Co-optimization on ecological adaptive cruise control and energy management of automated hybrid electric vehicles
Electrified drive systems and eco-driving technologies play a crucial role in promoting energy conservation. Eco-driving for hybrid electric vehicles(HEVs) is an intricate problem involving intertwined speed planning and energy management . In this context, an ecological adaptive cruise control (eco-ACC) and powertrain energy management strategy considering Signal Phase Timing Message (SPaT) can enhance both performance and real-time implementation. Specifically, this study develops a novel co-optimization method based on Pontryagin's minimum principle (PMP) that combines car-following control rules with the SPaT for a parallel HEV. The methodology involves the following steps: firstly, the parallel HEV model is established; secondly, the safe following distance model is constructed and the car-following control rules are devised to ensure safe driving. Subsequently, the co-optimization method based on PMP is then presented to simultaneously optimize the eco-driving problem of an ego-vehicle by converting the inter-vehicle distance constraint of the lead-vehicle into the limitation of the speed of the ego-vehicle. Finally, simulations are conducted under different scenarios for both fused SPaT and non-fused SPaT strategy. The simulation results demonstrate a reduction in fuel consumption by 6.27 % and 5.69 % in two different scenarios, respectively, and a shorter driving time for the fused SPaT strategy compared to the non-fused SPaT strategy. • A novel car-following rules is proposed to ensure its safety. •An eco-ACC and energy management strategy is proposed with SPAT by combining the car-following control rules with the PMP. •The PMP is used to derive the explicitly optimal analytical solution of the eco-driving problem under signalized intersections. •The gearshift behavior of parallel HEV is considered by incorporating a single-parameter shift law. •Different methods are compared to validate the proposed method.
Authors
- Ziyou Song (ORCID: https://orcid.org/0000-0003-3164-5234)
- Lehua Xiao
- Serdar Coskun (ORCID: https://orcid.org/0000-0002-7080-0340)
- Qi Dong Zhao (ORCID: https://orcid.org/0000-0001-9713-1864)
- Yongtao Liu (ORCID: https://orcid.org/0000-0003-3643-4276)
- Shaobo Xie (ORCID: https://orcid.org/0000-0001-5437-0742)
- Jiacheng Li (ORCID: https://orcid.org/0000-0002-6996-4778)
- Fengqi Zhang (ORCID: https://orcid.org/0000-0001-9811-2593)
Institutions
- Chongqing University (CN)
- National University of Singapore (SG)
- Chang'an University (CN)
- Chery Automobile (China) (CN)
- Tarsus University (TR)
Publication Details
- Journal
- Energy
- Published
- 2024-10-25
- DOI
- https://doi.org/10.1016/j.energy.2024.133542
- Citations
- 12
- Primary Topic
- Traffic control and management
- Type
- article
- Field-Weighted Citation Impact
- 3.94