Integrated-Connected Eco-Driving System for PHEVs With Co-Optimization of Vehicle Dynamics and Powertrain Operations

In the past several decades, various types of technologies have been developed to improve vehicle fuel efficiency and reduce tailpipe emissions across different dimensions. For example, powertrain-related technologies improve fuel efficiency by optimizing the powertrain operations in response to dif...

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Veröffentlicht in:IEEE transactions on intelligent vehicles 2017-03, Vol.2 (1), p.2-13
Hauptverfasser: Xuewei Qi, Guoyuan Wu, Peng Hao, Boriboonsomsin, Kanok, Barth, Matthew J.
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Sprache:eng
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Zusammenfassung:In the past several decades, various types of technologies have been developed to improve vehicle fuel efficiency and reduce tailpipe emissions across different dimensions. For example, powertrain-related technologies improve fuel efficiency by optimizing the powertrain operations in response to different driving conditions (e.g., energy management system for plugin hybrid electric vehicles); another technology dimension lies in intelligent transportation systems (ITS), which improve vehicle fuel efficiency by optimizing the vehicle dynamics or speed under different traffic conditions (e.g., eco-speed harmonization and eco-approach and departure). However, very little effort has been made to investigate the combined benefit of integrating both powertrain and ITS technology dimensions together. In this paper, an integrated and connected eco-driving assistance system with co-optimization of vehicle dynamics and powertrain operations for PHEVs is proposed. To fully evaluate the performance of the proposed system at different vehicle automation levels, real-world driving data for different eco-driving technological stages were collected: uninformed manual driving, eco-driving with an in-vehicle advisory display, and an eco-driving system with automatic longitudinal control. The numerical analysis shows that the co-optimization is able to achieve on average 24% fuel savings for typical urban driving conditions.
ISSN:2379-8858
2379-8904
DOI:10.1109/TIV.2017.2708599