance metrics and reduce costs.
• This approach provides a foundation for further research into other parameters and components within various electric vehicle architectures (HEVs, PHEVs, FCEVs).